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Is It True They Negatively Engage? Mixed Method Research of Student Engagement in EFL Online Classrooms
Fahad Alzahrani ®
University of Tabuk, Tabuk, Saudi Arabia
ABSTRACT
Background. A leading concern in teaching and learning is how to increase the degree of student engagement in learning. Within the virtual educational environment, student engagement is a real issue facing instructors and teachers. Students in online classrooms are not able to engage in the same manner as in face-to-face settings.
Purpose. This study aims to explore the impact and reception of online education on student engagement in English as a foreign language (EFL) classroom.
Method. This study adopts a mixed-method approach, in order to understand student engagement online. Longitudinal self-report surveys (SRS) filled out by 127 undergraduate students after each class session throughout a four-week period were used to assess their engagement in online language classrooms. Focus-group interview transcriptions were used to triangulate the data and provide further information about student engagement in terms of gender difference, engagement growth over time, and engagement fostering or hindrance factors in virtual learning classrooms.
Results. Analysis showed that students were generally engaged during the weeks with some variances. Cognitive-social learning engagement showed dynamics among students in virtual language classrooms. Factors such as place of engagement and students' choice of device used to access the virtual session were found to influence student engagement in online classroom learning. Male and female students generally showed similar learning engagement in the virtual classes with disparities occurring over the study period.
Conclusion. The study results will be beneficial for researchers, instructors, and policymakers who are interested in understanding student engagement and who seek to improve the teaching experience.
KEYWORDS
student engagement, negative engagement, EFL, remote learning, online education
https://doi.org/10.17323/jle.2023.13736
Citation: Alzahrani F. (2023). Is It true they negatively engage? Mixed method
INTRODUCTION
research of student engagement in EFL online classrooms. Journal of Language and Education, 9(1), 41-58. https://doi. org/10.17323/jle.2023.13736
Correspondence:
Fahad Alzahrani, fahad_alzahrani7@hotmail.com
Received: January 15, 2022 Accepted: Mach 22, 2023 Published: March 31, 2023
There is a strong consensus that engagement is essential for individual learning. Many online language teaching instructors, however, complain that student enthusiasm and engagement in virtual classrooms are not as lively as in traditional classrooms. Students who typically engage in the traditional mode face distinctive challenges specific to e-learning. The flexibility and convenience offered in online learning are acknowledged, but students may hold negative attitudes and resistance to successful learning in virtual environments. As Oraif and Elyas (2021) claim, the language learning expe-
rience could be challenging for students and ineffectual in meeting their needs. Consequently, they might not engage with the course. This has raised a leading concern related to keeping students as motivated and engaged in online classrooms as they are in the traditional setting (Bolliger & Martin, 2018).
Online student engagement differs from engagement in face-to-face learning in numerous ways. O'Shea et al. (2015) asserted, "When shifting to online contexts, engagement takes on different manifestations, due to the lack of face-to-face contact and the ways in which teaching and learning are mediated through tech-
nology" (p. 43). As a result, without this critical component in place, students in the online environments report a lack of interest, and thus, a lower quality of work and less overall satisfaction (Martin, 2019).
Defining Engagement
Engagement is a psychological construct that is considered "a proverbial new kid on the block" (Reschly & Christenson, 2012, p.14), especially when compared with motivation, which has received a high level of interest (Boo et al., 2015). The vast body of research in motivation is claimed to have "stolen the show and diverted attention away from engagement" (Mercer & Dornyei, 2020, p. 5). Mercer and Dornyei contended that "motivation is undoubtedly necessary for 'preparing the deal', but engagement is indispensable for sealing the deal" (p.6).
The term "learner engagement" has been construed differently. One key feature of engagement that has consistently reiterated across its conceptualizations is 'action'. The action concept of engagement resonates with definitions such as that of Skinner et al. (2009) who viewed engagement as "energized, directed, and sustained actions" (p. 225) and that of Reeve who described, "the extent of a students' active involvement in a learning activity" (2012, p.150). In the arena of second language (L2) learning, engagement was construed by Ellis (2010) to describe learner responses to corrective feedback.
The multifaceted nature of engagement has been agreed upon. As Fredricks et al. (2004) proposed, the multidimensional construct of engagement comprises three main components: behavioral, cognitive, and emotional. The behavioral dimension involves the active participation of students. The cognitive dimension comprises a psychological investment by trying to understand complex ideas, self-regulation, exerting effort for solving challenging tasks and using deep learning. In classroom settings, the emotional dimension is "often manifested in learner's personal affective reactions in the target language-related activities or tasks" (Zhou et al., 2021, p. 88). An additional aspect of engagement was suggested as one main aspect of engagement. This aspect underlines the social interaction with peers and teachers, collaborative learning, sharing ideas and maintaining the relationships in the class. Importantly, these four dimensions are interconnected, despite the possibility of becoming positively engaged in one dimension, while disengaged or negatively engaged along another dimension.
In the realm of online education, and since many students tend not to use their web cameras (Castelli & Sarvary, 2020), many professors and instructors seem to believe that students are actually faking their engagement. Fake engagement in this manner is "reflected in behaviors that are made consciously or unconsciously, by learners to achieve an outside appearance of being attentive and on-task; however,
in reality, their internal states, are not congruent and, for diverse motives, they may be complying or just merely pretending compliance" (Mercer et al., 2021, p. 145). To put it differently, fake engagement occurs when there is behavioral engagement without being cognitively and emotionally engaged.
Related Works
Increased attention to the study of learner/student engagement is reflected in a recent large and growing body of research. A handbook-length work, such as Christenson et al. (2012) or richly edited books, such as Mercer & Dornyei (2020), Hiver et al. (2020), and Quaye et al. (2019) have been published on this area. This underlines the issue that understanding how to engage learners remains a pressing concern.
In the language classroom, several studies have made notable contributions related to the domain of learner engagement (see Oga-Baldwin, 2019; Philip & Duchesna, 2016, for review). In L2 classrooms, researchers such as Svalberg (2009, 2018) was one of the pioneers who attempted to understand the role of engagement in language acquisition and learning. He examined engagement from a very narrow-angle, namely, engagement with language (EWL), a model through which learners can develop language awareness.
