Student Engagement In Online Learning Research Articles

Analisis Perilaku Mahasiswa dalam Menemukan Literatur Rujukan Materi Diskusi Tutorial Online

This research analyzes students' behavior in searching for reference literature in online tutorial discussions, highlighting various approaches used in deepening understanding of learning materials. The results indicate that students actively utilize online tutorials as their primary source to enhance understanding and skills related to the courses they are taking, as well as actively participate in online discussions. However, some students exhibit less active participation, indicating variations in student engagement in online learning. Some factors influencing low participation include differences in learning preferences and time constraints. Therefore, it is recommended to develop clear participation guidelines, provide incentives to active students, and develop more interactive learning methods in online tutorials. Additionally, educational institutions should provide strong technical support to students to ensure active participation. These efforts are expected to enhance the quality of learning and interaction among members of the academic community in online learning.

Developing Gamified Learning Management Systems to Increase Student Engagement in Online Learning Environments

Online learning has become a trend in today’s digital age. Accessibility, flexibility, a wide variety of learning resources, collaboration and communication, and the use of technology and innovation are reasons for the increasing popularity of online learning. However, student engagement is often low and requires innovative solutions to increase it. This study aims to develop and analyze the effectiveness of gamified Learning Management Systems (LMS) in increasing student engagement in online learning. The research method used is the ADDIE model, which consists of Analysis, Design, Development, Implementation, and Evaluation. The subjects of this study were students of one of the private universities in Indonesia who attended online lectures during the pandemic. Data collected using questionnaires, observation sheets, and interview guidelines were then analyzed using descriptive statistics. The results showed that gamified Learning Management Systems (LMS) was able to increase student engagement in online learning. However, technical limitations and inadequate institutional support were barriers to implementing gamified LMSs. In conclusion, developing gamified LMS can be an effective alternative strategy to increase student engagement in online learning and positively influence their academic performance. Overall, this research contributes to the development of gamified LMS in Indonesia and provides insight into the effectiveness of gamification strategies in increasing student engagement in the online learning environment.

Investigating learning designers’ perceptions of student cognitive engagement in online learning

Online learning has rapidly grown internationally in Higher Education due to advanced digital technologies and the COVID-19 pandemic. In addition, it offers flexibility and convenience for students. According to Meyer (2014), student engagement has a positive relationship with student satisfaction, persistence and academic performance, particularly in online learning environments. This pilot study aims to investigate how learning designers perceive students' cognitive engagement in online learning to inform the design and creation of online tasks and activities that foster these behaviours. Eight learning designers from two Australian universities participated in semi-structured interviews. They were asked three sets of questions in relation to students’ cognitive engagement during three types of interactions (Moore, 1989) – learner-to-teacher, learner-to-learner and learner-to-content interactions in online learning. Research indicates that these interactions foster student engagement in online learning environments (Bolliger & Martin, 2018; Kennedy, 2020; Martin & Bolliger, 2018). Thematic analysis (Braun & Clarke, 2012) was used to analyse the semi-structured interview transcripts. The data revealed three principal themes: (1) learning design considerations at the unit design and activity levels, (2) student learning footprints in an LMS and their artefacts, and (3) teachers’ and students’ preparedness prior to and during the units and virtual classes. First, eight design considerations were suggested by learning designers to create effective and engaging online learning environments. These design considerations were broad-ranging and encompassed the type of pedagogical strategies, the learning environment, content structure and concept checks to improve cognitive engagement. Furthermore, most of them tended to believe that interactive and collaborative activities could foster cognitive engagement in online learning. Second, the students’ learning footprint and their artefacts relate to their qualitative or quantitative contribution during the learning process. In this study, the student learning footprint includes the relevance of responses and individual student’s analytics in LMS (e.g., the number of clicks in LMS, the time spent watching videos, etc). It was not decisive which, if any of these, would provide better engagement, but both were suggested by learning designers as indicative of cognitive engagement. Finally, an unexpected descriptor for cognitive engagement, but a reasonably common suggestion from learning designers was that the preparedness of students and teachers was a factor that could impact the cognitive engagement of students. This included whether students had sufficient underpinning knowledge, prior experience of the subject or so much prior knowledge that they disengaged from “too simple” content and concepts. The preparedness of teachers extended to the clarity of instruction, whether they knew the intention of what they were teaching, and whether students were aware of where this was taking them. In future studies, we intend to explore how university teachers and students perceive cognitive engagement while preparing and during online teaching and learning and the correlations between the perceptions of learning designers, teachers and students. We hope the final findings can shape the teaching and learning process in Australian universities to provide an effective and engaging learning experience for students.

