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PhD Transferable Skills

Translating your skills and experiences.

Transferable skills are skills you acquire or learn in one setting that can be applied or translated to new and different settings, environments, and activities. Doctoral students often fall into the trap of seeing their skills as applicable in only one setting, thus do not recognize that they are qualified for a wide variety of career paths. Don’t let this happen to you! In the table below you will find a list of skills most sought after by employers. In the final column of the table are examples of activities that demonstrate these essential skills. For several of the skills you can also take online assessments to identify which areas you still need to develop.

ESSENTIAL SKILLS: Adaptability , Analytic skills , Balance & resilience , Communication skills ( oral and written ), Conflict resolution/negotiation , Cultural/Intercultural , Discipline-specific skills , Ethics & Integrity , Follow-through/Ability to get things done , Fundraising , Independent (self-starter), Intelligence , Inter-/Multi- disciplinary , Interpersonal skills , Leadership (program) , Leadership (personnel/management) , Networking & collaboration , Organization , Outreach , Project management , Research , Self-direction/Entrepreneurial skills , Supervision , Technical skills (information technology), Work ethic

Essential Skills and Competencies for Graduate Students 1 :

1 Contents of table are adapted from Blickley, et al. (2012). “Graduate Student’s Guide to Necessary Skills for Nonacademic Conservation Careers.” Conservation Biology, 27:1. 2 Winterton, Delamare - Le Deist, and Stringfellow (2006). “Typology of knowledge, skills and competences: clarification of the concept and prototype.”

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• Graduate Student Skills (UIUC) [PDF]

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10 PhD Transferable Skills You Can Use in Most Jobs

“No one wants to hire PhDs because they are overqualified and too independent!”

This is one thing PhDs are tired of hearing. How can your PhD be a liability to your career? Rather, recruiters prefer PhD candidates over others not just for their qualification but for their PhD transferable skills.

Table of Contents

What are PhD Transferable Skills?

PhD Transferable skills are exactly what the name suggests! These are skills other than technical skills that you develop in your academic program. Furthermore, these skills are so versatile that they can be used everywhere, irrespective of the designation or field. Transferable skills are desirable because if you already have them, your employer will not have to train you on them. Consequently, you can make positive contributions in any career with these skills.

Which are the PhD Transferable Skills that You Must Develop?

Considering that a doctorate degree is the highest degree in most fields, the skills that are required to excel in the same are impeccable. Undoubtedly, researchers pursuing their Ph.Ds. or postdocs develop technical skills related to their research. However, what they also need to develop is a host of research transferable skills they can use as they progress in their careers.

Which are 10 PhD Transferable Skills You Can Use in Most Jobs?

With the surge of jobs for PhD in STEM, recruiters struggle to fill those positions with talented candidates. They are always in need of trained professionals who know how to create information from scratch, and not just recreate it in a tinkering manner.

While your work experience and education during PhD is an asset, you’d be surprised to find out that employers in most sectors pay close attention to your skill set. According to a recently published survey report by LinkedIn, 57% of respondents identified soft transferable skills as more important than hard skills (technical knowledge).

Here, we list 10 significant PhD transferable skills students can use in most jobs.

1. Project Management

The most apparent thought that comes to anyone’s mind while thinking about PhD is “project management” skills. A successful research experience goes hand-in-hand with a well-planned project. As simple as it may sound, the management skills of a PhD graduate are not confined to his/her project. It starts right from ideation of the research project to final submission, which results in an ultimate success of the project. Different stages of a PhD’s journey demands customized planning and organizing to ensure that deadlines are met and projects are completed efficiently and effectively. Furthermore, a PhD makes sure that all plans are duly incorporated. Employers seek candidates with PhD transferable skills as they want someone who can not only see a task through, but can visualize what needs to happen on a project from start to finish.

2. Accelerated Learning

As a doctor of philosophy, the ability to ascertain knowledge runs thick in the veins of a PhD researcher. An inquisitive mind and quick comprehension of technical things is interlinked to your accelerated learning ability. Moreover, being a PhD, you attend conferences and read papers to stay on top of the latest trends in your field. Consequently, PhD transferable skills ensure employers of your ability to understand technical procedures, protocols, and methodologies.

3. Time Management

Time waits for none! The key to a tension-free and smooth workflow is effective time management . While planning is important, defining your deadlines, setting realistic and achievable goals, and adhering to them takes you a long way! At a job, every moment spent on an unfocused or frivolous task, is a waste of money. Contradictorily, time management may not be viewed similarly in academia. However, as a PhD your motive has been to complete your program in time. This acts as a serious motivation to develop excellent time management skills.

4. Attention to Detail

One of the essential core skills of a PhD is paying attention to the details. To the best of your experience as a researcher, you are aware that mistakes can be missed in the bat of an eye. Therefore, it is a known fact that PhDs are one of the finest people to make sure that each project runs through a fine-tooth comb. As a result, employers can count on you for detail-oriented assignments that require critical assessment and corrections.

5. Ability to Collaborate

As stated earlier, PhDs are not new to working in groups to achieve common goals. Your significant contribution in research groups, as a researcher and author during your PhD program demonstrates your ability to collaborate . Employers seek candidates who are team players making positive contributions to the success of a group.

6. Writing Proficiency

Given the nature of modern technology, writing may not be a primary task of most job profiles. However, it sure is an essential element for academic and allied knowledge dissemination careers. In due course of pursuing a PhD, you come across countless reading material from authors all around the world. This subsequently stocks up your bank of vocabulary and enhances your writing skills for an unambiguous conveyance of messages and information.

7. Leadership Skills

Leadership skills aren’t only your ability to supervise and manage a team, but to take the lead on a project and get a team to follow through and achieve goals. As a PhD you’re the “lead” for your project. While it doesn’t necessarily involve leading other people, it still means being responsible for major decisions to accomplish targets. Additionally, it is common for PhD students to work in research groups and collaborate on shared projects. Nonetheless, they also demonstrate leadership while organizing conferences and seminars for their department or university. PhDs are also seen showing leadership skills while advising students and mentoring peers.

8. Critical Thinking and Analysis

As a PhD, it’s a given that you are able to analyze data and provide logical reasoning to it. Throughout your program, you collect data, analyze it, and draw conclusions. The ability of a PhD to critically examine everything and deliver logical reasoning behind it is not new to anyone. A PhD is well versed with 360-degree logical thinking without being biased. Employers seek these research transferable skill of a PhD to consider alternative solutions to a problem and suggest next steps for efficient functioning.

9. Communication Skills

This is the master of PhD transferable skills. Even if you decide to step into a career that is a 180-degree sweep from your PhD, you’d still need to communicate! Your ability to communicate efficiently is developed right from preparing for your PhD interview, presenting papers and posters at academic conferences, defending your thesis, etc. As verbal communication affects your ability to work with your peers, it is one of the most sought after research transferable skills by employers.

10. Adaptability

A PhD isn’t only about specialization. Rather, it’s about the ability to specialize. During your PhD you learn to tackle a new topic, solve it, and move on to the next problem. Almost all careers require employees to focus on specific topics and projects in detail to achieve a specific goal. Your ability of in-depth specialization in academic research project demonstrates adaptability and flexibility —quite literally!

So the next time you are asked, “What skills do you bring to this position?”, you certainly know how to answer that! Brush up your PhD transferable skills to help you make the right career switch. Remember that your PhD isn’t a liability after all. In fact, it’s an asset! Let us know how you acquired these valuable skills that are highly sought after by employers today.

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The 7 Essential Transferable Skills All PhDs Have

During your PhD, you’re not just learning about your research topic. You’re also learning core skills that apply to jobs both in and out of academia. Most institutions don’t teach you to articulate these transferable skills in a way that aligns with how they’re described in the business world. Knowing your skills increases your value as a candidate.

Written Communication

It takes practice to become a good writer. Fortunately, as PhD student you have years of practice writing papers, conference abstracts, journal manuscripts, and of course your dissertation. The feedback you receive from your supervisor and peer reviewers will help improve your communication skills.

Research skills are valuable even in many fields outside of academia. As a trained researcher, you are able to determine the best approach to a question, find relevant data, design a way to analyze it, understand a large amount of data, and then synthesize your findings. You even know how to use research to persuade others and defend your conclusions.

Public Speaking                   

Strong oral communications skills are always valued, and PhD students get more public speaking opportunities than most. Through conference talks, poster presentations, and teaching, you will learn to feel comfortable in front of a larger audience, engage them, and present complex ideas in a straightforward way. Winning a teaching award or being recognized as the best speaker at a conference is a concrete way to prove your public speaking skills.

Project Management

Even if you’re not working as a project manager, every job requires some degree of project management. Fortunately, a PhD is an exercise in project management. Finishing your dissertation requires you to design a project, make a realistic timeline, overcome setbacks, and manage stakeholders. During this time, you will also have to manage long-term projects at the same time as short-term goals which requires strong organizational skills.

Mentoring and teaching are the two main way PhD student can learn leadership and management skills. As a teacher or mentor, you have to figure out how to motivate someone and help them accomplish a goal. You also get experience evaluating someone’s performance (grading) and giving constructive feedback.

Critical Thinking

Every PhD student learns critical thinking skills whether they realize it or not. You are trained to approach problems systematically, see the links between ideas, evaluate arguments, and analyze information to come up with your own conclusions. Any industry can benefit from someone who knows “how to think”.

Collaboration

Very few jobs require you to work completely independently, and academia isn’t one of them. Your dissertation is a solo project, but on a day to day basis you work with other people on your experiments or preparing a journal manuscript. Doing these tasks successfully requires knowing how to divide up a task, get along with others, communicate effectively, and resolve conflict.

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• CAREER COLUMN
• 15 December 2021

‘Hard’ skills from our PhDs remain relevant beyond academia

• Jonathan McGuire 0 &
• Samantha Baggott 1

Jonathan McGuire is director of data and analytics at the National Disability Insurance Scheme (NDIS) Quality and Safeguards Commission in Sydney, Australia.

You can also search for this author in PubMed   Google Scholar

Samantha Baggott is assistant director of data and analytics at the National Disability Insurance Scheme (NDIS) Quality and Safeguards Commission in Sydney, Australia.

When we first started looking at non-academic career options after our PhDs in cognitive science, it seemed that it was our ‘soft’ skills that would transfer beyond academia to the ‘real world’ — things such as resilience, critical thinking, communication and collaboration. These do transfer, of course, but after being on the other side of the recruitment process in management roles at a government agency, we now think this undersells the more academic skills developed during a PhD.

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doi: https://doi.org/10.1038/d41586-021-03756-0

This is an article from the Nature Careers Community, a place for Nature readers to share their professional experiences and advice. Guest posts are encouraged .

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The top 3 skills needed to do a PhD are skills employers want too

Senior Lecturer and Academic Lead, University of Sydney

Associate Professor, Macquarie University

Disclosure statement

Lilia Mantai is an Executive Member of the Australasian Council for Undergraduate Research (ACUR), a non-for-profit association promoting undergraduate research.

Mauricio Marrone developed the data dashboard and is the founder of ResGap.com.

Macquarie University and University of Sydney provide funding as members of The Conversation AU.

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More and more people are applying to do a PhD. What many don’t know is it takes serious skills to do one – and, more importantly, complete it.

We analysed the selection criteria for PhD candidates on a platform that advertises PhD programs. Our analysis of thousands of these ads revealed exactly what types of skills different countries and disciplines require.

Why do a PhD in the first place?

People pursue a PhD for many reasons. They might want to stand out from the crowd in the job market, learn how to do research, gain a deeper expertise in an area of interest, or pursue an academic career.

Sadly, too many PhD students never finish. The PhD turns out to be too hard, not well supported, mentally taxing, financially draining, etc. Dropping the PhD often means significant financial loss for institutions and individuals, not to mention the psychological costs of other consequences such as low self-esteem, anxiety and loneliness .

Read more: 1 in 5 PhD students could drop out. Here are some tips for how to keep going

Our society and economy can only benefit from a better-educated workforce, so it is in the national interest to manage PhD intakes and be clear about expectations. The expansion of doctoral education led to a more competitive selection process, but the criteria are opaque.

To clarify PhD expectations, we turned to a European research job platform supported by EURAXESS (a pan-European initiative by the European Commission) where PhD programs are advertised as jobs. Required skills are listed in the selection criteria. We analysed 13,562 PhD ads for the types of skills different countries and disciplines require.

We made three specific findings.

1. Top 3 skills needed for a PhD

It turns out that it takes many so-called transferable skills to do a PhD. These are skills that can be translated and applied to any professional context. The top three required skills are:

communication – academic writing, presentation skills, speaking to policy and non-expert audiences

research – disciplinary expertise, data analysis, project management

interpersonal – leadership, networking, teamwork, conflict resolution.

Trending skill categories are digital (information processing and visualisation) and cognitive (abstract, critical and creative thinking and problem-solving).

Previous research shows transferable skills are requested for post-PhD careers, including both academic and non-academic jobs. Our research shows such skills are already required to do a PhD. Those keen to do a PhD are well advised to provide strong evidence of such skills when applying.

2. Skill demands vary by country and discipline

Skill demands significantly differ by country and discipline. For example, 62% of medical science ads mention interpersonal skills. This is twice as often as in biological science ads. Digital and cognitive skills score much higher in the Netherlands than in other countries.

Our research article reports on 2016-2019 data and the top five represented countries (Netherlands, Germany, France, Spain and the UK) and the top five represented disciplines (biological sciences, physics, chemistry, engineering and medical sciences). However, you can use this tool for granular detail on 52 countries – including non-European countries like Australia, New Zealand, the US, etc. – and 37 disciplines included in the data sample. For continuously updated data, please visit https://www.resgap.com/ .

3. PhD expectations are rising

We see a rise in PhD expectations over time (2016-2019) as more skills are listed year on year. The publish or perish culture prevails and rising demands on academics have led to calls for more engaged research, collaborations with industry, and research commercialisation .

PhD students get accustomed early to competitiveness and high expectations.

Read more: Is it a good time to be getting a PhD? We asked those who've done it

Research-based learning needs to start early

These insights have implications for pre-PhD education and pathways. Undergraduate and postgraduate degrees can further promote PhD readiness by embedding authentic hands-on research with academic or corporate partners, either as part of the curriculum or as extracurricular activities.

Many postgraduate degrees offer authentic research project work opportunities but are shorter. Those entering the PhD without a postgraduate degree miss out on developing essential research skills.

Authentic research experiences need to happen early on in higher education. Organisations like the Council on Undergraduate Research ( CUR ), the Australasian Council for Undergraduate Research ( ACUR ) and the British Conference of Undergraduate Research ( BCUR ) are designed to support institutions and individuals to do this effectively. They showcase great models of undergraduate research.

To get a good idea of what undergraduate research looks like, start with this comprehensive paper and catch up on undergraduate research news from Australasia .

We know research-based learning develops employability skills such as critical thinking, resilience and independence.

Embed career development in PhD programs

Doctoral training needs to take note, too, if it is to further build on the skill set that PhD applicants bring with them.

The good news is doctoral education has transformed in recent decades. It’s catching up to the call for better-skilled graduates for a range of careers. The training focus has shifted towards generating practice-based and problem-solving knowledge, and engaged research with other sectors.