Similar to the situation in traditional classrooms, one of the most prominent questions involves keeping students motivated and engaged in the online setting (Bolliger & Martin, 2018). Thus, numerous studies have targeted student engagement in the EFL virtual classroom (e.g., Bolliger & Martin, 2018; Almossa, 2021; Kim, 2021; Martin, 2019; Oraif & Elyas, 2021; O'Shea et al., 2015; Soffer & Cohen, 2019; Yun-dayani et al., 2021). The results of these studies suggest that engagement in a non-face-to-face learning environment is impacted. Therefore, several strategies can be utilized in the online learning environment to enhance student engagement (Bolliger & Martin, 2018).
Studies such as Almossa (2021), Oraif and Elyas (2021), Yun-dayani et al. (2021), and Khlaif et al. (2021) investigated student engagement during the shift to emergency remote teaching. Numerous contexts have been targeted in exploring student engagement. In the Saudi context, a few contributions, such as Al-Bogami & Elyas (2020), Almossa (2021), and Oraif & Elyas (2021) were made. Almossa (2021) investigated the experiences and opinions of college students shared on their Twitter accounts about their engagement with online learning and assessment. By analyzing tweet posts, the findings suggested that cognitive, behavioral, and affective engagement with learning have been considerably impacted by online assessment. According to Almossa, this was attributed to several challenges that arose due to the
sudden shift in the learning mode, such as communication, fairness, technical and assessment issues.
Among the few studies investigating online student engagement in the Saudi context, there is the study by Oraif & Elyas (2021) which explores learners' level of engagement in 'My School' (Madrasati). This is a school platform in Saudi Arabia, where the results uncover a high level of engagement among EFL learners. Applied exclusively to female learners, Al-Bogami & Elyas (2020) also investigated the effect of handheld devices in EFL classrooms on student engagement. Through a mixed-method approach, they studied the use of the iPad and its apps for EFL engagement and learning among 20 middle school students. The findings suggest that the apps bolster engagement level and learning compared to traditional teaching paradigms. The focus in both studies - Bogami & Elyas (2020) and Oraif & Elyas (2021) - was on young female learners (i.e., middle school and high school age students). Some studies focused on gender differences and online EFL classroom engagement. These studies have revealed that there are no significant impacts on gender variation and engagement in EFL virtual learning environments (Almusharraf & Almusharraf, 2021; Devrim & Irem, 2020; Benhadj, 2021). There is a persisting stereotype that girls are better at language learning than boys. Is this stereotypic belief still in place is thus one of the aims of the present study: to further investigate gender differences and engagement for college level students learning English in online classrooms.
In terms of the assessment of student engagement, Zhou et al. (2021, p. 80) confirmed that "[t]o date there is no single instrument that is accepted for use across contexts - just as there is none that is accepted as a field-specific measure of engagement." Yet, different approaches were followed in the sciences of education and learning for measuring student engagement. Examples of these measurement methods include self-reported surveys and questionnaires (e.g., Oraif & Elyas, 2021), direct observations, and interviews (e.g., Yundayani et al., 2021). The most frequent methods used for measuring student engagement are self-reported surveys (SRS) and questionnaires, as used in the current study. In SRS and questionnaires, students are "presented with items describing different facets of engagement and are directed to choose the response from a range of possibilities that best describes them" (Zhou et al., 2021, p. 80).
Other approaches employed in previous literature for the purpose of assessing student engagement include traditional methods, such as self-reports, teacher ratings of students, observations of students' performances, and measurement of bio-signals. Alternatively, students' reflections on their experiences and opinions on social media platforms such as Twitter, which are likely to mirror their engagement explicitly or implicitly with online learning, have given rise to some attention (for example, Almossa, 2021). A new strategy which uses learners' facial expressions to assess the level
of engagement in non-face-to-face learning situations was also proposed by Kim (2021). For further measures, Zhou et al. (2021) explored the past, present, and future of how learner engagement can be assessed in the L2 classroom.
That being said, this study casts light on the engagement of college level students in the online EFL classroom in the Saudi context. Specifically, this study aims to explore the effect of online teaching and virtual reality on language classroom engagement of college students during the pandemic era. This study was motivated by one of the key findings of Alzahrani et al. (2022) study, which recommended that the reasons behind students not engaging positively in EFL online classrooms be explored.
Research Questions
The study aims to gain comprehensive answers and insights to the following research questions (RQ):
(1) How do Saudi students evaluate their engagement in an online classroom?
(2) Which aspect of engagement is reported by Saudi students to be highest in the online classroom, and which is the lowest?
(3) Is there a gender difference in student engagement within these online classrooms?
(4) Does student engagement grow over time in online classrooms?
(5) What factors do Saudi students report to be enhancing or hindering their engagement in online classrooms?
METHOD
Background
This study was conducted in a Saudi public university's compulsory junior-year writing course. The data was drawn from an eight-week summer term, from May to July 2021. The course was offered in two sections: one section was for female students and taught by a female instructor, whereas the other section was for male students and taught by the researcher, as a male instructor. The female instructor's role was only to collect the data and provide it to the researcher; she was not involved as a researcher in this study. The time of each of the sessions was 3 hours, and twice a week. This course was offered fully online by the Language and Translation Department, for both computer science major students and information technology major students.
In order to carry out this research, a completely online course was designed in which course content as well as
all online materials and sources were developed by the researcher who taught the male section. Both sections shared the same course content, assessment structure, and tools. After setting up the course on Blackboard, the university's official learning management system (LMS), a course copy was exported and shared with the female instructor, in order to maintain the same quality of instruction. All course sessions were synchronously taught. Typical pedagogical activities in almost all sessions included instructor presentations, group discussions, question sessions with instructor feedback, quizzes, and exams, YouTube video clips, assignment tutorials, Collaborate Ultra Breakout group, and reference to the course textbook.
Study Sample
Convenience sampling was used in the study. The students were all of the Saudi nationality whose second language is English. They had different levels of English proficiency, but were mostly intermediate learners. This was determined by the successful completion of the English language program, offered by the university as a requirement, qualifying students for B 1 (intermediate English) in the Common European Framework of Reference (CEFR). The students' native language was Arabic. Total enrollment at the time of the research (i.e., summer 2021) was 127 students (both sections).
Data Collection and Procedures
This was a mixed-method study which utilized both quantitative and qualitative approaches. The mixed methods used in this research are primarily for a triangulation strategy, which seeks corroboration, convergence, and correspondence of results from different methods (Greene et al., 1989). The following three instruments were used:
Self-Report Surveys (SRS)
For the quantitative analysis, a longitudinal survey, aka self-report survey (SRS), was used. A sample of items is in Appendix (A). A longitudinal survey is defined as "one that collects data from the same sample elements on multiple occasions over time" (Lynn, 2009, p. 1). In the literature, this self-report instrument has been used commonly and shown good reliability (e.g., Fuller et al. (2018); Hiver et al. (2020) and Oga-Bakdwin & Fryer (2021).
