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Assessing Cognitive Factors of Modular Distance Learning of K-12 Students Amidst the COVID-19 Pandemic towards Academic Achievements and Satisfaction

Yung-tsan jou.

1 Department of Industrial and Systems Engineering, Chung Yuan Christian University, Taoyuan 320, Taiwan; wt.ude.ucyc@uojty (Y.-T.J.); moc.oohay@enimrahcrolfas (C.S.S.)

Klint Allen Mariñas

2 School of Industrial Engineering and Engineering Management, Mapua University, Manila 1002, Philippines

3 Department of Industrial Engineering, Occidental Mindoro State College, San Jose 5100, Philippines

Charmine Sheena Saflor

Associated data.

Not applicable.

The COVID-19 pandemic brought extraordinary challenges to K-12 students in using modular distance learning. According to Transactional Distance Theory (TDT), which is defined as understanding the effects of distance learning in the cognitive domain, the current study constructs a theoretical framework to measure student satisfaction and Bloom’s Taxonomy Theory (BTT) to measure students’ academic achievements. This study aims to evaluate and identify the possible cognitive capacity influencing K-12 students’ academic achievements and satisfaction with modular distance learning during this new phenomenon. A survey questionnaire was completed through an online form by 252 K-12 students from the different institutions of Occidental Mindoro. Using Structural Equation Modeling (SEM), the researcher analyses the relationship between the dependent and independent variables. The model used in this research illustrates cognitive factors associated with adopting modular distance learning based on students’ academic achievements and satisfaction. The study revealed that students’ background, experience, behavior, and instructor interaction positively affected their satisfaction. While the effects of the students’ performance, understanding, and perceived effectiveness were wholly aligned with their academic achievements. The findings of the model with solid support of the integrative association between TDT and BTT theories could guide decision-makers in institutions to implement, evaluate, and utilize modular distance learning in their education systems.

1. Introduction

The 2019 coronavirus is the latest infectious disease to develop rapidly worldwide [ 1 ], affecting economic stability, global health, and education. Most countries have suspended thee-to-face classes in order to curb the spread of the virus and reduce infections [ 2 ]. One of the sectors impacted has been education, resulting in the suspension of face-to-face classes to avoid spreading the virus. The Department of Education (DepEd) has introduced modular distance learning for K-12 students to ensure continuity of learning during the COVID-19 pandemic. According to Malipot (2020), modular learning is one of the most popular sorts of distance learning alternatives to traditional face-to-face learning [ 3 ]. As per DepEd’s Learner Enrolment and Survey Forms, 7.2 million enrollees preferred “modular” remote learning, TV and radio-based practice, and other modalities, while two million enrollees preferred online learning. It is a method of learning that is currently being used based on the preferred distance learning mode of the students and parents through the survey conducted by the Department of Education (DepEd); this learning method is mainly done through the use of printed and digital modules [ 4 ]. It also concerns first-year students in rural areas; the place net is no longer available for online learning. Supporting the findings of Ambayon (2020), modular teaching within the teach-learn method is more practical than traditional educational methods because students learn at their own pace during this modular approach. This educational platform allows K-12 students to interact in self-paced textual matter or digital copy modules. With these COVID-19 outbreaks, some issues concerned students’ academic, and the factors associated with students’ psychological status during the COVID-19 lockdown [ 5 ].

Additionally, this new learning platform, modular distance learning, seems to have impacted students’ ability to discover and challenged their learning skills. Scholars have also paid close attention to learner satisfaction and academic achievement when it involves distance learning studies and have used a spread of theoretical frameworks to assess learner satisfaction and educational outcomes [ 6 , 7 ]. Because this study aimed to boost academic achievement and satisfaction in K-12 students, the researcher thoroughly applied transactional distance theory (TDT) to understand the consequences of distance in relationships in education. The TDT was utilized since it has the capability to establish the psychological and communication factors between the learners and the instructors in distance education that could eventually help researchers in identifying the variables that might affect students’ academic achievement and satisfaction [ 8 ]. In this view, distance learning is primarily determined by the number of dialogues between student and teacher and the degree of structuring of the course design. It contributes to the core objective of the degree to boost students’ modular learning experiences in terms of satisfaction. On the other hand, Bloom’s Taxonomy Theory (BTT) was applied to investigate the students’ academic achievements through modular distance learning [ 6 ]. Bloom’s theory was employed in addition to TDT during this study to enhance students’ modular educational experiences. Moreover, TDT was utilized to check students’ modular learning experiences in conjuction with enhacing students’ achievements.

This study aimed to detect the impact of modular distance learning on K-12 students during the COVID-19 pandemic and assess the cognitive factors affecting academic achievement and student satisfaction. Despite the challenging status of the COVID-19 outbreak, the researcher anticipated a relevant result of modular distance learning and pedagogical changes in students, including the cognitive factors identified during this paper as latent variables as possible predictors for the utilization of K-12 student academic achievements and satisfaction.

1.1. Theoretical Research Framework

This study used TDT to assess student satisfaction and Bloom’s theory to quantify academic achievement. It aimed to assess the impact of modular distance learning on academic achievement and student satisfaction among K-12 students. The Transactional Distance Theory (TDT) was selected for this study since it refers to student-instructor distance learning. TDT Moore (1993) states that distance education is “the universe of teacher-learner connections when learners and teachers are separated by place and time.” Moore’s (1990) concept of ”Transactional Distance” adopts the distance that occurs in all linkages in education, according to TDT Moore (1993). Transactional distance theory is theoretically critical because it states that the most important distance is transactional in distance education, rather than geographical or temporal [ 9 , 10 ]. According to Garrison (2000), transactional distance theory is essential in directing the complicated experience of a cognitive process such as distance teaching and learning. TDT evaluates the role of each of these factors (student perception, discourse, and class organization), which can help with student satisfaction research [ 11 ]. Bloom’s Taxonomy is a theoretical framework for learning created by Benjamin Bloom that distinguishes three learning domains: Cognitive domain skills center on knowledge, comprehension, and critical thinking on a particular subject. Bloom recognized three components of educational activities: cognitive knowledge (or mental abilities), affective attitude (or emotions), and psychomotor skills (or physical skills), all of which can be used to assess K-12 students’ academic achievement. According to Jung (2001), “Transactional distance theory provides a significant conceptual framework for defining and comprehending distance education in general and a source of research hypotheses in particular,” shown in Figure 1 [ 12 ].

Theoretical Research Framework.

1.2. Hypothesis Developments and Literature Review

This section will discuss the study hypothesis and relate each hypothesis to its related studies from the literature.

There is a significant relationship between students’ background and students’ behavior .

The teacher’s guidance is essential for students’ preparedness and readiness to adapt to a new educational environment. Most students opt for the Department of Education’s “modular” distance learning options [ 3 ]. Analyzing students’ study time is critical for behavioral engagement because it establishes if academic performance is the product of student choice or historical factors [ 13 ].

There is a significant relationship between students’ background and students’ experience .

Modules provide goals, experiences, and educational activities that assist students in gaining self-sufficiency at their speed. It also boosts brain activity, encourages motivation, consolidates self-satisfaction, and enables students to remember what they have learned [ 14 ]. Despite its success, many families face difficulties due to their parents’ lack of skills and time [ 15 ].

There is a significant relationship between students’ behavior and students’ instructor interaction .

Students’ capacity to answer problems reflects their overall information awareness [ 5 ]. Learning outcomes can either cause or result in students and instructors behavior. Students’ reading issues are due to the success of online courses [ 16 ].

There is a significant relationship between students’ experience and students’ instructor interaction .

The words “student experience” relate to classroom participation. They establish a connection between students and their school, teachers, classmates, curriculum, and teaching methods [ 17 ]. The three types of student engagement are behavioral, emotional, and cognitive. Behavioral engagement refers to a student’s enthusiasm for academic and extracurricular activities. On the other hand, emotional participation is linked to how children react to their peers, teachers, and school. Motivational engagement refers to a learner’s desire to learn new abilities [ 18 ].

There is a significant relationship between students’ behavior and students’ understanding .

Individualized learning connections, outstanding training, and learning culture are all priorities at the Institute [ 19 , 20 ]. The modular technique of online learning offers additional flexibility. The use of modules allows students to investigate alternatives to the professor’s session [ 21 ].

There is a significant relationship between students’ experience and students’ performance .

Student conduct is also vital in academic accomplishment since it may affect a student’s capacity to study as well as the learning environment for other students. Students are self-assured because they understand what is expected [ 22 ]. They are more aware of their actions and take greater responsibility for their learning.

There is a significant relationship between students’ instructor interaction and students’ understanding .

Modular learning benefits students by enabling them to absorb and study material independently and on different courses. Students are more likely to give favorable reviews to courses and instructors if they believe their professors communicated effectively and facilitated or supported their learning [ 23 ].

There is a significant relationship between students’ instructor interaction and students’ performance.

Students are more engaged and active in their studies when they feel in command and protected in the classroom. Teachers play an essential role in influencing student academic motivation, school commitment, and disengagement. In studies on K-12 education, teacher-student relationships have been identified [ 24 ]. Positive teacher-student connections improve both teacher attitudes and academic performance.

There is a significant relationship between students’ understanding and students’ satisfaction .

Instructors must create well-structured courses, regularly present in their classes, and encourage student participation. When learning objectives are completed, students better understand the course’s success and learning expectations. “Constructing meaning from verbal, written, and graphic signals by interpreting, exemplifying, classifying, summarizing, inferring, comparing, and explaining” is how understanding is characterized [ 25 ].

There is a significant relationship between students’ performance and student’s academic achievement .

Academic emotions are linked to students’ performance, academic success, personality, and classroom background [ 26 ]. Understanding the elements that may influence student performance has long been a goal for educational institutions, students, and teachers.

There is a significant relationship between students’ understanding and students’ academic achievement .

Modular education views each student as an individual with distinct abilities and interests. To provide an excellent education, a teacher must adapt and individualize the educational curriculum for each student. Individual learning may aid in developing a variety of exceptional and self-reliant attributes [ 27 ]. Academic achievement is the current level of learning in the Philippines [ 28 ].

There is a significant relationship between students’ performance and students’ satisfaction .

Academic success is defined as a student’s intellectual development, including formative and summative assessment data, coursework, teacher observations, student interaction, and time on a task [ 29 ]. Students were happier with course technology, the promptness with which content was shared with the teacher, and their overall wellbeing [ 30 ].

There is a significant relationship between students’ academic achievement and students’ perceived effectiveness .

Student satisfaction is a short-term mindset based on assessing students’ educational experiences [ 29 ]. The link between student satisfaction and academic achievement is crucial in today’s higher education: we discovered that student satisfaction with course technical components was linked to a higher relative performance level [ 31 ].

There is a significant relationship between students’ satisfaction and students’ perceived effectiveness.

There is a strong link between student satisfaction and their overall perception of learning. A satisfied student is a direct effect of a positive learning experience. Perceived learning results had a favorable impact on student satisfaction in the classroom [ 32 ].

2. Materials and Methods

2.1. participants.

The principal area under study was San Jose, Occidental Mindoro, although other locations were also accepted. The survey took place between February and March 2022, with the target population of K-12 students in Junior and Senior High Schools from grades 7 to 12, aged 12 to 20, who are now implementing the Modular Approach in their studies during the COVID-19 pandemic. A 45-item questionnaire was created and circulated online to collect the information. A total of 300 online surveys was sent out and 252 online forms were received, a total of 84% response rate [ 33 ]. According to several experts, the sample size for Structural Equation Modeling (SEM) should be between 200 and 500 [ 34 ].

2.2. Questionnaire

The theoretical framework developed a self-administered test. The researcher created the questionnaire to examine and discover the probable cognitive capacity influencing K-12 students’ academic achievement in different parts of Occidental Mindoro during this pandemic as well as their satisfaction with modular distance learning. The questionnaire was designed through Google drive as people’s interactions are limited due to the effect of the COVID-19 pandemic. The questionnaire’s link was sent via email, Facebook, and other popular social media platforms.