Read more: It's time to reduce the number of PhD students, or rethink how doctoral programs work

Some institutions now offer skill and career training. Generally, though, this sort of training is left to the graduates themselves. Many current PhD candidates will attest that the highly regulated and tight PhD schedule leaves little room for voluntary activities to make them more employable.

Most PhD candidates also know more than half of them will not score a long-term academic job. Institutions would serve them better by formally embedding tailored career development opportunities in PhD programs that prepare for academic and non-academic jobs .

It’s not only PhD graduates’ professional and personal well-being that will benefit but also the national economy.

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6 Essential Research Skills to Excel in a Clinical Research PhD Program 

Blog summary .

• Introduction 
• 1. Mastering Literature Review 
• 2. Proficiency in Experimental Design 
• 3. Skills in Data Collection 
• 4. Communicating Findings Effectively 
• 5. Emphasizing Collaboration and Networking 
• 6. Adaptability and Innovation 
• Challenges in Developing Research Skills 

Dreaming of a fulfilling career in clinical research?

Introduction  .

Beginning a PhD program in clinical research requires a deep comprehension of the area’s complexities, making it a complicated intellectual endeavour. This introduction explores the fundamentals of a PhD programme in clinical research and highlights the significance of developing certain research abilities. As we explore the critical components that define success in this academic pursuit, it becomes evident that mastering these skills contributes to educational excellence and prepares individuals for impactful contributions in the dynamic realm of clinical research. 

1. Mastering Literature Review  

Mastering the art of literature review is paramount for any individual pursuing a PhD in Clinical Research . Beyond the basics, efficient utilization of online databases is a skill that will be frequented throughout the program. Aspiring researchers should become adept at navigating platforms like PubMed, Scopus, and Google Scholar to access the latest and most relevant literature. 

Critical analysis techniques play a crucial role in this skill set. Evaluating the credibility and relevance of sources, identifying key themes, and synthesizing information are essential aspects of constructing a robust theoretical framework for research studies. The literature review sets the stage for formulating research questions and hypotheses, making it a cornerstone skill. 

2. Proficiency in Experimental Design  

At the core of any research endeavour lies the design of experiments. Crafting clear and testable hypotheses is a fundamental aspect of this skill. As individuals pursue a PhD in Clinical Research, the ability to choose suitable methodologies and plan statistical analyses becomes increasingly critical. 

The selection of appropriate methodologies depends on the nature of the research—whether qualitative, quantitative, or a combination of both. This decision shapes the data collection methods and, consequently, the reliability and validity of the research findings. Proficiency in statistical analysis is crucial for drawing meaningful conclusions and ensuring the overall rigour of the study. 

Proficiency in experimental design is essential for success in clinical research PhD programs , as it empowers individuals to craft clear hypotheses, select appropriate methodologies, and plan statistical analyses, thereby ensuring the reliability and validity of research findings.

3. Skills in Data Collection  

Accurate and reliable data collection is the bedrock of successful clinical research. The selection of appropriate instruments, ensuring data accuracy, and navigating ethical considerations are integral components of this skill. As individuals pursuing a PhD in Clinical Research, these aspects are vital in producing research that stands up to scrutiny. 

Choosing the suitable instruments involves a meticulous evaluation of their validity and reliability. Researchers should align instruments with research objectives, ensuring they provide trustworthy data. Ensuring data accuracy demands attention to detail and adherence to standardized protocols, while ethical considerations necessitate a keen awareness of participants’ rights and ethical guidelines. 

4. Communicating Findings Effectively  

Even groundbreaking research remains incomplete without effective communication. Crafting clear and concise research reports, developing compelling visuals, and honing presentation skills for conferences are indispensable subtopics within this skill. 

The ability to craft clear research reports involves structuring information logically and ensuring the narrative flows seamlessly. Researchers should communicate their findings in a manner accessible to experts and non-experts, emphasizing the practical implications of the research. 

Presentation skills for conferences are essential in disseminating research findings. Individuals pursuing a PhD in Clinical Research should be prepared to articulate their work confidently, engage with the audience effectively, and participate in meaningful discussions. 

5. Emphasizing Collaboration and Networking  

Clinical research is inherently collaborative, making building professional relationships, active participation in research communities, and fostering teamwork essential to success. As individuals pursue a PhD in Clinical Research, the ability to collaborate becomes a valuable asset. 

Building professional relationships involves networking with colleagues, mentors, and professionals in the field. Networking opportunities arise at conferences, workshops, and collaborative research projects. Building a solid professional network opens doors for information sharing and possible teamwork on upcoming research projects. 

Active participation in research communities, whether local or virtual, allows individuals to stay informed on current trends, share insights, and seek advice from peers. The collective wisdom of a research community can significantly enhance individual research endeavours. 

Active participation in online PhD in clinical research programs offers invaluable networking opportunities, enabling students to build professional relationships, stay abreast of current trends, and leverage the collective wisdom of virtual research communities for enhanced academic success.

6. Adaptability and Innovation  

The research landscape is dynamic, requiring researchers to navigate changes, embrace technological advancements, and foster innovations in clinical research. Adaptability and innovation are indispensable subtopics within this skill set. 

Navigating changes in the research landscape involves staying informed about emerging methodologies, technologies, and trends. As individuals pursuing a PhD in Clinical Research, researchers should be proactive in updating their skills and methods to stay at the forefront of advancements in their field. 

Embracing technological advancements enhances the efficiency and precision of research activities. Investigating the combination of virtual reality, artificial intelligence, and data analytics can improve the calibre of data gathering, processing, and sharing. 

Don’t miss out on exploring our insightful blog on “ Current Trends in Quality Assurance of Clinical Research ” to gain deeper insights into ensuring the integrity and excellence of research practices in the field.

Challenges in Developing Research Skills  

While developing research skills is rewarding, it is not without challenges. Overcoming common obstacles and strategies for skill enhancement are vital aspects of this subtopic. As individuals pursue a PhD in Clinical Research, acknowledging and addressing these challenges is key to success.  Common obstacles in developing research skills include time constraints, resource limitations, and the complexity of research methodologies.

Researchers should approach these challenges with resilience, seeking solutions and prioritizing continuous improvement.  Developing new skills requires a dedication to lifelong learning , looking for mentorship, and taking advantage of professional development opportunities. It is crucial for people pursuing a PhD in clinical research to adopt a growth attitude and acknowledge that skill improvement is a continuous process. 

Conclusion  

Mastering the essential research skills this comprehensive guide outlines is paramount for success in a Clinical Research PhD Program. These skills collectively shape well-rounded researchers, ranging from the meticulous art of literature review to proficiency in experimental design, data collection, effective communication, collaboration, and adaptability. Beyond academic excellence, these competencies prepare individuals for impactful contributions in the dynamic landscape of clinical research.  

As aspiring PhD candidates navigate the challenges inherent in skill development, acknowledging and addressing obstacles while embracing continuous learning and a growth mindset is key. By doing so, individuals not only overcome challenges but also position themselves as adept professionals ready to innovate and lead in the evolving field of clinical research. 

Turn your dreams into reality by mastering critical research skills.

The program primarily focuses on advanced research methodologies and applications within clinical research. 

Mastering the literature review is vital as it forms the foundation for constructing robust theoretical frameworks, research questions, and hypotheses. 

Effective communication is crucial for crafting clear research reports, developing visuals, and honing presentation skills, ultimately enhancing the impact of research. 

Because clinical research is collaborative by nature, networking with other professionals and participating in research communities can help exchange knowledge and encourage future collaboration. 

Strategies include a commitment to continuous learning, seeking mentorship, and actively engaging in professional development to address time and resource limitations. 

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Career opportunities for a clinical research scientist, explore career opportunities in alternative medicine, value of an online emba for your career growth, career and financial prospects of clinical research scientists, related posts, the purpose of studying phd in clinical research, from awareness to action: pursuing a phd in clinical research, 7 time management hacks every clinical research phd student should master , explore the current trends in quality assurance of clinical research.

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7 resources to help phd students succeed on their doctoral journey.

It takes a village and a variety of skills to succeed in the doctoral world. Here are a few of the many resources Wharton Doctoral Programs offers to help.

Like most of our doctoral students, perhaps you’re preparing to go into academia after completing your PhD. Being a professor and researcher today often involves opportunities to share your research with a larger audience than a classroom of students. The doctoral journey is meant to prepare you with the wide array of skills you’ll need to be effective whether you’re in front of the classroom or a conference stage.

That includes the polish to present and speak publicly with ease, the writing and communication skills to craft your dissertation and journal articles, the analytical know-how to research thoroughly and gather meaningful data, and the ability to teach — colleagues, pupils, or the general public, whatever the case may be. And, if you have family, you’ll need support in getting them through this journey with you.

Wharton Doctoral Programs offers a wide range of resources to help you thrive in the PhD program and prepare you for life beyond it. Here are a few of the top Wharton resources our students have highlighted as most beneficial:

1. 5 Slides 5 Minutes

Researchers often have the opportunity to share their work with a larger audience through social media and mass media outlets — but it requires nuanced communication skills. How do you take complex findings and communicate them to a general audience concisely without oversimplifying the message?

That’s the focus of 5 Slides 5 Minutes. Launched in 2014, this low-stakes, high-potential event enables PhD students to present an abstract to students, faculty, and staff to practice engaging non-experts in their research topic. Students receive an invitation to participate via email from the Doctoral Programs Office.

After students present, they can work with Wharton Communications Program to review their presentation and get tips on how to improve their communication skills. Wharton’s renowned faculty also share valuable insights with students about these presentations.

“We focus on individuals. We help them convey their research content most effectively given their style and personality,” said Lisa Warshaw, Director of the Wharton Communications Program.

2. Dissertation Boot Camp

The name might sound intimidating, but some students think of Dissertation Boot Camp as a two-week writers’ retreat. Hosted twice a year by the Graduate Student Center, it’s designed for students who have dissertation status but haven’t presented their proposal yet.

The camp offers an environment and support for intense, focused writing time as well as a review on the steps, deadlines, and University policies. Limited to 20 students, the small group gives writers a chance to make connections with others who are going through the dissertation process and provides participants with the structure and motivation to overcome typical roadblocks along the way.

3. Wharton Communications Program

The Wharton Communication Program helps Wharton PhD students become more effective communicators and thus better presenters, public speakers, and writers — all critical skills in academia. All doctoral students are provided with access to on-site, one-on-one writing coaching during the academic year.

Wharton PhD students are required to attend two workshops: First-Year Communications Workshop in the fall and First-Year Writing Workshop in the spring. The skills-based approach adopted in the workshops helps students develop their personal style and strengthen their confidence as communicators.

Through multiple practice opportunities, video recording of speeches, and rigorous feedback, the program provides students with a thorough foundation in communication theory and for doctoral students, focuses on research presentations and job talks.

4. Teacher Development Program Workshop

Offered in conjunction with the Center for Teaching and Learning , the Teacher Development Program is a four-session course. It gives doctoral students a foundation in core teaching practices to support their teaching at Penn.

By helping with presentation skills and academic job placement, the workshop prepares students to become faculty in the future. Ian Petrie , Senior Associate Director, Center for Teaching and Learning described the workshop as “a collective, collaborative program.” Each week features “microteaching” demonstrations, where participants conduct a brief lesson and get feedback from their peers and the directors.

The intent is that faculty and graduate students will engage and learn from each other to master fundamental teaching methods. “Every PhD student can leave the program having gained some new tools for teaching,” Petrie said. This exchange happens when doctoral students observe “talented colleagues from other departments to get a glimpse of how they teach.”

Students also have the opportunity to enroll in the CTL Teaching Certificate program to hone teaching skills and grasp a commitment to developing as teachers.

“I’d like everyone to come out of the experience feeling more confident about their skills as an instructor or presenter,” Petrie said. “Anything I can do to support doctoral students in achieving their goals is extremely gratifying.”

5. Wharton Research Data Services (WRDS)

With more than 50,000 corporate, academic, and government users, Wharton Research Data Services (WRDS) is the global gold standard in data management, research analytics, and thought leadership. Researchers at more than 450 institutions in 36 countries across the globe depend upon this award-winning research platform and business intelligence tool — and researchers are doing the work to grow it right here on Wharton’s campus.

“The fact that the people who create the data, research analytics, and tools are here is super important,” said Prof. Cathy Schrand, Vice Dean of Wharton Doctoral Programs. “I’ve had early access to WRDS before it even became available to other subscribers. Top universities all over the world that have subscriptions to WRDS may only have access to certain elements of it, but we have access to all of it and it’s here on site which does provide an advantage.” The platform allows researchers to access more than 350 terabytes of data in one location that spans across multiple disciplines, including accounting, banking, economics, ESG (environmental, social, and governance), finance, health care, insurance, marketing, and statistics. “WRDS is by far the most important source of datasets for academic researchers. As a Wharton PhD student, you automatically get unrestricted access to every one of these databases,” said Itamar Drechsler, associate professor of finance at Wharton and NYU’s Stern School of Business, who has experience on both sides of the classroom – he earned his PhD from Wharton in 2009.

6. Wharton Behavioral Lab

A shared resource for all Wharton faculty, the Wharton Behavioral Laboratory (WBL) provides a variety of services that support data collection for behavioral research on business-related topics. The primary goal is to enhance the research productivity of Wharton faculty by minimizing the operational costs, both time and money, of conducting research. With two locations — one in Steinberg Hall Dietrich Hall and another in Jon Huntsman Hall, doctoral students can gather original data through lab experiments and panels, instead of using secondary data created by others. Each year, the lab collects about 23,000 subject hours of data. Research from WBL can consistently be found in national and international publications such as the Journal of Behavioral Decision Making, the Journal of Experimental Psychology: General, Proceedings of the National Academy of Sciences, the Journal of Neuroscience, Psychology, and Economics, and the Journal of Business Ethics .

7. Support for Families

For some PhD students, attending Wharton means relocating their families to a new city. To help students and their families ease the transition to PhD life, the Wharton Doctoral Program Office hosts the Maternity/Paternity Workshop , an annual event that talks about the resources available to PhD students with families.

Here are a couple of the key resources they highlight in the workshop:

• The Doctoral Programs Office allows eligible students to apply for up to one year of additional school-level funding beyond their allotted funded year. Furthermore, students are eligible for up to eight weeks of time-off for childbirth and adoption and have the option of taking unpaid Family Leave of Absence.
• At Penn, the Family Resource Center provides additional resources and facilities, such as a children’s playroom and two private lactation rooms, which cater to the needs of students with families. The Center also has two grant programs for PhD students to help offset the cost of childcare and family expenses, and health insurance for dependents.
• Wharton Doctoral Partners & Families is a student-run online resource created to communicate the resources at Penn and Philadelphia to partners and families. Its mission is to empower members to transition and settle into their new lives.

Posted: November 6, 2018

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Doctoral Programs

Start your doctoral journey.

Whether you’re just starting your research on PhD programs or you’re ready to apply, we’ll walk you through the steps to take to become a successful PhD candidate.

Deciding to get a PhD

You might be surprised to find out what you can do with a PhD in business.