The SRS was distributed over the first four weeks of the term amongst students who were enrolled in the course. The SRS consisted of a total of 34 five-point Likert scale statements divided into sections according to the four sub-scales (i.e., behavioral, cognitive, emotional, and social), as well as four questions at the very beginning for eliciting demographic information. Responses ranged from 1 (referring to "Very untrue of me") to 5 ("Very true of me"). Items of the SRS were adapted from validated instruments used in two re-
cent research studies: Hiver et al. (2020) and Oga-Bakdwin & Fryer (2021).
The SRS was created online using Google forms in which all students could complete the questionnaire online. Students were asked to take the survey after each class session throughout the first 4 weeks (i.e., eight class sessions in total). This period was selected in the aims of examining this phenomenon in no less than half of the semester. In addition, as suggested by Lynn (2009), "the longer the period of time over which a longitudinal survey collects data, the richer and more valuable the data are likely to be." (p. 14). The SRS was developed bilingually (in English and Arabic). Finally, this instrument was valid and reliable as shown by Cronbach's alpha coefficient testing for reliability as internal consistency (Cronbach, 1951) (score= .837 which is high reliability (>.7)).
Focus Group Interviews
Students from both sections were invited immediately after the last session of the term to participate in a focus group. The purpose of these exploratory focused, in-depth group interviews was to further understand and triangulate the quality and character of learner engagement, in particular, their perspectives on why and when they were engaged or not.
Two interviews were conducted in week 8. One interview was dedicated to male students, and another was exclusive to female students. This was to encourage the participants to speak freely and comfortably. The interviews were semi-structured in which open-ended questions were formulated and used. Each interview lasted about 20 minutes in length. Interview questions were in the students' native language of Arabic, and the students were encouraged to answer in Arabic or English, whichever was convenient for them, in order to ensure full understanding and expression. Generally, students preferred to use English to answer interview questions.
Interview questions were piloted on two students with similar characteristics, in order to check for meaning, obtain feedback on how interview questions come across, help revise the question structures, decide whether more need to be included, or some deleted, and "to learn about [my] effectiveness as a moderator—do [I] need to modify the amount of involvement [I am] having in the interview?" (Breen, 2006, p. 471).
Both interviews were audio-recorded. In order to minimize interviewer effects, students were told that their responses will not have any effect on their course grades. As an instructor and a researcher, my own point of view on the topic or my relation to the students did not influence my way of moderating the interviews. In fact, the female students were interviewed by me and the male students were interviewed
by the other instructor. As recommended by Breen (2006), "it is always important to demonstrate reflexivity as an interviewer" (p. 473). Interview transcriptions were later looked at for theme extraction in light of the research questions.
Data Analysis
For the quantitative data, descriptive statistics were employed using SPSS® (v. 24), in order to analyze students' responses to the SRS items in terms of frequency, mean, percentage, and standard deviation to assess student engagement level during online learning. T-test, one-way ANOVA, repeated measures ANOVA, and correlation analyses were used in the analysis of the data as well. Further analysis was carried out, in order to determine different sources and post-hoc multiple comparisons were utilized using the Least Significant Difference (LSD) test.
In order to identify and organize shared experiential themes in qualitative data, thematic analysis, as proposed by Braun & Clarke (2006), was used. This methodology was used to interpret data collected from the semi-structured interviews. Interview data was analyzed and reported using six stages for developing thematic analysis: (1) establishing familiarity with the data, (2) generating initial codes, (3) searching for themes, (4) reviewing themes, (5) defining and naming themes, and (6) producing the report.
Ethical Considerations
A high standard of ethical considerations was followed throughout the process of conducting this research. All data was generated with students' explicit permission. No participant was coerced into participating in the study. Every student could withdraw from the study at any point in time without repercussions.
According to Cohen et al. (2007), since interviews might be considered an intrusion into the personal lives of partici-
pants, especially with regard to the sensitivity of questions, ethical considerations were maintained at all stages of the interview process. Further oral consent was obtained at the beginning of the interview session, and each participant was informed that the session was being audio/video recorded. The follow-up interviews were conducted with the participants one week after the course finished, in order to reduce the possibility that students would be unduly influenced. In addition, for purposes of anonymity, pseudonyms were used to identify participants in all research processes, and any identifying markers were removed to protect students' identities.
RESULTS
This section commences with the quantitative statistical results and presents a detailed exposition of the observed data.
Results of SRS
Participants in the SRS
A total of 127 students (72 females and 55 males) took part in the surveys of the current study. No less than 50% of students attending each class session participated in the SRS. In fact, in the end-of-class surveys their participation reached 95% in many of the class sessions. Table 1 presents student frequency of participation in filling out the survey over the course of four weeks. No student's responses were excluded from the analysis.
"In-home" engagement versus "out-of-home" engagement were possible factors that might have affected student online engagement. The majority of the students reported they attended the online sessions from home (92.5%). Only 4.67% accessed sessions in their cars during class time or
Table 1
Student Record of Participation in In-Class Surveys Based on Class Sessions
Session# Male students (/55) Female students (/72) Total
1 40 (91%) 62 (95%) 102
2 50 (91%) 62 (95%) 112
3 38 (73%) 43 (66%) 81
4 42 (93%) 58 (90%) 100
5 41 (85%) 46 (70%) 87
6 43 (86%) 42 (60%) 85
7 41 (91%) 38 (61%) 79
8 41(82%) 34 (50%) 75
721
from public places such as coffee shops, hospitals, or restaurants. On the other hand, in all four weeks, a high percentage of students (49.1%) used personal computers (i.e., desktop or laptop) to access the virtual sessions. 24.7% of them used cell phones, while 7.9% used tablets to access the virtual sessions. The following findings are organized according to the guiding research questions.
Analysis of SRS
RQ1 which asked: How do students evaluate their engagement in online classrooms? was answered through the production of means, and standard deviations for the survey statements. As displayed in Table 2, students showed a generally high classroom engagement. That is, engagement in writing classes among Saudi college learners, when online learning was adopted, was generally at a high level of 'True of me' (mean=3.88, SD=0.44). Here, students had a similar engagement in general in all four weeks, indicating "True of me" with a mean score of 3.84 (SD=0.37) in week one, 3.89 (SD=0.45) in week two, 3.89 (SD=0.46) in week 3, and 3.91 (SD=0.51) in week four.