Online learning and language

Online learning is a well-established mode for tertiary education and training. However, technology-mediated learning at a distance continues to face challenges to participant engagement, despite the proliferation of models of effective online learning and the implementation of increasingly sophisticated technologies to enhance learning (Bragg, Walsh & Heyeres, 2021). The critical need to build and maintain relationships for effective learning continues to be confounded by the geographic and temporal distribution of online participants as well as the nuances of the technology in use. Online learning occurs in collaborative text-spaces within learning management systems, social media spaces and their attendant learning objects such as forums, many of which foreground language as the primary resource for making meaning with others. As such, ongoing challenges to engagement in online learning may be viewed with fresh eyes by considering the language-based interpersonal affordances of these text-spaces. This pecha kucha presentation examines how the language choices made by learning facilitators impact on student engagement in online learning. It draws on a case study of the strategic use of evaluative language – the language used to express feelings and build relationships - by one teacher educator to engage initial teacher education students in online learning. Underpinned by the Systemic Functional Linguistic model of language (Halliday & Matthiessen, 2014) and following Martin & White (2005), appraisal analysis of weekly forum posts across three iterations of a unit of study shows how changes to language choices made by the teacher educator positively impacted on student engagement. This illuminates the relationship between online learning and language, and how judicious use of language-based meaning making resources can be used to improve online participant engagement.

Teacher Autonomy Support Influence on Online Learning Engagement: The Mediating Roles of Self-Efficacy and Self-Regulated Learning

Higher education faculty’s autonomous support of online teaching can promote students engagement in online context. This study collected 492 Chinese university students’ survey questionnaires and applied structural equation model to measure their teacher autonomy support, self-efficacy, self-regulated learning (SRL), and online learning engagement. This study adopted self-determination theory (SDT), systematically explored the relationship between teachers’ autonomy support and student learning engagement from the perspective of online contexts, and examined the mediating effects of students’ self-efficacy and self-regulated learning (SRL) in online contexts. This study found that teacher autonomy support had a significant effect on student engagement in online learning, and was mediated by self-efficacy. Teacher-directed support had a significant effect on student engagement in online learning mediated by SRL. Teacher-directed support had a significant impact on online learning with self-efficacy and SRL as the main mediating variables. Therefore, this study gave a fresh perspective to improve students’ online learning engagement, that is to say, teachers were encourage to improve students’ autonomy in practical teaching on the basis of giving students autonomy support. Students can promote online learning engagement by strengthening self-efficacy and self-regulation through organizational exchanges and mutual assistance and cooperation of students.

Student Engagement in Virtual Learning: The Self-Determination Theory Perspective

The exploratory case study explored how the lecturers motivate the students to engage in team-based online learning and how technologies in e-learning and remote classrooms motivate student engagement. Engagement is a multidimensional construct that includes behaviour, emotions, and cognition, essential in learning outcomes. Involving 101 undergraduate students, questionnaires and virtual interviews were conducted with the participants to elicit their perceptions and experiences concerning student engagement. Following the Self-Determination Theory framework of Deci and Ryan (1985), this study proved that students’ engagement in the team-based online learning model is based on three perspectives: competence, sense of belonging, and autonomy. The theory highlights the importance of motivation and fulfilment of three basic human needs: autonomy, competence and relatedness. Data was collected through interviews and questionnaires focusing on the perceptions and experiences of undergraduate students who had participated in fully online learning for four semesters. Thematic analysis was used to analyze data divided into categories based on the Self-Determination Theory framework. The findings reveal that students’ engagement in team-based online learning is influenced by their need for competence, belonging, and autonomy. Overall, this research highlights the importance of addressing student engagement in online learning and provides insight into how lecturers and technology can motivate and enhance student engagement in team-based online learning. Lecturers must continually adapt their instructional strategies and leverage technology to maintain and increase student engagement during the online learning experience

A Model of Student Engagement in Online Learning

In the field of online learning, the topic of engagement has drawn a lot of attention. According to research, when students engage in their own learning, they experience a variety of benefits, including greater motivation and achievement. Several metrics for gauging student engagement have been proposed in previous studies. Few, however, have been created to assess involvement in online learning contexts. The goal of this study is to create an instrument for measuring student involvement in online learning settings. A critical synthesis of the literature was carried out by categorizing and then critically reviewing the literature in order to construct and integrate the variables that could aid in successful learning outcomes, leading to the development of a framework that can guide in achieving student engagement. This study confirms earlier findings while also directing the development of a student engagement framework for online learning systems. The suggested model would bring value to literature by enhancing and improving understanding of the elements influencing student engagement in an online learning environment, resulting in active student learning.

