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Abdullah Saykili; Sinan Aydin; Yusuf Zafer Can Ugurhan; Aylin Öztürk; Mustafa Kemal Birgin – Technology, Knowledge and Learning, 2025
Learning analytics offer unprecedented opportunities for tracking and storing learning behaviors, thereby providing chances for optimizing learner engagement and success. The limited adoption of learning analytics by educational institutions hinders efforts to optimize learning processes through organizational and educational interventions,…
Descriptors: Undergraduate Students, Online Courses, Learning Analytics, Student Characteristics
Conrad Borchers; Zachary A. Pardos – Journal of Learning Analytics, 2025
Inadequate consideration of course workload in undergraduate students' course selections has contributed to adverse academic outcomes. At the same time, credit hours, the default institutional metric to convey time-based course workload to students, has been shown to capture students' experienced workload insufficiently. Recent research documents…
Descriptors: Course Selection (Students), Difficulty Level, Undergraduate Students, Learning Analytics
Priya Harindranathan; James Folkestad; Jemshid K. – Journal of Educational Technology, 2025
Due to the use of online learning platforms and learning management systems, students are now working unsupervised on quiz-taking platforms. These unsupervised online forms of assessment are replacing traditional supervised quizzes in conventional classrooms. It is unclear whether the quiz-taking behaviors of students in these settings align with…
Descriptors: Undergraduate Students, Microbiology, Science Education, Computer Assisted Testing
Kasra Lekan; Zachary A. Pardos – Journal of Learning Analytics, 2025
Choosing an undergraduate major is an important decision that impacts academic and career outcomes. In this work, we investigate augmenting personalized human advising for major selection using a large language model (LLM), GPT-4. Through a three-phase survey, we compare GPT suggestions and responses for undeclared first- and second-year students…
Descriptors: Technology Uses in Education, Artificial Intelligence, Academic Advising, Majors (Students)
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
Aylin Ozturk; Robin Schmucker; Tom Mitchell; Alper Tolga Kumtepe – International Educational Data Mining Society, 2025
This study investigates the heterogeneity in the effects of a Learning Analytics Dashboard (LAD) intervention, which provides personalized feedback messages, across a diverse population of learners. Specifically, it evaluates the impact of the LAD on learners' total material usage and final grades, considering variables such as age, sex, prior…
Descriptors: Learning Analytics, Learning Management Systems, Feedback (Response), Grades (Scholastic)
Khalid Alalawi; Rukshan Athauda; Raymond Chiong; Ian Renner – Education and Information Technologies, 2025
Learning analytics intervention (LAI) studies aim to identify at-risk students early during an academic term using predictive models and facilitate educators to provide effective interventions to improve educational outcomes. A major impediment to the uptake of LAI is the lack of access to LAI infrastructure by educators to pilot LAI, which…
Descriptors: Intervention, Learning Analytics, Guidelines, Prediction
Maya Usher; Noga Reznik; Gilad Bronshtein; Dan Kohen-Vacs – Journal of Learning Analytics, 2025
Computational thinking (CT) is a critical 21st-century skill that equips undergraduate students to solve problems systematically and think algorithmically. A key component of CT is computational creativity, which enables students to generate novel solutions within programming constraints. Humanoid robots are increasingly explored as promising…
Descriptors: Computation, Thinking Skills, Creativity, Robotics
René Lobo-Quintero – Journal of Learning Analytics, 2025
This study investigates the integration of artificial intelligence into the Think-Pair-Share (TPS) methodology through a learning analytics lens. Using a mixed-methods quasi-experimental design (N=140), we examined how an AI-enhanced collaborative platform influences creative thinking among computer science undergraduates. The experimental group…
Descriptors: Artificial Intelligence, Cooperative Learning, Creative Thinking, Undergraduate Students
Jelena Jovanovic; Andrew Zamecnik; Abhinava Barthakur; Shane Dawson – Education and Information Technologies, 2025
Higher education institutions are increasingly seeking ways to leverage the available educational data to make program and course quality improvements. The development of automated curriculum analytics can play a substantial role in this effort by bringing novel and timely insights into course and program quality. However, the adoption of…
Descriptors: Learning Analytics, Curriculum Evaluation, Evaluation Methods, Educational Objectives
Chang Lu; Okan Bulut; Carrie Demmans Epp; Mark Gierl – Distance Education, 2025
Engagement is essential for improving academic outcomes, especially in technology-enhanced learning (TEL) environments where self-regulated learning is critical. This study investigated the longitudinal impacts of different levels of engagement on undergraduate students' short-term and long-term academic outcomes in TEL. Using a learning analytics…
Descriptors: Learner Engagement, Outcomes of Education, Technology Uses in Education, Educational Technology
Mustafa Tepgec; Joana Heil; Dirk Ifenthaler – Assessment & Evaluation in Higher Education, 2025
Despite the widespread implementation of learning analytics (LA)-based feedback systems, there exists a gap in empirical investigations regarding their influence on learning outcomes. Moreover, existing research primarily focuses on individual differences, such as self-regulation and motivation, overlooking the potential of feedback literacy (FL).…
Descriptors: Feedback (Response), Learning Analytics, Outcomes of Education, Transfer of Training
Hanall Sung; Mitchell J. Nathan – International Journal of Educational Technology in Higher Education, 2025
In various technology-enhanced learning (TEL) environments, knowledge co-creation progresses through multimodal interactions that integrate verbal and nonverbal modalities, such as speech and gestures. This study investigated two distinct analytical approaches for analyzing multimodal interactions--triangulating and interleaving--by applying them…
Descriptors: Technology Uses in Education, Epistemology, Research and Development, Nonverbal Learning
J. M. Fernández Oro; P. García Regodeseves; L. Santamaría Bertolín; J. González Pérez; R. Barrio-Perotti; A. Pandal Blanco – Technology, Knowledge and Learning, 2025
Learning Analytics tools are employed to assess student engagement with the Virtual Campus in an undergraduate Fluid Mechanics course at university level in Spain. This is aimed at obtaining a diagnosis of the course problematics which include low attendance rates, poor performance on activity tests and exams and a high number of re-enrolments. A…
Descriptors: Learning Analytics, Electronic Learning, Undergraduate Study, Mechanics (Physics)
Tanjun Liu; Dana Gablasova – Computer Assisted Language Learning, 2025
Collocations, a crucial component of language competence, remain a challenge for L2 learners across all proficiency levels. While the data-driven learning (DDL) approach has shown great potential for collocation learning from a shorter-term perspective, this study investigates its effectiveness in the long term, examining both linguistic gains and…
Descriptors: Phrase Structure, Learning Analytics, English (Second Language), Second Language Instruction
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