Higher education student engagement in times of pandemic: the role of e-learning system usability and teacher behavior

Dahleez, Khalid Abed; El‐Saleh, Ayman A.; Alawi, Abrar Mohammed Al; Fattah, Fadi Abdel Muniem Abdel

doi:10.1108/ijem-04-2021-0120

Cited by 23 publications

(26 citation statements)

References 67 publications

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“…These research results also confirm previous study findings that showed that perceived level of usability significantly correlates with learners’ engagement [ 24 ]. Learners who perceive the system as easy to use, will be more engaged and motivated.…”

Section: Discussionsupporting

confidence: 91%

Perceived Level of Usability as an Evaluation Metric in Adaptive E-learning

Alghabban

Hendley

2022

SN COMPUT. SCI.

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The global spread of COVID-19 has shifted the learning process towards e-learning. In this context, a critical challenge for researchers is to understand and evaluate the effectiveness of e-learning, especially when the learning is adapted to the needs of individual users. In this work we argue that the learner’s perception of the level of usability of a system is a valuable metric that gives an insight into the learners’ engagement and motivation to learn. Little attention has been paid to this metric. In this paper we explore why this is important and valuable. We present a case study which uses the System Usability Scale (SUS) questionnaire to measure the user’s perception of usability as an indirect (proxy) measure of engagement. A between-subject experiment was conducted with 41 learners with dyslexia. The intervention group used the adaptive version of the e-learning system that matched the material to the needs of the learner. The control group used a standard version. At the end, learning gain and SUS scores were assessed. The correlation between learning performance and the perceived level of usability was positive and moderate (0.517, p < 0.05) among participants in the intervention group. However, learning performance and perceived level of usability were unrelated in the control group (− 0.364, p > 0.05). From this, and other work, it appears that using a learner’s assessment of the usability of a system is an effective way to measure their attitude to their learning. It reflects their perception of its suitability to their needs and this, in turn, is likely to affect their engagement and motivation. As such, this provides an effective instrument to judge whether adaptation based on learner needs has been successful.

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Section: Discussionsupporting

confidence: 91%

Perceived Level of Usability as an Evaluation Metric in Adaptive E-learning

Alghabban

Hendley

2022

SN COMPUT. SCI.

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“…Both academic and behavioural engagements were the least dominant. In this case, as pointed out earlier, a study by Dahleez et al (2021) that investigated the effects of MOODLE usability and teacher behavior on student engagement found both variables impacted students' agentic, behavioral, emotional and cognitive engagements positively. However, in the present study as is the case with the first cohort, the second cohort student engagement differed from the findings by Bond et al (2020) as cognitive engagement, and not behavioral engagement, was the dominant engagement dimension.…”

Section: Second Cohort Student Engagementsupporting

confidence: 52%

“…During the current period of the COVID-19 pandemic, there are already studies that have been conducted on student engagement in the HE sector. Examples of these studies are those by Chen., Kaczmarek, and Ohyama (2020); Dahleez et al (2021); Hewson and Chung (2021) and Reguera and Lopez (2021). For instance, the study by Chen et al (2020) investigated student engagement together with the learning outcomes and students' perceptions of an online course that incorporated quizzes, tasks and tests as a formative assessment.…”

Section: Literature Reviewmentioning

confidence: 99%

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Leveraging Student Engagement through MS Teams at an Open and Distance E-learning Institution

Chaka

Nkhobo

Lephalala

2022

JEELR

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The current paper reports on a study that was conducted at the University of South Africa (UNISA) in 2021. The study involved three cohorts of undergraduate students (n = 20, n = 12 and n = 18), where each cohort participated in one of the virtual sessions offered on MS Teams as part of their modules’ virtual classes. Employing a case study research design, the study used the interactions students had on MS Teams through messages in each session to determine how such messages served as indicators of student engagement. Four student engagement dimensions, namely emotional, behavioral, cognitive and academic engagement, were the focus of this study. Two of the findings of this study are: (a) only few students dominated the messages posted during the three live virtual sessions; and (b) cognitive and emotional engagement dimensions were the two predominant dimensions of student engagement. The paper ends with the implications and recommendations.

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“…Matching is especially important when working with new or poor students, as they are prone to frustration at this stage of their education. Dahleez et al (2021) proposes three benefits of identifying learning styles: academic, personal, and professional. Meanwhile Maxwell-Stuart & Huisman (2018) examined the effect of matching or mismatching learning and teaching styles on student achievement.…”

Section: Literature Reviewmentioning

confidence: 99%