Promoting engagement in online learning beyond COVID‐19: Possible strategies and directions for future research

AbstractIn the aftermath of the global pandemic, online learning is now ubiquitous around the world. Yet, although online learning has become a common learning approach across the globe, it is still viewed as a weaker option than on‐campus face‐to‐face learning. Specifically, the lack of student engagement in online learning poses a persistent problem to many educators. In this article, we describe three key challenges of fully online learning: students being more easily distracted, students lacking self‐regulation skills and students feeling isolated. Next, we present three possible strategies to address these challenges: promoting active learning through the online flipped classroom model, promoting self‐regulation skills and reducing the sense of isolation through the use of chatbots. For each of the three strategies, we provide a description with relevant empirical studies based on our own work as well as previous work in the literature and discuss possible directions for further research.

Student Engagement in Online Learning Among Undergraduate Nursing Students

Aims: Student engagement (SE) is a significant factor for success in online learning. The low of SE will impact students' academic achievement. Purpose: This study aimed to describe SE in online learning at the Faculty of Nursing, Universitas Padjadjaran.  Methods: This study was quantitative descriptive research. The population was undergraduate nursing students (N=862). The sample criteria were that respondents were active students of the Faculty of Nursing, Universitas Padjadjaran for the 2020/2021 period from the Jatinangor and Pangandaran campuses. The sampling technique was total sampling with a response rate of 64,3% (n=554). Data were collected using the Online Community and Student Engagement Scale. Data were analyzed using descriptive statistics and presented in frequency distribution tables.  Results: The results showed that more than half of students (52.7%) had a low category of SE, and nearly half (47.3%) have shown a high category of SE in online learning. Students had low levels of Community Building with the Instructor, Community Building with Classmates, and Engagement with Learning (57.4%; 58.3%; and 51.8%, respectively). The SE level that the respondent currently has has the potential to be increased along with the ongoing process during the lecture period. Conclusion: More than half of students had a low category of SE in online learning this could have a negative impact on student achievement and educational completion rates. Therefore, intense interactions through discussions between students and lecturers, constructive feedback, and motivational support are highly recommended to be provided by the faculty and peers for improving the SE.

Determinants Affecting Student Engagement in Online Learning: Examining Teaching Styles and Students’ Computer Self-Efficacy

Determinants Affecting Student Engagement in Online Learning: Examining Teaching Styles and Students’ Computer Self-Efficacy

The influence of social media literacy on student engagement in online learning

AbstractBackgroundRecent years have seen the proliferation of online courses that have been initiated either in accordance with the natural rhythms of educational technology growths or in force majeure situations. This adds complexity to understanding the influence of potential factors on online student engagement.ObjectivesThe present study conducted an essential inspection to explore the relationship between student social media literacy and their engagement in online learning settings.MethodologyA sample of 1015 undergraduate students participated in this study and the partial least squares structural equation modelling (PLS‐SEM) was chosen for evaluating the research model. In addition, to provide more information on the prioritization of strategic actions, the importance‐performance map analysis (IPMA) was also performed.ResultsIn a two‐factor construct, social media literacy was found to have a significantly positive relationship with aspects of student engagement in the online learning environment. The influence of technical competence is still undeniable, but the effect of cognitive competence on online student engagement is more significant. In addition, appearing in the fourth quadrant (low performance ‐ high importance) in all IPMA presentations, the anticipatory reflection is the construct that should be prioritized for improvement to augment student engagement in online learning.

The role of instructional quality on online learning intentions of university students: The technology acceptance model of Zoom

E-learning technology has a vital role to play in supporting the realization of learning goals during the COVID-19 pandemic. One that is often used is video conferencing technology from Zoom. Many studies have discussed the important role of e-learning technology, but there are still limited studies that examine how the role of Zoom technology in increasing student engagement in online learning. Thus, this study focuses to reveal the impact of online instructional quality using Zoom video conferencing technology on increasing students’ online learning intentions. We use the technology acceptance model (TAM) approach to answer the objectives of this study. This study randomly involved 190 students at Universitas Negeri Jakarta, Indonesia through an online questionnaire. We used structural equation modeling (SEM) analysis to examine the effect on each variable. In addition, we also use a bootstrap confidence interval estimate to investigate the role of mediation. The study results reveal that students' online learning intentions are influenced by perceived usefulness and ease of using Zoom. Also, perceived usefulness and ease of use are proven to mediate the effect of instructional quality on students’ online learning intentions using Zoom video conferencing technology. The results of this study provide important implications for education practitioners to develop engaging online learning for students.