Is an Academic Career for You ? What Makes a Successful PhD Student

Preparing for the Doctoral Path

The skills, relationships, and knowledge you need to prepare yourself for a career in academics.

How the PhD Program Works How to Become a Successful PhD Applicant

Choosing the right program

What’s the difference between PhD programs? Find out how to choose one that fits your goals.

What to Consider When Choosing a Doctoral Program

Starting an application

Tips for a successful application process.

Application Requirements Preparing Your PhD Application

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A Nontraditional Applicant Gets the Call

• Transferable PhD Skills You Can Use in Any Career
• After a PhD
• Having a PhD demonstrates that you have a host of skills desirable for employers, allowing you to pursue a non academic career path.
• Transferable skills from a PhD include interpersonal skills, work ethic, problem-solving, time management, independence & responsibility, adaptability and report writing.
• It is important to sell yourself to potential employers by identifying and relating these transferable skills to the job you are applying for.

This page will explain how your PhD has prepared you for a career outside of academia, and how to make the most of your transferable skills when looking for a job.

Can PhD Doctorates Work in Any Role?

A common misconception we hear is that individuals with PhDs must pursue a career in academia. This is usually due to a lack of industrial work experience PhD students have upon obtaining their doctorate. However, this is not the case as one of the key benefits of a PhD is the transferable skills it brings.

Transferable Skills from A PhD

By completing a PhD you will have demonstrated several skills which make you desirable for employers. It is essential that you recognise these skills and can use them to sell yourself in your CV .

Transferable skills from a PhD include:

Communication

Throughout your PhD, you will have been required to work with others, be it supervisors or examiners. You will also have been required to communicate your ideas (often complex and detailed theories) succinctly and to those with less background knowledge than you. Communication skills are essential in the workplace, regardless of the job, as it shows the ability to work in a team effectively .

Completing a PhD is no easy task. In doing so, you have shown a drive to ‘ get the job done ’.

Problem Solving

Throughout your PhD, you will have encountered several problems you overcame. Use these as examples to show your ability to use creative thinking  to devise  solutions  to these problems.

Data Analysation

Most PhD research projects will involve some degree of data analysation. The ability to interpret complex information and identify relevant data is a valuable skill in numerical fields such as science and engineering. You are also likely to have developed your research skills which shows you can identify types of bias, anomalies and trends which is useful in statistical roles such as accounting.

Time Management

An important skill in the workplace is the ability to  prioritise and organise   tasks . With your PhD degree, you should be able to convince potential employers that you can establish realistic timelines and remain to deadlines. You are also able to engage in both short and long term planning . Time management skills are particularly useful for those pursuing project management or leadership roles.

Independence & Responsibility

Perhaps one of the most important things you have shown throughout your research project is your ability to take responsibility  for your  development . A potential employer should see you as someone who does not need constant instructions, but someone who can take ownership of problems and resolve them using their own  independent judgement .

Adaptability

It is unlikely that you will have stuck to your original plan. Things happen and you will have been required to adapt on the fly during your PhD. This is common transferable skill employers are looking for if they operate in volatile markets.

Report Writing

You have been able to summarise approximately three years or more worth of work in a single thesis. This shows your ability to filter through massive amounts of information, identify the key points , and get these points across to the reader. The ability to ‘cut out the waffle’ or ‘get to the point’ is a huge asset in the professional industry.

Useful Phrases To Demonstrate Your Skills

From the above list, it’s clear that a PhD provides you with a host of transferable skills employers look for in candidates. The key is to relate these skills to the job you are applying for.

To help you with this, we’ve put together a few common examples of phrases we hear from doctorates that can be refined for job-seeking purposes. It’s imperative not to stretch the truth or to mislead them but focus on convincing your potential employers how your PhD has prepared you for the role you are applying for.

Other Specialist Skills

Aside from these PhD transferable skills, you may have also developed expertise in more specialised areas of knowledge . For example, as part of your PhD were you required to use Computer Programming? Were you required to use Medical Equipment? Did you organise events? Not only are these skills in themselves, but they have inherent  soft skills  too.

Make sure you get these skills across to your potential employer as they will help demonstrate how valuable you are.

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Doctor of Philosophy in Education

Additional Information

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The Harvard Ph.D. in Education trains cutting-edge researchers who work across disciplines to generate knowledge and translate discoveries into transformative policy and practice.

Offered jointly by the Harvard Graduate School of Education and the Harvard Kenneth C. Griffin Graduate School of Arts and Sciences, the Ph.D. in Education provides you with full access to the extraordinary resources of Harvard University and prepares you to assume meaningful roles as university faculty, researchers, senior-level education leaders, and policymakers.

As a Ph.D. candidate, you will collaborate with scholars across all Harvard graduate schools on original interdisciplinary research. In the process, you will help forge new fields of inquiry that will impact the way we teach and learn. The program’s required coursework will develop your knowledge of education and your expertise in a range of quantitative and qualitative methods needed to conduct high-quality research. Guided by the goal of making a transformative impact on education research, policy, and practice, you will focus on independent research in various domains, including human development, learning and teaching, policy analysis and evaluation, institutions and society, and instructional practice.   

Curriculum Information

The Ph.D. in Education requires five years of full-time study to complete. You will choose your individual coursework and design your original research in close consultation with your HGSE faculty adviser and dissertation committee. The requirements listed below include the three Ph.D. concentrations: Culture, Institutions, and Society; Education Policy and Program Evaluation; and Human Development, Learning and Teaching . 

We invite you to review an example course list, which is provided in two formats — one as the full list by course number and one by broad course category . These lists are subject to modification. 

Ph.D. Concentrations and Examples

Summary of Ph.D. Program

Doctoral Colloquia  In year one and two you are required to attend. The colloquia convenes weekly and features presentations of work-in-progress and completed work by Harvard faculty, faculty and researchers from outside Harvard, and Harvard doctoral students. Ph.D. students present once in the colloquia over the course of their career.

Research Apprenticeship The Research Apprenticeship is designed to provide ongoing training and mentoring to develop your research skills throughout the entire program.

Teaching Fellowships The Teaching Fellowship is an opportunity to enhance students' teaching skills, promote learning consolidation, and provide opportunities to collaborate with faculty on pedagogical development.

Comprehensive Exams  The Written Exam (year 2, spring) tests you on both general and concentration-specific knowledge. The Oral Exam (year 3, fall/winter) tests your command of your chosen field of study and your ability to design, develop, and implement an original research project.

Dissertation  Based on your original research, the dissertation process consists of three parts: the Dissertation Proposal, the writing, and an oral defense before the members of your dissertation committee.

Culture, Institutions, and Society (CIS) Concentration

In CIS, you will examine the broader cultural, institutional, organizational, and social contexts relevant to education across the lifespan. What is the value and purpose of education? How do cultural, institutional, and social factors shape educational processes and outcomes? How effective are social movements and community action in education reform? How do we measure stratification and institutional inequality? In CIS, your work will be informed by theories and methods from sociology, history, political science, organizational behavior and management, philosophy, and anthropology. You can examine contexts as diverse as classrooms, families, neighborhoods, schools, colleges and universities, religious institutions, nonprofits, government agencies, and more.

Education Policy and Program Evaluation (EPPE) Concentration

In EPPE, you will research the design, implementation, and evaluation of education policy affecting early childhood, K–12, and postsecondary education in the U.S. and internationally. You will evaluate and assess individual programs and policies related to critical issues like access to education, teacher effectiveness, school finance, testing and accountability systems, school choice, financial aid, college enrollment and persistence, and more. Your work will be informed by theories and methods from economics, political science, public policy, and sociology, history, philosophy, and statistics. This concentration shares some themes with CIS, but your work with EPPE will focus on public policy and large-scale reforms.

Human Development, Learning and Teaching (HDLT) Concentration

In HDLT, you will work to advance the role of scientific research in education policy, reform, and practice. New discoveries in the science of learning and development — the integration of biological, cognitive, and social processes; the relationships between technology and learning; or the factors that influence individual variations in learning — are transforming the practice of teaching and learning in both formal and informal settings. Whether studying behavioral, cognitive, or social-emotional development in children or the design of learning technologies to maximize understanding, you will gain a strong background in human development, the science of learning, and sociocultural factors that explain variation in learning and developmental pathways. Your research will be informed by theories and methods from psychology, cognitive science, sociology and linguistics, philosophy, the biological sciences and mathematics, and organizational behavior.

Program Faculty

The most remarkable thing about the Ph.D. in Education is open access to faculty from all Harvard graduate and professional schools, including the Harvard Graduate School of Education, the Faculty of Arts and Sciences, the Harvard Kennedy School, the Harvard Law School, Harvard Medical School, and the Harvard School of Public Health. Learn about the full Ph.D. Faculty.

Jarvis R. Givens

Jarvis Givens studies the history of American education, African American history, and the relationship between race and power in schools.

Paul L. Harris

Paul Harris is interested in the early development of cognition, emotion, and imagination in children.

Meira Levinson

Meira Levinson is a normative political philosopher who works at the intersection of civic education, youth empowerment, racial justice, and educational ethics. 

Luke W. Miratrix

Luke Miratrix is a statistician who explores how to best use modern statistical methods in applied social science contexts.

Eric Taylor

Eric Taylor studies the economics of education, with a particular interest in employer-employee interactions between schools and teachers — hiring and firing decisions, job design, training, and performance evaluation.

Paola Uccelli

Paola Ucelli studies socio-cultural and individual differences in the language development of multilingual and monolingual students.

View Ph.D. Faculty

Dissertations.

The following is a complete listing of successful Ph.D. in Education dissertations to-date. Dissertations from November 2014 onward are publicly available in the Digital Access to Scholarship at Harvard (DASH) , the online repository for Harvard scholarship.

• 2022 Graduate Dissertations (265 KB pdf)
• 2021 Graduate Dissertations (177 KB pdf)
• 2020 Graduate Dissertations (121 KB pdf)
• 2019 Graduate Dissertations (68.3 KB pdf)

Student Directory

An opt-in listing of current Ph.D. students with information about their interests, research, personal web pages, and contact information:

Doctor of Philosophy in Education Student Directory

Introduce Yourself

Tell us about yourself so that we can tailor our communication to best fit your interests and provide you with relevant information about our programs, events, and other opportunities to connect with us.

Program Highlights

Explore examples of the Doctor of Philosophy in Education experience and the impact its community is making on the field:

Reshaping Teacher Licensure: Lessons from the Pandemic

Olivia Chi, Ed.M.'17, Ph.D.'20, discusses the ongoing efforts to ensure the quality and stability of the teaching workforce

Lost in Translation

New comparative study from Ph.D. candidate Maya Alkateb-Chami finds strong correlation between low literacy outcomes for children and schools teaching in different language from home

Current students

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• Graduate qualities

Researcher graduate qualities for the PhD

The researcher graduate qualities will assist you to develop the skills and knowledge you need to become an exceptional PhD researcher and get career-ready.

The University of Sydney has developed a set of graduate qualities to define and enrich the PhD, and support you to get ready for a post-doctoral career in industry or research.

The researcher graduate qualities focus on building deep disciplinary expertise and a range of broader, transferrable skills that will enhance your research activities and career possibilities.

The eleven qualities cover cultural competence, interdisciplinary effectiveness, professional, ethical, personal identity, influence, critical thinking and problem-solving, communication, information and digital literacy, inventiveness, engagement and project planning and delivery.

From 2021 onwards, early career researchers will have access to development activities including coursework, mentoring programs, workshops, global mobility experiences, self-reflection exercises and competitions, challenges or projects.

What this means for your candidature

The researcher graduate qualities have been designed to help guide students and supervisors through a student's PhD candidature. During your supervision meetings, the graduate qualities will provide you with a point-of-reference to contemplate your achievement of skills and experience as your candidature progresses, and to have a conversation with your supervisor about further development opportunities or training you may need while you complete your thesis project.

How to update your Research graduate qualities record

After your supervision meetings, you will need to log your graduate qualities discussion in RECS. Log into RECS , select ‘My project’, then ‘Researcher graduate qualities’. Here you can review previous submission by selecting the relevant date or you can add a new record. Once you have completed a new record, there is an option to send to your supervisor for comment.

The eleven qualities

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PhD transferable skills

Sometimes it's difficult for PhD students to identify what skills they have since the academic experience is not necessarily focused on articulating skill sets. We also often find that PhD students struggle, understandably, to present the transferability of their academic experiences to non-academic contexts. Here are examples of PhD skill sets and ways to describe them.

• Define a problem and identify possible causes
• Comprehend large amounts of information
• Form and defend independent conclusions
• Design an experiment, plan, or model that defines a problem, tests potential resolutions and implements a solution
• Facilitate group discussions or conduct meetings
• Motivate others to complete projects (group or individual)
• Respond appropriately to positive or negative feedback
• Effectively mentor subordinates and/or peers
• Collaborate on projects
• Teach skills or concepts to others
• Navigate complex bureaucratic environments
• Manage a project or projects from beginning to end
• Identify goals and/or tasks to be accomplished and a realistic timeline for completion
• Prioritize tasks while anticipating potential problems
• Maintain flexibility in the face of changing circumstances
• Identify sources of information applicable to a given problem
• Understand and synthesize large quantities of data
• Design and analyze surveys
• Develop organizing principles to effectively sort and evaluate data 
• Work effectively under pressure and to meet deadlines
• Comprehend new material and subject matter quickly
• Work effectively with limited supervision
• Prepare concise and logically-written materials
• Organize and communicate ideas effectively in oral presentations to small and large groups
• Write at all levels — brief abstract to book-length manuscript
• Debate issues in a collegial manner and participate in group discussions
• Use logical argument to persuade others
• Explain complex or difficult concepts in basic terms and language
• Write effective grant proposals

PhD prepared: research skill development across the undergraduate years

International Journal for Researcher Development

ISSN : 2048-8696

Article publication date: 9 May 2016

Many countries are looking for ways to enable students to engage more effectively with PhD study. This paper aims to consider the effects of explicit discipline-specific research skill development embedded in multiple semesters of an undergraduate degree on PhD preparedness.

Design/methodology/approach

This case study of one Bachelor of Health Science programme determined the effectiveness of the implementation of a conceptual model, the Researcher Skill Development framework, across the undergraduate degree programme. Data were gathered through interviews of 9 academic staff and 14 students in their fourth year of undergraduate study, which is a research-focused year.

All students and academics stated the benefits of the use of the Researcher Skill Development framework in undergraduate study including: deepening metacognition of research processes; assisting students toward acting and thinking like researchers; and the research-capacity building of the school. While all academics and all but one student recommended that the framework be used early in the degree programme, a number of interviewees specified problems with the existing implementation of the framework.

Research limitations/implications

While the results are not generalisable, the approach is worth studying in other degree programme-wide contexts to determine its broader capacity to enable students to be more research ready for PhD study when compared to current practice.

Practical implications

When adapted to the context, whole-of-degree research skill development may enable developing countries to have more students and developed countries to better prepared students commencing PhD studies.

Originality/value

No studies currently provide results for explicit research skill development across a degree programme, or of the benefits of this approach for PhD preparation.