Table 2
Means and Standard Deviations for SRS Data
Weeks Mean SD
One 3.84 0.37
Two 3.89 0.45
classes (mean=3.43; SD=0.42). Nevertheless, this indicates a "True of me" (see Table 3). A closer look into the data showed that although student cognitive engagement was ranked the highest in week 1 (Mean=4.33, SD=0.43), it declined to the lowest rate in weeks two, three, and four (Mean=3.45, 3.48 and 3.49, respectively). However, the behavioral type of engagement was the highest across weeks 2, 3, and 4 (Mean=4.14, 4.17, and 4.18, respectively). In fact, all four student engagement aspects ranked similarly across weeks 2, 3, and 4.
To answer RQ3: Is there a gender difference in students' engagement?, analysis of an independent sample t-test (see Tables 4, 5, 6, and 7) showed that, in week 1, there was no significant difference between male and female students regarding engagement in online classroom as a whole (P>.05). However, significant differences were found between male and female students in the behavioral type of engagement (P<.05). The difference was in favor of females (mean=4.26) as opposed to (mean=4.02) for males (Table 4). Put simply, female participants showed higher engagement in behavioral activities such as effort, participation, initiative-taking, and persistence. Moreover, in week 1, significant differences were found between male and female students in other types of engagement such as cognitive and social engagements (P<.05). This time, male students were cognitively and socially more engaged than their female counterparts (mean=3.43, 3.87, respectively for male students) (mean=3.27, 3.39, respectively for female students).
Three 3.89 0.46
Four 3.91 0.51
All 4 weeks 3.88 0.44
To answer RQ2, it was found that, generally speaking, student behavioral engagement was rated the highest in all four weeks indicating "True of me" with a mean score of 4.16 (SD=0.63). This was followed by emotional engagement (mean=3.98; SD=0.48) and then social engagement (mean=3.74; SD=0.88). SRS data also showed that students were cognitively the least engaged during the eight virtua-
In week 2, as shown in Tables 6, no significant difference was found between males and females in regard to their engagement in the online classroom as a whole (P>.05). However, significant differences were found between male and female students in emotional engagement (P<.05). The difference was in favor of females (mean=4.08) in contrast to (mean=3.90) for males. In week 3, significant differences were found between male and female students in cognitive engagement (P<.05). The difference was in favor of females (Mean=3.55) in contrast to (3.41) for males (see Table 7). However, in week 4, no significant differences were found
Table 3
Student Engagement in Online Classroom Based on Engagement Domains
Weeks Week 1 Week 2 Week 3 Week 4 Total
Subscales Mean D S Rank Mean D S Rank Mean D S Rank Mean D S Rank Mean D S Rank
Behavioral 4.16 0.56 2 4.14 0.63 1 4.17 0.64 1 4.18 0.70 1 4.16 0.63 1
Cognitive 4.33 0.43 1 3.45 0.40 4 3.48 0.41 4 3.49 0.45 4 3.43 0.42 4
Emotional 3.97 0.39 3 4.00 0.49 2 3.97 0.51 2 3.98 0.56 2 3.98 0.48 2
Social 3.59 0.92 4 3.82 0.85 3 3.73 0.86 3 3.84 0.86 3 3.74 0.88 3
Table 4
Independent Sample T-Test Results (Week 1)
Students N Mean SD t P value
Male 90 3.84 0.38
General 0.093 .926 ns
Female 124 3.83 0.36
Male 90 4.02 0.63
Behavioral 3.054 .003**
Female 124 4.26 0.48
Male 90 3.43 0.38
Cognitive 2.272 .006**
Female 124 3.27 0.44
Male 90 3.95 0.38
Emotional 0.647 .518 ns
Female 124 3.98 0.40
Male 90 3.87 0.87
Social 3.918 .000**
Female 124 3.39 0.91
Note: ** significant at .01 level, * significant at .05 level, ns= not significant
Table 5
Independent Sample T-Test Results (Week 2)
Students N Mean SD t P value
Male 80 3.82 0.46
General 1.804 .073 ns
Female 101 3.95 0.45
Male 80 4.10 0.62
Behavioral 0.766 .445 ns
Female 101 4.17 0.63
Male 80 3.41 0.41
Cognitive 1.248 .214 ns
Female 101 3.48 0.39
Male 80 3.90 0.50
Emotional 2.459 .015*
Female 101 4.08 0.48
Male 80 3.75 0.84
Social 1.016 .311 ns
Female 101 3.87 0.85
Note: * significant at .05 level, ns= not significant
between male and female students regarding engagement in the online classroom as a whole (P>.05). This indicates that both male and female participants showed similar engagement in the online classroom.
ANOVA was employed to examine any significant difference between students regarding engagement in online classrooms, i.e. in answers to RQ4: Does student engagement grow over time? As shown in Table 8, analysis did not report a significant F statistic effect regarding engagement in online classrooms as a whole and regarding behavioral and emotional engagement. Nevertheless, there was a significant F statistic effect reported in regard to the cognitive engagement type and the social engagement (P<.05) indicating significant differences in engagement across all weeks.
As evident in Table 9, the post-hoc test revealed that significant differences in cognitive engagement occurred between
week 1, on the one hand, versus weeks 2, 3, and 4, on the other hand. The difference trend was in favor of cognitive engagement in week 2, week 3 and week 4 due to the highest mean (3.45, 3.48, 3.49) respectively. There is a steady increase in cognitive engagement from week to week, reaching the highest average in week 4. The conclusion can be drawn that cognitive engagement grows over time. Furthermore, results analysis (Table 9) reported significant differences in social engagement occurring between week 1, versus weeks 2 and 4. The difference trend was in favor of social engagement in week 2 and week 4 due to the highest mean (3.82, 3.84), respectively. This concludes that there is a steady increase in cognitive engagement from week to week, reaching the highest average in week 4. Students' social engagement does grow over time as well.
