Advertisement

Advertisement

A Survey on the Effectiveness of Online Teaching–Learning Methods for University and College Students

  • Article of professional interests
  • Published: 05 April 2021
  • Volume 102 , pages 1325–1334, ( 2021 )

Cite this article

  • Preethi Sheba Hepsiba Darius   ORCID: orcid.org/0000-0003-0882-6213 1 ,
  • Edison Gundabattini   ORCID: orcid.org/0000-0003-4217-2321 2 &
  • Darius Gnanaraj Solomon   ORCID: orcid.org/0000-0001-5321-5775 2  

127k Accesses

30 Citations

Explore all metrics

Online teaching–learning methods have been followed by world-class universities for more than a decade to cater to the needs of students who stay far away from universities/colleges. But during the COVID-19 pandemic period, online teaching–learning helped almost all universities, colleges, and affiliated students. An attempt is made to find the effectiveness of online teaching–learning methods for university and college students by conducting an online survey. A questionnaire has been specially designed and deployed among university and college students. About 450 students from various universities, engineering colleges, medical colleges in South India have taken part in the survey and submitted responses. It was found that the following methods promote effective online learning: animations, digital collaborations with peers, video lectures delivered by faculty handling the subject, online quiz having multiple-choice questions, availability of student version software, a conducive environment at home, interactions by the faculty during lectures and online materials provided by the faculty. Moreover, online classes are more effective because they provide PPTs in front of every student, lectures are heard by all students at the sound level of their choice, and walking/travel to reach classes is eliminated.

Avoid common mistakes on your manuscript.

Introduction

Critical thinking and creativity of students increase with innovative educational methods according to the world declaration on higher education in the twenty-first century [ 1 ]. Innovative educational strategies and educational innovations are required to make the students learn. There are three vertices in the teaching–learning process viz., teaching, communication technology through digital tools, and innovative practices in teaching. In the first vertex, the teacher is a facilitator and provides resources and tools to students and helps them to develop new knowledge and skills. Project-based learning helps teachers and students to promote collaborative learning by discussing specific topics. Cognitive independence is developed among students. To promote global learning, teachers are required to innovate permanently. It is possible when university professors and researchers are given space to new educational forms in different areas of specializations. Virtual classrooms, unlike traditional classrooms, give unlimited scope for introducing teaching innovation strategies. The second vertex refers to the use of Information and Communication Technology (ICT) tools for promoting innovative education. Learning management systems (LMS) help in teaching, learning, educational administration, testing, and evaluation. The use of ICT tools promotes technological innovations and advances in learning and knowledge management. The third vertex deals with innovations in teaching/learning to solve problems faced by teachers and students. Creative use of new elements related to curriculum, production of something new, and transformations emerge in classrooms resulting in educational innovations. Evaluations are necessary to improve the innovations so that successful methods can be implemented in all teaching and learning community in an institution [ 2 ]. The pandemic has forced digital learning and job portal Naukri.com reports a fourfold growth for teaching professionals in the e-learning medium [ 3 ]. The initiatives are taken by the government also focus on online mode as an option in a post-covid world [ 4 ]. A notable learning experience design consultant pointed out that, educators are entrusted to lead the way as the world changes and are actively involved in the transformation [ 5 ]. Weiss notes that an educator needs to make the lectures more interesting [ 6 ].

This paper presents the online teaching–learning tools, methods, and a survey on the innovative practices in teaching and learning. Advantages and obstacles in online teaching, various components on the effective use of online tools, team-based collaborative learning, simulation, and animation-based learning are discussed in detail. The outcome of a survey on the effectiveness of online teaching and learning is included. The following sections present the online teaching–learning tools, the details of the questionnaire used for the survey, and the outcome of the survey.

Online Teaching and Learning Tools

The four essential parts of online teaching [ 7 ] are virtual classrooms, individual activities, assessments in real-time, and collaborative group work. Online teaching tools are used to facilitate faculty-student interaction as well as student–student collaborations [ 8 ]. The ease of use, the satisfaction level, the usefulness, and the confidence level of the instructor is crucial [ 9 ] in motivating the instructor to use online teaching tools. Higher education institutes recognize the need to accommodate wide diverse learners and Hilliard [ 10 ] points out that technical support and awareness to both faculty and student is essential in the age of blended learning. Data analytics tool coupled with the LMS is essential to enhance [ 11 ] the quality of teaching and improve the course design. The effective usage of online tools is depicted in Fig.  1 comprising of an instructor to student delivery, collaboration among students, training for the tools, and data analytics for constant improvement of course and assessment methods.

figure 1

The various components of effective usage of online tools

Online Teaching Tools

A plethora of online teaching tools are available and this poses a challenge for decision-makers to choose the tools that best suits the needs of the course. The need for the tools, the cost, usability, and features determine which tools are adopted by various learners and institutions. Many universities have offered online classes for students. These are taken up by students opting for part-time courses. This offers them flexibility in timing and eliminates the need for travel to campus. The pandemic situation in 2019 has forced many if not all institutions to completely shift classes online. LMS tools are packaged as Software as a Service (SaaS) and the pricing generally falls into 4 categories: (i) per learner, per month (ii) per learner, per use (iii) per course (iv) licensing fee for on-premise installation [ 12 ].

Online Learning Tools

Online teaching/learning as part of the ongoing semester is typically part of a classroom management tool. GSuite for education [ 13 ] and Microsoft Teams [ 14 ] are both widely adopted by schools and colleges during the COVID-19 pandemic to effectively shift regular classes online. Other popular learning management systems that have been adopted as part of blended learning are Edmodo [ 15 ], Blackboard [ 16 ], and MoodleCloud [ 17 ]. Davis et al. [ 18 ] point out advantages and obstacles for both students and instructors about online teaching shown in Table 1 .

The effectiveness of course delivery depends on using the appropriate tools in the course design. This involves engaging the learners and modifying the course design to cater to various learning styles.

A Survey on Innovative Practices in Teaching and Learning

The questionnaire aims to identify the effectiveness of various online tools and technologies, the preferred learning methods of students, and other factors that might influence the teaching–learning process. The parameters were based on different types of learners, advantages, and obstacles to online learning [ 10 , 18 ]. Questions 1–4 are used to comprehend the learning style of the student. Questions 5–7 are posed to find out the effectiveness of the medium used for teaching and evaluation. Questions 8–12 are framed to identify the various barriers to online learning faced by students.

This methodology is adopted as most of the students are attending online courses from home and polls of this kind will go well with the students from various universities. Students participated in the survey and answered most of the questionnaire enthusiastically. The only challenge was a suitable environment and free time for them to answer the questionnaire, as they are already loaded with lots of online work. Students from various universities pursuing professional courses like engineering and medicine took part in this survey. They are from various branches of sciences and technologies. Students are from private universities, colleges, and government institutions. Figure  2 shows the institution-wise respondents. Microsoft Teams and Google meet platforms were used for this survey among university, medical college, and engineering college students. About 450 students responded to this survey. 52% of the respondents are from VIT University Vellore, Tamil Nadu, 23% of the respondents are from CMR Institute of Technology (CMRIT), Bangalore, 15% of the respondents are from medical colleges and 10% are from other engineering colleges. During this pandemic period, VIT students are staying with parents who are living in different states of India like Andhra, Telangana, Kerala, Karnataka, MP, Haryana, Punjab, Maharashtra, Andaman, and so on. Only a few students are living in Tamil Nadu. Some of the students are staying with parents in other countries like Dubai, Oman, South Africa, and so on. Some of the students of CMRIT Bangalore are living in Bangalore and others in towns and villages of Karnataka state. Students of medical colleges are living in different parts of Tamil Nadu and students of engineering colleges are living in different parts of Andhra Pradesh. Hence, the survey is done in a wider geographical region.

figure 2

Institution-wise respondents

Figure  3 shows the branch-wise respondents. It is shown that 158 students belong to mechanical/civil engineering. 108 respondents belong to computer science and engineering, 68 students belong to medicine, 58 students belong to electrical & electronics engineering, and electronics & communication engineering. 58 students belong to other disciplines.

figure 3

Branch-wise respondents

Questionnaire Used

Students were assured of their confidentiality and were promised that their names would not appear in the document. A list of the questions asked as part of the survey is given below.