• PhD preparation
• Research capacity building
• Researcher Skill Development

Willison, J. and Buisman-Pijlman, F. (2016), "PhD prepared: research skill development across the undergraduate years", International Journal for Researcher Development , Vol. 7 No. 1, pp. 63-83. https://doi.org/10.1108/IJRD-07-2015-0018

Emerald Group Publishing Limited

Copyright © 2016, John Willison and Femke Buisman-Pijlman Published by Emerald Group Publishing Limited.

This article is published under the Creative Commons Attribution (CC BY 3.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial & non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/3.0/legalcode

Introduction

Increasing the proportion of students commencing and completing PhD study is a priority in nations with developing higher education systems such as Cambodia ( Om, 2011 ), China ( OECD, 2008 ) and Fiji ( University of the South Pacific, 2013 ) or with large changes in university student demography, such as in South Africa ( Mafenya, 2014 ). In countries with established higher education systems, such as the USA, England and Australia, there is some controversy about whether there is a need for increased completion numbers or rather for students who are better prepared when commencing PhD and who complete it with a deeper and broader skill set ( DIISR, 2011 ). In all cases, strategies to nurture research skills well in advance of PhD are being sought and implemented in a range of contexts. Strategies to improve PhD preparedness come under the umbrella of undergraduate research and range from resource-intensive mentored summer scholarships to approaches that are based in the curriculum ( Jenkins and Healey, 2009 ). Studies have asserted the benefits of mentored undergraduate research experiences to increase PhD preparation ( Kardash, 2000 ; Lopatto, 2004 ); however, these have only been found to confirm a research-orientation in students already interested in postgraduate research; they do not seem to motivate students who were not considering this previously to participate ( Hunter et al. , 2007 ). Moreover, mentored internships do not reach all students, for example, those who may have latent capacities for postgraduate research. A few single-context studies have shown useful, but possibly short-lived, positive outcomes from the development of research skills in semester-length courses in the regular curriculum ( Chaplin, 2003 ; Hoskins et al. , 2007; Luckie et al. , 2004 ).

One promising approach to nurture research skills of all students in undergraduate degrees is the use of a conceptual model called the Research Skill Development framework ( Willison and O’Regan, 2006/2015 ) in curriculum and assessment design. Nine years after the first version of the Research Skill Development framework was published ( Willison and O’Regan, 2006/2015 , 2007 ), it is being piloted at the institution level in Australia ( Monash University, 2015 ), the USA ( University of Wisconsin Stout, 2015 ) and in nations of the Pacific ( University of South Pacific, 2013 ), as well as informing individual discipline approaches in countries as diverse as Cambodia ( Om, 2011 ) and England (Burkill, 2009).

Evaluation of use of the Research Skill Development framework

The Research Skill Development (RSD) framework has been used and evaluated in a number of individual semester-length course contexts in disciplines as different as Biomedical Sciences ( Munns and Chilton, 2014 ), Business ( Willison et al. , 2009a , 2009b ), Engineering ( Cochrane et al. , 2009 ), English ( Osborn, 2012 ), Nursing ( Pretorius et al. , 2013 ) and Physics ( Menke, 2013 ), as well as interdisciplinary studies ( Venning and Buisman-Pijlman, 2013 ). A multi-institution study showed that use of the RSD framework could effectively help individual educators and small teams to design semester-length courses that developed students’ discipline-specific research skills in many disciplines and year levels ( Willison, 2012 ). However, the study also showed that benefits of explicit research skill development could be lost unless there was follow-on explicit development. This paper presents the first study showing the impact of explicit and coherent research skill development and assessment embedded in the curriculum over the time span of an undergraduate degree programme ( Willison, 2012 ). Such studies are required to determine the long-term efficacy of upskilling and motivating undergraduate students toward PhD studies ( Salter and Atkins, 2014 ). A model that embeds research skill development in the curriculum is of particular interest because it has the potential to be more efficient and more equitable and has a broader reach than mentored undergraduate research models; there is also evidence that some research skills, such as posing researchable questions, may be better developed in-curriculum than in mentored models ( Willison, 2012 ).

The research presented here focused on the effectiveness of in-curriculum use of the RSD during the undergraduate degree in preparing students for PhD studies. Students were enrolled in a research-orientated, non-compulsory, fourth and final year of a Bachelor of Health Science, called the Honours year. Many students were exposed to the RSD during their undergraduate degree from the first year on. The Honours year embedded an extended version of the conceptual model, called the Researcher Skill Development (RSD7) framework ( Willison and O’Regan, 2008/2015 ). Next, the RSD7 is described, followed by the research context, methodology, results, discussion and conclusions.

Conceptual framework: the Researcher Skill Development framework

The RSD7 framework is based on the RSD ( Willison and O’Regan, 2006/2015 ), with the only difference being an extension of the original five-level continuum to seven levels of autonomy, and so it is called the RSD7 for short. The framework was extended to seven levels to bring in the unequivocally “capital R” research, so that the whole university community would be on the same continuum, from a first-year student to a high-profile professor.

An immediate benefit was the uptake of the RSD7 by academics involved in the Bachelor of Health Science to guide the assessment during the Honours years. The structurally similar five-level version of the framework, had not been taken up at Honours despite its use for six years in the Bachelor of Health Science with first-year students.

The RSD7 is a conceptual framework that is deliberately general in nature, so academics can adapt it to their context. It is a conceptual framework rather than, say, a rubric because it can be operationalised in many ways. The advantage of providing a more generic structure that can be adapted into more explicit rubrics was used in the VALUE rubric which was validated in a large range of degrees and institutions. This rubric was developed by the Association of American Colleges and Universities ( Rhodes and Finley, 2013 ), and its generic nature helped with the uptake in a large range of settings. The VALUE rubric does not provide a range of descriptors for the levels of student autonomy; however, the RSD7 was salient for the research-oriented year of this study due to its articulation of researcher autonomy.

The RSD7 framework has been used in numerous ways, such as facilitating conversations between PhD students and their supervisors ( Velautham and Picard, 2009 ); conversations with indigenous students about empowerment and knowledge; introducing students to necessary aspects of research processes; and for analysing teaching, learning and assessments elements in curricula. In this study, the prevalent mode of use was to scaffold the creation of marking rubrics.

This study evaluated the use of the RSD and the RSD7 to frame research skill development and assessment across a degree programme to prepare students for PhD study.

Facets of research

Embark and clarify : Researchers embark on research, determining and clarifying the need for knowledge while taking note of ethical, cultural and social/team considerations.

Find and generate : Researchers find information and generate data relevant to the research using appropriate methodologies.

Evaluate and reflect : Researchers evaluate information and data and reflect on all processes used.

Organise and manage : Researchers organise information and data, and manage the research process of individuals and of teams.

Analyse and synthesise : Researchers analyse information and data, and synthesise new knowledge to produce coherent individual and team understandings.

Communicate and apply : Researchers write, speak and perform the processes, understandings and applications of the research, and respond to feedback, mindful of ethical, cultural and social/team issues (based on Willison and O’Regan, 2006/2015 ).

The separation of research processes into six distinct facets is, of course, artificial, as these facets frequently co-occur and overlap. Moreover, research is often characterised by a lack of clarity, fuzziness and even messiness, and therefore, the process is certainly not linear. It may be that the neater, more coherent and linear final phase is most commonly reported in journal articles, but this hides the actual processes used in research into the unknown. However, delineating facets associated with research makes the processes involved explicit, and for many students this equates to being learnable. Delineation is a first step towards demystifying research.

Seven levels of student autonomy

A second step in demystification afforded by the RSD7 is to clarify how much scope students have in initiating research projects and determining processes, and in negotiating final solutions and communications. The specific task or assignment sets the boundaries of autonomy. Making student and supervisor expectations of scope and autonomy clear may be a major factor in a successful mentor-mentee relationship, and one for which the RSD7 has provided effective guidance ( Velautham and Picard, 2009 ). A common anecdotal complaint from students in the Bachelor of Health Science was that they were initially only given very limited amounts of autonomy in undergraduate courses, while they were expected to show independent research skills in Honours. This was also evident in one ( Drew et al. , 2002 ) but not in another ( Allan, 2012 ) study of Honours students.

In the RSD7, the amount of scope is called “Extent of Researcher Autonomy” and is represented as a continuum delineated by seven levels. Considering the end of the continuum with minimal autonomy, Prescribed Research (Level 1 of Figure 1 ), the supervisor models discipline-specific approaches of how to commence, including question framing, hypothesis posing and/or goal setting. The student-researcher follows highly prescriptive guidance, such as tightly defined procedures or guided readings.

Bounded Research (Level 2) requires some limited student-researcher decisions, for example a choice between two given methods. The shift from Prescribed Research to Bounded Research is not trivial, as some beginning researchers struggle when decisions are necessary or grey areas are to be considered.

With Scaffolded Research (Level 3), the parameters of the research are determined by the supervisor, but student-researchers will need to make numerous decisions about what do and so work with a high degree of independence within the parameters set.

The move to Level 4 is into the zone of “researcher instigated” and so has corresponding difficulties: Self-initiated Research describes a move that is instigated by the researcher, with support and advice provided by the supervisor. Researchers may, for example, identify gaps in the literature as the launching pad, select appropriate methodologies and apply analytical techniques, and the supervisor ensures that directions are attainable within the parameters of resources and time.

In Open Research (Level 5), the research is initiated and propelled by the researcher in his or her own direction using self-chosen methodologies and audiences. At this level of autonomy, supervisors provide advice rather than prescriptions. Parameters still exist in terms of disciplinary conventions, and so Open Research does not allow for lack of rigour, as the degree of rigour to be applied is appropriate to the year-level of study and disciplinary norms.

The move to Level 6 is into the realm of discipline leading. The distinctive feature of the move to Adopted Research is where directions chosen and outcomes of research are used by others in the field, for example, by citing, adopting methodologies, being informed by research outcomes or following gaps the researcher has identified.

Enlarging Research (Level 7) is where the researcher changes the nature of the conversation in the discipline, e.g. through a reconceptualisation of what is worth researching or in the development of major research methodologies. This is research that reshapes or enlarges the parameters of the discipline, or conceivably consolidates and refocuses its mandate. Individual researchers may participate in research teams that make a broad contribution that is widely cited or used, even when they themselves have their directions prescribed, bounded or scaffolded by supervisors. In a team then, different personnel may be operating at different levels of autonomy, depending on their roles. Here, individual contributions combine into something bigger than the sum of the parts because the research-leader is operating at a higher level, moving into areas that the field follows.

The six facets of research form the vertical axis of the RSD7 framework, and the seven levels of autonomy comprise the horizontal axis. The resulting table cells are populated with details appropriate to these facets for each specified level. The elaboration of the original framework to include Levels 6 and 7 and so bring in the “discipline leading” aspects of research was introduced in 2008 ( Willison and O’Regan, 2008 ). The RSD7 has been used early in PhD candidature ( Velautham and Picard, 2009 ), for doctoral education more generally ( Matas, 2012 ) and masters level ( Willison et al. , 2009a , 2009b ; Venning and Buisman-Pijlman, 2013 ), but not previously been considered in an undergraduate research context.

Research context

The research took place at School of Medical Science, which is part of a faculty of Health Sciences in one of the research-intensive universities in Australia. In this context, a “school” is an administrative umbrella for several cognate disciplines. The School teaches into the Bachelor of Health Sciences, Bachelor of Sciences, MBBS, Bachelor of Dentistry and Bachelor of Nursing and offers several postgraduate degrees. The School has a strong focus on Honours which, as noted, is the standard pathway to PhD study at the moment. In total, 39 academics and around 80 title-holders and affiliate staff, 35 Honours students and 57 PhD students were associated with the school at the time of conducting interviews.

The School had two early adopters who consistently used the five-level version of the RSD framework from 2005 with large first-year courses in which student numbers increased from 90 in 2005 to 400 in 2013. Uptake of the framework from 2005 occurred on the initiative of individual course coordinators in undergraduate courses. The second author had been working with the RSD7 from 2008 in postgraduate by coursework courses ( Venning and Buisman-Pijlman, 2013 ) and towards the end of 2011, initiated a conversation about the integration of the RSD7 through all the years of the degrees. The School quickly moved to use the RSD7 to conceptualise how to frame Honours-Year assessment in two of the three disciplines of the School commencing in February 2012 (with the third discipline following in 2013), and the resulting marking rubrics that were framed by the RSD7 are publicly available ( Medical Science Honours Marking Rubrics, 2012 ). The way the RSD7 was operationalised was to provide students with task-specific assessment criteria in matrices (rubrics) that are structured according to the six facets; these provide the grade descriptors for tasks, clarifying the expectations for an assignment at a certain year level and autonomy level ( Medical Science, 2012 ). Rubrics in the USA are typically used for quality control of the curriculum design at the university level ( Kuh et al. , 2014 ), but RSD-inspired rubrics were directly used at the School of Medical Science in this study with the intention of improving students’ research-oriented learning, including through the tools of assessment and feedback.

What are the benefits and disadvantages of the use of the RSD7-framed rubrics in the Honours year from academics’ and students’ perspectives?

What do Honours students and academics recommend about RSD/RSD7 use in the entire undergraduate degree programme?

Research method

Ethics approval for the study was gained from the University’s Human Research Ethics Committee, as part of a the larger study spanning different faculties, which was funded by an Australian Government grant from the Office of Learning and Teaching. Interviews were arranged and conducted in keeping with the ethics protocol in May and June 2012. After informed consent of participants was obtained in writing, the interviews of approximately 1 h duration were conducted face to face and audio recorded. A semi-structured interview protocol ( Wengraf, 2001 ) with 14 questions was used, having been piloted in other contexts ( Willison, 2012 ) and fine-tuned for this context. Criteria for reporting qualitative studies ( Tong et al. , 2007 ) were addressed in developing the methodology. Purposive sampling was used to gather interviewees with the intention to collect information from students and staff with a range of exposures and experiences of the RSD7. The second author and another academic in the School both suggested a broad range of students in terms of research competence and potential experience in Honours; they also recommended staff for interviews based on diversity of background, year level each taught, attitude to teaching innovations and familiarity with the RSD7, ranging from no awareness, to extensive use of the framework with students.

Of the 35 Honours students in the School in 2012, 14 were invited to be interviewed and all attended the interview (ten female, four male). This represents 40 per cent of the Honours students and was representative of the gender balance of the Honours student cohort. Four students opted to be interviewed in pairs, in keeping with ethics requirements that students could choose to have a companion in the interview; this resulted in a total of 12 interviews with students; however, each student response was distinguished in the transcription process to keep their responses separate. The Honours students were selected from the two disciplines that were using the RSD7-framed rubrics in Honours in 2012. Of the 39 academic staff in the School, 13 (33 per cent) were invited to be interviewed and nine (six male, three female) attended the interview individually (69 per cent accepted), comprising 23 per cent of academics in the School and representing the gender mix of staff.

Data collection and analysis

During the semi-structured interviews, additional probing took place when an answer seemed incomplete, in conflict with previous answers or worth seeking additional information. The 21 interviews in total yielded a range of benefits and disadvantages of the School’s use of the RSD7 in Honours, and when no additional information emerged, suggesting near-saturation of data, no further interviews were arranged.

