Relations between Student Online Learning Behavior and Academic Achievement in Higher Education: A Learning Analytics Approach

Jo, Il Hyun; Yu, Taeho; Lee, Hyeyun; Kim, Yeonjoo

doi:10.1007/978-3-662-44188-6_38

Cited by 32 publications

(24 citation statements)

References 11 publications

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“…This finding differs from the finding obtained by Jo et al (2015), who claimed that "total logins to LMS had a significant correlation with final grades." As a result of linear regression analysis, a statistically significant and positive causal relationship was found between GPA and the total time spent in the LMS.…”

Section: Discussioncontrasting

confidence: 99%

“…As a result of linear regression analysis, a statistically significant and positive causal relationship was found between GPA and the total time spent in the LMS. This finding also differs from the finding obtained by Jo et al (2015), who reported that "total study time in LMS did not predict final grades." Castaño-Muñoz et al (2014) point out that time spent without any interaction will not increase learning success.…”

Section: Discussioncontrasting

confidence: 99%

“…According to Elias (2011), learning analytics is closely tied to fields such as Web analytics, academic analytics, educational data mining, action analytics, and business intelligence (entire processes of taking strategic decision for the institution utilizing data analyses or algorithms). The rest of the related literature regarding learning analytics mostly focuses on evaluating the learning process (Blikstein, 2011), making learning predictions (Arnold & Pistilli, 2012), and providing feedback (Jo, Yu, Lee, & Kim, 2015).…”

Section: Literature Reviewmentioning

confidence: 99%

“…In their predictive model research Jo et al (2015) attempted to determine the significant components of learning analytics that support the learning achievement of students. The study was carried out with 41 undergraduate students in a South Korean university.…”

Section: Literature Reviewmentioning

confidence: 99%

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Determining the Effects of LMS Learning Behaviors on Academic Achievement in a Learning Analytic Perspective

Fırat

2016

JITE:Research

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Two of the most important outcomes of learning analytics are predicting students' learning and providing effective feedback. Learning Management Systems (LMS), which are widely used to support online and face-to-face learning, provide extensive research opportunities with detailed records of background data regarding users' behaviors. The purpose of this study was to investigate the effects of undergraduate students' LMS learning behaviors on their academic achievements. In line with this purpose, the participating students' online learning behaviors in LMS were examined by using learning analytics for 14 weeks, and the relationship between students' behaviors and their academic achievements was analyzed, followed by an analysis of their views about the influence of LMS on their academic achievement. The present study, in which quantitative and qualitative data were collected, was carried out with the explanatory mixed method. A total of 71 undergraduate students participated in the study. The results revealed that the students used LMSs as a support to face-to-face education more intensively on course days (at the beginning of the related lessons and at nights on course days) and that they activated the content elements the most. Lastly, almost all the students agreed that LMSs helped increase their academic achievement only when LMSs included such features as effectiveness, interaction, reinforcement, attractive design, social media support, and accessibility.

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Section: Discussioncontrasting

confidence: 99%

Section: Discussioncontrasting

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

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Determining the Effects of LMS Learning Behaviors on Academic Achievement in a Learning Analytic Perspective

Fırat

2016

JITE:Research

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“…Alanyazın incelendiğinde etkileşim verilerine dayalı öğrenen profillerinin incelendiği çalışmalar (Jo, Yu, Lee & Kim, 2015;Jo, Park, Yoon & Sung, 2016;Macfadyen & Dawson, 2010;Taraghi, Saranti, Ebner, Müller, & Großmann, 2015) mevcuttur. Bu çalışmaların önemli bir kısmı öğrenen gezinimlerine dayalı olarak öğrenen profillerinin ortaya konulmasına yöneliktir.…”

Section: Introductionunclassified

E-Öğrenme Ortamlarinda Öğrenen Özelli̇kleri̇ne Dayali Etki̇leşi̇m Profi̇lleri̇ni̇n Beli̇rlenmesi̇

Şahi̇n¹,

Keskin²,

Özgür³

et al. 2017

Eğitim Teknolojisi Kuram Ve Uygulama

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The aim of the study is determining the interaction profiles of learners in e-learning environments in terms of motivation and learning strategies. The study was conducted with 65 learners taking Computer Networks and Communication course for six weeks. The learners used the Moodle environment as a learning management system (LMS) in the context of the course. In this environment, learners interacted with the course content, discussions, assessment tasks, and instructor. Research data were obtained by keeping the interaction data in database and the self-reported measures. During the analysis of data firstly a ranking was made based on the learners' interactions by the grey relation analyze. Optimal scaling analysis was used to examine the relationship between learners' interaction profiles, motivation and cognitive strategies. It has been observed that learners, who interact at high level, have higher elaboration and regulation cognitive strategies; and those who interact low level, have lover elaboration and regulation cognitive strategies. As a result of these findings, it became clear that the cognitive strategies preferred by learners are an important factor in the interactions in e-learning environments.

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Students' perspectives of digital transformation of higher education in Bosnia and Herzegovina

Bećirović

Dervić

2022

E J Info Sys Dev Countries

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Since the COVID‐19 pandemic prompted numerous global changes, educational institutions in Bosnia and Herzegovina were forced to adapt their educational approaches, with schools and universities implementing alternative teaching and learning practices. Thus, this study aimed to investigate students' perspectives on the digital transformation of higher education in Bosnia and Herzegovina, including their preferences for hybrid, online, or face‐to‐face teaching models, their internet habits and readiness for e‐learning, their attitudes and satisfaction with online learning, and their computer anxiety. The research sample consisted of 330 students studying in a variety of fields and academic years at both public and private universities. The data was gathered via an online questionnaire. A multinomial logistic regression analysis revealed a significant effect of students' field of study, year of study, and university status on their preferences for hybrid, online, and face‐to‐face classes. However, the MANOVA test revealed that the aforementioned factors have an insignificant effect on students' internet habits and readiness for e‐learning, attitudes and satisfaction with online learning, and computer anxiety, all of which have an insignificant impact on student's academic achievement as determined by standard multiple regression analyses. Additionally, multivariate analysis revealed that students' preferences for hybrid, online, and face‐to‐face classes have a significant influence on their internet habits and readiness for e‐learning, attitudes, and satisfaction with online learning, and computer anxiety. The findings of this study may aid in a better understanding of tertiary education's digital transformation and the improvement of educational policy, curricula, and instructional and learning strategies.

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Relations between Student Online Learning Behavior and Academic Achievement in Higher Education: A Learning Analytics Approach

Cited by 32 publications

References 11 publications

Determining the Effects of LMS Learning Behaviors on Academic Achievement in a Learning Analytic Perspective

Determining the Effects of LMS Learning Behaviors on Academic Achievement in a Learning Analytic Perspective

E-Öğrenme Ortamlarinda Öğrenen Özelli̇kleri̇ne Dayali Etki̇leşi̇m Profi̇lleri̇ni̇n Beli̇rlenmesi̇

Students' perspectives of digital transformation of higher education in Bosnia and Herzegovina

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