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Wenyi Lu; Joseph Griffin; Troy D. Sadler; James Laffey; Sean P. Goggins – Journal of Learning Analytics, 2025
Game-based learning (GBL) is increasingly recognized as an effective tool for teaching diverse skills, particularly in science education, due to its interactive, engaging, and motivational qualities, along with timely assessments and intelligent feedback. However, more empirical studies are needed to facilitate its wider application in school…
Descriptors: Game Based Learning, Predictor Variables, Evaluation Methods, Educational Games
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)
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
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
Yousri Attia Mohamed Abouelenein; Shaimaa Abdul Salam Selim; Tahani Ibrahim Aldosemani – Smart Learning Environments, 2025
Learning analytics provides valuable data to inform the best decisions for each learner. This study, based on adaptive environment (AE) learning analytics dashboards, examines how instructor interventions affect student self-regulation abilities and academic performance. It identifies the self-regulation categories requiring the most support to…
Descriptors: Foreign Countries, Higher Education, Preservice Teachers, Learning Analytics
Dimitrios Tzimas; Stavros Demetriadis – TechTrends: Linking Research and Practice to Improve Learning, 2025
Learning analytics (LA) is an educational innovation that enhances teaching practices and facilitates student learning. However, the degree of LA adoption across schools remains limited, and teachers who adopt LA do not engage with it consistently. Based on the unified theory of acceptance and use of technology (UTAUT) as a framework, we conducted…
Descriptors: Learning Analytics, Kindergarten, Elementary Secondary Education, Teacher Attitudes
Wen-shuang Fu; Jia-hua Zhang; Di Zhang; Tian-tian Li; Min Lan; Na-na Liu – Journal of Educational Computing Research, 2025
Cognitive ability is closely associated with the acquisition of programming skills, and enhancing learners' cognitive ability is a crucial factor in improving the efficacy of programming education. Adaptive feedback strategies can provide learners with personalized support based on their learning context, which helps to stimulate their interest…
Descriptors: Feedback (Response), Cognitive Ability, Programming, Computer Science Education
Conrad Borchers; Cindy Peng; Qianru Lyu; Paulo F. Carvalho; Kenneth R. Koedinger; Vincent Aleven – Grantee Submission, 2025
Many AIED systems support self-regulated learning, yet, support for setting and achieving practice goals has received little attention. We examine how middle school students respond to system-recommended practice goals, building on the success of similar data-driven recommendations in other domains. We introduce an adaptive dashboard in an…
Descriptors: Goal Orientation, Student Attitudes, Self Control, Intelligent Tutoring Systems
Jeongwon Lee; Dongho Kim – Journal of Computing in Higher Education, 2025
Although learning analytics dashboards (LADs) are being recognized as tools that can enhance engagement--a crucial factor for the success of asynchronous online higher education--their impact may be limited without a solid theoretical basis for motivation. Furthermore, the processes through which students make decisions using dashboards and engage…
Descriptors: Self Determination, Learning Analytics, Educational Technology, Learner Engagement
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)
Yiqiu Zhou; Jina Kang; Yeyu Wang; Muhammad Ashiq – Educational Technology Research and Development, 2025
The complex processes of collaborative knowledge construction require a multimodal approach to capture the interplay between learners, tools, and the environment. While existing studies have recognized the importance of considering multiple modalities, there remains a need for a comprehensive framework that explicitly models the dynamics of…
Descriptors: Cooperative Learning, Computer Simulation, Astronomy, Network Analysis
Teija Paavilainen; Sonsoles López-Pernas; Sanna Väisänen; Sini Kontkanen; Laura Hirsto – Technology, Knowledge and Learning, 2025
In digitalized learning processes, learning analytics (LA) can help teachers make pedagogically sound decisions and support pupils' self-regulated learning (SRL). However, research on the role of the pedagogical dimensions of learning design (LD) in influencing the possibilities of LA remains scarce. Primary school presents a unique LA context…
Descriptors: Learning Analytics, Independent Study, Elementary Education, Instructional Design
Seyma Ulukok-Yildirim; Duygu Sonmez – Journal of Education in Science, Environment and Health, 2025
Today, the importance of artificial intelligence in science learning and teaching is rapidly increasing. The growing interest in this field and the resulting increase in academic publications on the subject make it challenging to understand its progress and trends on a global scale. Furthermore, a literature review reveals a notable lack of…
Descriptors: Bibliometrics, Literature Reviews, Artificial Intelligence, Science Education
Hussain, Sadiq; Gaftandzhieva, Silvia; Maniruzzaman, Md.; Doneva, Rositsa; Muhsin, Zahraa Fadhil – Education and Information Technologies, 2021
Educational data mining helps the educational institutions to perform effectively and efficiently by exploiting the data related to all its stakeholders. It can help the at-risk students, develop recommendation systems and alert the students at different levels. It is beneficial to the students, educators and authorities as a whole. Deep learning…
Descriptors: Regression (Statistics), Academic Achievement, Learning Analytics, Models
Ifenthaler, Dirk, Ed.; Sampson, Demetrios G., Ed.; Isaías, Pedro, Ed. – Cognition and Exploratory Learning in the Digital Age, 2021
This volume focuses on the implications of digital technologies for educators and educational decision makers that is not widely represented in the literature. While there are many volumes on how one might integrate a particular technology, there are no volumes on how digital technologies can or should be exploited to address the needs and propel…
Descriptors: Educational Technology, Technology Integration, Learning Processes, Learning Analytics

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