The top-level extraction of data included all student or academic comments that addressed the research questions: benefits and disadvantages of RSD7-framed rubrics in Honours and recommendations for RSD7 use in years one to three of Medical Science degree programmes. The first author identified emerging themes which broadly conveyed student and academic sentiments of the benefits. The second author fine-tuned the initial phrasing of categories so that they reflected more accurately the data, and this took place in an iterative process until there was agreement on coding between both authors. Further commentary on the internal consistencies of themes in the emerging paper was provided by four independent peers, which led to clearer phrasing of each theme. A presentation of data and preliminary analysis was provided to a School meeting attended by 35 academic, professional staff and students, and attendees were invited to give feedback on the analysis of the findings, a process which provided confirmation of emerging themes.

Of the 14 Honours students interviewed, 10 had experienced RSD-framed rubrics in two consecutive first-year Human Biology courses, while four students had not encountered the use of RSD-framed rubrics previous to the Honours Year. All Honours students expressed knowledge of the RSD7-based marking rubrics for their assignments and projects during Honours, and one indicated seeing the RSD7 framework itself. Of the nine academics interviewed, six had direct exposure to the RSD7 framework previously and three were exposed to it during the interview for the first time. The RSD7 framework was implemented through multiple task-specific rubrics, framed by the six facets of research and used throughout the Honours year, including with a literature review, a short research proposal poster presentation day and a final research paper ( Medical Science 2012 ): “So we are using it consistently for all of the assessment items” (Academic 3).

The results below are structured to address the research questions. Italics in quotes from the interviews are added for emphasis.

Benefits of the RSD7 implementation in Honours year

There were two major themes concerning benefits of the School’s use of the RSD7-based criteria.

Student metacognition lifted capacity as a researcher.

[…] a good guide because you can see all the levels; you can see where you are. You compare yourself to the data. It takes a skill to be honest to yourself; that’s the first skill. When you look at the different levels, you can see where you are fitting and then you look at the levels ahead, at what are your areas of improvement so you can improve yourself […] (Student 1).

This use of “see where you are” and “look at the levels ahead” gives the idea of a conceptual map for discipline-specific processes involving a self-revealing of each student’s position and where he or she needed to go. This clarity of understanding through making the required skills explicit enabled students to also be honest with yourself , and revisitation of these skills on multiple occasions enabled one to improve yourself . Self-honesty and self-improvement are hallmarks of metacognitive processes, where students are aware of their own cognition and actively strive to improve.

[…] you know exactly what’s required of you, so you’re aware of it in everything you do […]. I think it’s better to be clear from the beginning that that’s what’s expected of you (Student 9).

It would have been good to have it last year […] it’s more specific in terms of the structures and it’s easier to see where you need to improve your strengths or weaknesses (Student 3).

[…] in my first assessment, I was assessed to be in the 2B range, and I was of course not happy about that, which is why I spoke to my coordinator, and he explained it , because we didn’t know if you are following your recipe, like, the supervisor’s recipe, or is this your idea […]. So that to me all okay, I need to make it very clear in my writing, and from now on in my theses, that this is my idea (Student 14).

For this student, the criteria were not self-evident, but rather required a clarifying conversation, which helped the student realise that he needed to delineate what his own work was, so that assessors would know. The RSD7-based rubric criteria merely articulated this issue in writing, but the conversation with his supervisor clarified the student’s needed response.

[…] you need wine and pizza when you introduce this […]. get them to mark somebody else’s work (Academic 8).

Because I was exposed to research experience, hands-on research experience, in terms of being in a lab and working in a lab and understanding that, okay, it’s not just about having an abstract, an introduction and discussion; it’s about how all of that work that goes into it and it actually comes together at the end. Sort of understanding the broader scope of things made more sense for me, personally (Student 10).

I think a lot of people might do this sort of thing intuitively, and what this [RSD7] has done is just spelt out what probably the good teachers were trying to do in any case […] (Academic 8).

I see the framework being what I’ll call nebulous enough for everybody to be able to accommodate it. Because it’s not very prescriptive. It just sets a framework, and everybody can work within a framework […] [yet] it’s relatively comprehensive in what it describes over all (Academic 2).

So I think it does help that it’s not completely structured , but at the same time that structure also really, really helps (Student 5).

I suppose being exposed to that framework in the Honours year as well, I sort of felt […] when you’re out there on your own as a researcher , that’s essentially what you do (Student 10).

School’s research capacity and profile.

[T]here is an increasing pool of people who are maybe becoming very enthusiastic about how this will get them better students or raise the profile (Academic 3).

In working with PhD students, the thing that often leads to conflict is a conflict of expectations and a mismatch of those expectations. Something like this [RSD7 framework] lets students know where a PhD supervisor expects them to be and where a PhD student thinks they should be (Academic 4).

I think the staff who do a lot of research who are taking some of these courses [that use the RSD7], or running some of these courses, I think they probably see the link more than some of the staff who mainly just teach […] [and never] talk about the link between that and research (Academic 9).

If you’re developing the skills of researchers or colleagues or whatever, there needs to be some sort of feedback that, if you like, gives some idea of where the strengths are and where the weaknesses are, if these people are going to be writing research grants and whatever […] (Academic 3).

I was getting a bit scared when I was looking at level 7. Gosh, am I working at this level? Which is where you would expect academics to be working […]. I think it could be useful for promotions , when you’re looking at – particularly when you’re going from level C to level D […] this is really what they’re marking: where are you sitting in the international arena ? (Academic 5).

This academic saw the potential of the RSD7 to inform her and others’ research trajectories, ultimately enhancing the research profile of the School.

Disadvantages of RSD7 implementation

The major theme emerging as a disadvantage, stated by 8 of the 14 Honours students and 4 of the 9 academics, concerned problems associated with rubrics based on the RSD7, and their use.

I kind of find that sometimes they [School-wide RSD7-framed rubric criteria] don’t apply very well to the assignment […] our projects are vastly different […]. I don’t understand how the same marking scheme can apply when it’s so specific for what it’s looking for […] one of the ones for the lit review was use of up-to-date relevant literature . It’s like, I don’t have any […] (Student 11).

Objectives clear, focussed and innovative, extending past supervisor guidelines ( Medical science, 2012 ).

Some of it, you think, how will assessors know that we’re doing that? […] Assessors] don’t know what we and our supervisors talk about in our meetings, so they don’t know whether or not we’re going beyond our supervisors. I think that’s a bit stupid at times (Student 5).

I’ve found out that assessors are also quite subjective . I have one assessor that says I am in level 4 and 5; I have another one that says I’m in level 2 and 3 […]. So I’ve found that this framework is really subjective […] although they make markers a lot more accountable (Student 4).

This student is understandably troubled by the perennial problem of inter-rater reliability, and there is no surprise that mere criteria do not guarantee reliable scores, as this is frequently reported in the literature ( Sadler, 2009 , 2014 ). While the student was perplexed by the need to deal with multiple subjective perspectives at once, she appreciated that the markers would at least be able to defend their decisions for where they allocated marks, even if they did not agree with other markers.

We get a rubric for every single assessment, and they’re all completely different. They’re very much for each assessment, and I hate them (Student 11).

These comments suggest that some students were not aware of the common framing of the RSD four months into Honours, seeing each rubric as separate “for each assessment”.

[…] what looks really clear on a piece of paper in an assessment task list becomes a lot more complex. Say you’re in a seminar and someone is talking about a particular area and trying to tease out a quite complicated presentation so that you can tick off numerous little boxes can be quite difficult (Academic 6).

There’s also some attempt to explicitly link assessment items with the Research Skill Development Framework, but there’s also the issue, you’re trying to micromanage how people mark […] (Academic 6).

This touches on tensions around academic autonomy versus a shared conceptualisation, and this tension will be revisited in the discussion.

Recommendations for undergraduate from first year to third year

It [the RSD rubric] tells you a lot, because I remember one of the criteria was to be specific […] in my [First Year] Human Biology course […] so I think it’s very relevant to Honours, because when we were doing our first seminar, some of the topics were really broad. Automatically you think: I have to be specific otherwise it’s too broad […] (Student 7).

I think that would have been a good thing, especially if it was consistent throughout the years , because by the third year it would be a lot more ingrained and it wouldn’t be a novel thing that you’re looking at (Student 2).

Since the beginning [of First Year], they have given us assignments based on this criteria. You might not have liked the assignments, but because they have been consistently applying this structure to all of our assignments, we have come to think that way for science , in the perspective of science and writing […] (Student 4).

I always remember these [RSD-framed] marking criteria sheets, but I think if they were emphasised more and you know that they kind of reinforce these facets a little more strongly throughout every year, it would be really, really good, I reckon (Student 6).

But if it’s dribbled through in these undergraduate years, it then makes the Honours a lot easier, and then makes the PhD a lot easier, because a lot of students struggle in their first year [of PhD] (Academic 2).

This “dribbling” also gives a sense of what academics thought was the best ways of administering RSD7: earlier than Honours, but not “injected” forcefully and not over-emphasised. In other words, there was a desire that the RSD7 be used to provide structure and scaffolding, but not to the extent that it was inflicted in ways counter to effective learning or to academic autonomy.

I loved what I did [in First year], but I just remember a lot of my friends used to sit there complaining, just going, this rubric sheet doesn’t make much sense because why am I ever going to need to do any of this stuff […] (Student 10).

I didn’t pay attention to it [RSD7-framed rubric in First Year], because it was kind of at the back of the assessment. They were never kind of made a big deal, whereas in Honours we kind of get handed this, like, go find this (Student 12).

[…] sort of helps us to be a bit more flexible […] [and] sort of makes you think more, I think, because other people have different ideas and expect different things (Student 8).

This student perceived that a pre-determined structure may negatively affect flexible thinking.

So there has to be what I’ll call a program wide approach where all the academic staff need to get together, or as many as possible, so you have the First-Year group there and Second Year and Third Year, and they all learn from one another (Academic 2).

A large majority of students and academics interviewed perceived that the marking criteria framed by the RSD7, located in appropriate courses and assessments across the degree programme, had reinforcing and multiplying effects on learning discipline-specific research skills.

In terms of RQ1 , there are clear benefits of the RSD7 for consistently informing learning, teaching and assessment processes throughout the Honours year. These benefits included that the RSD7 framework was perceived to fit closely to the nature of research in Medical Science, enable students to think metacognitively as researchers and help build the research capacity of students, academics and the School as a whole. These points are in agreement with a study of student inquiry that found “when appropriately framed (especially with the relevant student motivation and autonomy ), such lessons can become deeply internalized” ( Allchin et al. , 2014 , p. 469, italics added ). Disadvantages of the RSD7-framed rubrics mainly focussed on the specific criteria, where some were perceived to be too prescriptive, too vague, subjective or irrelevant, in keeping with research on pre-determined assessment criteria ( Adcroft, 2011 ; Sadler, 2009 , 2014 ).

For both advantages and disadvantages communication was pivotal to the learning enterprise, with effective communication not guaranteed by the use of the RSD7-based marking rubrics, but more likely enabled by conversations framed by them. For example, one student in Section 5.2 perceived that the criterion about going beyond supervisor’s guidelines was “stupid”; however, Section 5.1 presented a student who also referred to this same criteria and found it provided substantial insight after discussing with his supervisor, saying that in reflection “I need to make it very clear […]” The first student said how will assessors know? The second student agreed that assessors wouldn’t know ; therefore, I need to make it very clear in my writing . This demonstrates that written criteria alone are insufficient for at least some students to clarify assessment requirements.

Another element exposed above is that the RSD7 prompted academics to make visible criteria that are frequently left implicit for students. The general facet of “embarks and clarifies” was operationalised as the problematic, but necessary, description of “going beyond supervisor’s guidelines”, an honest exposure of assessment of expectations of high-performing students in the initiation of research. However, using the framework to unearth and articulate implicit criteria explicitly does not make the words or ideas immediately sensible or palatable, but preferably would be part of a process, whereby students critically analyse the criteria rather than reactively thinking “stupid”. Based on the differential response between students noted above, the RSD-framed criteria need to be used as a learning and conversation tool at least as much as an assessment tool, so that more students have an it-got-me-thinking reaction. It has been found elsewhere that the RSD framework frequently promotes a shift to making explicit that which has often been left implicit ( Willison, 2012 ).

That some students saw several criteria as irrelevant, such as “recent literature” suggests that these students could better apprehend the standards of the discipline, and take pains to explain why their specific research does not fit the common practice. The criterion should suggest to the student – initially, with guidance from the supervisor, the need to explain why she is relying on what looks like out-of-date material. Overall, the effective use of the RSD7 and its resulting rubrics seemed to require dialogue between students and academics, in keeping with the academic who suggested introducing the rubrics with pizza. It seems that the marking rubrics framed by the RSD7 were like a “frozen conversation”, where the dense articulations of what is being sought needed to be defrosted by human-to-human contact to enable more fluid understandings.

RQ2 was “What do Honours students and academics recommend about RSD7 use in the entire undergraduate degree programme?” All those interviewed, except one Honours student, stated that RSD7 could be used to advantage earlier in the undergraduate degree than Honours. There was a strong emerging sense that across-the-years, explicit research skill development informed by the RSD7 is a way to enable the education needed before and during Honours, and to provide the preparation for PhD study. This may be contrasted with another study which found that without explicit development, there was a risk that research skills may atrophy from one year to the next ( Willison, 2012 ). An explicit and ongoing upskilling process is more likely to overcome the problem that without appropriate structure and guidance, by the end of their degree, students tend to perform open-inquiry projects at “the same level of sophistication as in their introductory core course” ( Chaplin, 2003 , p. 231).

Repeated exposures of the same framing of the RSD7 maximise the potential for student metacognition, where they make their cognition visible to themselves and, as Student 4 said, because across the years of the degree “ they have been consistently applying this structure to all of our assignments, we have come to think that way for science”. Students’ awareness of their own thinking processes are heightened through repeated and diverse exposures to the same six facets of the RSD in multiple contexts, and their potential for self-propelled learning is enhanced as shown by Student 1’s statement “ you can improve yourself” . Metacognition was noted to be of paramount importance for fostering professional growth by a study on inquiry skills in science ( Michalsky, 2012 ), and to student growth as researchers in this present study. Student metacognition evident in this study resulted in a dawning appreciation that the specifics of rubric criteria change time and again, but the six facets of the research process are the same, and the boosted metacognition fundamentally improved most interviewed students’ approaches to researching.

[…] there is need for professors to be more proactive in helping their students gain intellectual proficiency not just as part of doctoral studies but also for undergraduates and master’s degree students (italics added).

[…] given the growth of ever more detailed marking schemes for assessments, does feedback become something which is too specific to a single episode of assessment rather than generalisable to the learning experience as a whole ( Adcroft, 2011 ).

A large majority of students interviewed were able to generalise to the learning experience as a whole, where they were metacognitive and considered themselves being prepared as researchers. This reported skill development is also in keeping with other studies of the RSD7 at the postgraduate level, ( Venning and Buisman-Pijlman, 2013 ; Velautham and Picard, 2011) which, together with this study, suggest that the RSD7 could be used in master’s degrees as well as Honours degrees to better prepare students for PhD study. Any programme-level implementation of the RSD would need to balance advantages, such as coherency in the programme, with the dangers associated with over-riding individual academic’s autonomy.