Unravelling the relationship between student engagement and learning outcomes in emergency online learning: a synthesis of quantitative and qualitative results

Adopting a mixed methods approach, this study examined the relationships between undergraduate students’ motivation, engagement and learning outcomes during the COVID-19 pandemic. An online questionnaire survey was administered to collect quantitative and qualitative data. A sample of 10,060 undergraduates from 23 universities in China participated in the survey. The results of quantitative analyses largely confirmed the hypothesised relationships between students’ motivation, engagement and the two learning outcome indicators (i.e. mastery of generic skills and overall satisfaction). The qualitative analyses not only supported the quantitative findings, but also identified four types of learning outcomes of online learning emerging from the data. The results indicated that emergent online learning had a favourable influence on students’ learning strategies, but had mixed or negative effects on their learning effectiveness, attitudes and emotions. The qualitative results revealed eight major factors that facilitated or hindered students’ engagement in online learning during the pandemic. These findings contribute to the conceptualisation and measurement of student engagement in online learning, and emphasise the need to conduct mixed methods research in different learning contexts. The implications for improving online learning and teaching in higher education are discussed.

Learning Analytics on Student Engagement to Enhance Students’ Learning Performance: A Systematic Review

The study of learning analytics provides statistical analysis and extract insights from data, particularly in education. Various studies regarding student engagement in online learning have been conducted at tertiary institutions to verify its effects on students’ learning performance. However, there exists a knowledge gap whereby the types of student-engagement issues derived from learning analytics have not been collectively studied thus far. In order to bridge the knowledge gap, this paper engages a new systematic literature review (SLR) that analysed 42 articles using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). The existing research on student engagement in online learning does not extensively integrate the five types of online engagement proposed by Redmond et al., and the use of learning analytics on the subject matter is also limited. Thus, this review sheds light on the types of student engagement indicated by using learning analytics, hoping to enhance students’ learning performance in online learning. As revealed in the findings, some studies measured multifaceted engagement to enhance students’ learning performance, but they are limited in number. Thus, it is recommended that future research incorporate multifaceted engagement such as social, cognitive, collaborative, behavioural, and emotional engagement in online learning and utilise learning analytics to improve students’ learning performance. This review could serve as the basis for future research in online higher education.

Psychometric properties of the university student engagement inventory among Chinese students

PurposeSince the onset of the COVID-19 pandemic in China, student engagement in online learning has been a critical issue for all educational institutions. The university student engagement inventory (USEI) is the most used scale for assessing the construct of student engagement. The present study aimed to evaluate the psychometric properties of the USEI among 1504 Chinese university students who completed a survey through an online platform between December 2020 and January 2021.Design/methodology/approachIn this cross-sectional study, content validity, construct validity and reliability of the scale were assessed.FindingsThe results supported the three-factor model with acceptable goodness of fit (χ2 (71) = 369.717, p = 0.13, χ2/df = 5.207, comparative fit index (CFI) = 0.967, normed fit index (NFI) = 0.960, Tucker–Lewis index (TLI) = 0.958, standardized root mean square residual (SRMR) = 0.030, root mean square error of approximation (RMSEA) (90% CI) = 0.053 [0.049, 0.057]), good internal consistency and construct reliability (Cronbach's alpha and omega coefficient >0.70) and strong convergent validity. Also, the measurement invariance was confirmed across gender.Originality/valueThis study showed that the 3-factor structure of USEI with Chinese university students had good construct validity, internal consistency and reliability. It could help measure student engagement in online learning in China.

Rhetoric and realities in Australian universities of student engagement in online learning: Implications for a post-pandemic era

The issue of student engagement in online learning (SEOL) environments which gained attention during the COVID-19 pandemic, continues to be a significant topic of interest in the innovative scholarship of teaching and learning space within business schools. This paper explores academic perspectives on the rhetoric and realities of SEOL in Australian universities. The study employs an exploratory qualitative research approach utilising interview (n = 33) data and content analysis of university policies and documents. The findings highlight technological hurdles, administrative negligence, piecemeal professional development initiatives, and policy ambiguities impeding SEOL. The paper discusses the implications of these findings in the context of the professional development of academics in a post-pandemic era. The paper makes broader analytical contributions toward evaluating the implementation of SEOL-related policies in Australian universities and beyond.

