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Eamon Vale; Garry Falloon – Online Learning, 2024
This research investigated the potential of learning analytics (LA) as a tool for identifying and evaluating K-12 student behaviors associated with active learning when using video learning objects within an online learning environment (OLE). The study focused on the application of LA for evaluating K-12 student engagement in videobased…
Descriptors: Learning Analytics, Elementary School Students, Secondary School Teachers, Electronic Learning
Badal, Yudish Teshal; Sungkur, Roopesh Kevin – Education and Information Technologies, 2023
The outbreak of COVID-19 has caused significant disruption in all sectors and industries around the world. To tackle the spread of the novel coronavirus, the learning process and the modes of delivery had to be altered. Most courses are delivered traditionally with face-to-face or a blended approach through online learning platforms. In addition,…
Descriptors: Prediction, Models, Learning Analytics, Grades (Scholastic)
Hatice Yildiz Durak – Education and Information Technologies, 2025
Feedback is critical in providing personalized information about educational processes and supporting their performance in online collaborative learning environments. However, giving effective feedback and monitoring its effects, which is especially important in online environments, is a complex issue. Although providing feedback by analyzing…
Descriptors: Feedback (Response), Online Systems, Electronic Learning, Learning Analytics
Nick Hopwood; Tracey-Ann Palmer; Gloria Angela Koh; Mun Yee Lai; Yifei Dong; Sarah Loch; Kun Yu – International Journal of Research & Method in Education, 2025
Student emotions influence assessment task behaviour and performance but are difficult to study empirically. The study combined qualitative data from focus group interviews with 22 students and 4 teachers, with quantitative real-time learning analytics (facial expression, mouse click and keyboard strokes) to examine student emotional engagement in…
Descriptors: Psychological Patterns, Student Evaluation, Learning Analytics, Learner Engagement
Zheng, Lanqin; Zhong, Lu; Fan, Yunchao – Education and Information Technologies, 2023
Online collaborative learning (OCL) has been a mainstream pedagogy in the field of higher education. However, learners often produce off-topic information and engage less during online collaborative learning compared to other approaches. In addition, learners often cannot converge in knowledge, and they often do not know how to coregulate with…
Descriptors: Electronic Learning, Cooperative Learning, Undergraduate Students, Learning Analytics
Elena Drugova; Irina Zhuravleva; Ulyana Zakharova; Adel Latipov – Journal of Computer Assisted Learning, 2024
Background: Driven by the ongoing need to provide high-quality learning and teaching, universities recently have shown an increased interest in using learning analytics (LA) for improving learning design (LD). However, the evidence of such improvements is scarce, and the maturity of such research is unclear. Objectives: This study is aimed to…
Descriptors: Learning Analytics, Instructional Design, Higher Education, Instructional Improvement
Lu, Chang; Cutumisu, Maria – International Journal of Educational Technology in Higher Education, 2022
In traditional school-based learning, attendance was regarded as a proxy for engagement and key indicator for performance. However, few studies have explored the effect of in-class attendance in technology-enhanced courses that are increasingly provided by secondary institutions. This study collected n = 367 undergraduate students' log files from…
Descriptors: Learner Engagement, Academic Achievement, Formative Evaluation, Attendance Patterns
Kew, Si Na; Tasir, Zaidatun – Education and Information Technologies, 2022
The emergence of Learning Analytics has brought benefits to the educational field, as it can be used to analyse authentic data from students to identify the problems encountered in e-learning and to provide intervention to assist students. However, much is still unknown about the development of Learning Analytics intervention in terms of providing…
Descriptors: Learning Analytics, Intervention, Electronic Learning, Educational Technology
Krishnamoorthy, Lakshmi; Merchant, Zahira – Pedagogical Research, 2023
Persuasion is inherent to the instructional process. Instructions delivered through online programs do not always generate expected and consistent learning outcomes, and hence persuasion in online instructional design is even more critical. Through this mixed-method study, we aim to identify the most widely used persuasive design techniques, the…
Descriptors: Persuasive Discourse, Instructional Design, Electronic Learning, Learner Engagement
Gomathy Ramaswami; Teo Susnjak; Anuradha Mathrani – Journal of Learning Analytics, 2023
Learning Analytics Dashboards (LADs) are gaining popularity as a platform for providing students with insights into their learning behaviour patterns in online environments. Existing LAD studies are mainly centred on displaying students' online behaviours with simplistic descriptive insights. Only a few studies have integrated predictive…
Descriptors: Learner Engagement, Learning Analytics, Electronic Learning, Student Behavior
Brown, Alice; Lawrence, Jill; Basson, Marita; Redmond, Petrea – Higher Education Research and Development, 2022
Student engagement is consistently identified as a key predictor of learner outcomes within the online learning environment. However, there is limited guidance about using proactive strategies to improve engagement for low and non-engaged students: for example by specifically employing course learning analytics (CLA) and nudging strategies in…
Descriptors: Electronic Learning, Learner Engagement, Instructional Improvement, College Instruction
Utamachant, Piriya; Anutariya, Chutiporn; Pongnumkul, Suporn – Smart Learning Environments, 2023
Apart from good instructional design and delivery, effective intervention is another key to strengthen student academic performance. However, intervention has been recognized as a great challenge. Most instructors struggle to identify at-risk students, determine a proper intervention approach, trace and evaluate whether the intervention works.…
Descriptors: Intervention, Learning Analytics, Learning Management Systems, Programming
Richard M. Baylis; Malcolm J. Beynon – Accounting Education, 2024
Lecture Capture (LC) material is accepted to be an available and accessible resource for students in universities across the world. This exploratory study investigates the "when viewing" LC material engagement of accounting undergraduate students. Three categories of engagement are defined, Near-Event-Viewing (NEV), Get-Round-to-Viewing…
Descriptors: Accounting, Lecture Method, Teaching Methods, Undergraduate Students
Torres Castro, Uriel Eduardo; Pineda-Báez, Clelia – Journal of Further and Higher Education, 2023
The objective of this article is to analyse the development and content of research in the global literature on student agency in higher education (SAHE) based on a bibliometric review of 224 articles published in the Scopus database during the period 2000-2022. VOSviewer, Excel, and Tableau software were used to analyse the texts. The review…
Descriptors: Personal Autonomy, Higher Education, Social Cognition, Student Motivation
Erkan Er; Safak Silik; Sergen Cansiz – Journal of Learning Analytics, 2024
E-learning platforms have become increasingly popular in K--8 education to promote student learning and enhance classroom teaching. Student interactions with these platforms produce trace data, which are digital records of learning processes. Although trace data have been effective in identifying learners' engagement profiles in higher education…
Descriptors: Foreign Countries, Elementary Secondary Education, Grade 1, Grade 2