The respondents had to complete two sections of the questionnaire. The first is their demographic information, including their age, gender, and grade level. The second is about their perceptions of modular learning. The questionnaire is divided into 12 variables: (1) Student’s Background, (2) Student’s Experience, (3) Student’s Behavior, (4) Student’s Instructor Interaction, (5) Student’s Performance, (6) Student’s Understanding, (7) Student’s Satisfaction, (8) Student’s Academic Achievement, and (9) Student’s Perceived Effectiveness. A 5-point Likert scale was used to assess all latent components contained in the SEM shown in Table 1 .

The construct and measurement items.

2.3. Structural Equation Modeling (SEM)

All the variables have been adapted from a variety of research in the literature. The observable factors were scored on a Likert scale of 1–5, with one indicating “strongly disagree” and five indicating “strongly agree”, and the data were analyzed using AMOS software. Theoretical model data were confirmed by Structural Equation Modeling (SEM). SEM is more suitable for testing the hypothesis than other methods [ 53 ]. There are many fit indices in the literature, of which the most commonly used are: CMIN/DF, Comparative Fit Index (CFI), AGFI, GFI, and Root Mean Square Error (RMSEA). Table 2 demonstrates the Good Fit Values and Acceptable Fit Values of the fit indices, respectively. AGFI and GFI are based on residuals; when sample size increases, the value of the AGFI also increase. It takes a value between 0 and 1. The fit is good if the value is more significant than 0.80. GFI is a model index that spans from 0 to 1, with values above 0.80 deemed acceptable. An RMSEA of 0.08 or less suggests a good fit [ 54 ], and a value of 0.05 to 0.08 indicates an adequate fit [ 55 ].

Acceptable Fit Values.

3. Results and Discussion

Figure 2 demonstrates the initial SEM for the cognitive factors of Modular Distance learning towards academic achievements and satisfaction of K-12 students during the COVID-19 pandemic. According to the figure below, three hypotheses were not significant: Students’ Behavior to Students’ Instructor Interaction (Hypothesis 3), Students’ Understanding of Students’ Academic Achievement (Hypothesis 11), and Students’ Performance to Students’ Satisfaction (Hypothesis 12). Therefore, a revised SEM was derived by removing this hypothesis in Figure 3 . We modified some indices to enhance the model fit based on previous studies using the SEM approach [ 47 ]. Figure 3 demonstrates the final SEM for evaluating cognitive factors affecting academic achievements and satisfaction and the perceived effectiveness of K-12 students’ response to Modular Learning during COVID-19, shown in Table 3 . Moreover, Table 4 demonstrates the descriptive statistical results of each indicator.

Initial SEM with indicators for evaluating the cognitive factors of modular distance learning towards academic achievements and satisfaction of K-12 students during COVID-19 pandemic.

Revised SEM with indicators for evaluating the cognitive factors of modular distance learning towards academic achievements and satisfaction of K-12 students during the COVID-19 pandemic.

Summary of the Results.

Descriptive statistic results.

The current study was improved by Moore’s transactional distance theory (TDT) and Bloom’s taxonomy theory (BTT) to evaluate cognitive factors affecting academic achievements and satisfaction and the perceived effectiveness of K-12 students’ response toward modular learning during COVID-19. SEM was utilized to analyze the correlation between Student Background (SB), Student Experience (SE), Student Behavior (SBE), Student Instructor Interaction (SI), Student Performance (SP), Student Understanding (SAU), Student Satisfaction (SS), Student’s Academic achievement (SAA), and Student’s Perceived effectiveness (SPE). A total of 252 data samples were acquired through an online questionnaire.

According to the findings of the SEM, the students’ background in modular learning had a favorable and significant direct effect on SE (β: 0.848, p = 0.009). K-12 students should have a background and knowledge in modular systems to better experience this new education platform. Putting the students through such an experience would support them in overcoming all difficulties that arise due to the limitations of the modular platforms. Furthermore, SEM revealed that SE had a significant adverse impact on SI (β: 0.843, p = 0.009). The study shows that students who had previous experience with modular education had more positive perceptions of modular platforms. Additionally, students’ experience with modular distance learning offers various benefits to them and their instructors to enhance students’ learning experiences, particularly for isolated learners.

Regarding the Students’ Interaction—Instructor, it positively impacts SAU (β: 0.873, p = 0.007). Communication helps students experience positive emotions such as comfort, satisfaction, and excitement, which aim to enhance their understanding and help them attain their educational goals [ 62 ]. The results revealed that SP substantially impacted SI (β: 0.765; p = 0.005). A student becomes more academically motivated and engaged by creating and maintaining strong teacher-student connections, which leads to successful academic performance.

Regarding the Students’ Understanding Response, the results revealed that SAA (β: 0.307; p = 0.052) and SS (β: 0.699; p = 0.008) had a substantial impact on SAU. Modular teaching is concerned with each student as an individual and with their specific capability and interest to assist each K-12 student in learning and provide quality education by allowing individuality to each learner. According to the Department of Education, academic achievement is the new level for student learning [ 63 ]. Meanwhile, SAA was significantly affected by the Students’ Performance Response (β: 0.754; p = 0.014). It implies that a positive performance can give positive results in student’s academic achievement, and that a negative performance can also give negative results [ 64 ]. Pekrun et al. (2010) discovered that students’ academic emotions are linked to their performance, academic achievement, personality, and classroom circumstances [ 26 ].

Results showed that students’ academic achievement significantly positively affects SPE (β: 0.237; p = 0.024). Prior knowledge has had an indirect effect on academic accomplishment. It influences the amount and type of current learning system where students must obtain a high degree of mastery [ 65 ]. According to the student’s opinion, modular distance learning is an alternative solution for providing adequate education for all learners and at all levels in the current scenario under the new education policy [ 66 ]. However, the SEM revealed that SS significantly affected SPE (β: 0.868; p = 0.009). Students’ perceptions of learning and satisfaction, when combined, can provide a better knowledge of learning achievement [ 44 ]. Students’ perceptions of learning outcomes are an excellent predictor of student satisfaction.

Since p -values and the indicators in Students’ Behavior are below 0.5, therefore two paths connecting SBE to students’ interaction—instructor (0.155) and students’ understanding (0.212) are not significant; thus, the latent variable Students’ Behavior has no effect on the latent variable Students’ Satisfaction and academic achievement as well as perceived effectiveness on modular distance learning of K12 students. This result is supported by Samsen-Bronsveld et al. (2022), who revealed that the environment has no direct influence on the student’s satisfaction, behavior engagement, and motivation to study [ 67 ]. On the other hand, the results also showed no significant relationship between Students’ Performance and Students’ Satisfaction (0.602) because the correlation p -values are greater than 0.5. Interestingly, this result opposed the other related studies. According to Bossman & Agyei (2022), satisfaction significantly affects performance or learning outcomes [ 68 ]. In addition, it was discovered that the main drivers of the students’ performance are the students’ satisfaction [ 64 , 69 ].

The result of the study implies that the students’ satisfaction serves as the mediator between the students’ performance and the student-instructor interaction in modular distance learning for K-12 students [ 70 ].

Table 5 The reliabilities of the scales used, i.e., Cronbach’s alphas, ranged from 0.568 to 0.745, which were in line with those found in other studies [ 71 ]. As presented in Table 6 , the IFI, TLI, and CFI values were greater than the suggested cutoff of 0.80, indicating that the specified model’s hypothesized construct accurately represented the observed data. In addition, the GFI and AGFI values were 0.828 and 0.801, respectively, indicating that the model was also good. The RMSEA value was 0.074, lower than the recommended value. Finally, the direct, indirect, and total effects are presented in Table 7 .

Construct Validity Model.

Direct effect, indirect effect, and total effect.

Table 6 shows that the five parameters, namely the Incremental Fit Index, Tucker Lewis Index, the Comparative Fit Index, Goodness of Fit Index, and Adjusted Goodness Fit Index, are all acceptable with parameter estimates greater than 0.8, whereas mean square error is excellent with parameter estimates less than 0.08.

4. Conclusions

The education system has been affected by the 2019 coronavirus disease; face-to-face classes are suspended to control and reduce the spread of the virus and infections [ 2 ]. The suspension of face-to-face classes results in the application of modular distance learning for K-12 students according to continuity of learning during the COVID-19 pandemic. With the outbreak of COVID-19, some issues concerning students’ academic Performance and factors associated with students’ psychological status are starting to emerge, which impacted the students’ ability to learn. This study aimed to perceive the impact of Modular Distance learning on the K-12 students amid the COVID-19 pandemic and assess cognitive factors affecting students’ academic achievement and satisfaction.

This study applied Transactional Distance Theory (TDT) and Bloom Taxonomy Theory (BTT) to evaluate cognitive factors affecting students’ academic achievements and satisfaction and evaluate the perceived effectiveness of K-12 students in response to modular learning. This study applied Structural Equation Modeling (SEM) to test hypotheses. The application of SEM analyzed the correlation among students’ background, experience, behavior, instructor interaction, performance, understanding, satisfaction, academic achievement, and student perceived effectiveness.

A total of 252 data samples were gathered through an online questionnaire. Based on findings, this study concludes that students’ background in modular distance learning affects their behavior and experience. Students’ experiences had significant effects on the performance and understanding of students in modular distance learning. Student instructor interaction had a substantial impact on performance and learning; it explains how vital interaction with the instructor is. The student interacting with the instructor shows that the student may receive feedback and guidance from the instructor. Understanding has a significant influence on students’ satisfaction and academic achievement. Student performance has a substantial impact on students’ academic achievement and satisfaction. Perceived effectiveness was significantly influenced by students’ academic achievement and student satisfaction. However, students’ behavior had no considerable effect on students’ instructor interaction, and students’ understanding while student performance equally had no significant impact on student satisfaction. From this study, students are likely to manifest good performance, behavior, and cognition when they have prior knowledge with regard to modular distance learning. This study will help the government, teachers, and students take the necessary steps to improve and enhance modular distance learning that will benefit students for effective learning.

The modular learning system has been in place since its inception. One of its founding metaphoric pillars is student satisfaction with modular learning. The organization demonstrated its dedication to the student’s voice as a component of understanding effective teaching and learning. Student satisfaction research has been transformed by modular learning. It has caused the education research community to rethink long-held assumptions that learning occurs primarily within a metaphorical container known as a “course.” When reviewing studies on student satisfaction from a factor analytic perspective, one thing becomes clear: this is a complex system with little consensus. Even the most recent factor analytical studies have done little to address the lack of understanding of the dimensions underlying satisfaction with modular learning. Items about student satisfaction with modular distance learning correspond to forming a psychological contract in factor analytic studies. The survey responses are reconfigured into a smaller number of latent (non-observable) dimensions that the students never really articulate but are fully expected to satisfy. Of course, instructors have contracts with their students. Studies such as this one identify the student’s psychological contact after the fact, rather than before the class. The most important aspect is the rapid adoption of this teaching and learning mode in Senior High School. Another balancing factor is the growing sense of student agency in the educational process. Students can express their opinions about their educational experiences in formats ranging from end-of-course evaluation protocols to various social networks, making their voices more critical.

Furthermore, they all agreed with latent trait theory, which holds that the critical dimensions that students differentiate when expressing their opinions about modular learning are formed by the combination of the original items that cannot be directly observed—which underpins student satisfaction. As stated in the literature, the relationship between student satisfaction and the characteristic of a psychological contract is illustrated. Each element is translated into how it might be expressed in the student’s voice, and then a contract feature and an assessment strategy are added. The most significant contributor to the factor pattern, engaged learning, indicates that students expect instructors to play a facilitative role in their teaching. This dimension corresponds to the relational contract, in which the learning environment is stable and well organized, with a clear path to success.

5. Limitations and Future Work

This study was focused on the cognitive capacity of modular distance learning towards academic achievements and satisfaction of K-12 students during the COVID-19 pandemic. The sample size in this study was small, at only 252. If this study is repeated with a larger sample size, it will improve the results. The study’s restriction was to the province of Occidental Mindoro; Structural Equation Modeling (SEM) was used to measure all the variables. Thus, this will give an adequate solution to the problem in the study.

