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Mengke Wang; Taotao Long; Na Li; Yawen Shi; Zengzhao Chen – Education and Information Technologies, 2025
Feedback plays an indispensable role in pre-service teachers' microteaching practice. It provides essential information about their microteaching performance, which is of great significance in their reflection and improvement. As AI and teaching analytics advance, feedback is no longer exclusively human-generated. AI technologies are increasingly…
Descriptors: Feedback (Response), Preservice Teachers, Microteaching, Reflection
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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
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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
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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
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Riina Kleimola; Laura Hirsto; Heli Ruokamo – Education and Information Technologies, 2025
Learning analytics provides a novel means to support the development and growth of students into self-regulated learners, but little is known about student perspectives on its utilization. To address this gap, the present study proposed the following research question: what are the perceptions of higher education students on the utilization of a…
Descriptors: Self Management, College Students, Learning Analytics, Student Development
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Christopher C. Y. Yang; Jiun-Yu Wu; Hiroaki Ogata – Education and Information Technologies, 2025
Blended learning (BL) combines traditional classroom activities with online learning resources, enabling students to obtain higher academic performance through well-defined interactive learning strategies. However, lacking the capacity to self-regulate their learning, many students might fail to comprehensively study the learning materials after…
Descriptors: Blended Learning, Educational Technology, Learning Analytics, Self Management
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Zhicheng Dai; Yue Yang; Zengzhao Chen; Ling Wang; Liang Zhao; Xiaoliang Zhu; Junxia Xiong – Education and Information Technologies, 2025
Higher education is beginning to focus on how to effectively cultivate IoT engineers who possess both hard skills and soft skills. Therefore, from the perspective of activity theory and combining it with project-based learning, this study constructed a project-based learning framework based on activity theory and applied this framework to an IoT…
Descriptors: Active Learning, Student Projects, Teacher Effectiveness, Instructional Effectiveness
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Yunus Kökver; Hüseyin Miraç Pektas; Harun Çelik – Education and Information Technologies, 2025
This study aims to determine the misconceptions of teacher candidates about the greenhouse effect concept by using Artificial Intelligence (AI) algorithm instead of human experts. The Knowledge Discovery from Data (KDD) process model was preferred in the study where the Analyse, Design, Develop, Implement, Evaluate (ADDIE) instructional design…
Descriptors: Artificial Intelligence, Misconceptions, Preservice Teachers, Natural Language Processing
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Yuxiao Xie; Ziyi Xie; Siyu Chen; Lei Shen; Zhizhuang Duan – Education and Information Technologies, 2025
The National College English Test Band 4 (CET-4) is a key test to assess the English language ability of Chinese university students, and the success rate of the test is important to improve the quality of their English learning. Artificial intelligence technology can be used to predict and explore the factors influencing the success rate. This…
Descriptors: Language Tests, English (Second Language), Second Language Learning, Second Language Instruction
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Yiming Liu; Xiao Hu; Jeremy Tzi Dong Ng; Zhengyang Ma; Xiaoyan Lai – Education and Information Technologies, 2025
Collaborative problem solving (CPS) has emerged as a crucial 21st century competence that benefits students' studies, future careers, and general well-being, prevailing across disciplines and learning approaches. Given the complex and dynamic nature of CPS, teacher-facing learning analytics dashboards (LADs) have increasingly been adopted to…
Descriptors: Learning Analytics, Learning Management Systems, Student Evaluation, Cooperation