Another layer of inferential analysis was performed, in order to identify any significant differences that may exist be-
Table 6
Independent Sample T-Test Results (Week 3)
Students N Mean SD t P value
Male 84 3.82 0.45
General 1.786 .076 ns
Female 88 3.95 0.45
Male 84 4.11 0.64
Behavioral 1.379 .170 ns
Female 88 4.24 0.64
Male 84 3.41 0.39
Cognitive 2.236 .027*
Female 88 3.55 0.42
Male 84 3.91 0.51
Emotional 1.435 .153 ns
Female 88 4.02 0.49
Male 84 3.67 0.88
Social 0.860 .391 ns
Female 88 3.78 0.85
N.B. ^significant at .05 level, ns= not significant Table 7
Independent Sample T-Test Results (Week 4)
Group N Mean SD t P value
Male 82 3.90 0.49
General 0.252 .801 ns
Female 72 3.92 0.52
Male 82 4.22 0.69
Behavioral 0.891 .374 ns
Female 72 4.12 0.71
Male 82 3.46 0.44
Cognitive 0.879 .381 ns
Female 72 3.52 0.45
Male 82 3.96 0.54
Emotional 0.600 .549 ns
Female 72 4.01 0.59
Male 82 3.79 0.91
Social 0.793 .429 ns
Female 72 3.90 0.79
Note: ns= not significant
tween the participants in terms of the specific locations of attending the online session (e.g., from home or outside the house), as well as choice of device (e.g., laptop, tablet, cellphone) used to access the virtual session. The results are presented below.
On conducting a one-way ANOVA test, as seen in Table 10, a relationship was established between student engagement and the location where they attended the virtual sessions. There is a significant F statistic effect regarding engagement in online classrooms, depending on the location of attending the online sessions (P<.05). In this regard, the ANOVA test reported a significant F statistic effect regarding the two types of engagement: behavioral and emotional (P<.05). No significant F statistic effect was reported in cognitive engagement or social engagement (P>.05).
Results of post hoc comparisons revealed that significant differences in engagement in online classrooms occurred between students attending the online sessions from home, and those from other locations such as a car or public places. Students who reported they were at home when attending the online session had higher average points (mean=3.90), when compared to students attending from other locations. Significant differences were also found in both the behavioral and the emotional engagement types. The differences in both were in favor of students who reported attending the virtual classes from their homes, with mean scores of 4.20 and 4.00, respectively. It can thus be concluded that students attending the online sessions from home had a higher engagement level in online classrooms, and that their behavioral and emotional engagements are significantly associated with the location where they attend the virtual classroom.
Table 8
ANOVA Results
Sum of Squares df Mean Square F Sig.
Between Groups .554 3 .185
General Within Groups 140.754 717 .196 .940 .421
Total 141.307 720
Between Groups .164 3 .055
Behavioral Within Groups 281.835 717 .393 .139 .936
Total 282.000 720
Between Groups 2.982 3 .994
Cognitive Within Groups 126.652 717 .177 5.628 .001**
Total 129.634 720
Between Groups .149 3 .050
Emotional Within Groups 168.786 717 .235 .211 .888
Total 168.936 720
Between Groups 7.366 3 2.455
Social Within Groups 550.657 717 .768 3.197 .023*
Total 558.023 720
Note: ** significant at .01 level, * significant at .05 level, ns= not significant Table 9
Post-HOC Multiple Comparisons
Mean Week 1 Week 2 Week 3 Week 4
Week 1 3.33 -
Week 2 3.45 0.12*
Cognitive Week 3 3.48 0.15**
Week 4 3.49 0.15**
Total 3.43
Week 1 3.59
Week 2 3.82 0.22*
Social Week 3 3.73
Week 4 3.84 0.25**
Total 3.74
Note: ** significant at .01 level, * significant at .05 level
The subsequent analysis examined student engagement in relation to their choice of device (e.g., laptop, tablet, cellphone). Analysis revealed an association between student engagement and the devices used by the student to access virtual classes. ANOVA results, in Table 11, reported a significant F statistic effect regarding engagement in online classroom according to devices used by students to access virtual sessions, F(10.243), (P<.05) and significant F statistic effect in three types of engagement, namely, behavioral, emotion-
al, and social engagement (P<.05). There was no significant main effect on student cognitive engagement.
An LSD post-hoc analysis (Table 12) showed that students who attended online sessions using a personal computer, whether a laptop or a desktop, were significantly more engaged (m=3.93) than those who joined the online classroom from cellphones (m=3.78). In fact, data showed that those who reported they used tablets to log in to sessions had the highest levels of engagement (mean=4.00), when compared
Table 10
Differences in Engagement according to the Location of Attending the Online Sessions
Sum of Squares df Mean Square F Sig.
Between Groups 4.111 7 .587
General Within Groups 137.143 711 .193 3.045 .004**
Total 141.254 718
Between Groups 14.204 7 2.029
Behavioral Within Groups 267.127 711 .376 5.401 .000**
Total 281.331 718
Between Groups 1.112 7 .159
Cognitive Within Groups 128.486 711 .181 .879 .522
Total 129.598 718
Between Groups 4.805 7 .686
Emotional Within Groups 163.454 711 .230 2.986 .004**
Total 168.259 718
Between Groups 4.395 7 .628
Social Within Groups 553.266 711 .778 .807 .582
Total 557.661 718
Note: ** significant at .01 level , ns= not significant
Table 11
ANOVA Results
Sum of Squares df Mean Square F Sig.
Between Groups 3.912 2 1.956
General engagement Within Groups 129.095 676 .191 10.243 .000**
Total 133.008 678
Between Groups 8.430 2 4.215
.000**
Behavioral Within Groups 250.979 676 .371 11.354
Total 259.410 678
Between Groups .655 2 .328
.164
Cognitive Within Groups 122.234 676 .181 1.812
Total 122.890 678
Between Groups 4.235 2 2.118
Emotional Within Groups 155.905 676 .231 9.182 .000**
Total 160.140 678
Between Groups 5.308 2 2.654
Social Within Groups 525.482 676 .777 3.414 .033**
Total 530.790 678
Note: ** significant at .01 level , ns= not significant
to users of mobile phones or even personal computers. Participants, thus, differed in their learning engagement according to their choices of device to attend the online classroom.
Significant differences were reported in behavioral, emotional, and social engagement aspects in connection to students' choice of devices. As displayed in Table 14, students who used tablets to join the sessions showed better engagement in terms of behavioral (mean=4.31), emotional (mean=4.09), and social engagement (mean=3.90). Students who used cellphones were the least engaged behaviorally, emotionally, and socially compared to those using other device types (mean= 4.02, 3.88, 3.61, respectively).
An LSD post-hoc analysis (Table 12) showed that students who attended online sessions using a personal computer, whether a laptop or a desktop, were significantly more engaged (m=3.93) than those who joined the online classroom from cellphones (m=3.78). In fact, data showed that those who reported they used tablets to log in to sessions had the highest levels of engagement (mean=4.00), when compared to users of mobile phones or even personal computers. Participants, thus, differed in their learning engagement according to their choices of device to attend the online classroom.
emotionally, and socially compared to those using other device types (mean= 4.02, 3.88, 3.61, respectively).