The current study underlines that combining TDT and BTT can positively impact the research outcome. The contribution the current study might make to the field of modular distance learning has been discussed and explained. Based on this research model, the nine (9) factors could broadly clarify the students’ adoption of new learning environment platform features. Thus, the current research suggests that more investigation be carried out to examine relationships among the complexity of modular distance learning.

Funding Statement

This research received no external funding.

Author Contributions

Data collection, methodology, writing and editing, K.A.M.; data collection, writing—review and editing, Y.-T.J. and C.S.S. All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

Informed consent statement.

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

Conflicts of interest.

The authors declare no conflict of interest.

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Original research article, insights into students’ experiences and perceptions of remote learning methods: from the covid-19 pandemic to best practice for the future.

• 1 Minerva Schools at Keck Graduate Institute, San Francisco, CA, United States
• 2 Ronin Institute for Independent Scholarship, Montclair, NJ, United States
• 3 Department of Physics, University of Toronto, Toronto, ON, Canada

This spring, students across the globe transitioned from in-person classes to remote learning as a result of the COVID-19 pandemic. This unprecedented change to undergraduate education saw institutions adopting multiple online teaching modalities and instructional platforms. We sought to understand students’ experiences with and perspectives on those methods of remote instruction in order to inform pedagogical decisions during the current pandemic and in future development of online courses and virtual learning experiences. Our survey gathered quantitative and qualitative data regarding students’ experiences with synchronous and asynchronous methods of remote learning and specific pedagogical techniques associated with each. A total of 4,789 undergraduate participants representing institutions across 95 countries were recruited via Instagram. We find that most students prefer synchronous online classes, and students whose primary mode of remote instruction has been synchronous report being more engaged and motivated. Our qualitative data show that students miss the social aspects of learning on campus, and it is possible that synchronous learning helps to mitigate some feelings of isolation. Students whose synchronous classes include active-learning techniques (which are inherently more social) report significantly higher levels of engagement, motivation, enjoyment, and satisfaction with instruction. Respondents’ recommendations for changes emphasize increased engagement, interaction, and student participation. We conclude that active-learning methods, which are known to increase motivation, engagement, and learning in traditional classrooms, also have a positive impact in the remote-learning environment. Integrating these elements into online courses will improve the student experience.

Introduction

The COVID-19 pandemic has dramatically changed the demographics of online students. Previously, almost all students engaged in online learning elected the online format, starting with individual online courses in the mid-1990s through today’s robust online degree and certificate programs. These students prioritize convenience, flexibility and ability to work while studying and are older than traditional college age students ( Harris and Martin, 2012 ; Levitz, 2016 ). These students also find asynchronous elements of a course are more useful than synchronous elements ( Gillingham and Molinari, 2012 ). In contrast, students who chose to take courses in-person prioritize face-to-face instruction and connection with others and skew considerably younger ( Harris and Martin, 2012 ). This leaves open the question of whether students who prefer to learn in-person but are forced to learn remotely will prefer synchronous or asynchronous methods. One study of student preferences following a switch to remote learning during the COVID-19 pandemic indicates that students enjoy synchronous over asynchronous course elements and find them more effective ( Gillis and Krull, 2020 ). Now that millions of traditional in-person courses have transitioned online, our survey expands the data on student preferences and explores if those preferences align with pedagogical best practices.

An extensive body of research has explored what instructional methods improve student learning outcomes (Fink. 2013). Considerable evidence indicates that active-learning or student-centered approaches result in better learning outcomes than passive-learning or instructor-centered approaches, both in-person and online ( Freeman et al., 2014 ; Chen et al., 2018 ; Davis et al., 2018 ). Active-learning approaches include student activities or discussion in class, whereas passive-learning approaches emphasize extensive exposition by the instructor ( Freeman et al., 2014 ). Constructivist learning theories argue that students must be active participants in creating their own learning, and that listening to expert explanations is seldom sufficient to trigger the neurological changes necessary for learning ( Bostock, 1998 ; Zull, 2002 ). Some studies conclude that, while students learn more via active learning, they may report greater perceptions of their learning and greater enjoyment when passive approaches are used ( Deslauriers et al., 2019 ). We examine student perceptions of remote learning experiences in light of these previous findings.

In this study, we administered a survey focused on student perceptions of remote learning in late May 2020 through the social media account of @unjadedjade to a global population of English speaking undergraduate students representing institutions across 95 countries. We aim to explore how students were being taught, the relationship between pedagogical methods and student perceptions of their experience, and the reasons behind those perceptions. Here we present an initial analysis of the results and share our data set for further inquiry. We find that positive student perceptions correlate with synchronous courses that employ a variety of interactive pedagogical techniques, and that students overwhelmingly suggest behavioral and pedagogical changes that increase social engagement and interaction. We argue that these results support the importance of active learning in an online environment.

Materials and Methods

Participant pool.

Students were recruited through the Instagram account @unjadedjade. This social media platform, run by influencer Jade Bowler, focuses on education, effective study tips, ethical lifestyle, and promotes a positive mindset. For this reason, the audience is presumably academically inclined, and interested in self-improvement. The survey was posted to her account and received 10,563 responses within the first 36 h. Here we analyze the 4,789 of those responses that came from undergraduates. While we did not collect demographic or identifying information, we suspect that women are overrepresented in these data as followers of @unjadedjade are 80% women. A large minority of respondents were from the United Kingdom as Jade Bowler is a British influencer. Specifically, 43.3% of participants attend United Kingdom institutions, followed by 6.7% attending university in the Netherlands, 6.1% in Germany, 5.8% in the United States and 4.2% in Australia. Ninety additional countries are represented in these data (see Supplementary Figure 1 ).

Survey Design

The purpose of this survey is to learn about students’ instructional experiences following the transition to remote learning in the spring of 2020.

This survey was initially created for a student assignment for the undergraduate course Empirical Analysis at Minerva Schools at KGI. That version served as a robust pre-test and allowed for identification of the primary online platforms used, and the four primary modes of learning: synchronous (live) classes, recorded lectures and videos, uploaded or emailed materials, and chat-based communication. We did not adapt any open-ended questions based on the pre-test survey to avoid biasing the results and only corrected language in questions for clarity. We used these data along with an analysis of common practices in online learning to revise the survey. Our revised survey asked students to identify the synchronous and asynchronous pedagogical methods and platforms that they were using for remote learning. Pedagogical methods were drawn from literature assessing active and passive teaching strategies in North American institutions ( Fink, 2013 ; Chen et al., 2018 ; Davis et al., 2018 ). Open-ended questions asked students to describe why they preferred certain modes of learning and how they could improve their learning experience. Students also reported on their affective response to learning and participation using a Likert scale.

The revised survey also asked whether students had responded to the earlier survey. No significant differences were found between responses of those answering for the first and second times (data not shown). See Supplementary Appendix 1 for survey questions. Survey data was collected from 5/21/20 to 5/23/20.

Qualitative Coding

We applied a qualitative coding framework adapted from Gale et al. (2013) to analyze student responses to open-ended questions. Four researchers read several hundred responses and noted themes that surfaced. We then developed a list of themes inductively from the survey data and deductively from the literature on pedagogical practice ( Garrison et al., 1999 ; Zull, 2002 ; Fink, 2013 ; Freeman et al., 2014 ). The initial codebook was revised collaboratively based on feedback from researchers after coding 20–80 qualitative comments each. Before coding their assigned questions, alignment was examined through coding of 20 additional responses. Researchers aligned in identifying the same major themes. Discrepancies in terms identified were resolved through discussion. Researchers continued to meet weekly to discuss progress and alignment. The majority of responses were coded by a single researcher using the final codebook ( Supplementary Table 1 ). All responses to questions 3 (4,318 responses) and 8 (4,704 responses), and 2,512 of 4,776 responses to question 12 were analyzed. Valence was also indicated where necessary (i.e., positive or negative discussion of terms). This paper focuses on the most prevalent themes from our initial analysis of the qualitative responses. The corresponding author reviewed codes to ensure consistency and accuracy of reported data.

Statistical Analysis

The survey included two sets of Likert-scale questions, one consisting of a set of six statements about students’ perceptions of their experiences following the transition to remote learning ( Table 1 ). For each statement, students indicated their level of agreement with the statement on a five-point scale ranging from 1 (“Strongly Disagree”) to 5 (“Strongly Agree”). The second set asked the students to respond to the same set of statements, but about their retroactive perceptions of their experiences with in-person instruction before the transition to remote learning. This set was not the subject of our analysis but is present in the published survey results. To explore correlations among student responses, we used CrossCat analysis to calculate the probability of dependence between Likert-scale responses ( Mansinghka et al., 2016 ).

Table 1. Likert-scale questions.

Mean values are calculated based on the numerical scores associated with each response. Measures of statistical significance for comparisons between different subgroups of respondents were calculated using a two-sided Mann-Whitney U -test, and p -values reported here are based on this test statistic. We report effect sizes in pairwise comparisons using the common-language effect size, f , which is the probability that the response from a random sample from subgroup 1 is greater than the response from a random sample from subgroup 2. We also examined the effects of different modes of remote learning and technological platforms using ordinal logistic regression. With the exception of the mean values, all of these analyses treat Likert-scale responses as ordinal-scale, rather than interval-scale data.

Students Prefer Synchronous Class Sessions

Students were asked to identify their primary mode of learning given four categories of remote course design that emerged from the pilot survey and across literature on online teaching: live (synchronous) classes, recorded lectures and videos, emailed or uploaded materials, and chats and discussion forums. While 42.7% ( n = 2,045) students identified live classes as their primary mode of learning, 54.6% ( n = 2613) students preferred this mode ( Figure 1 ). Both recorded lectures and live classes were preferred over uploaded materials (6.22%, n = 298) and chat (3.36%, n = 161).

Figure 1. Actual (A) and preferred (B) primary modes of learning.

In addition to a preference for live classes, students whose primary mode was synchronous were more likely to enjoy the class, feel motivated and engaged, be satisfied with instruction and report higher levels of participation ( Table 2 and Supplementary Figure 2 ). Regardless of primary mode, over two-thirds of students reported they are often distracted during remote courses.

Table 2. The effect of synchronous vs. asynchronous primary modes of learning on student perceptions.

Variation in Pedagogical Techniques for Synchronous Classes Results in More Positive Perceptions of the Student Learning Experience

To survey the use of passive vs. active instructional methods, students reported the pedagogical techniques used in their live classes. Among the synchronous methods, we identify three different categories ( National Research Council, 2000 ; Freeman et al., 2014 ). Passive methods (P) include lectures, presentations, and explanation using diagrams, white boards and/or other media. These methods all rely on instructor delivery rather than student participation. Our next category represents active learning through primarily one-on-one interactions (A). The methods in this group are in-class assessment, question-and-answer (Q&A), and classroom chat. Group interactions (F) included classroom discussions and small-group activities. Given these categories, Mann-Whitney U pairwise comparisons between the 7 possible combinations and Likert scale responses about student experience showed that the use of a variety of methods resulted in higher ratings of experience vs. the use of a single method whether or not that single method was active or passive ( Table 3 ). Indeed, students whose classes used methods from each category (PAF) had higher ratings of enjoyment, motivation, and satisfaction with instruction than those who only chose any single method ( p < 0.0001) and also rated higher rates of participation and engagement compared to students whose only method was passive (P) or active through one-on-one interactions (A) ( p < 0.00001). Student ratings of distraction were not significantly different for any comparison. Given that sets of Likert responses often appeared significant together in these comparisons, we ran a CrossCat analysis to look at the probability of dependence across Likert responses. Responses have a high probability of dependence on each other, limiting what we can claim about any discrete response ( Supplementary Figure 3 ).

Table 3. Comparison of combinations of synchronous methods on student perceptions. Effect size (f).