Questionnaire:

Sample group: B Tech students from different branches of sciences across various engineering institutions and MBBS medical students.

Which of the methods engage you personally to learn digitally ?

Individual assignment

Small group (No. 5 students) work

Large group (No. 10 students and more) work

Project-based learning

Which of the digital collaborations enables you to work on a specific task at ease

Two by two (2 member team)

Small group workgroup (No. 5 students) work

Which of the digital approaches motivate you to learn

Whiteboard and pen

PowerPoint presentation

Digital pen and slate

My experience with online learning from home digitally

I am learning at my own pace comfortably

My situational challenges are not suitable

I can learn better with uninterrupted network connectivity

I am distracted with various activities at home, viz. TV, chatting, etc.

Which type of recorded video lecture is more effective for learning ?

delivered by my faculty

delivered by NPTEL

delivered by reputed Overseas Universities

delivered by unknown experts

Which type of quiz is more effective for testing the understanding?

Traditional—pen and paper—MCQ

Traditional—pen and paper—short answers

Online quiz—MCQ

Online quiz—short answers

Student version software downloaded from the internet is useful for learning

Unable to decide

Online teaching – learning takes place effectively because:

Every student can hear the lecture clearly

PPTs are available right in front of every student

Students can ask doubts without much reservation

Students need not walk long distances before reaching the class

Which of the following statements is true of online learning off-campus ?

No one disturbs me during my online learning.

My friend/family member/roommate/neighbor occasionally disturb me

My friend/family member/roommate/neighbor constantly disturb me

At home/place of residence, how many responsibilities do you have?

I don’t have many responsibilities.

I have a moderate amount of responsibilities, but I have sufficient time for online learning.

I have many responsibilities; I don’t have any time left for online learning.

What is your most preferred method for clearing doubts in online learning?

Ask the professor during/after an online lecture

Post the query in a discussion forum of your class and get help from your peers

Go through online material providing an additional explanation.

Which of the following devices do you use for your online learning?

A laptop/desktop computer

A smartphone

Other devices

Outcome of the survey

Students would prefer to work in a group of 5 students to engage personally in digital learning as seen from Fig.  4 .

figure 4

Personal engagement in digital learning

Digital collaboration to enable students to work at ease on a specific task is to allow them to work in small groups of 5 students as seen in Fig.  5 .

figure 5

Digital collaboration to enable students to work at ease

Animations are found to be the best digital approach motivating many students to learn as seen in Fig.  6 .

figure 6

Digital approaches that motivate students to learn

The online learning experience of students is shown in Fig.  7 . The majority of students have said that they can learn at their own pace comfortably through online learning.

figure 7

The online learning experience of students

The effectiveness of the recorded video lecture is shown in Fig.  8 . The majority of students agree that the video lectures delivered by his/her faculty teaching the subject help students to learn effectively.

figure 8

More effective recorded video lecture

Online quiz having multiple-choice questions (MCQ) is preferred by most of the students for testing their understanding of the subject as seen in Fig.  9 .

figure 9

More effective quiz for testing the understanding

The usefulness of the student version of the software downloaded from the internet is shown in Fig.  10 . 45.7% of the students agree that it is useful for learning whereas 45.2% of them are unable to decide. The rest of the students feel that the student version of the software is not useful.

figure 10

The usefulness of the student version of the software

The reasons for the effectiveness of online teaching–learning are shown in Fig.  11 . The majority of the students, feel that the PPTs are available right in front of every student so that following the lecture makes the learning effective. In universities where a fully flexible credit system (FFCS) is followed, students need to walk long distances for reaching their classrooms. Day Scholars in universities as well as engineering colleges are required to travel a considerable distance before reaching the first-hour class. According to many students, online learning is more effective since walking/traveling is completed eliminated. If the voice of the faculty member is feeble, students sitting in the last few rows of the class would not hear the lecture completely. Some students feel that online learning is more effective since the lecture is reaching every student irrespective of the number of students in a virtual classroom.

figure 11

Reasons for the effectiveness of online teaching–learning

50.3% of students agree that they do not have any disturbance during online learning and it is more effective. Many of them feel that occasionally their friends or relatives disturb students during their online learning as shown in Fig.  12 .

figure 12

Disturbances during online learning

Figure  13 shows the environment at home for online learning. 76.9% of the respondents stated that they have a moderate amount of responsibilities at home but they have sufficient time for online learning. 16.1% of them have said that they do not have many responsibilities whereas 7% of them claimed that they have many responsibilities at home and they do not have any time left for online learning.

figure 13

The environment at home for online learning

Figure  14 shows the methods adopted for clearing doubts in online learning. 43.2% of the respondents ask the Professor and get their doubts clarified during online lectures. 25.5% of them post queries in the discussion forum and help from peers. 31.3% of them go through the online materials providing additional explanation and get their doubts clarified.

figure 14

Methods adopted for clearing doubts in online learning

Figure  15 shows the devices used by students for online learning. Most of the students use laptop/desktop computers, many of them use smartphones and very few students use tablets.

figure 15

Devices used for online learning

The association between responses 1 and 2 is tested using the chi-square test. The results are presented in Table 2 which shows the observed cell totals, expected cell values, and chi-square statistic for each cell. It is seen that association exists between several responses between questions.

The observed cell values indicate that the highest association is found between responses 1b and 2b since both these responses are related to a small working group having 5 members. The lowest association is found between the responses of 1c and 2a having the lowest observed cell value and expected cell value. The reason for this is response 1c shows the work done by a 10 member team and the response 2a shows a two-member team. The chi-square statistic is 65.6025. The p value is < 0.00001. The result is significant at p  < 0.05.

The outcome of a survey on the effectiveness of innovations in online teaching–learning methods for university and college students is presented. About 450 students belonging to VIT Vellore, CMRIT Bangalore, Medical College, Pudukkottai, and engineering colleges have responded to the survey. A questionnaire designed for taking is survey is presented. The chi-square statistic is 65.6025. The p value is < 0.00001. The result is significant at p  < 0.05. Associations between several responses of questions exist. The survey undertaken provides an estimate of the effectiveness and pitfalls of online teaching during the online teaching that has been taking place during the pandemic. The study done paves the way for educators to understand the effectiveness of online teaching. It is important to redesign the course delivery in an online mode to make students engaged and the outcome of the survey supports these aforementioned observations.

The outcome of the survey is given below:

A small group of 5 students would help students to have digital collaboration and engage personally in digital learning.

Animations are found to be the best digital approach for effective learning.

Online learning helps students to learn at their own pace comfortably.

Students prefer to learn from video lectures delivered by his/her faculty handling the subject.

Online quiz having multiple-choice questions (MCQ) preferred by students.

Student version software is useful for learning.

Online classes are more effective because they provide PPTs in front of every student, lectures are heard by all students at the sound level of their choice, and walking/travel to reach classes is eliminated.

Students do not have any disturbances or distractions which make learning more effective.

But for a few students, most of the students have no or limited responsibilities at home which provides a good ambiance and a nice environment for effective online learning.

Students can get their doubts clarified during lectures, by posting queries in discussion forums and by referring to online materials provided by the faculty.

World Declaration on Higher Education for the Twenty-first Century: Vision and Action (1998) https://unesdoc.unesco.org/ark:/48223/pf0000141952 . Accessed on 10 December 2020.

S. Cadena-Vela, J.O. Herrera, G. Torres, G. Mejía-Madrid, Innovation in the university, in: Proceedings of the Sixth International Conference on Technological Ecosystems for Enhancing Multiculturality-TEEM’18 (2018), pp. 799–805. https://doi.org/10.1145/3284179.3284308

Demand for online tutors soars, pay increases 28%. Times of India (2020) https://timesofindia.indiatimes.com/city/chennai/demand-for-online-tutors-soars-pay-increases-28/articleshow/77939414.cms . Accessed on 7 December 2020

Can 100 top universities expand e-learning opportunities for 3.7 crore students. Times of India (2020) https://timesofindia.indiatimes.com/home/education/news/can-100-top-universities-expand-e-learning-opportunities-for-3-7-crore-students/articleshow/76032068.cms . Accessed on 9 December 2020.