Since there are multiple measurement opportunities for the dependent variables (i.e., engagement in online classroom and its subscales), GLM repeated measures was employed to examine student engagement growth over time. The results of GLM repeated measures are presented in Table 13.
Gender was selected as a between-subjects factor. Table 13 contains data about the within-subject factor, time, and its interactions with the independent variable (gender). The main effect for engagement in online classroom is a test of the null hypothesis that all levels of within-subjects factor are equal. It is a test of the hypothesis that engagement in online classroom levels are equal across the four weeks. There appear to be statistically significant differences between engagement in online classroom levels across the four weeks. The F statistic (350.320) and its associated significance level (P<.001) indicate that can reject this hypothesis as false.
Results of Focus Group Interviews
Description of Participants
Significant differences were reported in behavioral, emotional, and social engagement aspects in connection to students' choice of devices. As displayed in Table 14, students who used tablets to join the sessions showed better engagement in terms of behavioral (mean=4.31), emotional (mean=4.09), and social engagement (mean=3.90). Students who used cellphones were the least engaged behaviorally,
Table 12
Results of Post-HOC Multiple Comparisons Using (LSD) Test
In total, 18 students participated in two focus group online interviews. Eight participants were female, and ten were male, all of them aged between 18 and 24 years. The findings presented below encapsulate the experiences of online students in engaging with the undergraduate writing course.
Mean Differences
Cell phone 3.78
1 vs. 2 (.15**)
General Computer 3.93 1 vs. 3 (.22**)
Tablet 4.00
Cell phone 4.02
1 vs. 2 (.23**)
Behavioral Computer 4.25
1 vs. 3 (.28**)
Tablet 4.31
Cell phone 3.88
1 vs. 2 (.16**)
Emotional Computer 4.04
1 vs. 3 (.22**)
Tablet 4.09
Cell phone 3.61
1 vs. 2 (.16*)
Social Computer 3.77 1 vs. 3 (.29*)
Tablet 3.90
Note: **significant at .01 level, *significant at .05 level
Table 13
Statistics for the Effects in the Model
Tests of Within-Subjects Effects
Source Type III Sum of Squares df Mean Square F Sig.
Time Sphericity Assumed 98.389 3 32.796 350.320 .000**
Greenhouse-Geisser 98.389 2.013 48.884 350.320 .000**
Huynh-Feldt 98.389 2.021 48.679 350.320 .000**
Lower-bound 98.389 1.000 98.389 350.320 .000**
Time Sphericity Assumed 1.198 3 .399 4.266 .005**
*Gender
Greenhouse-Geisser 1.198 2.013 .595 4.266 .014*
Huynh-Feldt 1.198 2.021 .593 4.266 .014*
Lower-bound 1.198 1.000 1.198 4.266 .039*
Error Sphericity Assumed 201.935 2157 .094
(Time)
Greenhouse-Geisser 201.935 1447.128 .140
Huynh-Feldt 201.935 1453.222 .139
Lower-bound 201.935 719.000 .281
Note: ** significant at .01 level, * significant at .05 level Table 14
Themes of interview transcripts
# Theme Frequency %
1 Students' self-evaluation of engagement in the online course 18 100
2 Factors attributed to students' high engagement 6 33
3 Students' perspectives on engagement in online classrooms versus in a non-face-to-face classrooms 13 72
4 Students' engagement throughout the semester 11 61
5 Reflective Moments when students felt fully engaged 8 44
6 Influence of location/place of class attendance on students' engagement 15 83
Analysis of Semi-Structured Interviews
The primary purpose of conducting student interviews was to answer RQ5 and to triangulate the data of other research questions through different sources. From the focus group interviews, six overarching themes relating to online student engagement were identified and constructed during the analytical process. As shown in Table 13, the themes were: 1) student self-evaluation of engagement in the online course; 2) Factors attributed to a high level of student engagement; 3) Student perspectives on engagement in online classrooms versus in a non-face-to-face classrooms; 4) Student engagement throughout the semester; 5) Reflective moments when students felt fully engaged; and 6) Influence of presence/place of class attendance on student engagement. These themes are presented below using paraphrases and individual direct quotes. Some quotes were altered to remove filler language (e.g., um, like) and provide clarity without changing the meaning of quotes.
Theme 1: student self-evaluation of engagement in online learning. Across the focus groups, students described how well they were engaged in the course. The students showed a high level of satisfaction of their engagement with the online class. In fact, they all reported that they were engaged well in the course. One student answered, "I personally find my engagement in this course to be excellent." Another student rated, "I would give my engagement 85%".
Theme 2: Factors attributed to a high level of student engagement in the online course. This theme accounts for students' perspectives on the factors that attributed to their high level of engagement in the online classroom. Based on interview data, pleasant experiences in the online course which led to a high level of engagement were attributed to four factors. These factors are discussed below.
1. The first factor is in regards to the engaging nature of teaching, which Hipkins (2012) discussed saying, "Teach-
ers' curricular intentions and the manner they construct learning opportunities in the classroom have an impact on engagement" (p. 441). In this respect, one student said, "Class sessions tended to be enthusiastic in nature. And, each class is even more engaging than the one before".
2. The interactive nature of the course and lectures was one point which facilitated their engagement. This course was demanding, interactive, and hands-on when compared to other courses. Students were expected, for example, to discuss the topic in hand, respond to discussion board questions and post their answers to Blackboard forums. This point was described by one of the interviewees "Classes contained a lot of interactive components, such as homework you assign, screen sharing and its accompanying activities, and student discussion".
3. One key factor underlined by the students in regard to their classroom engagement was the well-designed, pedagogical methods in the course. One student attributed his high level of engagement to course assignments and in-class activities in which he thought they
"motivate students to learn and participate, and ultimately, were reflected on students' outcomes".
4. The instructor's role as a motivator was reported by students in both groups to be central in enhancing classroom engagement. One student believed "The instructor plays a role in connecting students with the course and materials. Whenever the instructor acts harshly, students are more likely to feel alienated. However, in this course, I, frankly, can say I enjoyed the class. I made sure I do the in-class activities, because we were motivated to do so. So, yes, generally, it's all about the instructor's efforts in engaging the students". Similarly, students valued the professor's role on this matter, and one student commented, "Classroom engagement depends on the professor. If she is engaging, a student will feel motivated." Another student further explained, "You attract students' attention all the time. This way, students stay engaged all the time and never feel bored". This seems to be in line with Tomlinson & Moon (2013) who contend that "Engagement in the classroom results when a student's attention is attracted to an idea or a task and is held there because the idea or task seems worthwhile (p.7).