Limitations and biases of the study

This study was conducted with a proportion of academics from one school and students from one honours cohort, so the study cannot be generalised to all the School’s academics and students, or to other schools and honours cohorts. The study risked a conformation bias; however, there is evidence especially in Section 5.2 that disconfirming evidence was gathered and presented, to mitigate this potential bias to some extent. The study was conducted at an Australian university, and this raises the question about generalisation to other settings and counties. The bachelor and Honours year are comparable to, for example, the UK system or the longer undergraduate science degrees where time is reserved for extended periods of research internships. It is noteworthy that a grading rubric based on the RSD7 was used successfully in The International Master of Science in Addiction Studies, which is taught by partner universities in the USA, the UK and Australia ( Venning and Buisman-Pijlman, 2013 ). The consistent use in this current study of a common conceptual framework to inform rubric construction over multiple year levels to inform the students of their progress and to provide guidance on how to improve seems to be innovative. This use of a conceptual framework may require a cultural shift for academics who may otherwise be focussed on collecting the data from rubrics for accreditation purposes ( Kuh et al. , 2014 ) without seeing the broader educational issue.

Notwithstanding the above comments, this study is an improvement on studies that have focussed on RSD implementation by several academics ( Peirce et al. , 2012 ; Pretorius et al. , 2013 ; Willison et al. , 2009a ; 2009b ) or many academics working individually or in small teams ( Willison, 2012 ): these studies of early adopters risk “early implementer” bias. This current study has considered a whole-school context, where not all those involved in implementation are convinced about the approach. This more closely mirrors the second phase of implementation of an innovation, which, in education, typically is less successful than first-phase pilot studies. Broader studies are needed to reveal more fully the advantages, disadvantages, limitations and successful methods of implementation of the RSD7 at the multiple school and institution levels.

Conclusions

In this current study, the RSD7 provided a conceptual language-in-common which enabled meaningful conversations between academics and students, even if people did not always agree on what was being said. The RSD7 framework was perceived by academics and students to fit closely to the nature of research in Medical Science, and by operationalising it as rubrics, academics were prompted to state clearly the criteria that are frequently left implicit. As academics made research skill development explicit over an extended timeframe, students found that research processes were both more visible and were increasingly internalised so that you came to think that way for science . The large majority of those interviewed suggested strongly that multiple and varied exposures to the same six RSD7 facets across the years of undergraduate study enabled substantial long-term benefits, including maturation of their research skills due to heightened metacognitive processes and identification of themselves as researchers. In this way, the RSD7 was perceived to build the research capacity of students, academics and the School as a whole.

The RSD7 opens up possibilities of using a structure which is sufficiently nebulous yet directed for long-term guidance and reinforcement of student research skill development. However, multi-school and whole-of-institution studies are needed to delve more deeply into how effectively the RSD7 may help with the development of student research skills in many contexts, and with the selection of students who are suited for post-graduate research. For countries with sufficient or excess PhDs, as well as for countries striving to increase PhD enrolments, the RSD7 presents the potential for students to be more research-ready on commencement of their research degrees and so have enhanced outcomes in terms of graduate qualities and outputs. In the School of Medical Science in this study, implementation and use of the RSD7 enabled fluid understandings and conversations around research processes and so it was an important part of students becoming researchers and researchers becoming renowned.

Researcher Skill Development framework

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Further reading

Bahr , N. and Lloyd , M. ( 2011 ), “ Course cohesion: an elusive goal for tertiary education ”, Journal of Learning Design , Vol. 4 No. 4 , pp. 21 - 36 .

Acknowledgements

The authors thank the colleagues and students of the school that was the focus of this study for their contributions. This study was supported by a grant from the Office of Learning and Teaching, Australia.

Corresponding author

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Research skills requirement, doctoral.

To define the expectations for doctoral research skills prior to the comprehensive examination for graduate students admitted Fall 2011 or before.

Graduate students admitted Fall 2011 or before.

Specific research skills requirements vary with graduate degree programs, but all reflect the expectation of a significant research skill component distinct from, but strongly supportive of, the dissertation. Traditionally, a reading knowledge of two (2) foreign (non-English) languages, a demonstrated competence in reading, writing, and speaking in one (1) foreign language, or a reading knowledge of one (1) foreign language and demonstrated proficiency in some other research skill, such as computer science, has been required. However, to fit research training to the needs of the individual student, some programs have found it appropriate to regard as research skills formal training in ancillary areas or within a broad spectrum of skills. A statement concerning research skills should appear in each departmental or program section of this catalog and in any graduate study guides issued by departments, programs, or schools.

This policy applies to doctoral students admitted prior to Fall 2011. Doctoral students admitted Fall 2011 or later must adhere to the Research Skills and Responsible Scholarship Policy .

When the aspirant has met the requirements for research skills recommended by the program and approved by the school, the program must report this fact to the Graduate Division on the appropriate form, certifying that the student is prepared to proceed to the comprehensive oral examination. If a program requires research skills that are tested separately from the program, completion of each requirement should be reported immediately to the Graduate Division so that it may be recorded on the student’s permanent record.

Because foreign language and computer science competences are the most commonly used research skills requirements, the formal procedures that have been established for demonstration of these competences are listed here for guidance.

Foreign Language

An aspirant who wishes to demonstrate a reading knowledge of a foreign language ordinarily may do so in one of two ways: (1) pass a language examination devised and administered by the student’s own department in consultation with the appropriate KU language department or (2) complete DANE 101, DTCH 101, FREN 100, GERM 101, ITAL 100, RUSS 101, or SPAN 100 with a grade of C or higher, or LAT 101 with a grade of B or higher. If some other language is proposed, arrangements should be made through the major or departmental adviser with the appropriate language department or competent testing authority. Some graduate degree programs accept as evidence of language competence the certification of a graduate student by a qualified KU professor in a given language at the fourth level of competence in reading, comprehension, and speaking or accept 16 hours in a single language taken at this or another university as a graduate or undergraduate student. Requirements for demonstrating competence in reading, writing, and speaking one (1) foreign language are set by the language departments. The student should ask these departments for further information and advice. In all cases, the Graduate Division should be notified which method each student has used to satisfy this requirement.

A student whose native language is not English may use the native language to fulfill the language requirement only if the language is considered an adequate research tool for the program.

Computer Science

To establish competence in computer science, a student must (a) demonstrate proficiency in a commonly used programming language and (b) create at least one (1) original program on a problem that is certified by the graduate degree program as important and relevant to the field of study.

As specified by the graduate degree program, requirement (a) may be met by passing an examination developed and administered by the Department of Electrical Engineering and Computer Science or by satisfactorily completing an appropriate course in computer science. In consultation with the department, the Department of Electrical Engineering and Computer Science provides certification of requirement (b).

Office of Graduate Studies 785-864-8040

Research Skills and Responsible Scholarship

07/27/2023: Added Approved by, updated policy formatting.

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The Most Important Research Skills (With Examples)

• What Are Hard Skills?
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• What Are What Are Life Skills?
• What Are Social Media Skills Resume?
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Research skills are the ability to find out accurate information on a topic. They include being able to determine the data you need, find and interpret those findings, and then explain that to others. Being able to do effective research is a beneficial skill in any profession, as data and research inform how businesses operate.

Whether you’re unsure of your research skills or are looking for ways to further improve them, then this article will cover important research skills and how to become even better at research.

Key Takeaways

Having strong research skills can help you understand your competitors, develop new processes, and build your professional skills in addition to aiding you in finding new customers and saving your company money.

Some of the most valuable research skills you can have include goal setting, data collection, and analyzing information from multiple sources.

You can and should put your research skills on your resume and highlight them in your job interviews.

What are research skills?

Why are research skills important, 12 of the most important research skills, how to improve your research skills, highlighting your research skills in a job interview, how to include research skills on your resume, resume examples showcasing research skills, research skills faqs.

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Research skills are the necessary tools to be able to find, compile, and interpret information in order to answer a question. Of course, there are several aspects to this. Researchers typically have to decide how to go about researching a problem — which for most people is internet research.

In addition, you need to be able to interpret the reliability of a source, put the information you find together in an organized and logical way, and be able to present your findings to others. That means that they’re comprised of both hard skills — knowing your subject and what’s true and what isn’t — and soft skills. You need to be able to interpret sources and communicate clearly.

Research skills are useful in any industry, and have applications in innovation, product development, competitor research, and many other areas. In addition, the skills used in researching aren’t only useful for research. Being able to interpret information is a necessary skill, as is being able to clearly explain your reasoning.

Research skills are used to:

Do competitor research. Knowing what your biggest competitors are up to is an essential part of any business. Researching what works for your competitors, what they’re doing better than you, and where you can improve your standing with the lowest resource expenditure are all essential if a company wants to remain functional.

Develop new processes and products. You don’t have to be involved in research and development to make improvements in how your team gets things done. Researching new processes that make your job (and those of your team) more efficient will be valued by any sensible employer.

Foster self-improvement. Folks who have a knack and passion for research are never content with doing things the same way they’ve always been done. Organizations need independent thinkers who will seek out their own answers and improve their skills as a matter of course. These employees will also pick up new technologies more easily.

Manage customer relationships. Being able to conduct research on your customer base is positively vital in virtually every industry. It’s hard to move products or sell services if you don’t know what people are interested in. Researching your customer base’s interests, needs, and pain points is a valuable responsibility.

Save money. Whether your company is launching a new product or just looking for ways to scale back its current spending, research is crucial for finding wasted resources and redirecting them to more deserving ends. Anyone who proactively researches ways that the company can save money will be highly appreciated by their employer.

Solve problems. Problem solving is a major part of a lot of careers, and research skills are instrumental in making sure your solution is effective. Finding out the cause of the problem and determining an effective solution both require accurate information, and research is the best way to obtain that — be it via the internet or by observation.

Determine reliable information. Being able to tell whether or not the information you receive seems accurate is a very valuable skill. While research skills won’t always guarantee that you’ll be able to tell the reliability of the information at first glance, it’ll prevent you from being too trusting. And it’ll give the tools to double-check .

Experienced researchers know that worthwhile investigation involves a variety of skills. Consider which research skills come naturally to you, and which you could work on more.

Data collection . When thinking about the research process, data collection is often the first thing that comes to mind. It is the nuts and bolts of research. How data is collected can be flexible.

For some purposes, simply gathering facts and information on the internet can fulfill your need. Others may require more direct and crowd-sourced research. Having experience in various methods of data collection can make your resume more impressive to recruiters.

Data collection methods include: Observation Interviews Questionnaires Experimentation Conducting focus groups

Analysis of information from different sources. Putting all your eggs in one source basket usually results in error and disappointment. One of the skills that good researchers always incorporate into their process is an abundance of sources. It’s also best practice to consider the reliability of these sources.

Are you reading about U.S. history on a conspiracy theorist’s blog post? Taking facts for a presentation from an anonymous Twitter account?

If you can’t determine the validity of the sources you’re using, it can compromise all of your research. That doesn’t mean just disregard anything on the internet but double-check your findings. In fact, quadruple-check. You can make your research even stronger by turning to references outside of the internet.

Examples of reliable information sources include: Published books Encyclopedias Magazines Databases Scholarly journals Newspapers Library catalogs

Finding information on the internet. While it can be beneficial to consulate alternative sources, strong internet research skills drive modern-day research.

One of the great things about the internet is how much information it contains, however, this comes with digging through a lot of garbage to get to the facts you need. The ability to efficiently use the vast database of knowledge that is on the internet without getting lost in the junk is very valuable to employers.

Internet research skills include: Source checking Searching relevant questions Exploring deeper than the first options Avoiding distraction Giving credit Organizing findings

Interviewing. Some research endeavors may require a more hands-on approach than just consulting internet sources. Being prepared with strong interviewing skills can be very helpful in the research process.

Interviews can be a useful research tactic to gain first-hand information and being able to manage a successful interview can greatly improve your research skills.

Interviewing skills involves: A plan of action Specific, pointed questions Respectfulness Considering the interview setting Actively Listening Taking notes Gratitude for participation

Report writing. Possessing skills in report writing can assist you in job and scholarly research. The overall purpose of a report in any context is to convey particular information to its audience.

Effective report writing is largely dependent on communication. Your boss, professor , or general reader should walk away completely understanding your findings and conclusions.

Report writing skills involve: Proper format Including a summary Focusing on your initial goal Creating an outline Proofreading Directness

Critical thinking. Critical thinking skills can aid you greatly throughout the research process, and as an employee in general. Critical thinking refers to your data analysis skills. When you’re in the throes of research, you need to be able to analyze your results and make logical decisions about your findings.

Critical thinking skills involve: Observation Analysis Assessing issues Problem-solving Creativity Communication

Planning and scheduling. Research is a work project like any other, and that means it requires a little forethought before starting. Creating a detailed outline map for the points you want to touch on in your research produces more organized results.

It also makes it much easier to manage your time. Planning and scheduling skills are important to employers because they indicate a prepared employee.

Planning and scheduling skills include: Setting objectives Identifying tasks Prioritizing Delegating if needed Vision Communication Clarity Time-management

Note-taking. Research involves sifting through and taking in lots of information. Taking exhaustive notes ensures that you will not neglect any findings later and allows you to communicate these results to your co-workers. Being able to take good notes helps summarize research.

Examples of note-taking skills include: Focus Organization Using short-hand Keeping your objective in mind Neatness Highlighting important points Reviewing notes afterward

Communication skills. Effective research requires being able to understand and process the information you receive, either written or spoken. That means that you need strong reading comprehension and writing skills — two major aspects of communication — as well as excellent listening skills.

Most research also involves showcasing your findings. This can be via a presentation. , report, chart, or Q&A. Whatever the case, you need to be able to communicate your findings in a way that educates your audience.

Communication skills include: Reading comprehension Writing Listening skills Presenting to an audience Creating graphs or charts Explaining in layman’s terms

Time management. We’re, unfortunately, only given 24 measly hours in a day. The ability to effectively manage this time is extremely powerful in a professional context. Hiring managers seek candidates who can accomplish goals in a given timeframe.

Strong time management skills mean that you can organize a plan for how to break down larger tasks in a project and complete them by a deadline. Developing your time management skills can greatly improve the productivity of your research.

Time management skills include: Scheduling Creating task outlines Strategic thinking Stress-management Delegation Communication Utilizing resources Setting realistic expectations Meeting deadlines

Using your network. While this doesn’t seem immediately relevant to research skills, remember that there are a lot of experts out there. Knowing what people’s areas of expertise and asking for help can be tremendously beneficial — especially if it’s a subject you’re unfamiliar with.

Your coworkers are going to have different areas of expertise than you do, and your network of people will as well. You may even know someone who knows someone who’s knowledgeable in the area you’re researching. Most people are happy to share their expertise, as it’s usually also an area of interest to them.

Networking involves: Remembering people’s areas of expertise Being willing to ask for help Communication Returning favors Making use of advice Asking for specific assistance

Attention to detail. Research is inherently precise. That means that you need to be attentive to the details, both in terms of the information you’re gathering, but also in where you got it from. Making errors in statistics can have a major impact on the interpretation of the data, not to mention that it’ll reflect poorly on you.