C. Malemed, Retooling instructional design (2019). https://theelearningcoach.com/elearning2-0/retooling-instructional-design/ accessed on 8 December 2020

C. Wiess, COVID-19 and its impact on learning (2020). https://elearninfo247.com/2020/03/16/covid-19-and-its-impact-on-learning/ . Accessed on 10 December 2020

E. Alqurashi, Technology tools for teaching and learning in real-time, in Educational Technology and Resources for Synchronous Learning in Higher Education (IGI Global, 2019), pp. 255–278

J.M. Mbuva, Examining the effectiveness of online educational technological tools for teaching and learning and the challenges ahead. J. Higher Educ. Theory Pract. 15 (2), 113 (2015)

Google Scholar  

S.N.M. Mohamad, M.A.M. Salleh, S. Salam, Factors affecting lecturer’s motivation in using online teaching tools. Procedia Soc. Behav. Sci. 195 , 1778–1784 (2015)

Article   Google Scholar  

A.T. Hilliard, Global blended learning practices for teaching and learning, leadership and professional development. J. Int. Educ. Res. 11 (3), 179–188 (2015)

M. Moussavi, Y. Amannejad, M. Moshirpour, E. Marasco, L. Behjat, Importance of data analytics for improving teaching and learning methods, in Data Management and Analysis (Springer, Cham, 2020), pp. 91–101

P. Berking, S. Gallagher, Choosing a learning management system, in Advanced Distributed Learning (ADL) Co-Laboratories (2013), pp 40–62

R.J.M. Ventayen, K.L.A. Estira, M.J. De Guzman, C.M. Cabaluna, N.N. Espinosa, Usability evaluation of google classroom: basis for the adaptation of gsuite e-learning platform. Asia Pac. J. Educ. Arts Sci. 5 (1), 47–51 (2018)

B.N. Ilag, Introduction: microsoft teams, in Introducing Microsoft Teams (Apress, Berkeley, CA, 2018), pp. 1–42

A.S. Alqahtani, The use of Edmodo: its impact on learning and students’ attitudes towards it. J. Inf. Technol. Educ. 18 , 319–330 (2019)

J. Uziak, M.T. Oladiran, E. Lorencowicz, K. Becker, Students’ and instructor’s perspectives on the use of Blackboard Platform for delivering an engineering course. Electron. J. E-Learn. 16 (1), 1 (2018)

T. Makarchuk, V. Trofimov, S. Demchenko, Modeling the life cycle of the e-learning course using Moodle Cloud LMS, in Conferences of the Department Informatics , No. 1 (Publishing house Science and Economics Varna, 2019), pp. 62–71

N.L. Davis, M. Gough, L.L. Taylor, Online teaching: advantages, obstacles, and tools for getting it right. J. Teach. Travel Tour. 19 (3), 256–263 (2019)

Download references

Author information

Authors and affiliations.

Department of Computer Science and Engineering, CMR Institute of Technology, Bangalore, 560037, India

Preethi Sheba Hepsiba Darius

School of Mechanical Engineering, Vellore Institute of Technology, Vellore, 632014, India

Edison Gundabattini & Darius Gnanaraj Solomon

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Darius Gnanaraj Solomon .

Additional information

Publisher's note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Darius, P.S.H., Gundabattini, E. & Solomon, D.G. A Survey on the Effectiveness of Online Teaching–Learning Methods for University and College Students. J. Inst. Eng. India Ser. B 102 , 1325–1334 (2021). https://doi.org/10.1007/s40031-021-00581-x

Download citation

Received : 10 August 2020

Accepted : 18 March 2021

Published : 05 April 2021

Issue Date : December 2021

DOI : https://doi.org/10.1007/s40031-021-00581-x

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

  • Learning management
  • Learning environment
  • Teaching and learning
  • Digital learning
  • Collaborative learning
  • Online learning
  • Find a journal
  • Publish with us
  • Track your research

U.S. flag

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

  • Publications
  • Account settings
  • Advanced Search
  • Journal List
  • Wiley - PMC COVID-19 Collection

Logo of pheblackwell

Online and face‐to‐face learning: Evidence from students’ performance during the Covid‐19 pandemic

Carolyn chisadza.

1 Department of Economics, University of Pretoria, Hatfield South Africa

Matthew Clance

Thulani mthembu.

2 Department of Education Innovation, University of Pretoria, Hatfield South Africa

Nicky Nicholls

Eleni yitbarek.

This study investigates the factors that predict students' performance after transitioning from face‐to‐face to online learning as a result of the Covid‐19 pandemic. It uses students' responses from survey questions and the difference in the average assessment grades between pre‐lockdown and post‐lockdown at a South African university. We find that students' performance was positively associated with good wifi access, relative to using mobile internet data. We also observe lower academic performance for students who found transitioning to online difficult and who expressed a preference for self‐study (i.e. reading through class slides and notes) over assisted study (i.e. joining live lectures or watching recorded lectures). The findings suggest that improving digital infrastructure and reducing the cost of internet access may be necessary for mitigating the impact of the Covid‐19 pandemic on education outcomes.

1. INTRODUCTION

The Covid‐19 pandemic has been a wake‐up call to many countries regarding their capacity to cater for mass online education. This situation has been further complicated in developing countries, such as South Africa, who lack the digital infrastructure for the majority of the population. The extended lockdown in South Africa saw most of the universities with mainly in‐person teaching scrambling to source hardware (e.g. laptops, internet access), software (e.g. Microsoft packages, data analysis packages) and internet data for disadvantaged students in order for the semester to recommence. Not only has the pandemic revealed the already stark inequality within the tertiary student population, but it has also revealed that high internet data costs in South Africa may perpetuate this inequality, making online education relatively inaccessible for disadvantaged students. 1

The lockdown in South Africa made it possible to investigate the changes in second‐year students' performance in the Economics department at the University of Pretoria. In particular, we are interested in assessing what factors predict changes in students' performance after transitioning from face‐to‐face (F2F) to online learning. Our main objectives in answering this study question are to establish what study materials the students were able to access (i.e. slides, recordings, or live sessions) and how students got access to these materials (i.e. the infrastructure they used).

The benefits of education on economic development are well established in the literature (Gyimah‐Brempong,  2011 ), ranging from health awareness (Glick et al.,  2009 ), improved technological innovations, to increased capacity development and employment opportunities for the youth (Anyanwu,  2013 ; Emediegwu,  2021 ). One of the ways in which inequality is perpetuated in South Africa, and Africa as a whole, is through access to education (Anyanwu,  2016 ; Coetzee,  2014 ; Tchamyou et al.,  2019 ); therefore, understanding the obstacles that students face in transitioning to online learning can be helpful in ensuring more equal access to education.

Using students' responses from survey questions and the difference in the average grades between pre‐lockdown and post‐lockdown, our findings indicate that students' performance in the online setting was positively associated with better internet access. Accessing assisted study material, such as narrated slides or recordings of the online lectures, also helped students. We also find lower academic performance for students who reported finding transitioning to online difficult and for those who expressed a preference for self‐study (i.e. reading through class slides and notes) over assisted study (i.e. joining live lectures or watching recorded lectures). The average grades between pre‐lockdown and post‐lockdown were about two points and three points lower for those who reported transitioning to online teaching difficult and for those who indicated a preference for self‐study, respectively. The findings suggest that improving the quality of internet infrastructure and providing assisted learning can be beneficial in reducing the adverse effects of the Covid‐19 pandemic on learning outcomes.

Our study contributes to the literature by examining the changes in the online (post‐lockdown) performance of students and their F2F (pre‐lockdown) performance. This approach differs from previous studies that, in most cases, use between‐subject designs where one group of students following online learning is compared to a different group of students attending F2F lectures (Almatra et al.,  2015 ; Brown & Liedholm,  2002 ). This approach has a limitation in that that there may be unobserved characteristics unique to students choosing online learning that differ from those choosing F2F lectures. Our approach avoids this issue because we use a within‐subject design: we compare the performance of the same students who followed F2F learning Before lockdown and moved to online learning during lockdown due to the Covid‐19 pandemic. Moreover, the study contributes to the limited literature that compares F2F and online learning in developing countries.