The whole atmosphere of the course was great, whether it was traditional or online. Yet, for me personally I sometimes felt distracted. However, the course was completely enjoyable. The online environment is not suitable for learning and studying. Sometimes, you get distracted by others who are surrounding you, yet, you try to stay focused in class. [student]
According to students, examples of distractions included another person coming into the room or a phone ringing. Class interaction was raised as an issue by the female group. One said, "In online classrooms, there is not much interaction. It's just the teacher speaking most of the time, and we just listen.".
However, not all the participants held the same stance. The majority of students disagreed with the notion of how the traditional classroom would be more engaging for learning. For many, the convenience and flexibility offered online were the most virtues mentioned. One participant noted, "I honestly was happy that this course was online. The instructor can stay connected with the students more. Students can easily interact and engage more in the class."
The female student group held a similar opinion on the effectiveness of online learning in terms of engagement. One student said, "Due to being online, we concentrated more". Furthermore, the female focus group students argued that for the introverted type of students, online courses are more advantageous, since they would be more beneficial and more engaging. One explained, "I favor online, because some students are shy to participate face-to-face, while online, everyone participates equally." Another agreed and stated, 'Yes, true! A shy student would not feel nervous when speaking or asking.". Another supported, "I myself cannot participate similarly in the physical classroom."
Theme 4: Engagement throughout the semester. This theme assesses how well students were engaged at the beginning of the term versus the middle or end. Almost all students in both focus groups believed their engagement was not as high when the term commenced, as towards the middle or the end of the term. Eleven students reported that they got connected and engaged more as the semester progressed. Examples included the following:
Theme 3: Students' perspectives on engagement in online classrooms versus in face-to-face classrooms. This theme reflects students' views of whether an online classroom is as engaging as a physical classroom. Although all students reported they were highly engaged in the class, only three students believed it would have been more engaging, if the course was offered in the traditional classroom. To this extent, one student believed that being at home is not as conducive to study as the traditional classroom. He explained:
"At the beginning, a student may feel introverted, but, as time passes by, one will start to get engaged more as he becomes familiar with the rules, other students, and interaction. So, engagement grows this way.".
"With time, there became more engagement in the course. We broke the ice!"
"At the very beginning, there was not a full classroom engagement, but we engaged more as time went on".
Theme 5: Reflective Moments when students felt fully engaged. This theme relates to students' perceptions of aspects which they found more engaging in the online classroom. As the semester progressed, students encountered variable levels of engagement. Students rated course requirements based on their usefulness in engaging students more. In other words, interviewees also reported on the times when they were highly engaged during the online class. Those times were as follows (listed from the most engaging to the least):
• Discussion board (DB) questions during class time.
• Class participation with the instructor.
ated with group work. Some students offered explanations to account for their perception. One student from the male focus group said, "I think discussion board was the most engaging, then class participation and the least was working in groups." This was explained, "When in groups, I noticed, students remain silent waiting for someone to start and take the lead. When there is no student to take the leader role, group discussion becomes less active." Another student supported, "One student should proactively initiate the discussion then other ones may start to engage.".
Theme 6: Influence of location/place of class attendance on student engagement.
• Group work activity.
Although all course requirements were perceived to be engaging from the point of view of students, student-controlled active learning activities, in particular, were highly appreciated. Participants believed that interaction and discussions undertaken as part of discussion board activities resulted in improved engagement. For example, one student asserted, "We were engaged more during discussion board questions. Because we were allowed enough time to think and answer questions assigned.". This highlights the connection between time allowed to do an activity and student cognitive engagement. Another student emphasized:
The fun part of discussion board activity is that when you allocate time for the activity, some students post their answers to the forum. This allowed us to brainstorm and check other students' answers. Then, you share and discuss answers along with hints. This motivated me to stay connected more."
This attitude was also reinforced by the female focus group. One of them added, "In other courses, DB activities are assigned like homework to be done later, not during class time. Your way was better because once finished, you go through students' answers and give feedback.". Additionaly, information and activities that were connected to students' lives were rated as highly engaging. Female students, especially, were in favor of this. Giving an example, one student noted, "When lessons contain information that can be applied to our personal lives, we stay focused and engaged more. For example, in one lesson, there was information on interviews; this was valuable and useful.". Another one added, "When lessons touch personal needs, we get more excited about the lesson and stay focused."
In students' narratives, the role of their peers as part of their learning engagement in the course was not valued so much. Students considered working in peers or groups with other classmates to be the least contribution to engagement, making it less "effective" in terms of engaging them online. Insight was also gained into some of the challenges associ-
Similar to the results of the SRS data, in-home engagement versus out-home engagement appeared to affect engagement. There seemed to be a consensus among both focus groups on the influence of student presence/ location during the time of attending virtual classes on student engagement. The following two extracts described their opinions towards how their engagement was affected according to where they were during the class time.
Home is usually calmer, but if I attend the class from a public place, it would be hard to pay attention.
In a coffee shop, I cannot stay focused 100%. So, yes, it differs based on my location.
Even if the setting is home, students agreed that it should be a quiet place without distractions. One student stated, 'The more people exist around you, the less engaged you become. So, as possible, I should isolate myself". Therefore, it is suggested to "Try to stay away from distractions." This required some students to create a study environment. A male student described, "I tried to create an environment similar to the university classroom." Another from the female group supported, "My room has become a study-specific environment. Full engagement requires certain characteristics of the environment."
DISCUSSION
Keeping students involved, engaged, and actively learning in online learning environments has challenged educators all over the world. In this study, there are several key findings based on the data collected. First, in regard to RQs 1 and 2, SRS data reported that students showed a general high level of engagement. Student behavioral engagement was rated the highest across all four weeks, followed by emotional engagement, and then social engagement. SRS analysis also showed that students were cognitively the least engaged during the eight virtual classes. In particular, students showed more meaningful engagement in week 1. Their cognitive engagement was ranked the highest in week
1 and the lowest in the other three weeks of investigation, during which the behavioral engagement type was highest, followed by emotional and then social engagements.