Investigating university student engagement in online learning: A case study in EFL classroom

The COVID-19 pandemic outbreak inevitably impacts the shift in teaching and learning activities worldwide. Online learning has been commonly applied in education, particularly in higher education. Notably, student engagement plays a pivotal role in the online classroom as it identifies critical elements of the learning process that can increase learning and outcomes. However, the question has been raised about whether student engagement between synchronous and asynchronous online classrooms is indistinguishable. Thus, this study investigates student engagement in a synchronous and asynchronous online classroom, particularly in an Indonesian English as a Foreign Language (EFL) context. A Likert-scale questionnaire and classroom observation (synchronous and asynchronous) were used to gather the data from 26 university students in a sample of EFL teaching in an Indonesian context. The study encompasses five elements of online engagement: social engagement, cognitive engagement, behavior engagement, collaborative engagement, and emotional engagement. The prominent finding has successfully revealed that university student engagement in online learning has different significance levels. Most students are more involved in synchronous online activities as they can interact with their professors and peers in real time. Synchronous and asynchronous learning provide substantial and comparable results. This study implies that synchronous and asynchronous activities should be incorporated into online learning to get more engaging interaction among students. This study has contributed to the growing literature on the student-teacher dynamic in online education. Further research could explore student engagement in online learning from other perspectives, such as the teacher's perspective and the use of learning media.

Statistical Assessment on Student Engagement in Asynchronous Online Learning Using the k-Means Clustering Algorithm

In this study, statistical assessment was performed on student engagement in online learning using the k-means clustering algorithm, and their differences in attendance, assignment completion, discussion participation and perceived learning outcome were examined. In the clustering process, three features such as the behavioral, emotional and cognitive aspects of student engagement were considered. Data for this study were collected from undergraduate students who enrolled in an asynchronous online course provided by Kyung Hee University in Republic of Korea in the fall semester of 2021. The students enrolled in the asynchronous online course were classified into two clusters with low and high engagement perceptions. In addition, their differences in attendance, assignment completion, discussion participation, interactions and perceived learning outcome were analyzed. The results of this study indicate that quantitative indicators on students’ online behaviors are not sufficient evidence to measure the level of student engagement and the students enrolled in the asynchronous online course were classified into two groups with low and high engagement perceptions. It is recommended that online instructors consider various strategies to facilitate interaction for the students with low engagement perceptions.

Designing an artificial intelligence tool to understand student engagement based on teacher's behaviours and movements in video conferencing

Video conferencing is an effective tool that promotes interaction and collaboration, increasing student engagement in online learning. This study is the second phase of design-based research to create a tool to generate a report of engaging teaching videos using deep learning as an artificial intelligence (AI) methodology. In this second phase, the authors have applied the characteristics and indicators of engaging teaching videos identified in the first phase, reported in another study, to develop an Artificial Intelligence enabled tool. Twenty-five recorded lecture videos presented to higher education students were annotated based on the indicators and characteristics of engaging teaching videos. An AI expert has assisted the authors in creating the Artificial Intelligence-enabled tool from the reports generated by this manual annotation. With the assistance of this tool, the engagement enhancing teachers' behaviours and movements can be identified from recorded lecture videos, and a report can be generated on engaging teaching videos. For the classification task of video analysis, the deep learning model is adopted in this research. The model is trained with manually annotated videos and determines class imbalance issues and misleading metrics. The model was further improved by adopting the oversampling technique. The second version of the tool achieved promising outputs with average precision, recall, f1-score, and balanced accuracy of 68, 75, 73, and 79%, respectively, in classifying the annotated videos at the indicator level. The tool can assist the education institutes in creating moderation in the lecture delivery and whether the teachers are utilising the technology effectively. Additionally, this can help teachers recognise the presence or absence of engagement-enhancing behaviours and movements during their video conferencing sessions.

A Review of Higher Education Students’ Online Engagement Under The COVID-19 Pandemic

The spread of COVID-19 has presented enormous challenges to higher education students all over the world, prompting these students to switch from face-to-face to online courses. Previous researchers have focused on how university students in specific countries engage in online learning. However, the engagement of university students in online learning on a larger scale has not been thoroughly investigated. This study provides a comprehensive discussion of student engagement in online learning at large higher education institutions around the world during the COVID-19 pandemic. This study focuses university students need to attend university online. Since “engagement” is considered a multidimensional term, this review evaluates studies related to the idea of global university students’ online “engagement” in terms of three unique but interconnected dimensions: behavioral, conscious, and emotional engagement. This review can serve as a reference point for higher education institutions, education policymakers, and teachers in various countries as they work to develop more effective solutions to increase online participation of university students.