Several studies that have also compared the effectiveness of online learning and F2F classes encounter methodological weaknesses, such as small samples, not controlling for demographic characteristics, and substantial differences in course materials and assessments between online and F2F contexts. To address these shortcomings, our study is based on a relatively large sample of students and includes demographic characteristics such as age, gender and perceived family income classification. The lecturer and course materials also remained similar in the online and F2F contexts. A significant proportion of our students indicated that they never had online learning experience before. Less than 20% of the students in the sample had previous experience with online learning. This highlights the fact that online education is still relatively new to most students in our sample.

Given the global experience of the fourth industrial revolution (4IR), 2 with rapidly accelerating technological progress, South Africa needs to be prepared for the possibility of online learning becoming the new norm in the education system. To this end, policymakers may consider engaging with various organizations (schools, universities, colleges, private sector, and research facilities) To adopt interventions that may facilitate the transition to online learning, while at the same time ensuring fair access to education for all students across different income levels. 3

1.1. Related literature

Online learning is a form of distance education which mainly involves internet‐based education where courses are offered synchronously (i.e. live sessions online) and/or asynchronously (i.e. students access course materials online in their own time, which is associated with the more traditional distance education). On the other hand, traditional F2F learning is real time or synchronous learning. In a physical classroom, instructors engage with the students in real time, while in the online format instructors can offer real time lectures through learning management systems (e.g. Blackboard Collaborate), or record the lectures for the students to watch later. Purely online courses are offered entirely over the internet, while blended learning combines traditional F2F classes with learning over the internet, and learning supported by other technologies (Nguyen,  2015 ).

Moreover, designing online courses requires several considerations. For example, the quality of the learning environment, the ease of using the learning platform, the learning outcomes to be achieved, instructor support to assist and motivate students to engage with the course material, peer interaction, class participation, type of assessments (Paechter & Maier,  2010 ), not to mention training of the instructor in adopting and introducing new teaching methods online (Lundberg et al.,  2008 ). In online learning, instructors are more facilitators of learning. On the other hand, traditional F2F classes are structured in such a way that the instructor delivers knowledge, is better able to gauge understanding and interest of students, can engage in class activities, and can provide immediate feedback on clarifying questions during the class. Additionally, the designing of traditional F2F courses can be less time consuming for instructors compared to online courses (Navarro,  2000 ).

Online learning is also particularly suited for nontraditional students who require flexibility due to work or family commitments that are not usually associated with the undergraduate student population (Arias et al.,  2018 ). Initially the nontraditional student belonged to the older adult age group, but with blended learning becoming more commonplace in high schools, colleges and universities, online learning has begun to traverse a wider range of age groups. However, traditional F2F classes are still more beneficial for learners that are not so self‐sufficient and lack discipline in working through the class material in the required time frame (Arias et al.,  2018 ).

For the purpose of this literature review, both pure online and blended learning are considered to be online learning because much of the evidence in the literature compares these two types against the traditional F2F learning. The debate in the literature surrounding online learning versus F2F teaching continues to be a contentious one. A review of the literature reveals mixed findings when comparing the efficacy of online learning on student performance in relation to the traditional F2F medium of instruction (Lundberg et al.,  2008 ; Nguyen,  2015 ). A number of studies conducted Before the 2000s find what is known today in the empirical literature as the “No Significant Difference” phenomenon (Russell & International Distance Education Certificate Center (IDECC),  1999 ). The seminal work from Russell and IDECC ( 1999 ) involved over 350 comparative studies on online/distance learning versus F2F learning, dating back to 1928. The author finds no significant difference overall between online and traditional F2F classroom education outcomes. Subsequent studies that followed find similar “no significant difference” outcomes (Arbaugh,  2000 ; Fallah & Ubell,  2000 ; Freeman & Capper,  1999 ; Johnson et al.,  2000 ; Neuhauser,  2002 ). While Bernard et al. ( 2004 ) also find that overall there is no significant difference in achievement between online education and F2F education, the study does find significant heterogeneity in student performance for different activities. The findings show that students in F2F classes outperform the students participating in synchronous online classes (i.e. classes that require online students to participate in live sessions at specific times). However, asynchronous online classes (i.e. students access class materials at their own time online) outperform F2F classes.

More recent studies find significant results for online learning outcomes in relation to F2F outcomes. On the one hand, Shachar and Yoram ( 2003 ) and Shachar and Neumann ( 2010 ) conduct a meta‐analysis of studies from 1990 to 2009 and find that in 70% of the cases, students taking courses by online education outperformed students in traditionally instructed courses (i.e. F2F lectures). In addition, Navarro and Shoemaker ( 2000 ) observe that learning outcomes for online learners are as effective as or better than outcomes for F2F learners, regardless of background characteristics. In a study on computer science students, Dutton et al. ( 2002 ) find online students perform significantly better compared to the students who take the same course on campus. A meta‐analysis conducted by the US Department of Education finds that students who took all or part of their course online performed better, on average, than those taking the same course through traditional F2F instructions. The report also finds that the effect sizes are larger for studies in which the online learning was collaborative or instructor‐driven than in those studies where online learners worked independently (Means et al.,  2010 ).

On the other hand, evidence by Brown and Liedholm ( 2002 ) based on test scores from macroeconomics students in the United States suggest that F2F students tend to outperform online students. These findings are supported by Coates et al. ( 2004 ) who base their study on macroeconomics students in the United States, and Xu and Jaggars ( 2014 ) who find negative effects for online students using a data set of about 500,000 courses taken by over 40,000 students in Washington. Furthermore, Almatra et al. ( 2015 ) compare overall course grades between online and F2F students for a Telecommunications course and find that F2F students significantly outperform online learning students. In an experimental study where students are randomly assigned to attend live lectures versus watching the same lectures online, Figlio et al. ( 2013 ) observe some evidence that the traditional format has a positive effect compared to online format. Interestingly, Callister and Love ( 2016 ) specifically compare the learning outcomes of online versus F2F skills‐based courses and find that F2F learners earned better outcomes than online learners even when using the same technology. This study highlights that some of the inconsistencies that we find in the results comparing online to F2F learning might be influenced by the nature of the course: theory‐based courses might be less impacted by in‐person interaction than skills‐based courses.

The fact that the reviewed studies on the effects of F2F versus online learning on student performance have been mainly focused in developed countries indicates the dearth of similar studies being conducted in developing countries. This gap in the literature may also highlight a salient point: online learning is still relatively underexplored in developing countries. The lockdown in South Africa therefore provides us with an opportunity to contribute to the existing literature from a developing country context.

2. CONTEXT OF STUDY

South Africa went into national lockdown in March 2020 due to the Covid‐19 pandemic. Like most universities in the country, the first semester for undergraduate courses at the University of Pretoria had already been running since the start of the academic year in February. Before the pandemic, a number of F2F lectures and assessments had already been conducted in most courses. The nationwide lockdown forced the university, which was mainly in‐person teaching, to move to full online learning for the remainder of the semester. This forced shift from F2F teaching to online learning allows us to investigate the changes in students' performance.

Before lockdown, classes were conducted on campus. During lockdown, these live classes were moved to an online platform, Blackboard Collaborate, which could be accessed by all registered students on the university intranet (“ClickUP”). However, these live online lectures involve substantial internet data costs for students. To ensure access to course content for those students who were unable to attend the live online lectures due to poor internet connections or internet data costs, several options for accessing course content were made available. These options included prerecorded narrated slides (which required less usage of internet data), recordings of the live online lectures, PowerPoint slides with explanatory notes and standard PDF lecture slides.

At the same time, the university managed to procure and loan out laptops to a number of disadvantaged students, and negotiated with major mobile internet data providers in the country for students to have free access to study material through the university's “connect” website (also referred to as the zero‐rated website). However, this free access excluded some video content and live online lectures (see Table  1 ). The university also provided between 10 and 20 gigabytes of mobile internet data per month, depending on the network provider, sent to students' mobile phones to assist with internet data costs.