Despite the variability in students' perceptions raised in focus group data, the majority appear to have had positive engagement in virtual classrooms with increased engagement linked towards the middle and the end of the term. Student academic performance data illustrates a high level of achievements among students in all course major requirements, with female students outperforming male students. This means that students were cognitively engaged, otherwise, they would have not been able to score high in course tests, exams and written assignments. These findings are in agreement with those of Oraif & Elyas (2021), which have shown a high level of engagement among students in the online classroom.
Furthermore, general engagement did not vary between male and female students during all four weeks of the online classroom which is in line with the aforementioned studies in the literature (Almusharraf & Almusharraf, 2021; Devrim & Irem, 2020; Benhadj, 2021). However, female students were behaviorally more engaged in week 1, whereas male students were cognitively and socially more engaged during the same week. In weeks 2 and 3, female students showed more emotional engagement and more cognitive engagement. In week 4, both groups of students showed similar learning engagement in the virtual classes. The dy-namicity of engagement was shown in the dimensions of cognition and social interactions in which they were found to grow over the course period, but behaviors and emotions were less likely to grow.
The qualitative data-based findings of this study indicated that successful student engagement in the virtual environment was influenced by a number of factors. The first was related to the engaging nature of the course and its interactive nature, how well it is designed and prepared, and how well it is facilitated with a motivator instructor. A key influence in online student engagement was found to come from how well prepared the course needed to to be, in order to engage students, and that in-class group work does not guarantee enrolment and participation. Tomlinson & Moon (2013) asserted, "Engagement in the classroom results when a student's attention is attracted to an idea or a task and is held there because the idea or task seems worthwhile." (p.7). Engagement is also a result of environmental facilitators such as classroom interpersonal relations and instructional quality, as well as personal factors such as motivation and aptitude" (Oga-Baldwin, 2019, p. 5).
Likewise, the job of the instructor in encouraging student engagement is a key factor. Influenced by self-determination theory and instructor's relatedness - one of three basic psychological needs - instructors "need to put enthusiasm into lessons, show an open, honest, and caring attitude to-
ward students, and encourage students to support each other" (Bao et al., 2021, p. 3). Jang et al. (2010) rightly pointed out, when students do engage in classroom learning, there is always some aspect of the instructor's behavior that plays a role in the initiation and regulation of student engagement. Consequently, the role of online instructors needs to change from being authoritative to being cooperative and engaging (Oraif & Elyas, 2021). Lack of teacher enthusiasm, as perceived by learners, was cited as the reason for social-behavioral learning disengagement in Chinese EFL classrooms (Dewaele & Li, 2021).
Learner-learner interaction is essential for the engagement of students in the online learning environment, as stressed by Bolliger and Martin (2018). However, interview and focus group transcripts have shown otherwise. Students did not seem to have engaged meaningfully online when they were assigned into groups. It could be that the strategies used in this course were not implemented effectively, in order to initiate and support learner-to-learner interaction. Although, in this course, several activities in establishing a supportive online environment for students were applied, as suggested by Ryle & Cumming (2007). Activities included doing icebreakers, posting welcome messages and regular informative announcements to establish expectations, posting discussions in advance to stimulate interest, and providing necessary resources. In fact, students were required to share and reflect on their own learning styles and those of other, as well as, preferences, and learning difficulties. Still, it could be that students did not feel they had an established sense of belonging to the class community.
The location when attending the online session and students' choice of device (e.g., laptop, tablet, cellphone) used to access the virtual session are two indicators which affect student engagement in virtual learning. With regard to the first, students who choose to log on to the online session while at home are more likely to engage well in the online course, especially in terms of behavioral and emotional engagements. The findings of Al Shammari's (2021) affirmed that although students may have used smartphones in their remote learning, they did not recommend them. They were rated the least preferred compared to laptops, tablets, and desktop computers. Furthermore, students who select laptops in accessing virtual sessions are more likely to show higher engagement than those with hand-held devices like tablets or smart phones, especially in terms of behavioral, emotional, and social engagement aspects.
The notion of location of engagement (i.e., home or out-of-home in places such as the car, coffee shops, malls... etc.) as another dimension in nurturing student engagement during virtual language classrooms was also emphasized by the thematic analysis of interviews. Public places were reported to be not ideal for a full and meaningful engagement in online classrooms. An environment suitable for meaningful
engagement is associated with calmness and free of distractions.
Limitations and Future Directions
Despite the strengths of this study, two limitations need to be acknowledged. First, the data in this study was based on a four-week period. In order to study the longer-term effects of the online mode on language learning, it may be necessary to consider a longer period. Second, data was obtained from one course, and generalizations could not be made. A variety of courses in the exploration of student engagement in the virtual space could help gain a deeper understanding of the impact and reception of online education and learning on student engagement. A factor to be explored in future research, could be the role of academic majors and their impact on language learning in student classroom engagement.
CONCLUSION
This research revisited the topical issue among language instructors that within the virtual educational environment student engagement is impacted. Both the technology-mediated learning/teaching and the lack of face-to-face- contact may have attributed to students exhibiting different manifestations of engagement in the online classroom. This study attempted to investigate the engagement level among students in an online intermediate-level writing class taking place in the Saudi EFL context. Its aim was to contribute to understanding the factors that could have an impact on engagement in online learning. It focuses specifically on the English language learning classroom.
The findings and analysis demonstrated several points. There are variances in the types of engagement (e.g., cognitive, behavioral, social, and emotional), and there are also aspects that may influence engagement in online classrooms as a whole, such as learner-to-learner interactions, the influence of the instructor, the location of attending
online classes, and the teaching materials amongst others. All these factors affect student engagement, which is a vital part of the learning process, but do not only depend on student behaviors. Instructors also have an important role in encouraging students and implementing more engaging activities in virtual classrooms to make the language learning experience more interactive and lively. Students generally had favorable attitudes towards online learning, during the period of distance study. Lastly, student engagement during the virtual learning experience was not affected especially in terms of behavior and emotion engagement dimensions.
Notably, online learning was able to achieve similar student engagement and learning outcomes as face-to-face learning. In today's fast-changing world, online learning and teaching has become more prevalent. Essential components that guarantee successful learning experiences need to be fulfilled, in order to obviate any sacrifice in the quality of education. Students should not be skeptical about distance study and seek to produce equivalent or better performance.
DECLARATION
The author received no financial support for the research.
ACKNOWLEDGEMENT
The author would like to thank the participating students of this research, in particular for their honesty and willingness to participate and wholehearted engagement.
DECLARATION OF COMPETITING INTEREST
None declared.
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