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Giannakos, Michail; Cukurova, Mutlu – British Journal of Educational Technology, 2023
This study presents the outcomes of a semi-systematic literature review on the role of learning theory in multimodal learning analytics (MMLA) research. Based on previous systematic literature reviews in MMLA and an additional new search, 35 MMLA works were identified that use theory. The results show that MMLA studies do not always discuss their…
Descriptors: Learning Theories, Multimedia Instruction, Learning Analytics, Research Reports
Using Analytics to Predict Students' Interactions with Learning Management Systems in Online Courses
Ali Alshammari – Education and Information Technologies, 2024
In online education, it is widely recognized that interaction and engagement have an impact on students' academic performance. While previous research has extensively explored interactions between students, instructors, and content, there has been limited exploration of course design elements that promote the fourth type of interaction:…
Descriptors: Learning Analytics, Learning Management Systems, Academic Achievement, Correlation
Hua Ma; Wen Zhao; Yuqi Tang; Peiji Huang; Haibin Zhu; Wensheng Tang; Keqin Li – IEEE Transactions on Learning Technologies, 2024
To prevent students from learning risks and improve teachers' teaching quality, it is of great significance to provide accurate early warning of learning performance to students by analyzing their interactions through an e-learning system. In existing research, the correlations between learning risks and students' changing cognitive abilities or…
Descriptors: College Students, Learning Analytics, Learning Management Systems, Academic Achievement
Sudeshna Pal; Patsy Moskal; Anchalee Ngampornchai – International Journal on E-Learning, 2024
This study investigated the effectiveness of blended instruction in enhancing student success in an advanced undergraduate engineering course. The research used learning analytics captured from pre-recorded lecture videos, course grade data, and student surveys. Results revealed positive correlations between lecture video viewership and course…
Descriptors: Blended Learning, Advanced Courses, Engineering Education, Undergraduate Students
So, Joseph Chi-Ho; Ho, Yik Him; Wong, Adam Ka-Lok; Chan, Henry C. B.; Tsang, Kia Ho-Yin; Chan, Ada Pui-Ling; Wong, Simon Chi-Wang – IEEE Transactions on Learning Technologies, 2023
Generic competence (GC) development is an integral part of higher education to provide holistic education and enhance student career development. It also plays a critical role in complementing the curriculum. Many tertiary institutions provide various GC development activities (GCDA). Moreover, institutions strongly need to further understand…
Descriptors: Predictor Variables, Higher Education, Online Courses, Correlation
Xiuyu Lin; Zehui Zhan; Xuebo Zhang; Jiayi Xiong – IEEE Transactions on Learning Technologies, 2024
The attribution of learning success or failure is crucial for students' learning and motivation. Effective attribution of their learning success or failure in the context of a small private online course (SPOC) could generate students' motivation toward learning success while an incorrect attribution would lead to a sense of helplessness. Based on…
Descriptors: Learning Analytics, Learning Processes, Learning Motivation, Attribution Theory
Heeryung Choi – ProQuest LLC, 2022
Learning analytics researchers have been diligently integrating trace data to study Self-Regulated Learning (SRL). Compared to traditionally used survey data, trace data, such as log or clickstream data designed and interpreted to understand a certain SRL construct, are considered to be more effective in capturing dynamic SRL as fine-grained…
Descriptors: Learning Analytics, Metacognition, Validity, Comparative Analysis
Amaya, Edna Johanna Chaparro; Restrepo-Calle, Felipe; Ramírez-Echeverry, Jhon J. – Journal of Information Technology Education: Research, 2023
Aim/Purpose: This article proposes a framework based on a sequential explanatory mixed-methods design in the learning analytics domain to enhance the models used to support the success of the learning process and the learner. The framework consists of three main phases: (1) quantitative data analysis; (2) qualitative data analysis; and (3)…
Descriptors: Learning Analytics, Guidelines, Student Attitudes, Learning Processes
Hess, Richard M. – ProQuest LLC, 2021
The purpose of this study was to explore and analyze the utilization of learning analytics data produced by a learning management system as an indicator of learners' self-regulation. In the Spring of 2021, 258 learners at a four-year, mid-Atlantic university provided access to their learning management system data. Of those 258 learners, 86…
Descriptors: Self Control, Integrated Learning Systems, Learning Analytics, Undergraduate Students
Summers, Robert J.; Higson, Helen E.; Moores, Elisabeth – Assessment & Evaluation in Higher Education, 2021
Effective use of learning analytics systems has been purported to confer various benefits to learners in terms of both attainment and retention. There is, however, little agreement on which data are meaningful or useful. Whilst measures of engagement might correlate with outcomes, thereby retrospectively 'predicting' them, there are fewer studies…
Descriptors: Learner Engagement, Learning Analytics, College Freshmen, Undergraduate Study
Mouri, Kousuke; Uosaki, Noriko; Hasnine, Mohammad; Shimada, Atsushi; Yin, Chengjiu; Kaneko, Keiichi; Ogata, Hiroaki – Interactive Learning Environments, 2021
This paper describes an automatic quiz generation system designed to support language learning that utilizes digital textbook logs. Learners often memorize words in digital textbooks while preparing for an examination, and they often use the highlight function for the words. Previous studies regarding annotations and highlights have shown that…
Descriptors: Computer Assisted Testing, Learning Analytics, Electronic Publishing, Textbooks
Xu, Jiajun; Dadey, Nathan – Applied Measurement in Education, 2022
This paper explores how student performance across the full set of multiple modular assessments of individual standards, which we refer to as mini-assessments, from a large scale, operational program of interim assessment can be summarized using Bayesian networks. We follow a completely data-driven approach in which no constraints are imposed to…
Descriptors: Bayesian Statistics, Learning Analytics, Scores, Academic Achievement
Hriez, Raghda Fawzey; Al-Naymat, Ghazi – Journal of Computing in Higher Education, 2021
Depicting the reason for the mismatch between instructor expectations of students' performance in advanced courses and their actual performance has been a challenging issue for a long time, which raises the question of why such a mismatch exists. An implicit reason for this mismatch is the student's weakness in prerequisite course skills. To solve…
Descriptors: Required Courses, Advanced Courses, Graphs, Outcomes of Education
Cormack, Sophie H.; Eagle, Laurence A.; Davies, Mark S. – Assessment & Evaluation in Higher Education, 2020
Many studies have found a relationship between students' self-reported procrastination and their grades. Few studies have used learning analytic data as a behavioural measure of procrastination in order to predict performance, and there is no systematic research on how this relationship may differ across assessments or disciplines. In this study…
Descriptors: Correlation, Time Management, Academic Achievement, Grades (Scholastic)
Darko, Charles – SAGE Open, 2021
"Blackboard" is an important Learning Management System (LMS) employed at most higher education institutions to engage and interact with students during their studies. Students within Material Science and Engineering (MSE) often use these LMS's to absorb mathematical derivations, scientific information and submit coursework tasks. In…
Descriptors: Integrated Learning Systems, Correlation, Grades (Scholastic), Academic Achievement
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