Sites available on zero‐rated website

Note : The table summarizes the sites that were available on the zero‐rated website and those that incurred data costs.

High data costs continue to be a contentious issue in Africa where average incomes are low. Gilbert ( 2019 ) reports that South Africa ranked 16th of the 45 countries researched in terms of the most expensive internet data in Africa, at US$6.81 per gigabyte, in comparison to other Southern African countries such as Mozambique (US$1.97), Zambia (US$2.70), and Lesotho (US$4.09). Internet data prices have also been called into question in South Africa after the Competition Commission published a report from its Data Services Market Inquiry calling the country's internet data pricing “excessive” (Gilbert,  2019 ).

3. EMPIRICAL APPROACH

We use a sample of 395 s‐year students taking a macroeconomics module in the Economics department to compare the effects of F2F and online learning on students' performance using a range of assessments. The module was an introduction to the application of theoretical economic concepts. The content was both theory‐based (developing economic growth models using concepts and equations) and skill‐based (application involving the collection of data from online data sources and analyzing the data using statistical software). Both individual and group assignments formed part of the assessments. Before the end of the semester, during lockdown in June 2020, we asked the students to complete a survey with questions related to the transition from F2F to online learning and the difficulties that they may have faced. For example, we asked the students: (i) how easy or difficult they found the transition from F2F to online lectures; (ii) what internet options were available to them and which they used the most to access the online prescribed work; (iii) what format of content they accessed and which they preferred the most (i.e. self‐study material in the form of PDF and PowerPoint slides with notes vs. assisted study with narrated slides and lecture recordings); (iv) what difficulties they faced accessing the live online lectures, to name a few. Figure  1 summarizes the key survey questions that we asked the students regarding their transition from F2F to online learning.

An external file that holds a picture, illustration, etc.
Object name is AFDR-33-S114-g002.jpg

Summary of survey data

Before the lockdown, the students had already attended several F2F classes and completed three assessments. We are therefore able to create a dependent variable that is comprised of the average grades of three assignments taken before lockdown and the average grades of three assignments taken after the start of the lockdown for each student. Specifically, we use the difference between the post‐ and pre‐lockdown average grades as the dependent variable. However, the number of student observations dropped to 275 due to some students missing one or more of the assessments. The lecturer, content and format of the assessments remain similar across the module. We estimate the following equation using ordinary least squares (OLS) with robust standard errors:

where Y i is the student's performance measured by the difference between the post and pre‐lockdown average grades. B represents the vector of determinants that measure the difficulty faced by students to transition from F2F to online learning. This vector includes access to the internet, study material preferred, quality of the online live lecture sessions and pre‐lockdown class attendance. X is the vector of student demographic controls such as race, gender and an indicator if the student's perceived family income is below average. The ε i is unobserved student characteristics.

4. ANALYSIS

4.1. descriptive statistics.

Table  2 gives an overview of the sample of students. We find that among the black students, a higher proportion of students reported finding the transition to online learning more difficult. On the other hand, more white students reported finding the transition moderately easy, as did the other races. According to Coetzee ( 2014 ), the quality of schools can vary significantly between higher income and lower‐income areas, with black South Africans far more likely to live in lower‐income areas with lower quality schools than white South Africans. As such, these differences in quality of education from secondary schooling can persist at tertiary level. Furthermore, persistent income inequality between races in South Africa likely means that many poorer black students might not be able to afford wifi connections or large internet data bundles which can make the transition difficult for black students compared to their white counterparts.

Descriptive statistics

Notes : The transition difficulty variable was ordered 1: Very Easy; 2: Moderately Easy; 3: Difficult; and 4: Impossible. Since we have few responses to the extremes, we combined Very Easy and Moderately as well as Difficult and Impossible to make the table easier to read. The table with a full breakdown is available upon request.

A higher proportion of students reported that wifi access made the transition to online learning moderately easy. However, relatively more students reported that mobile internet data and accessing the zero‐rated website made the transition difficult. Surprisingly, not many students made use of the zero‐rated website which was freely available. Figure  2 shows that students who reported difficulty transitioning to online learning did not perform as well in online learning versus F2F when compared to those that found it less difficult to transition.

An external file that holds a picture, illustration, etc.
Object name is AFDR-33-S114-g003.jpg

Transition from F2F to online learning.

Notes : This graph shows the students' responses to the question “How easy did you find the transition from face‐to‐face lectures to online lectures?” in relation to the outcome variable for performance

In Figure  3 , the kernel density shows that students who had access to wifi performed better than those who used mobile internet data or the zero‐rated data.

An external file that holds a picture, illustration, etc.
Object name is AFDR-33-S114-g001.jpg

Access to online learning.

Notes : This graph shows the students' responses to the question “What do you currently use the most to access most of your prescribed work?” in relation to the outcome variable for performance

The regression results are reported in Table  3 . We find that the change in students' performance from F2F to online is negatively associated with the difficulty they faced in transitioning from F2F to online learning. According to student survey responses, factors contributing to difficulty in transitioning included poor internet access, high internet data costs and lack of equipment such as laptops or tablets to access the study materials on the university website. Students who had access to wifi (i.e. fixed wireless broadband, Asymmetric Digital Subscriber Line (ADSL) or optic fiber) performed significantly better, with on average 4.5 points higher grade, in relation to students that had to use mobile internet data (i.e. personal mobile internet data, wifi at home using mobile internet data, or hotspot using mobile internet data) or the zero‐rated website to access the study materials. The insignificant results for the zero‐rated website are surprising given that the website was freely available and did not incur any internet data costs. However, most students in this sample complained that the internet connection on the zero‐rated website was slow, especially in uploading assignments. They also complained about being disconnected when they were in the middle of an assessment. This may have discouraged some students from making use of the zero‐rated website.

Results: Predictors for student performance using the difference on average assessment grades between pre‐ and post‐lockdown

Coefficients reported. Robust standard errors in parentheses.

∗∗∗ p  < .01.

Students who expressed a preference for self‐study approaches (i.e. reading PDF slides or PowerPoint slides with explanatory notes) did not perform as well, on average, as students who preferred assisted study (i.e. listening to recorded narrated slides or lecture recordings). This result is in line with Means et al. ( 2010 ), where student performance was better for online learning that was collaborative or instructor‐driven than in cases where online learners worked independently. Interestingly, we also observe that the performance of students who often attended in‐person classes before the lockdown decreased. Perhaps these students found the F2F lectures particularly helpful in mastering the course material. From the survey responses, we find that a significant proportion of the students (about 70%) preferred F2F to online lectures. This preference for F2F lectures may also be linked to the factors contributing to the difficulty some students faced in transitioning to online learning.

We find that the performance of low‐income students decreased post‐lockdown, which highlights another potential challenge to transitioning to online learning. The picture and sound quality of the live online lectures also contributed to lower performance. Although this result is not statistically significant, it is worth noting as the implications are linked to the quality of infrastructure currently available for students to access online learning. We find no significant effects of race on changes in students' performance, though males appeared to struggle more with the shift to online teaching than females.

For the robustness check in Table  4 , we consider the average grades of the three assignments taken after the start of the lockdown as a dependent variable (i.e. the post‐lockdown average grades for each student). We then include the pre‐lockdown average grades as an explanatory variable. The findings and overall conclusions in Table  4 are consistent with the previous results.

Robustness check: Predictors for student performance using the average assessment grades for post‐lockdown

As a further robustness check in Table  5 , we create a panel for each student across the six assignment grades so we can control for individual heterogeneity. We create a post‐lockdown binary variable that takes the value of 1 for the lockdown period and 0 otherwise. We interact the post‐lockdown dummy variable with a measure for transition difficulty and internet access. The internet access variable is an indicator variable for mobile internet data, wifi, or zero‐rated access to class materials. The variable wifi is a binary variable taking the value of 1 if the student has access to wifi and 0 otherwise. The zero‐rated variable is a binary variable taking the value of 1 if the student used the university's free portal access and 0 otherwise. We also include assignment and student fixed effects. The results in Table  5 remain consistent with our previous findings that students who had wifi access performed significantly better than their peers.