Mann-Whitney U pairwise comparisons were also used to check if improvement in student experience was associated with the number of methods used vs. the variety of types of methods. For every comparison, we found that more methods resulted in higher scores on all Likert measures except distraction ( Table 4 ). Even comparison between four or fewer methods and greater than four methods resulted in a 59% chance that the latter enjoyed the courses more ( p < 0.00001) and 60% chance that they felt more motivated to learn ( p < 0.00001). Students who selected more than four methods ( n = 417) were also 65.1% ( p < 0.00001), 62.9% ( p < 0.00001) and 64.3% ( p < 0.00001) more satisfied with instruction, engaged, and actively participating, respectfully. Therefore, there was an overlap between how the number and variety of methods influenced students’ experiences. Since the number of techniques per category is 2–3, we cannot fully disentangle the effect of number vs. variety. Pairwise comparisons to look at subsets of data with 2–3 methods from a single group vs. 2–3 methods across groups controlled for this but had low sample numbers in most groups and resulted in no significant findings (data not shown). Therefore, from the data we have in our survey, there seems to be an interdependence between number and variety of methods on students’ learning experiences.

Table 4. Comparison of the number of synchronous methods on student perceptions. Effect size (f).

Variation in Asynchronous Pedagogical Techniques Results in More Positive Perceptions of the Student Learning Experience

Along with synchronous pedagogical methods, students reported the asynchronous methods that were used for their classes. We divided these methods into three main categories and conducted pairwise comparisons. Learning methods include video lectures, video content, and posted study materials. Interacting methods include discussion/chat forums, live office hours, and email Q&A with professors. Testing methods include assignments and exams. Our results again show the importance of variety in students’ perceptions ( Table 5 ). For example, compared to providing learning materials only, providing learning materials, interaction, and testing improved enjoyment ( f = 0.546, p < 0.001), motivation ( f = 0.553, p < 0.0001), satisfaction with instruction ( f = 0.596, p < 0.00001), engagement ( f = 0.572, p < 0.00001) and active participation ( f = 0.563, p < 0.00001) (row 6). Similarly, compared to just being interactive with conversations, the combination of all three methods improved five out of six indicators, except for distraction in class (row 11).

Table 5. Comparison of combinations of asynchronous methods on student perceptions. Effect size (f).

Ordinal logistic regression was used to assess the likelihood that the platforms students used predicted student perceptions ( Supplementary Table 2 ). Platform choices were based on the answers to open-ended questions in the pre-test survey. The synchronous and asynchronous methods used were consistently more predictive of Likert responses than the specific platforms. Likewise, distraction continued to be our outlier with no differences across methods or platforms.

Students Prefer In-Person and Synchronous Online Learning Largely Due to Social-Emotional Reasoning

As expected, 86.1% (4,123) of survey participants report a preference for in-person courses, while 13.9% (666) prefer online courses. When asked to explain the reasons for their preference, students who prefer in-person courses most often mention the importance of social interaction (693 mentions), engagement (639 mentions), and motivation (440 mentions). These students are also more likely to mention a preference for a fixed schedule (185 mentions) vs. a flexible schedule (2 mentions).

In addition to identifying social reasons for their preference for in-person learning, students’ suggestions for improvements in online learning focus primarily on increasing interaction and engagement, with 845 mentions of live classes, 685 mentions of interaction, 126 calls for increased participation and calls for changes related to these topics such as, “Smaller teaching groups for live sessions so that everyone is encouraged to talk as some people don’t say anything and don’t participate in group work,” and “Make it less of the professor reading the pdf that was given to us and more interaction.”

Students who prefer online learning primarily identify independence and flexibility (214 mentions) and reasons related to anxiety and discomfort in in-person settings (41 mentions). Anxiety was only mentioned 12 times in the much larger group that prefers in-person learning.

The preference for synchronous vs. asynchronous modes of learning follows similar trends ( Table 6 ). Students who prefer live classes mention engagement and interaction most often while those who prefer recorded lectures mention flexibility.

Table 6. Most prevalent themes for students based on their preferred mode of remote learning.

Student Perceptions Align With Research on Active Learning

The first, and most robust, conclusion is that incorporation of active-learning methods correlates with more positive student perceptions of affect and engagement. We can see this clearly in the substantial differences on a number of measures, where students whose classes used only passive-learning techniques reported lower levels of engagement, satisfaction, participation, and motivation when compared with students whose classes incorporated at least some active-learning elements. This result is consistent with prior research on the value of active learning ( Freeman et al., 2014 ).

Though research shows that student learning improves in active learning classes, on campus, student perceptions of their learning, enjoyment, and satisfaction with instruction are often lower in active-learning courses ( Deslauriers et al., 2019 ). Our finding that students rate enjoyment and satisfaction with instruction higher for active learning online suggests that the preference for passive lectures on campus relies on elements outside of the lecture itself. That might include the lecture hall environment, the social physical presence of peers, or normalization of passive lectures as the expected mode for on-campus classes. This implies that there may be more buy-in for active learning online vs. in-person.

A second result from our survey is that student perceptions of affect and engagement are associated with students experiencing a greater diversity of learning modalities. We see this in two different results. First, in addition to the fact that classes that include active learning outperform classes that rely solely on passive methods, we find that on all measures besides distraction, the highest student ratings are associated with a combination of active and passive methods. Second, we find that these higher scores are associated with classes that make use of a larger number of different methods.

This second result suggests that students benefit from classes that make use of multiple different techniques, possibly invoking a combination of passive and active methods. However, it is unclear from our data whether this effect is associated specifically with combining active and passive methods, or if it is associated simply with the use of multiple different methods, irrespective of whether those methods are active, passive, or some combination. The problem is that the number of methods used is confounded with the diversity of methods (e.g., it is impossible for a classroom using only one method to use both active and passive methods). In an attempt to address this question, we looked separately at the effect of number and diversity of methods while holding the other constant. Across a large number of such comparisons, we found few statistically significant differences, which may be a consequence of the fact that each comparison focused on a small subset of the data.

Thus, our data suggests that using a greater diversity of learning methods in the classroom may lead to better student outcomes. This is supported by research on student attention span which suggests varying delivery after 10–15 min to retain student’s attention ( Bradbury, 2016 ). It is likely that this is more relevant for online learning where students report high levels of distraction across methods, modalities, and platforms. Given that number and variety are key, and there are few passive learning methods, we can assume that some combination of methods that includes active learning improves student experience. However, it is not clear whether we should predict that this benefit would come simply from increasing the number of different methods used, or if there are benefits specific to combining particular methods. Disentangling these effects would be an interesting avenue for future research.

Students Value Social Presence in Remote Learning

Student responses across our open-ended survey questions show a striking difference in reasons for their preferences compared with traditional online learners who prefer flexibility ( Harris and Martin, 2012 ; Levitz, 2016 ). Students reasons for preferring in-person classes and synchronous remote classes emphasize the desire for social interaction and echo the research on the importance of social presence for learning in online courses.

Short et al. (1976) outlined Social Presence Theory in depicting students’ perceptions of each other as real in different means of telecommunications. These ideas translate directly to questions surrounding online education and pedagogy in regards to educational design in networked learning where connection across learners and instructors improves learning outcomes especially with “Human-Human interaction” ( Goodyear, 2002 , 2005 ; Tu, 2002 ). These ideas play heavily into asynchronous vs. synchronous learning, where Tu reports students having positive responses to both synchronous “real-time discussion in pleasantness, responsiveness and comfort with familiar topics” and real-time discussions edging out asynchronous computer-mediated communications in immediate replies and responsiveness. Tu’s research indicates that students perceive more interaction with synchronous mediums such as discussions because of immediacy which enhances social presence and support the use of active learning techniques ( Gunawardena, 1995 ; Tu, 2002 ). Thus, verbal immediacy and communities with face-to-face interactions, such as those in synchronous learning classrooms, lessen the psychological distance of communicators online and can simultaneously improve instructional satisfaction and reported learning ( Gunawardena and Zittle, 1997 ; Richardson and Swan, 2019 ; Shea et al., 2019 ). While synchronous learning may not be ideal for traditional online students and a subset of our participants, this research suggests that non-traditional online learners are more likely to appreciate the value of social presence.

Social presence also connects to the importance of social connections in learning. Too often, current systems of education emphasize course content in narrow ways that fail to embrace the full humanity of students and instructors ( Gay, 2000 ). With the COVID-19 pandemic leading to further social isolation for many students, the importance of social presence in courses, including live interactions that build social connections with classmates and with instructors, may be increased.

Limitations of These Data

Our undergraduate data consisted of 4,789 responses from 95 different countries, an unprecedented global scale for research on online learning. However, since respondents were followers of @unjadedjade who focuses on learning and wellness, these respondents may not represent the average student. Biases in survey responses are often limited by their recruitment techniques and our bias likely resulted in more robust and thoughtful responses to free-response questions and may have influenced the preference for synchronous classes. It is unlikely that it changed students reporting on remote learning pedagogical methods since those are out of student control.

Though we surveyed a global population, our design was rooted in literature assessing pedagogy in North American institutions. Therefore, our survey may not represent a global array of teaching practices.

This survey was sent out during the initial phase of emergency remote learning for most countries. This has two important implications. First, perceptions of remote learning may be clouded by complications of the pandemic which has increased social, mental, and financial stresses globally. Future research could disaggregate the impact of the pandemic from students’ learning experiences with a more detailed and holistic analysis of the impact of the pandemic on students.

Second, instructors, students and institutions were not able to fully prepare for effective remote education in terms of infrastructure, mentality, curriculum building, and pedagogy. Therefore, student experiences reflect this emergency transition. Single-modality courses may correlate with instructors who lacked the resources or time to learn or integrate more than one modality. Regardless, the main insights of this research align well with the science of teaching and learning and can be used to inform both education during future emergencies and course development for online programs that wish to attract traditional college students.

Global Student Voices Improve Our Understanding of the Experience of Emergency Remote Learning

Our survey shows that global student perspectives on remote learning agree with pedagogical best practices, breaking with the often-found negative reactions of students to these practices in traditional classrooms ( Shekhar et al., 2020 ). Our analysis of open-ended questions and preferences show that a majority of students prefer pedagogical approaches that promote both active learning and social interaction. These results can serve as a guide to instructors as they design online classes, especially for students whose first choice may be in-person learning. Indeed, with the near ubiquitous adoption of remote learning during the COVID-19 pandemic, remote learning may be the default for colleges during temporary emergencies. This has already been used at the K-12 level as snow days become virtual learning days ( Aspergren, 2020 ).

In addition to informing pedagogical decisions, the results of this survey can be used to inform future research. Although we survey a global population, our recruitment method selected for students who are English speakers, likely majority female, and have an interest in self-improvement. Repeating this study with a more diverse and representative sample of university students could improve the generalizability of our findings. While the use of a variety of pedagogical methods is better than a single method, more research is needed to determine what the optimal combinations and implementations are for courses in different disciplines. Though we identified social presence as the major trend in student responses, the over 12,000 open-ended responses from students could be analyzed in greater detail to gain a more nuanced understanding of student preferences and suggestions for improvement. Likewise, outliers could shed light on the diversity of student perspectives that we may encounter in our own classrooms. Beyond this, our findings can inform research that collects demographic data and/or measures learning outcomes to understand the impact of remote learning on different populations.

Importantly, this paper focuses on a subset of responses from the full data set which includes 10,563 students from secondary school, undergraduate, graduate, or professional school and additional questions about in-person learning. Our full data set is available here for anyone to download for continued exploration: https://dataverse.harvard.edu/dataset.xhtml?persistentId= doi: 10.7910/DVN/2TGOPH .

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics Statement

Ethical review and approval was not required for the study on human participants in accordance with the local legislation and institutional requirements. The patients/participants provided their written informed consent to participate in this study.

Author Contributions

GS: project lead, survey design, qualitative coding, writing, review, and editing. TN: data analysis, writing, review, and editing. CN and PB: qualitative coding. JW: data analysis, writing, and editing. CS: writing, review, and editing. EV and KL: original survey design and qualitative coding. PP: data analysis. JB: original survey design and survey distribution. HH: data analysis. MP: writing. All authors contributed to the article and approved the submitted version.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

We want to thank Minerva Schools at KGI for providing funding for summer undergraduate research internships. We also want to thank Josh Fost and Christopher V. H.-H. Chen for discussion that helped shape this project.