There are proper procedures for citing sources that you should follow. That means that your sources will be properly credited, preventing accusations of plagiarism. In addition, it means that others can make use of your research by returning to the original sources.

Attention to detail includes: Double checking statistics Taking notes Keeping track of your sources Staying organized Making sure graphs are accurate and representative Properly citing sources

As with many professional skills, research skills serve us in our day to day life. Any time you search for information on the internet, you’re doing research. That means that you’re practicing it outside of work as well. If you want to continue improving your research skills, both for professional and personal use, here are some tips to try.

Differentiate between source quality. A researcher is only as good as their worst source. Start paying attention to the quality of the sources you use, and be suspicious of everything your read until you check out the attributions and works cited.

Be critical and ask yourself about the author’s bias, where the author’s research aligns with the larger body of verified research in the field, and what publication sponsored or published the research.

Use multiple resources. When you can verify information from a multitude of sources, it becomes more and more credible. To bolster your faith in one source, see if you can find another source that agrees with it.

Don’t fall victim to confirmation bias. Confirmation bias is when a researcher expects a certain outcome and then goes to find data that supports this hypothesis. It can even go so far as disregarding anything that challenges the researcher’s initial hunch. Be prepared for surprising answers and keep an open mind.

Be open to the idea that you might not find a definitive answer. It’s best to be honest and say that you found no definitive answer instead of just confirming what you think your boss or coworkers expect or want to hear. Experts and good researchers are willing to say that they don’t know.

Stay organized. Being able to cite sources accurately and present all your findings is just as important as conducting the research itself. Start practicing good organizational skills , both on your devices and for any physical products you’re using.

Get specific as you go. There’s nothing wrong with starting your research in a general way. After all, it’s important to become familiar with the terminology and basic gist of the researcher’s findings before you dig down into all the minutia.

A job interview is itself a test of your research skills. You can expect questions on what you know about the company, the role, and your field or industry more generally. In order to give expert answers on all these topics, research is crucial.

Start by researching the company . Look into how they communicate with the public through social media, what their mission statement is, and how they describe their culture.

Pay close attention to the tone of their website. Is it hyper professional or more casual and fun-loving? All of these elements will help decide how best to sell yourself at the interview.

Next, research the role. Go beyond the job description and reach out to current employees working at your desired company and in your potential department. If you can find out what specific problems your future team is or will be facing, you’re sure to impress hiring managers and recruiters with your ability to research all the facts.

Finally, take time to research the job responsibilities you’re not as comfortable with. If you’re applying for a job that represents increased difficulty or entirely new tasks, it helps to come into the interview with at least a basic knowledge of what you’ll need to learn.

Research projects require dedication. Being committed is a valuable skill for hiring managers. Whether you’ve had research experience throughout education or a former job, including it properly can boost the success of your resume .

Consider how extensive your research background is. If you’ve worked on multiple, in-depth research projects, it might be best to include it as its own section. If you have less research experience, include it in the skills section .

Focus on your specific role in the research, as opposed to just the research itself. Try to quantify accomplishments to the best of your abilities. If you were put in charge of competitor research, for example, list that as one of the tasks you had in your career.

If it was a particular project, such as tracking the sale of women’s clothing at a tee-shirt company, you can say that you “directed analysis into women’s clothing sales statistics for a market research project.”

Ascertain how directly research skills relate to the job you’re applying for. How strongly you highlight your research skills should depend on the nature of the job the resume is for. If research looks to be a strong component of it, then showcase all of your experience.

If research looks to be tangential, then be sure to mention it — it’s a valuable skill — but don’t put it front and center.

Example #1: Academic Research

Simon Marks 767 Brighton Blvd. | Brooklyn, NY, 27368 | (683)-262-8883 | [email protected] Diligent and hardworking recent graduate seeking a position to develop professional experience and utilize research skills. B.A. in Biological Sciences from New York University. PROFESSIONAL EXPERIENCE Lixus Publishing , Brooklyn, NY Office Assistant- September 2018-present Scheduling and updating meetings Managing emails and phone calls Reading entries Worked on a science fiction campaign by researching target demographic Organizing calendars Promoted to office assistant after one year internship Mitch’s Burgers and Fries , Brooklyn, NY Restaurant Manager , June 2014-June 2018 Managed a team of five employees Responsible for coordinating the weekly schedule Hired and trained two employees Kept track of inventory Dealt with vendors Provided customer service Promoted to restaurant manager after two years as a waiter Awarded a $2.00/hr wage increase SKILLS Writing Scientific Research Data analysis Critical thinking Planning Communication RESEARCH Worked on an ecosystem biology project with responsibilities for algae collection and research (2019) Lead a group of freshmen in a research project looking into cell biology (2018) EDUCATION New York University Bachelors in Biological Sciences, September 2016-May 2020

Example #2: Professional Research

Angela Nichols 1111 Keller Dr. | San Francisco, CA | (663)-124-8827 |[email protected] Experienced and enthusiastic marketer with 7 years of professional experience. Seeking a position to apply my marketing and research knowledge. Skills in working on a team and flexibility. EXPERIENCE Apples amp; Oranges Marketing, San Francisco, CA Associate Marketer – April 2017-May 2020 Discuss marketing goals with clients Provide customer service Lead campaigns associated with women’s health Coordinating with a marketing team Quickly solving issues in service and managing conflict Awarded with two raises totaling $10,000 over three years Prestigious Marketing Company, San Francisco, CA Marketer – May 2014-April 2017 Working directly with clients Conducting market research into television streaming preferences Developing marketing campaigns related to television streaming services Report writing Analyzing campaign success statistics Promoted to Marketer from Junior Marketer after the first year Timberlake Public Relations, San Francisco, CA Public Relations Intern – September 2013–May 2014 Working cohesively with a large group of co-workers and supervisors Note-taking during meetings Running errands Managing email accounts Assisting in brainstorming Meeting work deadlines EDUCATION Golden Gate University, San Francisco, CA Bachelor of Arts in Marketing with a minor in Communications – September 2009 – May 2013 SKILLS Marketing Market research Record-keeping Teamwork Presentation. Flexibility

What research skills are important?

Goal-setting and data collection are important research skills. Additional important research skills include:

Using different sources to analyze information.

Finding information on the internet.

Interviewing sources.

Writing reports.

Critical thinking.

Planning and scheduling.

Note-taking.

Managing time.

How do you develop good research skills?

You develop good research skills by learning how to find information from multiple high-quality sources, by being wary of confirmation bias, and by starting broad and getting more specific as you go.

When you learn how to tell a reliable source from an unreliable one and get in the habit of finding multiple sources that back up a claim, you’ll have better quality research.

In addition, when you learn how to keep an open mind about what you’ll find, you’ll avoid falling into the trap of confirmation bias, and by staying organized and narrowing your focus as you go (rather than before you start), you’ll be able to gather quality information more efficiently.

What is the importance of research?

The importance of research is that it informs most decisions and strategies in a business. Whether it’s deciding which products to offer or creating a marketing strategy, research should be used in every part of a company.

Because of this, employers want employees who have strong research skills. They know that you’ll be able to put them to work bettering yourself and the organization as a whole.

Should you put research skills on your resume?

Yes, you should include research skills on your resume as they are an important professional skill. Where you include your research skills on your resume will depend on whether you have a lot of experience in research from a previous job or as part of getting your degree, or if you’ve just cultivated them on your own.

If your research skills are based on experience, you could put them down under the tasks you were expected to perform at the job in question. If not, then you should likely list it in your skills section.

University of the People – The Best Research Skills for Success

Association of Internet Research Specialists — What are Research Skills and Why Are They Important?

MasterClass — How to Improve Your Research Skills: 6 Research Tips

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Sky Ariella is a professional freelance writer, originally from New York. She has been featured on websites and online magazines covering topics in career, travel, and lifestyle. She received her BA in psychology from Hunter College.

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Driving Innovations in Biostatistics with Denise Scholtens, PhD

“I'm continually surprised by new data types. I think that we will see the emergence of a whole new kind of technology that we probably can't even envision five years from now…When I think about where the field has come over the past 20 years, it's just phenomenal.”  —  Denise Scholtens, PhD  

• Director, Northwestern University Data Analysis and Coordinating Center (NUDACC)  
• Chief of Biostatistics in the Department of Preventive Medicine  
• Professor of Preventive Medicine in the Division of Biostatistics and of Neurological Surgery  
• Member of Northwestern University Clinical and Translational Sciences Institute (NUCATS)  
• Member of the Robert H. Lurie Comprehensive Cancer Center  

Episode Notes 

Since arriving at Feinberg in 2004, Scholtens has played a central role in the dramatic expansion of biostatistics at the medical school. Now the Director of NUDACC, Scholtens brings her expertise and leadership to large-scale, multicenter studies that can lead to clinical and public health practice decision-making.    

• After discovering her love of statistics as a high school math teacher, Scholtens studied bioinformatics in a PhD program before arriving at Feinberg in 2004.  
• Feinberg’s commitment to biostatistics has grown substantially in recent decades. Scholtens was only one of five biostatisticians when she arrived. Now she is part of a division with almost 50 people.  
• She says being a good biostatistician requires curiosity about other people’s work, knowing what questions to ask and tenacity to understand subtitles of so much data.   
• At NUDACC, Scholtens and her colleagues specialize in large-scale, multicenter prospective studies and clinical trials that lead to clinical or public health practice decision-making. They operate at the executive level and oversee all aspects of the study design.  
• Currently, Scholtens is involved with the launch of a large study, along with The Ohio State University, that received a $14 million grant to look at the effectiveness of aspirin in the prevention of hypertensive disorders in pregnancy.  
• Scholtens first started her work in data coordinating through the Hyperglycemia Adverse Pregnancy Outcome (HAPO) study, which looked at 25,000 pregnant individuals. This led to a continued interest in fetal and maternal health.   
• When it comes to supportive working environments, Scholtens celebrates the culture at Feinberg, and especially her division in biostatistics, for being collaborative as well as genuinely supportive of each other’s projects. She attributes this to strong leadership which established a culture with these guiding principles.   

Additional Reading  

• Read more about the ASPIRIN trial and other projects taking place at NUDACC   
• Discover a study linking mothers’ obesity-related genes to babies’ birth weight, which Scholtens worked in through the HAPO study   
• Browse all of Scholtens recent publications 

Recorded on February 21, 2024.

Continuing Medical Education Credit

Physicians who listen to this podcast may claim continuing medical education credit after listening to an episode of this program..

Target Audience

Academic/Research, Multiple specialties

Learning Objectives

At the conclusion of this activity, participants will be able to:

• Identify the research interests and initiatives of Feinberg faculty.
• Discuss new updates in clinical and translational research.

Accreditation Statement

The Northwestern University Feinberg School of Medicine is accredited by the Accreditation Council for Continuing Medical Education (ACCME) to provide continuing medical education for physicians.

Credit Designation Statement

The Northwestern University Feinberg School of Medicine designates this Enduring Material for a maximum of 0.50  AMA PRA Category 1 Credit(s)™.  Physicians should claim only the credit commensurate with the extent of their participation in the activity.

American Board of Surgery Continuous Certification Program

Successful completion of this CME activity enables the learner to earn credit toward the CME requirement(s) of the American Board of Surgery’s Continuous Certification program. It is the CME activity provider's responsibility to submit learner completion information to ACCME for the purpose of granting ABS credit.

All the relevant financial relationships for these individuals have been mitigated.

Disclosure Statement

Denise Scholtens, PhD, has nothing to disclose.  Course director, Robert Rosa, MD, has nothing to disclose. Planning committee member, Erin Spain, has nothing to disclose.  FSM’s CME Leadership, Review Committee, and Staff have no relevant financial relationships with ineligible companies to disclose.

Read the Full Transcript

[00:00:00] Erin Spain, MS: This is Breakthroughs, a podcast from Northwestern University Feinberg School of Medicine. I'm Erin Spain, host of the show. Northwestern University Feinberg School of Medicine is home to a team of premier faculty and staff biostatisticians, who are the driving force of data analytic innovation and excellence here. Today, we are talking with Dr. Denise Scholtens, a leader in biostatistics at Northwestern, about the growing importance of the field, and how she leverages her skills to collaborate on several projects in Maternal and Fetal Health. She is the Director of the Northwestern University Data Analysis and Coordinating Center, NUDACC, and Chief of Biostatistics in the Department of Preventive Medicine, as well as Professor of Preventive Medicine and Neurological Surgery. Welcome to the show.  

[00:01:02] Denise Scholtens, PhD: Thank you so much.  

[00:01:02] Erin Spain, MS: So you have said in the past that you were drawn to this field of biostatistics because you're interested in both math and medicine, but not interested in becoming a clinician. Tell me about your path into the field and to Northwestern.  

[00:01:17] Denise Scholtens, PhD: You're right. I have always been interested in both math and medicine. I knew I did not want to be involved in clinical care. Originally, fresh out of college, I was a math major and I taught high school math for a couple of years. I really enjoyed that, loved the kids, loved the teaching parts of things. Interestingly enough, my department chair at the time assigned me to teach probability and statistics to high school seniors. I had never taken a statistics course before, so I was about a week ahead of them in our classes and found that I just really enjoyed the discipline. So as much as I loved teaching, I did decide to go ahead and invest in this particular new area that I had found and I really enjoyed. So I wanted to figure out how I could engage in the field of statistics. Decided to see, you know, exactly how studying statistics could be applied to medicine. At the time, Google was brand new. So I literally typed in the two words math and medicine to see what would come up. And the discipline of biostatistics is what Google generated. And so here I am, I applied to grad school and it's been a great fit for me.  

[00:02:23] Erin Spain, MS: Oh, that's fantastic. So you went on to get a PhD, and then you came to Northwestern in 2004. And so tell me a little bit about the field then and how it's changed so dramatically since.  

[00:02:36] Denise Scholtens, PhD: So yes, I started here at Northwestern in 2004, just a few months after I had defended my thesis. At the time there was really an emerging field of study called bioinformatics. So I wrote my thesis in the space of genomics data analysis with what at the time was a brand new technology, microarrays. This was the first way we could measure gene transcription at a high throughput level. So I did my thesis work in that space. I studied at an institution with a lot of strengths and very classical statistics. So things that we think of in biostatistics like clinical trial design, observational study analysis, things like that. So I had really classic biostatistics training and then complimented that with sort of these emerging methods with these high dimensional data types. So I came to Northwestern here and I sort of felt like I lived in two worlds. I had sort of classic biostat clinical trials, which were certainly, you know, happening here. And, that work was thriving here at Northwestern, but I had this kind of new skillset, and I just didn't quite know how to bring the two together. That was obviously a long time ago, 20 years ago. Now we think of personalized medicine and genomic indicators for treatment and, you know, there's a whole variety of omics data variations on the theme that are closely integrated with clinical and population level health research. So there's no longer any confusion for me about how those two things come together. You know, they're two disciplines that very nicely complement each other. But yeah, I think that does speak to how the field has changed, you know, these sort of classic biostatistics methods are really nicely blended with a lot of high dimensional data types. And it's been fun to be a part of that.  