Interaction model

Notes : Coefficients reported. Robust standard errors in parentheses. The dependent variable is the assessment grades for each student on each assignment. The number of observations include the pre‐post number of assessments multiplied by the number of students.

6. CONCLUSION

The Covid‐19 pandemic left many education institutions with no option but to transition to online learning. The University of Pretoria was no exception. We examine the effect of transitioning to online learning on the academic performance of second‐year economic students. We use assessment results from F2F lectures before lockdown, and online lectures post lockdown for the same group of students, together with responses from survey questions. We find that the main contributor to lower academic performance in the online setting was poor internet access, which made transitioning to online learning more difficult. In addition, opting to self‐study (read notes instead of joining online classes and/or watching recordings) did not help the students in their performance.

The implications of the results highlight the need for improved quality of internet infrastructure with affordable internet data pricing. Despite the university's best efforts not to leave any student behind with the zero‐rated website and free monthly internet data, the inequality dynamics in the country are such that invariably some students were negatively affected by this transition, not because the student was struggling academically, but because of inaccessibility of internet (wifi). While the zero‐rated website is a good collaborative initiative between universities and network providers, the infrastructure is not sufficient to accommodate mass students accessing it simultaneously.

This study's findings may highlight some shortcomings in the academic sector that need to be addressed by both the public and private sectors. There is potential for an increase in the digital divide gap resulting from the inequitable distribution of digital infrastructure. This may lead to reinforcement of current inequalities in accessing higher education in the long term. To prepare the country for online learning, some considerations might need to be made to make internet data tariffs more affordable and internet accessible to all. We hope that this study's findings will provide a platform (or will at least start the conversation for taking remedial action) for policy engagements in this regard.

We are aware of some limitations presented by our study. The sample we have at hand makes it difficult to extrapolate our findings to either all students at the University of Pretoria or other higher education students in South Africa. Despite this limitation, our findings highlight the negative effect of the digital divide on students' educational outcomes in the country. The transition to online learning and the high internet data costs in South Africa can also have adverse learning outcomes for low‐income students. With higher education institutions, such as the University of Pretoria, integrating online teaching to overcome the effect of the Covid‐19 pandemic, access to stable internet is vital for students' academic success.

It is also important to note that the data we have at hand does not allow us to isolate wifi's causal effect on students' performance post‐lockdown due to two main reasons. First, wifi access is not randomly assigned; for instance, there is a high chance that students with better‐off family backgrounds might have better access to wifi and other supplementary infrastructure than their poor counterparts. Second, due to the university's data access policy and consent, we could not merge the data at hand with the student's previous year's performance. Therefore, future research might involve examining the importance of these elements to document the causal impact of access to wifi on students' educational outcomes in the country.

ACKNOWLEDGMENT

The authors acknowledge the helpful comments received from the editor, the anonymous reviewers, and Elizabeth Asiedu.

Chisadza, C. , Clance, M. , Mthembu, T. , Nicholls, N. , & Yitbarek, E. (2021). Online and face‐to‐face learning: Evidence from students’ performance during the Covid‐19 pandemic . Afr Dev Rev , 33 , S114–S125. 10.1111/afdr.12520 [ CrossRef ] [ Google Scholar ]

1 https://mybroadband.co.za/news/cellular/309693-mobile-data-prices-south-africa-vs-the-world.html .

2 The 4IR is currently characterized by increased use of new technologies, such as advanced wireless technologies, artificial intelligence, cloud computing, robotics, among others. This era has also facilitated the use of different online learning platforms ( https://www.brookings.edu/research/the-fourth-industrialrevolution-and-digitization-will-transform-africa-into-a-global-powerhouse/ ).

3 Note that we control for income, but it is plausible to assume other unobservable factors such as parental preference and parenting style might also affect access to the internet of students.

  • Almatra, O. , Johri, A. , Nagappan, K. , & Modanlu, A. (2015). An empirical study of face‐to‐face and distance learning sections of a core telecommunication course (Conference Proceedings Paper No. 12944). 122nd ASEE Annual Conference and Exposition, Seattle, Washington State.
  • Anyanwu, J. C. (2013). Characteristics and macroeconomic determinants of youth employment in Africa . African Development Review , 25 ( 2 ), 107–129. [ Google Scholar ]
  • Anyanwu, J. C. (2016). Accounting for gender equality in secondary school enrolment in Africa: Accounting for gender equality in secondary school enrolment . African Development Review , 28 ( 2 ), 170–191. [ Google Scholar ]
  • Arbaugh, J. (2000). Virtual classroom versus physical classroom: An exploratory study of class discussion patterns and student learning in an asynchronous internet‐based MBA course . Journal of Management Education , 24 ( 2 ), 213–233. [ Google Scholar ]
  • Arias, J. J. , Swinton, J. , & Anderson, K. (2018). On‐line vs. face‐to‐face: A comparison of student outcomes with random assignment . e‐Journal of Business Education and Scholarship of Teaching, , 12 ( 2 ), 1–23. [ Google Scholar ]
  • Bernard, R. M. , Abrami, P. C. , Lou, Y. , Borokhovski, E. , Wade, A. , Wozney, L. , Wallet, P. A. , Fiset, M. , & Huang, B. (2004). How does distance education compare with classroom instruction? A meta‐analysis of the empirical literature . Review of Educational Research , 74 ( 3 ), 379–439. [ Google Scholar ]
  • Brown, B. , & Liedholm, C. (2002). Can web courses replace the classroom in principles of microeconomics? American Economic Review , 92 ( 2 ), 444–448. [ Google Scholar ]
  • Callister, R. R. , & Love, M. S. (2016). A comparison of learning outcomes in skills‐based courses: Online versus face‐to‐face formats . Decision Sciences Journal of Innovative Education , 14 ( 2 ), 243–256. [ Google Scholar ]
  • Coates, D. , Humphreys, B. R. , Kane, J. , & Vachris, M. A. (2004). “No significant distance” between face‐to‐face and online instruction: Evidence from principles of economics . Economics of Education Review , 23 ( 5 ), 533–546. [ Google Scholar ]
  • Coetzee, M. (2014). School quality and the performance of disadvantaged learners in South Africa (Working Paper No. 22). University of Stellenbosch Economics Department, Stellenbosch
  • Dutton, J. , Dutton, M. , & Perry, J. (2002). How do online students differ from lecture students? Journal of Asynchronous Learning Networks , 6 ( 1 ), 1–20. [ Google Scholar ]
  • Emediegwu, L. (2021). Does educational investment enhance capacity development for Nigerian youths? An autoregressive distributed lag approach . African Development Review , 32 ( S1 ), S45–S53. [ Google Scholar ]
  • Fallah, M. H. , & Ubell, R. (2000). Blind scores in a graduate test. Conventional compared with web‐based outcomes . ALN Magazine , 4 ( 2 ). [ Google Scholar ]
  • Figlio, D. , Rush, M. , & Yin, L. (2013). Is it live or is it internet? Experimental estimates of the effects of online instruction on student learning . Journal of Labor Economics , 31 ( 4 ), 763–784. [ Google Scholar ]
  • Freeman, M. A. , & Capper, J. M. (1999). Exploiting the web for education: An anonymous asynchronous role simulation . Australasian Journal of Educational Technology , 15 ( 1 ), 95–116. [ Google Scholar ]
  • Gilbert, P. (2019). The most expensive data prices in Africa . Connecting Africa. https://www.connectingafrica.com/author.asp?section_id=761%26doc_id=756372
  • Glick, P. , Randriamamonjy, J. , & Sahn, D. (2009). Determinants of HIV knowledge and condom use among women in Madagascar: An analysis using matched household and community data . African Development Review , 21 ( 1 ), 147–179. [ Google Scholar ]
  • Gyimah‐Brempong, K. (2011). Education and economic development in Africa . African Development Review , 23 ( 2 ), 219–236. [ Google Scholar ]
  • Johnson, S. , Aragon, S. , Shaik, N. , & Palma‐Rivas, N. (2000). Comparative analysis of learner satisfaction and learning outcomes in online and face‐to‐face learning environments . Journal of Interactive Learning Research , 11 ( 1 ), 29–49. [ Google Scholar ]
  • Lundberg, J. , Merino, D. , & Dahmani, M. (2008). Do online students perform better than face‐to‐face students? Reflections and a short review of some empirical findings . Revista de Universidad y Sociedad del Conocimiento , 5 ( 1 ), 35–44. [ Google Scholar ]
  • Means, B. , Toyama, Y. , Murphy, R. , Bakia, M. , & Jones, K. (2010). Evaluation of evidence‐based practices in online learning: A meta‐analysis and review of online learning studies (Report No. ed‐04‐co‐0040 task 0006). U.S. Department of Education, Office of Planning, Evaluation, and Policy Development, Washington DC.
  • Navarro, P. (2000). Economics in the cyber‐classroom . Journal of Economic Perspectives , 14 ( 2 ), 119–132. [ Google Scholar ]
  • Navarro, P. , & Shoemaker, J. (2000). Performance and perceptions of distance learners in cyberspace . American Journal of Distance Education , 14 ( 2 ), 15–35. [ Google Scholar ]
  • Neuhauser, C. (2002). Learning style and effectiveness of online and face‐to‐face instruction . American Journal of Distance Education , 16 ( 2 ), 99–113. [ Google Scholar ]
  • Nguyen, T. (2015). The effectiveness of online learning: Beyond no significant difference and future horizons . MERLOT Journal of Online Teaching and Learning , 11 ( 2 ), 309–319. [ Google Scholar ]
  • Paechter, M. , & Maier, B. (2010). Online or face‐to‐face? Students' experiences and preferences in e‐learning . Internet and Higher Education , 13 ( 4 ), 292–297. [ Google Scholar ]
  • Russell, T. L. , & International Distance Education Certificate Center (IDECC) (1999). The no significant difference phenomenon: A comparative research annotated bibliography on technology for distance education: As reported in 355 research reports, summaries and papers . North Carolina State University. [ Google Scholar ]
  • Shachar, M. , & Neumann, Y. (2010). Twenty years of research on the academic performance differences between traditional and distance learning: Summative meta‐analysis and trend examination . MERLOT Journal of Online Learning and Teaching , 6 ( 2 ), 318–334. [ Google Scholar ]
  • Shachar, M. , & Yoram, N. (2003). Differences between traditional and distance education academic performances: A meta‐analytic approach . International Review of Research in Open and Distance Learning , 4 ( 2 ), 1–20. [ Google Scholar ]
  • Tchamyou, V. S. , Asongu, S. , & Odhiambo, N. (2019). The role of ICT in modulating the effect of education and lifelong learning on income inequality and economic growth in Africa . African Development Review , 31 ( 3 ), 261–274. [ Google Scholar ]
  • Xu, D. , & Jaggars, S. S. (2014). Performance gaps between online and face‐to‐face courses: Differences across types of students and academic subject areas . The Journal of Higher Education , 85 ( 5 ), 633–659. [ Google Scholar ]