Supplementary Material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/feduc.2021.647986/full#supplementary-material

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Keywords : online learning, COVID-19, active learning, higher education, pedagogy, survey, international

Citation: Nguyen T, Netto CLM, Wilkins JF, Bröker P, Vargas EE, Sealfon CD, Puthipiroj P, Li KS, Bowler JE, Hinson HR, Pujar M and Stein GM (2021) Insights Into Students’ Experiences and Perceptions of Remote Learning Methods: From the COVID-19 Pandemic to Best Practice for the Future. Front. Educ. 6:647986. doi: 10.3389/feduc.2021.647986

Received: 30 December 2020; Accepted: 09 March 2021; Published: 09 April 2021.

Reviewed by:

Copyright © 2021 Nguyen, Netto, Wilkins, Bröker, Vargas, Sealfon, Puthipiroj, Li, Bowler, Hinson, Pujar and Stein. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Geneva M. Stein, [email protected]

This article is part of the Research Topic

Covid-19 and Beyond: From (Forced) Remote Teaching and Learning to ‘The New Normal’ in Higher Education

• Research article
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• Published: 20 May 2020

Students’ perceptions on distance education: A multinational study

• Patricia Fidalgo 1 ,
• Joan Thormann 2 ,
• Oleksandr Kulyk 3 &
• José Alberto Lencastre 4  

International Journal of Educational Technology in Higher Education volume  17 , Article number:  18 ( 2020 ) Cite this article

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Many universities offer Distance Education (DE) courses and programs to address the diverse educational needs of students and to stay current with advancing technology. Some Institutions of Higher Education (IHE) that do not offer DE find it difficult to navigate through the steps that are needed to provide such courses and programs. Investigating learners’ perceptions, attitudes and willingness to try DE can provide guidance and recommendations for IHEs that are considering expanding use of DE formats. A survey was distributed to undergraduate students in Portugal, UAE and Ukraine. The results of this pilot study showed that in all three countries, students’ major concerns about such programs were time management, motivation, and English language skills. Although students were somewhat apprehensive many indicated they were interested in taking DE courses. Six recommendations informed by interpretation of students’ responses and the literature, are offered to assist institutions who want to offer DE as part of their educational strategy.

Introduction

The World Wide Web has made information access and distribution of educational content available to a large fraction of the world’s population and helped to move Distance Education (DE) to the digital era. DE has become increasingly common in many universities worldwide (Allen & Seaman, 2017 ). Nonetheless, there are still many universities that do not provide this opportunity because it is not part of their institutional culture. As DE becomes more prevalent, countries and Institutions of Higher Education (IHE) that do not provide DE courses will need to look at this option to retain and expand their student population. (Keegan, 1994 ; Nakamura, 2017 ).

In order to develop such programs, it is useful to determine if students are receptive to taking such online courses and are prepared to do so. This study addresses students’ perceptions and their interest in DE. In addition, it provides a comparative analysis across three countries whose IHEs do not have extensive offerings in DE. The results of this research provide some strategies to encourage and support students to take DE courses.

Literature review

A seminal article by Keegan ( 1980 ) presents key aspects of DE. Some of the elements are: physical separation of teacher and learner, learning occurs in the context of an educational institution, technical media are used, teacher and learner communicate, face to face meetings are possible, and an industrial model of providing education is used. More recently varying definitions of DE seem to be based on the perspective of various educators and to reflect the educational culture of each country and IHE. However, some common descriptors seem to be accepted by most stakeholders in the field. Distance education is an educational experience where instructors and learners are separated in time and space (Keegan, 2002 ) which means it can happen away from an academic institution and can lead to a degree or credential (Gunawardena, McIsaac, & Jonassen, 2008 ).

Although there are different types of DE, this research focuses on online learning. The following types of online learning will be investigated: synchronous, asynchronous, blended, massive online open courses (MOOC), and open schedule online courses. In synchronous instruction, teachers and learners meet (usually online) for a session at a predetermined time. According to Watts ( 2016 ) live streaming video and/or audio are used for synchronous interaction. Although videoconferencing allows participants to see each other this is not considered a face-to-face interaction because of the physical separation (Keegan, 1980 ).

Asynchronous instruction means that teachers and learners do not have synchronous sessions and that students have access to course content through the Internet at any time they want or need. Communication among the participants occurs mainly through email and online forums and is typically moderated by the instructor (Watts, 2016 ). According to Garrison ( 2000 ) “Asynchronous collaborative learning may well be the defining technology of the postindustrial era of distance education.” (p.12) Yet another type of DE is blended learning (BL). Garrison and Kanuka ( 2004 ) define BL as combining face-to-face classroom time with online learning experiences. Although it is not clear as to how much time is allocated to online in the blended model “the real test of blended learning is the effective integration of the two main components (face-to-face and Internet technology) such that we are not just adding on to the existing dominant approach or method.” (p.97) In the BL format different teaching strategies and instructional technology can be used to help individuals who have different learning styles, needs and interests (Tseng & Walsh Jr., 2016 ).

Another type of DE is MOOCs (Massive Online Open Courses). This format was first introduced in 2006 and offers distributed open online courses that are available without cost to a very large number of participants (Cormier, McAuley, Siemens, & Stewart, 2010 ). MOOCs origins can be traced to the Open Access Initiative in 2002 which advocates sharing knowledge freely through the Internet. By providing educational opportunities MOOCs can address the increasing demand for training and education (Zawacki-Richter & Naidu, 2016 ). Finally, in open schedule online courses students work asynchronously with all the materials being provided digitally. Although there are deadlines for submitting assignments, students working at their own pace have some independence as to when they do their coursework (Campus Explorer, 2019 ).

There are advantages and disadvantages in taking DE courses. Some of the advantages are self-paced study, time and space flexibility, time saving (no commute between home and school) and the fact that a distance learning course often costs less. Disadvantages include a sense of isolation, the struggle with staying motivated, lack of face-to-face interaction, difficulty in getting immediate feedback, the need for constant and reliable access to technology, and occasionally some difficulty with accreditation (De Paepe, Zhu, & Depryck, 2018 ; Lei & Gupta, 2010 ; Venter, 2003 ; Zuhairi, Wahyono, & Suratinah, 2006 ).

Most of the literature concerning student perception of DE courses, both blended and entirely online, involves students who have enrolled in online courses. Some articles address comparisons of perceptions between face-to-face and online students regarding DE (Daniels & Feather, 2002 ; Dobbs, del Carmen, & Waid-Lindberg, 2017 ; Hannay & Newvine, 2006 ; Lanier, 2006 ). Additional studies address adult and undergraduate students and cover many aspects of the online experience (Dobbs et al., 2017 ; Horspool & Lange, 2012 ; Seok, DaCosta, Kinsell, & Tung, 2010b , a ). However, little, if any research has been conducted that only addresses perceptions of students who live in countries in which few IHEs offer online courses.

In a study comparing online and face-to-face learning, Horspool and Lange ( 2012 ) found that students chose to take online courses to avoid travel time to class and scheduling problems. A majority of both face-to-face and online students did not experience technological issues. Both groups also found that communication with the instructor was adequate. Online students indicated that instructor response time to questions was prompt. By contrast online students perceived peer communication as occurring much less often. Course satisfaction was comparable for both formats (Horspool & Lange, 2012 ). Responses to another survey concerning online and traditional course formats found that students’ reasons for taking online courses included flexibility to accommodate work and family schedules, the ability to avoid commuting to the university and more online courses being available to them (Dobbs et al., 2017 ). Both online and traditional students agreed that traditional courses were easier, and they learned more in that format. They also concurred that online courses required more effort. Experienced online students indicated that the quality of their courses was good while traditional students who had never taken an online course felt that the quality of online courses was lower.

There is additional research that focuses on students including those enrolled in community colleges, MOOCs, blended learning as well as adult learners. Community college students’ and instructors’ perceptions of effectiveness of online courses were compared by Seok et al. ( 2010b , a ). The researchers focused on pedagogical characteristics (management, Universal Design for Learning, interaction, teaching design and content) and technical features (interface, navigation and support). In addition, responses were examined based on various aspects of the subjects’ demographics. Two surveys with 99 items were distributed electronically. One survey was for instructors and the other for students. In general, instructors and students indicated that teaching and learning online was effective. Female students responded more positively to most questions concerning effectiveness, and instructors also found it more positive (Seok et al., 2010b , a ).

Students who enrolled in a MOOC were motivated to take other courses in this format based on their perception that it was useful for achieving their goals. In addition, their motivation was high if the course was posted on a platform that was easy to use (Aharony & Bar-Ilan, 2016 ). This study also found that as students proceeded through the course, they gained confidence.

Blended learning was examined by Kurt and Yildirim ( 2018 ) to determine student satisfaction and what they considered to be important features of the blended format. The results indicated that the Turkish students who participated, almost unanimously felt that BL was beneficial and that their own role and the instructors’ role was central to their satisfaction. The authors stated, “the prominent components in the process have been identified as face-to-face lessons, the features of online course materials, LMS used, design-specific activities, process-based measurement and evaluation, student-student interaction and out-of-class sharing respectively.” (p. 439) DE has a growth potential and offers the opportunity to reach many people (Fidalgo, 2012 ), hence it can be used as a technique for mass education (Perraton, 2008 ). According to Perraton ( 2008 ) DE can be adapted to the needs of current and previous generations who did not complete their education. DE can also reach individuals who live in remote locations and do not have the means to attend school.

Methodology

Study goals.

The goal of this pilot study is to examine what undergraduate students’ perceptions are concerning DE and their willingness to enroll in this type of course. This study focuses on three countries that do not offer extensive DE accredited programs. By comparing three countries with similar DE profiles, commonalties and differences that are relevant and useful can be found. When the IHEs from these countries decide or have the conditions to move towards DE, the results of this study may help them adapt this format to their particular context and students’ needs. Results may also help IHEs plan their strategy for offering online courses to current and future students and attract prospective students who otherwise would not be able to enroll in the face-to-face courses that are available.

Research questions

Have undergraduate students taken an online course previously?

What are undergraduate students’ perceptions of distance education?

What are the reasons for undergraduate students to enroll/not enroll is distance education courses?

What preparation do undergraduate students feel they need to have before taking distance education courses?

What is the undergraduate students’ receptivity towards enrolling in distance education courses?

What types of distance education would undergraduate students be interested in taking?

This research was conducted at IHEs in three countries (Portugal, Ukraine and UAE). A description of each country’s sociodemographic and technological use provides a context for this study.

Portugal, a country located at the western end of the European continent, has a resident population of just over 10 million people (Instituto Nacional de Estatistica, 2019 ). Data collected by Instituto Nacional de Estatistica in 2019 indicated that almost 81% of households in Portugal had Internet access at home. According to the Portuguese National Statistical Institute ( 2019 ), the rate of Internet use by the adult population is about 76%. Among this population, people who attend or have completed secondary and higher education have a higher percentage of Internet use (98%) (Instituto Nacional de Estatistica, 2019 ).

The most used devices to access the Internet are smartphones and laptops. Regarding computer tasks, the most frequent ones are copying and moving files and folders and transferring files from the computer to other devices (PORDATA - Base de Dados Portugal Contemporâneo, 2017 ).

Among Internet users, 80% use social networks, which is a higher percentage than the European Union (EU) average. Mobile Internet access (outside the home and workplace and on portable devices) is 84% and maintains a strong growth trend (Instituto Nacional de Estatistica, 2019 ).