[00:04:17] Erin Spain, MS: There were only a handful of folks like you at Northwestern at the time. Tell me about now and the demand for folks with your skill set.  

[00:04:26] Denise Scholtens, PhD: When I came to Northwestern, I was one of a very small handful of biostatistics faculty. There were five of us. We were not even called a division of biostatistics. We were just here as the Department of Preventive Medicine. And a lot of the work we did was really very tightly integrated with the epidemiologists here in our department and we still do a lot of that for sure. There was also some work going on with the Cancer Center here at Northwestern. But yeah, a pretty small group of us, who has sort of a selected set of collaborations. You know, I contrast that now to our current division of biostatistics where we are over 20s, pushing 25, depending on exactly how you want to count. Hoping to bring a couple of new faculty on board this calendar year. We have a staff of about 25 statistical analysts. And database managers and programmers. So you know, when I came there were five faculty members and I think two master's level staff. We are now pushing, you know, pushing 50 people in our division here so it's a really thriving group.  

[00:05:26] Erin Spain, MS: in your opinion, what makes a good biostatistician? Do you have to have a little bit of a tough skin to be in this field?  

Denise Scholtens, PhD: I do think it's a unique person who wants to be a biostatistician. There are a variety of traits that can lead to success in this space. First of all, I think it's helpful to be wildly curious about somebody else's work. To be an excellent collaborative biostatistician, you have to be able to learn the language of another discipline. So some other clinical specialty or public health application. Another trait that makes a biostatistician successful is to be able to ask the right questions about data that will be collected or already have been collected. So understanding the subtleties there, the study design components that lead to why we have the data that we have. You know, a lot of our data, you could think of it in a simple flat file, right? Like a Microsoft Excel file with rows and columns. That certainly happens a lot, but there are a lot of incredibly innovative data types out there: wearables technology, imaging data, all kinds of high dimensional data. So I think a tenacity to understand all of the subtleties of those data and to be able to ask the right questions. And then I think for a biostatistician at a medical school like ours, being able to blend those two things, so understanding what the data are and what you have to work with and what you're heading toward, but then also facilitating the translation of those analytic findings for the audience that really wants to understand them. So for the clinicians, for the patients, for participants and the population that the findings would apply to.   

Erin Spain, MS: It must feel good, though, in those situations where you are able to help uncover something to improve a study or a trial.  

[00:07:07] Denise Scholtens, PhD: It really does. This is a job that's easy to get out of bed for in the morning. There's a lot of really good things that happen here. It's exciting to know that the work we do could impact clinical practice, could impact public health practice. I think in any job, you know, you can sometimes get bogged down by the amount of work or the difficulty of the work or the back and forth with team members. There's just sort of all of the day to day grind, but to be able to take a step back and remember the actual people who are affected by our own little niche in this world. It's an incredibly helpful and motivating practice that I often keep to remember exactly why I'm doing what I'm doing and who I'm doing it for.  

[00:07:50] Erin Spain, MS: Well, and another important part of your work is that you are a leader. You are leading the center, NUDACC, that you mentioned, Northwestern University Data Analysis and Coordinating Center. Now, this has been open for about five years. Tell me about the center and why it's so crucial to the future of the field.  

[00:08:08] Denise Scholtens, PhD: We specialize at NUDACC in large scale, multicenter prospective studies. So these are the clinical trials or the observational studies that often, most conclusively, lead to clinical or public health practice decision making. We focus specifically on multicenter work. Because it requires a lot of central coordination and we've specifically built up our NUDACC capacity to handle these multi center investigations where we have a centralized database, we have centralized and streamlined data quality assurance pipelines. We can help with central team leadership and organization for large scale networks. So we have specifically focused on those areas. There's a whole lot of project management and regulatory expertise that we have to complement our data analytics strengths as well. I think my favorite part of participating in these studies is we get involved at the very beginning. We are involved in executive level planning of these studies. We oversee all components of study design. We are intimately involved in the development of the data capture systems. And in the QA of it. We do all of this work on the front end so that we get all of the fun at the end with the statistics and can analyze data that we know are scientifically sound, are well collected, and can lead to, you know, really helpful scientific conclusions.  

[00:09:33] Erin Spain, MS: Tell me about that synergy between the clinicians and the other investigators that you're working with on these projects.  

[00:09:41] Denise Scholtens, PhD: It is always exciting, often entertaining. Huge range of scientific opinion and expertise and points of view, all of which are very valid and very well informed. All of the discussion that could go into designing and launching a study, it's just phenomenally interesting and trying to navigate all of that and help bring teams to consensus in terms of what is scientifically most relevant, what's going to be most impactful, what is possible given the logistical strengths. Taking all of these well informed, valid, scientific points of view and being a part of the team that helps integrate them all toward a cohesive study design and a well executed study. That's a unique part of the challenge that we face here at NUDACC, but an incredibly rewarding one. It's also such an honor and a gift to be able to work with such a uniformly gifted set of individuals. Just the clinical researchers who devote themselves to these kinds of studies are incredibly generous, incredibly thoughtful and have such care for their patients and the individuals that they serve, that to be able to sit with them and think about the next steps for a great study is a really unique privilege.  

[00:10:51] Erin Spain, MS: How unique is a center like this at a medical school?  

[00:10:55] Denise Scholtens, PhD: It's fairly unique to have a center like this at a medical school. Most of the premier medical research institutions do have some level of data coordinating center capacity. We're certainly working toward trying to be one of the nation's best, absolutely, and build up our capacity for doing so. I'm actually currently a part of a group of data coordinating centers where it's sort of a grassroots effort right now to organize ourselves and come up with, you know, some unified statements around the gaps that we see in our work, the challenges that we face strategizing together to improve our own work and to potentially contribute to each other's work. I think maybe the early beginnings of a new professional organization for data coordinating centers. We have a meeting coming up of about, I think it's 12 to 15 different institutions, academic research institutions, specifically medical schools that have centers like ours to try to talk through our common pain points and also celebrate our common victories.  

[00:11:51] Erin Spain, MS: I want to shift gears a little bit to talk about some of your research collaborations, many of which focus on maternal and fetal health and pregnancy. You're now involved with a study with folks at the Ohio State University that received a 14 million grant looking at the effectiveness of aspirin in the prevention of hypertensive disorders in pregnancy. Tell me about this work.  

[00:12:14] Denise Scholtens, PhD: Yes, this is called the aspirin study. I suppose not a very creative name, but a very appropriate one. What we'll be doing in this study is looking at two different doses of aspirin for trying to prevent maternal hypertensive disorders of pregnancy in women who are considered at high risk for these disorders. This is a huge study. Our goal is to enroll 10,742 participants. This will take place at 11 different centers across the nation. And yes, we at NUDACC will serve as the data coordinating center here, and we are partnering with the Ohio State University who will house the clinical coordinating center. So this study is designed to look at two different doses to see which is more effective at preventing hypertensive disorders of pregnancy. So that would include gestational hypertension and preeclampsia. What's really unique about this study and the reason that it is so large is that it is specifically funded to look at what's called a heterogeneity of treatment effect. What that is is a difference in the effectiveness of aspirin in preventing maternal hypertensive disorders, according to different subgroups of women. We'll specifically have sufficient statistical power to test for differences in treatment effectiveness. And we have some high priority subgroups that we'll be looking at. One is a self-identified race. There's been a noted disparity in maternal hypertensive disorders, for individuals who self identify according to different races. And so we will be powered to see if aspirin has comparable effectiveness and hopefully even better effectiveness for the groups who really need it, to bring those rates closer to equity which is, you know, certainly something we would very strongly desire to see. We'll also be able to look at subgroups of women according to obesity, according to maternal age at pregnancy, according to the start time of aspirin when aspirin use is initiated during pregnancy. So that's why the trial is so huge. For a statistician, the statisticians out there who might be listening, this is powered on a statistical interaction term, which doesn't happen very often. So it's exciting that the trial is funded in that way.  

[00:14:27] Erin Spain, MS: Tell me a little bit more about this and how your specific skills are going to be utilized in this study.  

[00:14:32] Denise Scholtens, PhD: Well, there are three biostatistics faculty here at Northwestern involved in this. So we're definitely dividing and conquering. Right now, we're planning this study and starting to stand it up. So we're developing our statistical analysis plans. We're developing the database. We are developing our randomization modules. So this is the piece of the study where participants are randomized to which dose of aspirin they're going to receive. Because of all of the subgroups that we're planning to study, we need to make especially sure that the assignments of which dose of aspirin are balanced within and across all of those subgroups. So we're going to be using some adaptive randomization techniques to ensure that that balance is there. So there's some fun statistical and computer programming innovation that will be applied to accomplish those things. So right now, there are usually two phases of a study that are really busy for us. That's starting to study up and that's where we are. And so yes, it is very busy for us right now. And then at the end, you know, in five years or so, once recruitment is over, then we analyze all the data,  

[00:15:36] Erin Spain, MS: Are there any guidelines out there right now about the use of aspirin in pregnancy. What do you hope that this could accomplish?  

 Prescribing aspirin use for the prevention of hypertension during pregnancy is not uncommon at all. That is actually fairly routinely done, but that it's not outcomes based in terms of which dosage is most effective. So 81 milligrams versus 162 milligrams. That's what we will be evaluating. And my understanding is that clinicians prescribe whatever they think is better, and I'm sure those opinions are very well informed but there is very little outcome based evidence for this in this particular population that we'll be studying. So that would be the goal here, would be to hopefully very conclusively say, depending on the rates of the hypertensive disorders that we see in our study, which of the two doses of aspirin is more effective. Importantly, we will also be tracking any side effects of taking aspirin. And so that's also very much often a part of the evaluation of You know, taking a, taking a drug, right, is how safe is it? So we'll be tracking that very closely as well. Another unique part of this study is that we will be looking at factors that help explain aspirin adherence. So we are going to recommend that participants take their dose of aspirin daily. We don't necessarily expect that's always going to happen, so we are going to measure how much of their prescribed dose they are actually taking and then look at, you know, factors that contribute to that. So be they, you know, social determinants of health or a variety of other things that we'll investigate to try to understand aspirin adherence, and then also model the way in which that adherence could have affected outcomes.  

Erin Spain, MS: This is not the first study that you've worked on involving maternal and fetal health. Tell me about your interest in this particular area, this particular field, and some of the other work that you've done.  

[00:17:31] Denise Scholtens, PhD: So I actually first got my start in data coordinating work through the HAPO study. HAPO stands for Hyperglycemia Adverse Pregnancy Outcome. That study was started here at Northwestern before I arrived. Actually recruitment to the study occurred between 2000 and 2006. Northwestern served as the central coordinating center for that study. It was an international study of 25,000 pregnant individuals who were recruited and then outcomes were evaluated both in moms and newborns. When I was about mid career here, all the babies that were born as a part of HAPO were early teenagers. And so we conducted a follow up study on the HAPO cohort. So that's really when I got involved. It was my first introduction to being a part of a coordinating center. As I got into it, though, I saw the beauty of digging into all of these details for a huge study like this and then saw these incredible resources that were accumulated through the conduct of such a large study. So the data from the study itself is, was of course, a huge resource. But then also we have all of these different samples that sit in a biorepository, right? So like usually blood sample collection is a big part of a study like this. So all these really fun ancillary studies could spin off of the HAPO study. So we did some genomics work. We did some metabolomics work. We've integrated the two and what's called integrated omics. So, you know, my work in this space really started in the HAPO study. And I have tremendously enjoyed integrating these high dimensional data types that have come from these really rich data resources that have all, you know, resulted because of this huge multicenter longitudinal study. So I kind of accidentally fell into the space of maternal and fetal health, to be honest. But I just became phenomenally interested in it and it's been a great place.  

[00:19:24] Erin Spain, MS: Would you say that this is also a population that hasn't always been studied very much in biomedical science?  

[00:19:32] Denise Scholtens, PhD: I think that that is true, for sure. There are some unique vulnerabilities, right, for a pregnant individual and for the fetus, right, and in that situation. You know, the vast majority of what we do is really only pertaining to the pregnant participant but, you know, there are certainly fetal outcomes, newborn outcomes. And so, I think conducting research in this particular population is a unique opportunity and there are components of it that need to be treated with special care given sort of this unique phase of human development and this unique phase of life.  

[00:20:03] Erin Spain, MS: So, as data generation just really continues to explode, and technology is advancing so fast, faster than ever, where do you see this field evolving, the field of biostatistics, where do you see it going in the next five to ten years?  

[00:20:19] Denise Scholtens, PhD: That's a great question. I think all I can really tell you is that I'm continually surprised by new data types. I think that we will see an emergence of a whole new kind of technology that we probably can't even envision five years from now. And I think that the fun part about being a biostatistician is seeing what's happening and then trying to wrap your mind around the possibilities and the actual nature of the data that are collected. You know, I think back to 2004 and this whole high throughput space just felt so big. You know, we could look at gene transcription across the genome using one technology. And we could only look at one dimension of it. Right now it just seems so basic. When I think about where the field has come over the past 20 years, it's just phenomenal. I think we're seeing a similar emergence of the scale and the type of data in the imaging space and in the wearable space, with EHR data, just. You know, all these different technologies for capturing, capturing things that we just never even conceived of before. I do hope that we continue to emphasize making meaningful and translatable conclusions from these data. So actionable conclusions that can impact the way that we care for others around us. I do hope that remains a guiding principle in all that we do.  

[00:21:39] Erin Spain, MS: Why is Northwestern Medicine and Northwestern Feinberg School of Medicine such a supportive environment to pursue this type of work?  

[00:21:47] Denise Scholtens, PhD: That's a wonderful question and one, honestly, that faculty candidates often ask me. When we bring faculty candidates in to visit here at Northwestern, they immediately pick up on the fact that we are a collaborative group of individuals who are for each other. Who want to see each other succeed, who are happy to share the things that we know and support each other's work, and support each other's research, and help strategize around the things that we want to accomplish. There is a strong culture here, at least in my department and in my division that I've really loved that continues to persist around really genuinely collaborating and genuinely sharing lessons learned and genuinely supporting each other as we move toward common goals. We've had some really strong, generous leadership who has helped us to get there and has helped create a culture where those are the guiding principles. In my leadership role is certainly something that I strive to maintain. Really hope that's true. I'm sure I don't do it perfectly but that's absolutely something I want to see accomplished here in the division and in NUDACC for sure.  

[00:22:50] Erin Spain, MS: Well, thank you so much for coming on the show and telling us about your path here to Northwestern and all of the exciting work that we can look forward to in the coming years.  

[00:22:59] Denise Scholtens, PhD: Thank you so much for having me. I've really enjoyed this.  

[00:23:01] Erin Spain, MS: You can listen to shows from the Northwestern Medicine Podcast Network to hear more about the latest developments in medical research, health care, and medical education. Leaders from across specialties speak to topics ranging from basic science to global health to simulation education. Learn more at feinberg. northwestern.edu/podcasts.  

Research Scientist, Foundation Model, Video Generation, University Graduates - 2024 Start (PhD)

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Research Scientist, Foundation Model, Video Generation

TikTok , Seattle, WA

Research Scientist in Foundation Model, Speech Understanding - 2024 Start (PhD)