Cengage Logo-Home Page

  • Instructors
  • Institutions
  • Teaching Strategies
  • Higher Ed Trends
  • Academic Leadership
  • Affordability
  • Product Updates

Black History Month 2024: African Americans and the Arts 

A woman reads a book

The national theme for Black History Month 2024 is “ African Americans and the Arts .”  

Black History Month 2024 is a time to recognize and highlight the achievements of Black artists and creators, and the role they played in U.S. history and in shaping our country today.  

To commemorate this year’s theme, we’ve gathered powerful quotes about learning, culture and equality from five historic Black American authors, teachers and artists who made a significant impact in the Arts, education ― and the nation.  

  Making history  

“Real education means to inspire people to live more abundantly, to learn to begin with life as they find it and make it better.” – Carter G. Woodson, Author, Journalist, Historian and Educator, 1875-1950  

Known as the “Father of Black History,” Carter G. Woodson was primarily self-taught in most subjects. In 1912, he became the second Black person to receive a Ph.D. from Harvard.   

He is the author of more than 30 books, including “T he Mis-Education of the Negro. ”  

Carter G. Woodson dedicated his life to teaching Black History and incorporating the subject of Black History in schools. He co-founded what is now the Association for the Study of African American Life and History, Inc. (ASALH) . In February 1926, Woodson launched the first Negro History Week , which has since been expanded into Black History Month.  

Carter G. Woodson

Providing a platform  

“I have created nothing really beautiful, really lasting, but if I can inspire one of these youngsters to develop the talent.” – Augusta Savage, Sculptor, 1892-1962  

An acclaimed and influential sculptor of the Harlem Renaissance, Augusta Savage was a teacher and an activist who fought for African American rights in the Arts. She was one out of only four women, and the only Black woman, commissioned for the 1939 New York World’s Fair. She exhibited one of her most famous works, “Lift Every Voice and Sing,” which she named after the hymn by James Weldon Johnson, sometimes referred to as the Black National Anthem. Her sculpture is also known as “ The Harp, ” renamed by the fair’s organizers.  

Photograph of Augusta Savage

Raising a voice  

“My mother said to me ‘My child listen, whatever you do in this world no matter how good it is you will never be able to please everybody. But what one should strive for is to do the very best humanly possible.’” – Marian Anderson, American Contralto, 1897-1993  

Marian Anderson broke barriers in the opera world. In 1939, she performed at the Lincoln Memorial in front of a crowd of 75,000 after the Daughters of the American Revolution (DAR) denied her access to the DAR Constitution Hall because of her race. And in 1955, Marian Anderson became the first African American to perform at the Metropolitan Opera. She sang the leading role as Ulrica in Verdi’s Un Ballo in Maschera.  

thesis of online learning

Influencing the world  

“The artist’s role is to challenge convention, to push boundaries, and to open new doors of perception.” – Henry Ossawa Tanner, Painter, 1859-1937  

Henry Ossawa Tanner is known to be the first Black artist to gain world-wide fame and acclaim. In 1877, he enrolled at the Pennsylvania Academy of the Fine Arts , where he was the only Black student. In 1891, Tanner moved to Paris to escape the racism he was confronted with in America. Here, he painted two of his most recognized works, “ The Banjo Lesson” and “ The Thankful Poor of 1894. ”    

In 1923, Henry O. Tanner was awarded the Chevalier of the Legion of Honor by the French government, France’s highest honor.  

Henry Ossawa Tanner

Rising up  

“Wisdom is higher than a fool can reach.” – Phillis Wheatley, Poet, 1753-1784  

At about seven years old, Phillis Wheatley was kidnapped from her home in West Africa and sold into slavery in Boston. She started writing poetry around the age of 12 and published her first poem, “ Messrs. Hussey and Coffin ,” in Rhode Island’s Newport Mercury newspaper in 1767.   

While her poetry spread in popularity ― so did the skepticism. Some did not believe an enslaved woman could have authored the poems. She defended her work to a panel of town leaders and became the first African American woman to publish a book of poetry. The panel’s attestation was included in the preface of her book.  

Phillis Wheatley corresponded with many artists, writers and activists, including a well-known 1 774 letter to Reverand Samson Occom about freedom and equality.  

Phillis Wheatley with pen and paper

Honoring Black History Month 2024  

Art plays a powerful role in helping us learn and evolve. Not only does it introduce us to a world of diverse experiences, but it helps us form stronger connections. These are just a few of the many Black creators who shaped U.S. history ― whose expressions opened many doors and minds.  

Black History Month is observed each year in February. To continue your learning, go on a journey with Dr. Jewrell Rivers, as he guides you through Black History in higher education. Read his article, “A Brief History: Black Americans in Higher Education.”  