Ukraine is one of the post-soviet countries located in Eastern Europe and it strives to be integrated in economic and political structures of the EU. The current population of the country is 42 million. Despite the low incomes of many Ukrainians, modern technological devices are widespread among the population. The State Statistics Service of Ukraine ( 2019 ) reported that there were 26 million Internet subscribers in the country in the beginning of 2019. However, Ukrainians do not have a high level of digital literacy yet. According to the Digital Transformation Ministry of Ukraine (Communications Department of the Secretariat of the CMU, 2019 ), almost 38% of Ukrainian people aged from 18 to 70 have poor skills in computer literacy and 15.1% of the citizens have no computer skills.

According to the survey conducted by the Digital Transformation Ministry of Ukraine (The Cabinet of Ministers of Ukraine, 2019 ) 27.5% Ukrainian families have a tablet, and 30.6% have one smart phone, 26.4% have two smart phones, 16.5% have three smart phones and 10.8% have four and more smart phones. As for laptops, 42.7% Ukrainian families have a laptop and 45.6% have a desktop computer (The Cabinet of Ministers of Ukraine, 2019 ). The data from the ministry did not indicate if families have multiple devices, however the data shows that technological devices are widespread.

The United Arab Emirates (UAE) is a country located in the Persian Gulf that borders with Oman and Saudi Arabia. The UAE has a population of 9.77 million and is one of the richest countries in the world based on gross domestic product (GDP) per capita. The resident population consists of 11,5% Emiratis and the remaining residents are expats from countries such as India, Pakistan, Philippines, Egypt and others (Global Media Insight, 2020 ).

Regarding technology use, 91% of the residents use mobile Internetand over 98% of the households have Internet access (Knoema, 2018 ). Mobile devices such as smartphones are used to access the Internet mainly at home or at work (Federal Competitiveness and Statistics Authority, 2017 ).

In 2017 the most frequent Internet activities were: sending/receiving emails (61%), posting information or instant messaging (55%), getting information about goods or services (45%), reading or downloading online newspapers, magazines or electronic books (41%) and telephoning over the Internet/VOIP (33%). Downloading movies, images, music, watching TV or video, or listening to radio or music is also a frequent activity performed by 27% of the Internet users followed by Internet banking (25%) and purchasing or ordering good and services (22%) (Federal Competitiveness and Statistics Authority, 2017 ).

While these three countries were selected due to the location of the researchers and thus provided convenience samples, the three countries have a similar lack of DE offerings. Online surveys were emailed to students enrolled in a variety of undergraduate face-to-face courses during the fall semester of 2018. The students in Portugal and the UAE were enrolled in a teacher education program and the survey was emailed to two course sections in Portugal (73 students) and four course sections in the UAE (108 students). At the IHE in Ukraine, students were majoring in applied mathematics, philology, diagnostics, social work and philosophy, and surveys were emailed to 102 students who were enrolled in five course sections. In Portugal and Ukraine, the URL for the online survey was emailed by the instructor of all the course sections. In the UAE the instructor who emailed the URL for the survey taught two of the course sections. The students in the other two sections knew this instructor from taking courses with her previously. The students participating in this study were a convenience sample based on the disciplines taught by the researchers.

Data collection

An online survey with 10 closed questions about undergraduate students’ perception and receptivity towards enrolling in DE courses was developed by the researchers. Ary, Jacobs, Sorensen, and Walker ( 2010 ) compared traditional methods (i.e. face-to-face, paper and pencil) with web-based surveys and found the latter to be are more effective for gathering data from many participants. The questions designed by the researchers were informed by their experience/practice as well as in-depth literature review. The survey was created to respond to the research questions that guided this study. Response choices to the multiple-choice questions were based on issues and concerns related to DE. Students’ responses were collected towards the end of the first semester of the 2018/19 academic year.

The survey was developed to address research questions that assess undergraduate students’ perceptions of DE and students’ receptivity towards enrolling in DE courses (c.f. Appendix ). The use of surveys allows researchers to “obtain information about thoughts, feelings, attitudes, beliefs, values, perceptions, personality and behavioral intentions of research participants.” (Johnson & Christensen, 2014 , p. 192) The survey questions included multiple response formats: Likert scale, select more than one response and multiple choice. Surveys for Portugal were presented in Portuguese. In Ukraine the surveys were translated into Ukrainian. Since English is the language of instruction at the UAE institution, their survey was in English. The URL for the survey was emailed to students by their instructors and was available in an online Google Form. The survey took approximately 10 min to complete. The study consisted of a “self-selected” convenience sample.

Data analysis

Survey results were recorded in Google Forms and an Excel spreadsheet was used to collect students’ responses. Descriptive statistics of the responses to the survey are presented in graphs and tables with percentages of responses displayed. The descriptive statistics provide summaries about the sample’s answers to each of the questions as well as measures of variability (or spread) and central tendency.

Research approval and data management

The research proposal was submitted to the Research and Grants Committee and approved by the Institutional Review Board of the college in the UAE. No personal information (name, College ID number or any other type of information that allows the identification of students) was asked from the students in the surveys. The surveys were anonymous. Only the Principal Investigator (PI) had access to all the data collected. The data will be stored in the PI’s password protected computer for 5 years.

Fifty five of the 73 Portuguese students who received the survey responded and 98 of the 108 UAE students responded. In the Ukraine 102 students were sent surveys and 70 responded. Below are participants’ responses to questions concerning age, gender, as well as level of confidence using the computer and the Internet.

Students’ age range was from 17 to 50 years old. Most students’ age ranges were between 17 and 29 years. Survey responses indicated that 7% of the students in the UAE were male and 93% female, in the Ukraine 43% were male and 57% female and in Portugal 9% male, and 91% female.

Participants were asked about their level of confidence using a computer and the Internet. Results are presented in Table  1 .

The use of participants from three countries allows the study of trends and to determine differences and/or similarities of perceptions about DE. Although the students were enrolled in courses in diverse content areas, they were all undergraduates, almost all under 30 years old, and most were confident using the computer and Internet. These demographic similarities provided a relatively cohesive group for this study while allowing a comparison across countries.

A range of questions were asked about students’ attitudes towards and experience with DE. To determine the participants’ experience with DE two questions were asked.

The data indicates that out of 223 students who responded to the survey, a total of 63 students have taken DE courses. Half of the Ukraine students, about one quarter of the UAE students and only 5% of students in the group from Portugal had taken DE courses (Fig.  1 ). As shown in Fig.  2 , of the students who have had previous experience in DE, most Ukraine students have taken one or two online courses, most UAE students have taken one course and a few Portuguese students have taken one course.

Students that have taken distance education courses

Number of distance education courses taken

More than half of Portuguese students, about two thirds of the Ukraine students and a little over one third of UAE students had a Very favorable or Favorable attitude towards DE. Approximately one third of Portuguese and Ukraine students were Neutral/Unable to judge their attitude. A little less than half of UAE students also indicated this. A small percentage of Portuguese, and one fifth of UAE students indicated their attitude was Very unfavorable or Unfavorable and no Ukraine students reported this (Table 2 ).

More than one third of Portuguese students shared that managing class and study time, saving time by choosing study location and working at their own pace were reasons to enroll in DE. About two thirds of the students from Ukraine reported that working at their own pace and managing their study time were reasons to enroll. A little more than half of these students reported that reasons for enrolling in DE included managing class time, saving time by selecting study location and not having to travel to school as well as having more options for courses or colleges to attend. Almost half of the UAE students had similar reasons for enrolling in a DE courses including managing class and study time, saving time by choosing study location and working at their own pace. In addition, a little more than half of the UAE students also shared that having more options for courses or colleges to attend were reasons to enroll. The reasons that were selected the least by all three groups were that courses were less expensive and enrolling in a preferred program (Tables  3 and 4 ).

Students were given eleven options as to why they would not enroll in DE courses, which are displayed in Tables  5 and 6 . Two reasons that were chosen most often were difficulty staying motivated and preferring face-to-face classes. A small number of Ukraine students reported this as a reason to not enroll in DE courses. Difficulty getting immediate feedback was also a concern for UAE students. Close to one third in the three groups indicated that difficulty contacting the instructor and interacting with peers as well as missing campus life are reasons for not enrolling. About one tenth of Portuguese, one fifth of Ukraine and one fifth of the UAE students reported difficulty getting accreditation as a reason for not enrolling. Not knowing enough about DE was indicated by one tenth of Portuguese, one fifth of Ukraine and one fifth of the UAE students. Only a small number of all the students indicated three categories that are frequently cited in the literature as preventing students from enrolling, these include access to technology, feeling of isolation and too great an expense.

Tables  7 and 8 show student responses to a question regarding the preparation they think they would need before enrolling in a DE course. A little over one tenth of the Portuguese students indicated that they needed better computer equipment, writing skills and a dedicated study space. About one quarter of these students reported they need better skills in the following areas: time management, computer and English language skills, as well as needing to have learning goals and objectives. Having a better Internet connection and the need to develop a study plan was shared by approximately one third of these students. Finally, the highest rated prerequisite for these Portuguese students was to be more motivated.

Few of the Ukraine students felt that they needed better computer equipment or skills, a dedicated study space or a better Internet connection at home. Their concerns focused on their behaviors as students since half or a little more than half felt they needed to be more motivated, have learning objectives and goals, a study plan and better management skills. About one third of these students also reported that they needed better English language skills.

The UAE students were less confident than the Ukraine students about computer skills and needing better equipment and a better Internet connection at home. Almost half of these UAE students reported their need for a study plan and motivation as their most pressing needs. Better management and English language skills were recorded by about one third of the students. One quarter of the UAE students felt they needed better writing skills and a dedicated study space.

Table 9 shows students’ interest in enrolling in DE courses. Almost one quarter of the Ukraine students are Extremely interested in taking DE courses and almost half are Somewhat interested. This contrasts with the students from Portugal who indicated that only 5% are Extremely interested and almost a quarter Somewhat interested. The UAE students’ interest in enrolling fell in between the students from the two other countries. One fifth to almost one third of all three groups were Neutral/Unable to judge. About one tenth of students from Ukraine reported Not being very interested or Not at all interested which contrasts with the Portuguese and UAE students whose numbers were about one half and one quarter respectively.

Tables  10 and 11 show the types of DE that the students were interested in trying. Portuguese students favored Open schedule courses, followed by Blended learning and Synchronous. Few of these students were interested in MOOCs and Asynchronous. More than half of the students from Ukraine were interested in MOOCs and Blended learning followed by Open schedule. About one third of these students were interested in Synchronous and Asynchronous. UAE students most popular formats were Open schedule and Blended learning followed by Synchronous and Asynchronous. There was little interest in MOOCs by the UAE students. Few Portuguese and Ukraine students indicated that they would not take a DE course, however, almost a quarter of the UAE students indicated this.

Data indicates close to a 100% of the UAE residents use the Internet at home or on their mobile devices (Knoema, 2018 ). By contrast a smaller percentage of individuals use the Internet in Portugal and the Ukraine (Infographics, 2019 ). Internet use in each country does not seem to greatly impact UAE students’ opinions regarding DE.

Students’ perceptions of DE vary across the participants from the three countries. Portuguese and Ukrainian students rated DE more favorably than UAE students. Half of the Ukrainian students have experience with DE which might account for their favorable attitude. In contrast, in Portugal only a very small percentage of the students had experience. However, this does not seem to have negatively influenced their attitude towards DE. The interest level and engagement with new technologies by Portuguese students may help explain the favorable perception the participants had toward DE. A study by Costa, Faria, and Neto ( 2018 ) found that 90% of Portuguese students use new technologies and 69% of them use new technologies more than an hour and a half a day. Based on three European studies, Diário de Noticias ( 2011 ) stated that Portuguese students “appear at the forefront of those who best master information and communication technologies (ICT).” (para.1) Another factor influencing respondents might be that currently, and for the first time, the Portuguese government has passed a law that will regulate DE in the country. This new law will open the possibility for other IHEs to provide DE courses that lead to a degree.

Ukrainian students reported a high level of confidence in operating technological devices. The reason for this may be, in part, because of state educational requirements. Since the end of the 1990s, all Ukrainian students in secondary schools have at least one computer course as a mandatory element of their curriculum. This course covers a wide range of issues, which vary from information society theory to applied aspects of computer usage. Among the seven learning goals of this course three address digital literacy (Ministry of Education and Science of Ukraine, 2017 ). Ukrainian students who responded to the survey have taken computer courses for at least 5 years.

