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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
Youqin Pan; Jian Gu – International Journal of Technology in Teaching and Learning, 2023
This paper explores the potential of using Chat Generative PreTrained Transformer (ChatGPT), a powerful language model, as an innovative tool to enhance education in the classroom. Drawing from firsthand experience, this paper demonstrates how ChatGPT can be integrated into the teaching and learning process of statistics and data analytics…
Descriptors: Teaching Methods, Learning Processes, Artificial Intelligence, Computer Software
Congning Ni; Bhashithe Abeysinghe; Juanita Hicks – International Electronic Journal of Elementary Education, 2025
The National Assessment of Educational Progress (NAEP), often referred to as The Nation's Report Card, offers a window into the state of U.S. K-12 education system. Since 2017, NAEP has transitioned to digital assessments, opening new research opportunities that were previously impossible. Process data tracks students' interactions with the…
Descriptors: Reaction Time, Multiple Choice Tests, Behavior Change, National Competency Tests
From Observation to Action: Enhancing Principal Candidates' Growth through Sequenced Practicum Tasks
Thomas Harvey; Donna Fong; Daryl Ann Borel; Johnny O’Connor – International Journal of Educational Leadership Preparation, 2025
This study explored the perceptions of principal candidates and their field supervisors regarding the impact of coherently sequenced practicum tasks on candidates' instructional leadership skills. The findings revealed that the quality of practicum experiences and the development of professional relationships between candidates and supervisors are…
Descriptors: Principals, Administrator Attitudes, Administrator Education, Supervisor Supervisee Relationship
Sheejamol P. T.; Anu Mary Chacko; S. D. Madhu Kumar – Electronic Journal of e-Learning, 2025
Traditional education, characterized by rigid curricula and inflexible teaching methods, often fails to accommodate the diverse cognitive profiles of neurodivergent learners, including those with Autism Spectrum Disorder (ASD), Attention Deficit Hyperactivity Disorder (ADHD), and dyslexia. Although e-Learning has introduced greater flexibility and…
Descriptors: Individualized Instruction, Gamification, Electronic Learning, Students with Disabilities
Emmanuel Amos; Harry Barton Essel; George Kwame Fobiri; Akwasi Adomako Boakye; Yaw Boateng Ampadu – SAGE Open, 2025
The increasing number of students in higher education has led to the formation of large class teaching and learning environments, which is a threat to quality education. The Department of Fashion Design and Textiles Studies of Kumasi Technical University is one such department that is facing this challenge. Computer-based technology has…
Descriptors: Foreign Countries, College Students, Design, Computer Uses in Education
Atasoy, Eda; Bozna, Harun; Sönmez, Abdulvahap; Aydin Akkurt, Ayse; Tuna Büyükköse, Gamze; Firat, Mehmet – Asian Association of Open Universities Journal, 2020
Purpose: This study aims to investigate the futuristic visions of PhD students at Distance Education department of Anadolu University on the use of learning analytics (LA) and mobile technologies together. Design/methodology/approach: This qualitative research study, designed in the single cross-section model, aimed to reveal futuristic visions of…
Descriptors: Active Learning, Learning Analytics, Handheld Devices, Student Attitudes
Han, Feifei; Pardo, Abelardo; Ellis, Robert A. – Journal of Computer Assisted Learning, 2020
This study examines the extent to which the learning orientations identified by student self-reports and the observation of their online learning events were related to each other and to their academic performance. The participants were 322 first-year engineering undergraduates, who were enrolled in a blended course. Using students' self-report on…
Descriptors: College Students, Electronic Learning, Blended Learning, Curriculum Design
Karaoglan Yilmaz, Fatma Gizem; Yilmaz, Ramazan – Technology, Knowledge and Learning, 2020
There is a growing interest in the use of learning analytics in higher education institutions. Learning analytics also appear to have the potential to be used to provide personalized feedback and support in online learning. However, when the literature is examined, the use of learning analytics for this purpose appears as a gap to be investigated.…
Descriptors: Student Attitudes, Individualized Instruction, Electronic Learning, Feedback (Response)
Ifenthaler, Dirk; Yau, Jane Yin-Kim – Educational Technology Research and Development, 2020
Study success includes the successful completion of a first degree in higher education to the largest extent, and the successful completion of individual learning tasks to the smallest extent. Factors affecting study success range from individual dispositions (e.g., motivation, prior academic performance) to characteristics of the educational…
Descriptors: Learning Analytics, Higher Education, Educational Research, Academic Achievement
Ghallabi, Sameh; Essalmi, Fathi; Jemni, Mohamed; Kinshuk – Education and Information Technologies, 2020
With the emergence of technology, the personalization of e-learning systems is enhanced. These systems use a set of parameters for personalizing courses. However, in literature, these parameters are not based on classification and optimization algorithms to implement them in the cloud. Cloud computing is a new model of computing where standard and…
Descriptors: Electronic Learning, Internet, Information Storage, Models
Avila, Cecilia; Baldiris, Silvia; Fabregat, Ramon; Graf, Sabine – British Journal of Educational Technology, 2020
The learning analytics (LA) field seeks to analyze data about students' interactions, and it has been applied in the development of tools for supporting both learning and teaching processes. Recent research has paid attention on how LA may benefit teachers in the creation of educational resources. However, most of the research on LA solutions is…
Descriptors: Learning Analytics, Open Educational Resources, Teacher Developed Materials, Instructional Material Evaluation
Zhao, Qun; Wang, Jin-Long; Pao, Tsang-Long; Wang, Li-Yu – Journal of Educational Technology Systems, 2020
This study uses the log data from Moodle learning management system for predicting student learning performance in the first third of a semester. Since the quality of the data has great influence on the accuracy of machine learning, five major data transmission methods are used to enhance data quality of log file in the data preprocessing stage.…
Descriptors: Classification, Learning, Accuracy, Prediction
Whitelock-Wainwright, Alexander; Gaševic, Dragan; Tsai, Yi-Shan; Drachsler, Hendrik; Scheffel, Maren; Muñoz-Merino, Pedro J.; Tammets, Kairit; Delgado Kloos, Carlos – Journal of Computer Assisted Learning, 2020
To assist higher education institutions in meeting the challenge of limited student engagement in the implementation of Learning Analytics services, the Questionnaire for Student Expectations of Learning Analytics (SELAQ) was developed. This instrument contains 12 items, which are explained by a purported two-factor structure of "Ethical and…
Descriptors: Questionnaires, Test Construction, Test Validity, Learning Analytics
Monllaó Olivé, David; Huynh, Du Q.; Reynolds, Mark; Dougiamas, Martin; Wiese, Damyon – Journal of Computing in Higher Education, 2020
Both educational data mining and learning analytics aim to understand learners and optimise learning processes of educational settings like Moodle, a learning management system (LMS). Analytics in an LMS covers many different aspects: finding students at risk of abandoning a course or identifying students with difficulties before the assessments.…
Descriptors: Identification, At Risk Students, Potential Dropouts, Online Courses

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