Related articles

Student reading a book

IMAGES

  1. Thesis Statement Distance Learning Google Classroom

    thesis of online learning

  2. (PDF) Online Education and Its Effective Practice: A Research Review

    thesis of online learning

  3. Thesis Statement Distance Learning Google Classroom

    thesis of online learning

  4. Essay on Online Education

    thesis of online learning

  5. English.docx

    thesis of online learning

  6. Online Thesis

    thesis of online learning

VIDEO

  1. The Thesis

  2. Three Minute Thesis

  3. How to make Dissertation? Complete Details about Dissertation / Thesis for Bachelors/ Masters Degree

  4. Finding HIGH-Impact Research Topics

  5. Why it's essential to know yourself as a thesis writer

COMMENTS

  1. The Impact of Online Learning on Student's Academic Performance

    online classes could affect the academic performance of students. This paper seeks to study the. impact of online learning on the academic performance of university students and to determine. whether education systems should increase the amount of online learning for traditional in-class. subjects.

  2. PDF THE DESIGN OF ONLINE LEARNING ENVIRONMENTS A Thesis

    THE DESIGN OF ONLINE LEARNING ENVIRONMENTS Daniel John Davis, B.A. Thesis Advisor: Wayne H. Osborn, PhD. ABSTRACT Data generated by GeorgetownX Massive Open Online Courses (MOOCs) is rich with information that can shed light on the way people interact with online learning environments. At

  3. PDF The Impact of Online Teaching on Higher Education

    THE IMPACT OF ONLINE TEACHING ON HIGHER EDUCATION FACULTY'S PROFESSIONAL IDENTITY AND THE ROLE OF TECHNOLOGY: THE COMING OF AGE OF THE VIRTUAL TEACHER: By EDWIGE SIMON M.A., Université Lille III, 2000 M.A., Indiana University, 2003 M.S., Indiana University, 2005 A thesis submitted to the Faculty of the Graduate School of the

  4. (PDF) Online Education and Its Effective Practice: A Research Review

    Based on the findings, the authors argued that effective online instruction is dependent upon 1) well-designed course content, motivated interaction between the instructor and learners,...

  5. The effects of online education on academic success: A meta ...

    Furthermore, online learning is described as a way of utilizing the internet to obtain the related learning sources during the learning process, to interact with the content, the teacher, and other learners, as well as to get support throughout the learning process (Ally, 2004 ).

  6. Learnings from the Impact of Online Learning on Elementary Students

    The researcher designed this study to examine the impacts of online learning on elementary students' mental and social and emotional well-being amid the COVID-19 pandemic. Also, this study addresses the broader range of extant inequities that may arise due to the shift to online learning (from educator and parent perspectives).

  7. PDF Theories and Frameworks for Online Education: Seeking an Integrated Model

    Picciano, A. G. (2017). Theories and frameworks for online education: Seeking an integrated model. Online Learning, 21(3), 166-190. doi: 10.24059/olj.v21i3.1225 Introduction In a provocative chapter of The Theory and Practice of Online Learning, Terry Anderson (2011) examines whether a common theory for online education can be developed.

  8. The Impact of Online Learning Strategies on Students' Academic

    Today, online learning is a challenging teaching strategy used by higher educational institutions (HEI) and requires ample technological and psychological preparation. This study aims to assess...

  9. Assessing the Impact of Online-Learning Effectiveness and Benefits in

    Online learning is one of the educational solutions for students during the COVID-19 pandemic. Worldwide, most universities have shifted much of their learning frameworks to an online learning model to limit physical interaction between people and slow the spread of COVID-19.

  10. A Survey on the Effectiveness of Online Teaching-Learning Methods for

    Online teaching-learning methods have been followed by world-class universities for more than a decade to cater to the needs of students who stay far away from universities/colleges. But during the COVID-19 pandemic period, online teaching-learning helped almost all universities, colleges, and affiliated students. An attempt is made to find the effectiveness of online teaching-learning ...

  11. (Pdf) Research on Online Learning

    They include: a critical review of what the research literature can tell us about blended learning relative to each of Sloan-C's five pillars of quality in online learning; two papers on one...

  12. Online and face‐to‐face learning: Evidence from students' performance

    Our main objectives in answering this study question are to establish what study materials the students were able to access (i.e. slides, recordings, or live sessions) and how students got access to these materials (i.e. the infrastructure they used).

  13. PDF ONLINE LEARNING EXPERIENCES AND SATISFACTION OF STUDENTS ON THE ...

    use technology and automation to address their concerns during online learning to meet students' changing needs and quality learning, too. Keywords: Remote Learning, Online Learning Experiences, Satisfaction, Technology, quality of Learning, learning issues INTRODUCTION People's lives have changed dramatically for almost two (2) years.

  14. PDF The Effectiveness and Challenges of Online Learning for Secondary ...

    online learning allows students to study in a "safe" environment, without experiencing embarrassment about asking questions. According to Harrison (2018), young children can access pictures and videos, navigate 'Youtube', and interact and participate in games and digital applications that are suited to their age.

  15. Grand Valley State University ScholarWorks@GVSU

    Students' Motivations and Barriers to Online Education Vladimir Abramenka Grand Valley State University Follow this and additional works at: https://scholarworks.gvsu.edu/theses Part of the Online and Distance Education Commons ScholarWorks Citation Abramenka, Vladimir, "Students' Motivations and Barriers to Online Education" (2015).

  16. Advantages and Challenges of Online Project Based Learning

    insufficient research on the facilitation of project-based learning (PBL) in an online platform. It will be a benefit to the education sector to have an effective facilitation method for project-based learning in an online platform. The purpose of this research is to identify the advantages and challenges in online Project-Based Learning.

  17. A Qualitative Case Study of Students' Perceptions of Their Experiences

    report, co-sponsored by the Online Learning Consortium, a collaborative community focused on the advancement of quality online education, revealed that enrollment in online courses had steadily increased over the past 14 years and as of Fall 2016, 31.6% of students were enrolled in at least one online education course (Seaman et al., 2018).

  18. PDF Learning Online: A Case Study Exploring Student Perceptions and ...

    The five main factors affecting learning on this course include: 1) pace of learning in an online environment, 2) learning style, 3) immediacy of feedback, 4) method of content delivery, and 5) issues around navigating content. These findings could help improve online teaching practice and learning quality in future courses.

  19. (PDF) The Effectiveness of Online Learning: Beyond No Significant

    This study examines the evidence of the effectiveness of online learning by organizing and summarizing the findings and challenges of online learning into positive, negative, mixed, and...

  20. A Comparison of face-to-face and online learning environments to

    This Thesis has been accepted for inclusion in UNLV Theses, Dissertations, Professional Papers, and Capstones by ... A COMPARISON OF FACE-TO-FACE AND ONLINE LEARNING ENVIRONMENTS TO PREPARE TEACHERS . TO USE TECHNOLOGY . by . Ashley Janel Addis . Bachelor of Science . Southern Illinois University, Carbondale .

  21. PDF Online Learning: Theory, Algorithms, and Applications

    This dissertation describes a novel framework for the design and analysis of online learning algorithms. We show that various online learning algorithms can all be derived as special cases of our algorithmic framework.

  22. (PDF) A study of effectiveness of online learning

    Dewan. Ms.Swati Agarwal, Dr.Jyoti Dewan, An Analysis of the Effectiveness of Online Learning in Colleges of Uttar Pradesh during the COVID 19 Lockdown, Journal of Xi'an University of Architecture ...

  23. Best Online Electrical Engineering Master's Degrees Of 2024

    Best Online Master's in Electrical Engineering Options. Johns Hopkins University. Columbia University in the City of New York. University of Southern California. Villanova University. Western ...

  24. PDF A CRITICAL STUDY OF EFFECTIVENESS OF ONLINE LEARNING ON STUDENTS ...

    There are about 15 schools of (Maharashtra Board of Secondary and Higher Secondary Schools) in Aurangabad city, out of this 1 school is selected randomly. Researcher took 50% of the sample as boys and 50% of the sample as girls. Table 1 shows distribution of students in Online Learning Environment and F2F Learning Environment.

  25. Black History Month 2024: African Americans and the Arts

    Published: 2/7/2024. The national theme for Black History Month 2024 is "African Americans and the Arts.". Black History Month 2024 is a time to recognize and highlight the achievements of Black artists and creators, and the role they played in U.S. history and in shaping our country today.