In the UAE, most DE courses and programs are not accredited by the Ministry of Education (United Arab Emirates Ministry of Education, 2016 ), which may account for UAE students lack of experience and their inability to judge this type of instruction.

It is worth analyzing the reasons why students enrolled or would enroll in DE courses. The reasons for taking DE courses, such as time management issues, are supported by studies concerning self-regulation and higher retention rates (Bradley, Browne, & Kelley, 2017 ; Peck, Stefaniak, & Shah, 2018 ). Students’ interest in having more control of their study time is also mentioned as one of the primary benefits of DE (Alahmari, 2017 ; Lei & Gupta, 2010 ). Regarding the reasons for not enrolling in DE courses, participants from the three countries mentioned difficulty contacting instructors and peers. Also, more than half of the students in Portugal and the UAE indicated they preferred face-to-face classes. Most students have spent their entire academic lives in traditional classes where interaction and immediate feedback from instructors and peers are more common. These concerns may be why students perceive they would lose a familiar type of interaction and have to engage with classroom participants in a new and different way (Carver & Kosloski Jr., 2015 ; Morris & Clark, 2018 ; Robinson & Hullinger, 2008 ; Summers, Waigandt, & Whittaker, 2005 ). It should be noted that the Portuguese and UAE students were enrolled in teacher education programs and are training to be face-to-face teachers. They may not understand the potential of DE format and are not preparing or expecting to use DE in their professional careers.

Difficulty being motivated was another reason chosen by the participants of the three countries to not enroll in DE courses. The lack of experience in this type of educational format may help explain student lack of confidence with their ability to study and stay on task. This response contrasts with the reasons reported for enrolling in DE courses such as controlling their study time. On one hand, participants like the prospect of having the ability to manage their own time. On the other hand, they are concerned they may lack the discipline they need to be successful.

Although the literature indicates that access to technology, isolation and expense are reasons frequently cited as preventing students from enrolling in DE courses (Lei & Gupta, 2010 ; Venter, 2003 ; Zuhairi et al., 2006 ), these reasons were selected by a very small percentage of the participants of this study. Access and affordability of technology has rapidly increased over the last decade which may help explain this inconsistency. Students may understand that DE courses are now less expensive than traditional university courses (Piletic, 2018 ) and they do not cite this as a reason for not enrolling. Relatively few students indicated they would feel isolated. Since this generation is in constant communication using technology (Diário de Notícias, 2011 ) they may not associate DE learning with isolation. However, it is interesting to note that there was a greater concern for interacting with instructors and peers than isolation.

The Ukrainian students are the most receptive to enrolling in DE courses. This is consistent with their positive perception of this type of learning. In addition, the previous experience of half of the participants may influence their interest as well as encourage their peers’ receptivity. UAE students do not have much experience and fewer than half are open to enrolling in DE courses. This may be due to their lack of experience and other concerns previously mentioned. Only one third of the Portuguese participants indicated their interest in enrolling in DE courses. This is in contrast with almost two thirds saying they had a favorable or very favorable attitude. The reasons for this inconsistency are not evident.

In terms of preparation needed to take DE courses, technical concerns were less of an issue for the participants of all three countries than skills and behaviors. Most participants’ answers focused on student skills including computer, English language and time management. Behaviors such as developing a study plan, having learning goals and objectives and being more motivated were also mentioned. The perceived need for better English language skills was expressed by about one third of the participants, none of whom have English as their native language. English speaking countries have been dominant in DE making English the most commonly used language in online learning (Sadykova & Dautermann, 2009 ). Regarding time management, half of the Ukrainian students expressed their need for improvement in contrast to approximately one third of the participants from the other countries. The difference among responses may be because the Ukrainian students are more self-reflective, or the others are more disciplined. Although both DE and face-to-face courses have deadlines for tasks and assessments, in the face-to-face courses, students meet in person with their instructors who may support and press them to do their work. Lack of in person contact may account for the participants feeling they need to improve these skills when taking DE courses (De Paepe et al., 2018 ). Students expressed concerns about lacking certain skills and having certain behaviors that would lead them to be reluctant to enroll in DE courses. The need for help and preparation are some of the concerns that participants reported. Perceived needs may account for the students’ apprehensions regarding taking DE courses. To promote this type of instruction, IHEs could address students’ concerns (Mahlangu, 2018 ).

Open schedule and blended learning courses were the two preferred formats stated by the participants. The reason that Open schedule is the most popular may be that it provides more freedom than other types of courses. Blended learning offers the familiar face-to-face instruction and some of the conveniences of DE which may be why participants are interested in this model.

Studies regarding the use of MOOCs in all three countries have been conducted indicating that researchers in these locations are aware that this course format is of potential interest to local students (Eppard & Reddy, 2017 ; Gallacher, 2014 ; Gonçalves, Chumbo, Torres, & Gonçalves, 2016 ; Sharov, Liapunova, & Sharova, 2019 ; Strutynska & Umryk, 2016 ). Ukrainian students selected MOOCs much more than students in the other countries. The reason for this may be that these students are more knowledgeable about MOOCs, because this type of course is usually at no cost and/or offered by prestigious IHEs (Cormier et al., 2010 ). However, this study did not ask why students were interested in MOOCs or other types of DE courses.

Limitations and future research

While this study offers useful information regarding undergraduate students’ perception and receptivity in taking DE courses, it has limited generalizability because of the size of the sample and the type of statistical analysis performed. Participants from two of the countries were enrolled in teacher education programs and were primarily female, thus future studies would benefit from including more students in diverse programs and a more equitable gender distribution.

Since many IHEs also offer programs for graduate students it would be useful to survey these students about their opinion and availability to enroll in DE courses. This would provide additional information for IHEs that are interested in developing DE programs.

There were some inconsistencies in the students’ responses such as Portuguese students’ interest in enrolling in DE courses not matching their favorable/ very favorable attitude towards DE. It would be helpful to conduct future research regarding this and other inconsistencies.

A study is currently being planned to collect data that will provide a larger and more diverse sample and include additional IHEs. This future research will potentially increase the available knowledge on how to provide DE for a greater number of students.

Conclusion and recommendations

Further development of DE courses and programs at IHEs in countries such as Portugal, UAE and Ukraine have good prospects. The students’ primary concerns regarding taking DE courses were similar among the three countries. These concerns included time management, motivation, and English language skills. However, this did not totally diminish participants interest in taking online courses especially for the Ukrainian students.

Based on this research, there are some obstacles that can be addressed to support the expansion of DE in the three countries that were studied and in other countries. The following recommendations may assist IHEs in promoting DE.

Recommendations for preparation within IHEs

IHEs can take proactive steps to prepare DE offerings, however, a one-size fit all model may not be appropriate for all countries and IHEs. Each institution needs to develop their own plan that meets the needs of their students and faculty. Data from this pilot study and the literature (Elbaum, McIntyre, & Smith, 2002 ; Hashim & Tasir, 2014 ; Hux et al., 2018 ) suggest that following steps might be taken:

Assess readiness to take DE courses through a survey and have students speak with counselors.

Provide pre-DE courses to build skills and behaviors based on students’ concerns.

Train instructors to develop and deliver DE courses that help to overcome obstacles such as motivation and time management.

Offer courses in a blended learning format to familiarize students with online learning which may provide a transitional model.

Recommendations for IHE outreach

This study shows that there is some student interest in enrolling in online courses. It is not sufficient for IHEs to make changes internally within their own institution. IHEs need to develop external strategies and actions that help advance the development of DE:

Promote DE in social media to target potential students and encourage them to take courses.

Urge government agencies to accredit DE courses and programs.

This pilot study provides some background information that may help IHEs to offer DE courses. Additional research about students’ preferences and needs regarding DE should be conducted. The sample size, IHEs included and participating countries could be expanded in order to gain a greater understanding.

Different cultural characteristics need to be taken into account in the development of online courses and programs. DE is being increasingly included by IHEs all around the world. To stay current, universities will need to find ways to offer DE to their current and prospective students.

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Patricia Fidalgo

Educational Technology Division, Lesley University, Cambridge, MA, USA

Joan Thormann

Philosophy Department, Oles Honchar Dnipro National University, Dnipropetrovs’ka oblast, Ukraine

Oleksandr Kulyk

Department of Curricular Studies and Educational Technology, University of Minho, Braga, Portugal

José Alberto Lencastre

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Patricia Fidalgo: design of the work, data collection, analysis, interpretation of data, and draft of the work. Joan Thormann: design of the work, analysis, interpretation of data, and draft of the work. Oleksandr Kulyk: data collection, interpretation of data, and draft of the work. José Alberto Lencastre: data collection. The author(s) read and approved the final manuscript.

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Online Survey Questions

1. If the students have taken any distance education courses previously and if yes, how many;

2. What are the students’ perceptions of distance education;

3. What are the reasons students would enroll in distance education courses;

4. What are the reasons students would not enroll in a distance education course;

5. What preparation do students feel they need before taking distance education courses;

6. What is the level of students’ interest towards enrolling in distance education courses;

7. What types of distance education would students be interested in trying;

8. What is the students’ age;

9. What is the students’ gender;

10. How confident do students feel using a computer and the Internet.

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Fidalgo, P., Thormann, J., Kulyk, O. et al. Students’ perceptions on distance education: A multinational study. Int J Educ Technol High Educ 17 , 18 (2020). https://doi.org/10.1186/s41239-020-00194-2

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DOI : https://doi.org/10.1186/s41239-020-00194-2

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Modular Learning: 8 Tips for Effective Online Teaching

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Due to the COVID-19 pandemic, many teachers in affected areas worldwide suddenly faced the task of getting their instructional materials ready to facilitate modular learning as a strategy for the sustained delivery of education to their students. I am one of these teachers, but the possibility of teaching the students exclusively online did not deter me because I have already worked on my instructional modules designed for online delivery.

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Besides, today’s trends follow a digital path as global technological innovations occur at light speed. Teachers have to keep up to be relevant.

Given the experience I gathered through the years, I would like to share eight tips on modular learning. These tips will somehow ease the teachers’ struggle for something they are not mentally and technically ready to face. The pandemic has changed the way teaching is carried out.

I start this discussion by defining modular learning, asynchronous versus asynchronous delivery of lessons, problems encountered, and solutions to those problems.

Earlier, I synthesized the lessons learned and the corresponding fixes in a learning model – the  Blended Website Learning Model  for more effective achievement of desired learning outcomes or most essential learning competencies (MELCs) for each course. You may refer to this model later on.

What is Modular Learning?

Modular learning, as the word connotes, uses learning modules that facilitate student learning by themselves. Modular learning is a form of distance learning that uses Self-Learning Modules (SLM) based on the most essential learning competencies (MELCS) developed by the teachers with the aid of curriculum developers.

The modules include sections on motivation and assessment that serve as teachers’ and students’ guides to achieve desired competencies. Feedback mechanisms aid teachers in monitoring student achievement and identify those who require follow-up interventions.

Self-paced learning modules can educate learners through carefully written guideposts that direct the learner on what action to take. The contents of the learning module follow a particular learning model that makes instruction effective. 

Upon our department chair’s advice, I used the 4H or  Experiential Learning Model  (ELM) based on the Experiential Learning Theory developed by educators for more than a century. I am not an education graduate. Hence, I have to study ELM carefully.

8 Tips to Achieve the Course Outcomes in Modular Learning

1. write your instructional tips to students online.

Teaching is a repetitive exercise. So what I did is to write articles about the lessons I teach and publish them online. I update those articles once in a while to ensure their relevance.

Although educational articles on almost anything under the sun can be found online, I find some tips lacking credibility and proper documentation. Thus, I embarked on my blogging platform (this website) to house my tips for students on specific topics I teach in the classroom.

I made sure that the tips I gave use the latest information or reliable references online for my students to refer to for further reading. Besides, many of the legitimate and well-referenced material are behind a paywall which my students do not have the means to purchase. Nevertheless, there are free, open-access articles that anyone can access with extra effort.

2. Compress and upload instructional materials on a fast-loading website

I uploaded all of my instructional modules in pdf on a fast-loading website I created at the beginning of the pandemic. I compress each module in the free pdf compressor provided by ilovepdf.com . Compressing the modules makes downloading into students’ smartphones easy. The small files also save them bandwidth, thus reduced data consumption in their internet subscription.

I studied website development for quite a while, anticipating the emphasis on modular learning in the future. I started with Webnode sometime in 2012. Webnode uses drag-and-drop technology, which works for a beginning website developer like me. I even purchased a domain name for my free account on that website.

However, after several years of use, I found the technology lacks the flexibility I need. I want to maintain an independent website without the costly upgrades when the traffic exceeds my subscription. Hence, I shifted to an independently hosted WordPress.org Content Management System (CMS) platform. But not before I practiced in the WordPress.com website.

WordPress as a Tool in Modular Learning

I used WordPress to develop the simple but fast-loading website that students can easily load on their cellphones. It scores an almost perfect speed of 99% in both mobile and desktop (Figure 1).

I used Neve, a WordPress theme with no frills nor bloat software, to delay loading. All instructional modules are instantly available to students after entering the password I gave them.

The instructional material website simply works. No frills, no fuss.

Anyone can easily create a WordPress website in minutes. Just have your email and password ready to create an account in WordPress.com for free. You can create your website later, like what I did when I first started. As you practice using the free WordPress website, you will get to be familiar with how websites work.

You may listen to the simple instruction in the video I give below. Knowing how to create your website will give you more opportunities to become digitally savvy. Modular learning will be much more easily as you gain experience and expertise.

3. Use a Learning Management System to assess student performance

I had a limited two-day training on the use of Moodle before the COVID-19 pandemic began. By a stroke of luck, I could use the LMS as a modular learning tool in the middle of the semester when the government declared a nationwide Enhanced Community Quarantine (ECQ) to stem the brewing spread of the dreaded virus.

Using a Learning Management System (LMS) such as the free, open-source Modular Object-Oriented Dynamic Learning Environment (MOODLE) can help a lot in designing quizzes and periodic examinations. The once time-consuming task of checking the students’ quizzes and periodic examinations is done real time.

Using a Learning Management System (LMS) such as the free, open-source Modular Object-Oriented Dynamic Learning Environment (Moodle™) can help a lot in designing quizzes and periodic examinations. The once time-consuming task of checking the students’ quizzes and periodic examinations is done real time .

Students get their quiz or exam results in a matter of seconds. Once they submit their quiz, long exam, or midterm or final exam, they get the results right away.

I give students two chances of taking the quiz or major examination, mindful of the glitch that students experience while taking the assessment. Last semester, the internet connection of some students break while taking the quiz. Hence, it is good practice to give them another chance. Further, giving the students another chance to take the quiz provides them an opportunity to correct their answers and establish mastery of the subject matter.

I pushed my knowledge of Moodle further, not by just being a user, but by studying the process of its installation, mainly as part of my hobby and partly as a challenge to create a website to house the LMS myself. Having my own Moodle site gives me the independence and freedom to innovate.

I realized I can create an independent Moodle site on my GoDaddy server. In short, I figured that the only thing I need to put Moodle to work was to register a unique domain name. I hosted Moodle in the same platform where my blogging site, Simplyeducate.me, is being hosted. The LMS had virtually a free ride as a sub-domain.

I don’t mind spending a little more for my convenience. It’s an investment to save time and effort. In addition, I learn and enjoy the new functionality as I implement the system.

Moodle takes time to load; it’s slow

Although Moodle was designed to house complete learning modules for learners, my students have trouble accessing it. I had the impression that Moodle, being an open source project, had too many functionalities that made it heavy to load. Also, many of my students use cellphones in accessing the lessons online.

After spending considerable time looking for answers online and tweaking the Moodle website, I gave up, even though I successfully enhanced the speed of the LMS. I cannot make the Moodle site load faster without adding more investment in Random Access Memory (RAM) capacities and having it work on a Solid State Drive (SSD). I have a limited budget for this expense.

But Moodle is a good performance assessment site that enhances modular learning

I found the assessment function of Moodle very useful, so I kept it as an assessment site that students will log on once they are ready. Another advantage is that the LMS enables me to prepare my quizzes easily and checks the quizzes and periodic exams automatically. I just record the points my students get in Excel to give the corresponding percentages on the different assessment criteria.

That functionality surely saved me time in checking the students’ performance. It’s even better than administering questions in a face-to-face learning session. It worked well for me serving as an assessment site. I just set the period wherein the quiz will be available to students.

Also, the system can shuffle the questions and the answers in the exam. Each student has a different set of questions and answers, ensuring a unique performance record.

4. Conduct regular short synchronous meetings to remind and update the students

I conduct regular, synchronous meetings with my students to give them a feel of classroom ambiance; it simulates a face-to-face interaction. While most of my students can attend the meeting via Zoom, a video teleconferencing software program, several of them could not connect to the internet for valid reasons.

Among the valid reasons I have learned from my students for their inability to connect during synchronous meetings are the following:

• poor internet connection,
• exhausted data allocation,
• attending to emergencies, and

Recording of synchronous meetings

Recognizing these student difficulties, I always record the proceedings of the synchronous meetings. I upload the zoom video in MP4 format in mediafire.com , the cloud service I have been using for easy access. Then I provide a link to the fast website I created for the instructional materials.

Once the students have the opportunity to go online after resolving their issues during synchronous meetings, they are able to access the proceedings of the meeting. The poor internet connection can be remedied by going online during non-peak hours. Midnight until the early hours of the morning appears to have fewer users online.

The recorded videos do not last more than an hour. Making them short saves bandwidth as well as limits file size to a manageable size that students can download with ease.

5. Follow-up students through Messenger

Almost everyone has an account on Facebook together with Messenger nowadays. I tell my students to communicate with me through Messenger if there are concerns that they need me to know.

During Zoom sessions, some students could not easily express their burdens while others listen. Hence, they can send private messages to prevent getting embarrassed for their queries.

Since most of my work is done online, I can readily see the notifications that I have messages from my students. I consider the communication part of my consultation time. It also presents an opportunity to empathize with the students on their unique concerns.

So far, Messenger has become an effective tool to connect with students and give them support, especially in crucial times. Also, it is easy to find them online if I need to issue additional instructions related to the subjects I teach.

6. Use an Ishikawa diagram to contextualize the Most Essential Learning Outcomes

Given the considerable time that students have to devote to keeping up with their subjects, I design my modules as briefly as I can muster without sacrificing the essential outcomes of the modules. I present these outcomes in an Ishikawa or fishbone diagram at the beginning of the semester.

Figure 2 presents an Ishikawa diagram showing the learning outcomes I prepared for my students. The diagram visualizes the expected competencies that students could gain during the semester. Guided by the outline, they will see their pace in context while performing the tasks at hand. Seeing the goal serves as motivation for them to go on.

The fishbone diagram motivates the students concerning the overall outcome of the things that they do each learning session. One learning activity progresses to another one that leads towards the goal of learning.

Hence, the process of modular learning becomes meaningful to students. Incremental, modular learning transpires.

7. Give generous time for achievement of MELCs

I give a generous time of at least two weeks for students to achieve the expected learning outcomes. Giving them leeway to perform and reflect on their assigned tasks facilitates retention and helps them perform at their very best.

Writing many tasks without enough time to ponder or reflect on their work leads to a half-baked performance. Thus, less than stellar work dampens the motivation to do things in the best way they can.

Seeing some prescribed MELCs as part of modular learning online, I get the impression that they’re more applicable to face-to-face interactions. Chances are, the students become overstressed with tasks to do without the focused guidance of their teachers, making online learning a mechanical activity fixated on compliance.

8. Use a Feedback table

To keep track of student performance and encourage them to perform within the time frame, I prepared a feedback table to show what stage they were already in. Whenever I meet the students during synchronous meetings, I present the feedback table to the class and ask them if I have recorded their submissions correctly.

Some of my students would tell me they have submitted, but I could not verify their submissions. Perhaps failing to upload is due to a poor internet connection. Given the real-time feedback I get via Messenger, they try again until they have successfully uploaded. I confirm that I have received their outputs. Thus, the student’s anxiety because of failure to upload the required submissions is eliminated or minimized.

The feedback table finds support in Dr. Tali Sharot’s book on changing people’s behavior. It emphasizes the importance of feedback to change people’s behavior.

I invite you to listen to the highly motivating speech of Dr. Sharot in TED Talk that can change not only your student’s behavior towards the assigned tasks but also your ingrained habits. The lecture emphasizes the importance of feedback.

The feedback table instantly tells me potential problems and takes corrective measures before they get worse. Students exert more effort to keep up with their classmates once they notice that some of their classmates have already accomplished the modules. Modular learning becomes more effective with a monitoring system like this.

Figure 3 provides an example of a feedback table where you can quickly troubleshoot submission problems and ensure that no student is left behind.

Modular Learning is here to Stay

Whether the pandemic will last for quite a time, online modular learning will become the norm rather than an exception. The educational system has already shifted to Education 4, in tune with  Industry 4.0 , where interconnectivity through the Internet of Things (IoT), lies at its core.

Despite the setbacks experienced by teachers on the  effects of modular learning , we must be progressive in our thinking. The challenges are not without answers as technology progresses. Most students can access a laptop, or virtually everyone can access a cell phone, to download educational materials like the ones I make available on my IM website.

Although some of my students are hundreds of miles away, or even on an island, they can still access my instructional modules using their cell phones. I make online learning easy for them by applying the tips I previously gave—make the website load faster by compressing images and videos and make my instructional modules simpler to follow. I focus on a few but crucial and  most essential  learning outcomes. 

Stop being bookish. This time it’s online learning, not face-to-face classes where you cram in everything you want to the detriment of your students.

A 30-minute or less synchronous meeting is more than enough to brief your students about the module, the expected learning outcomes, and ask a few questions to get their feedback on the modules and constraints on their performance.

Advanced countries are already eyeing the many uses of  machine learning , and interest is growing in getting a degree in this field. Are our students ready to become part of this technological development?

In the information age, teachers are no longer what they used to be. We are now facilitators and innovators of learning through online modular learning as the information age changed the way people gain information.

We must undo the belief that we are the authorities of knowledge. Digital technology has shaped how we live, learn, and navigate this increasingly automated world.

Kudos to all teachers! Let’s rock the world of online modular learning.

© P. A. Regoniel 22 June 2021

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About the author, patrick regoniel.

Dr. Regoniel, a faculty member of the graduate school, served as consultant to various environmental research and development projects covering issues and concerns on climate change, coral reef resources and management, economic valuation of environmental and natural resources, mining, and waste management and pollution. He has extensive experience on applied statistics, systems modelling and analysis, an avid practitioner of LaTeX, and a multidisciplinary web developer. He leverages pioneering AI-powered content creation tools to produce unique and comprehensive articles in this website.

Thank you for your comment. Teaching in the new normal requires constant innovation and a change in mindset.

Thank you so much for sharing this! The different modes of learning in this new normal are somehow confusing, but this really helped. I also appreciate the tips you gave on how to teach effectively in modular learning!

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Lived Experiences of Senior High School Learners Under the Online Learning Mode at Goshen School of Technology and Humanities

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Covid-19 impacted all sectors of the country particularly the education sector. Schools have no choice but to shut their operations from brick and mortar to flexible learning mode. This study intends to determine the lived experiences, the issues they have encountered, the support needed, and the gaps and challenges they are facing. This study utilized interviews, observations and used Collaizi's method in the data processing and analysis (cited in Sander, 2003, and Speziale & Carpenter, 2007). The themes that came out from the constructs of the interviewees were Learners under online learning mode encountered internet connectivity issues, inadequate learning tools for online, psychological issues, and physical health issues. The output of this paper is the proposed model for learners under online the learning.

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