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Samit Bhattacharya; Ujjwal Biswas; Shubham Damkondwar; Bhupender Yadav – Education and Information Technologies, 2024
Classroom monitoring using information communications technology (ICT) plays a significant role in enhancing teaching-learning in a blended learning environment. Learning analytics (LA) is such a popular classroom monitoring tool. LA helps teachers to the collection, interpretation, and analysis of students performance data generated during…
Descriptors: Information Technology, Learning Analytics, Blended Learning, Classroom Techniques
Irene Benedetto; Moreno La Quatra; Luca Cagliero; Lorenzo Canale; Laura Farinetti – Education and Information Technologies, 2024
Modern educational technology systems allow learners to access large amounts of learning materials such as educational videos, learning notes, and teaching books. Automated summarization techniques simplify the access and exploration of complex data collections by producing synthetic versions of the original content. This paper addresses the…
Descriptors: Learning Analytics, Documentation, Blended Learning, Video Technology
Oleksandra Poquet; Sven Trenholm; Marc Santolini – Educational Technology Research and Development, 2024
Interpersonal online interactions are key to digital learning pedagogies and student experiences. Researchers use learner log and text data collected by technologies that mediate learner interactions online to provide indicators about interpersonal interactions. However, analytical approaches used to derive these indicators face conceptual,…
Descriptors: Computer Mediated Communication, Interpersonal Communication, Online Courses, Discussion
Yang, Christopher C. Y.; Ogata, Hiroaki – Education and Information Technologies, 2023
The application of student interaction data is a promising field for blended learning (BL), which combines conventional face-to-face and online learning activities. However, the application of online learning technologies in BL settings is particularly challenging for students with lower self-regulatory abilities. In this study, a personalized…
Descriptors: Individualized Instruction, Learning Analytics, Intervention, Academic Achievement
Zhang, Shu; Yi, Jidong; Li, Zijie; Yang, Minghong – International Journal of Information and Communication Technology Education, 2022
In this paper, CiteSpace is used to conduct metrological and visual analysis of the core journals of blended learning research (2003-2021) collected by the China National Knowledge Infrastructure (CNKI). The results show that the number of studies on blended learning in China is increasing year by year, which indicates that the research on blended…
Descriptors: Foreign Countries, Blended Learning, Educational Research, Educational Trends
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
Eady, Michelle J.; Green, Corinne A.; Fulcher, David; Boniface, Tim – Journal of Further and Higher Education, 2022
Research has demonstrated a correlation between lecture attendance and students' academic achievement. However, students may not attend lectures for a variety of reasons. The provision of lecture recordings online can also negatively impact lecture attendance and student achievement. These facts implore us to be courageous and explore new…
Descriptors: Learning Analytics, Undergraduate Study, Curriculum Design, Teacher Education Curriculum
Du, Xiaoming; Ge, Shilun; Wang, Nianxin – International Journal of Information and Communication Technology Education, 2022
In the context of education big data, it uses data mining and learning analysis technology to accurately predict and effectively intervene in learning. It is helpful to realize individualized teaching and individualized teaching. This research analyzes student life behavior data and learning behavior data. A model of student behavior…
Descriptors: Prediction, Data, Student Behavior, Academic Achievement
Brott, Pamelia E. – Open Learning, 2023
This practical, practice-based article sets out to define and describe vlogging based on the author's experiences while teaching a blended learning course. Vlogging is a short duration video recording that engages the learner in critical self-reflection. It is a scaffolding strategy for moving students from a descriptive diary to situated…
Descriptors: Video Technology, Reflection, Educational Technology, Learning Analytics
Li, Kam Cheong; Wong, Billy Tak-ming – Journal of Computing in Higher Education, 2023
This paper reports a comprehensive review of literature on personalised learning in STEM and STEAM (or STE(A)M) education, which involves the disciplinary integration of Science, Technology, Engineering, and Mathematics, as well as Arts. The review covered the contexts of STE(A)M education where personalised learning was adopted, the objectives of…
Descriptors: Individualized Instruction, STEM Education, Art Education, Educational Objectives
Jennifer Scianna; Rogers Kaliisa – Educational Technology Research and Development, 2024
Educational researchers have pointed to socioemotional dimensions of learning as important in gaining a more nuanced description of student engagement and learning. However, to date, research focused on the analysis of emotions has been narrow in its focus, centering on affect and sentiment analysis in isolation while neglecting how emotions…
Descriptors: Computer Mediated Communication, Discussion, Discourse Analysis, Asynchronous Communication
Yangyang Luo; Xibin Han; Chaoyang Zhang – Asia Pacific Education Review, 2024
Learning outcomes can be predicted with machine learning algorithms that assess students' online behavior data. However, there have been few generalized predictive models for a large number of blended courses in different disciplines and in different cohorts. In this study, we examined learning outcomes in terms of learning data in all of the…
Descriptors: Prediction, Learning Management Systems, Blended Learning, Classification
Sudeshna Pal; Patsy Moskal; Anchalee Ngampornchai – International Journal on E-Learning, 2024
This study investigated the effectiveness of blended instruction in enhancing student success in an advanced undergraduate engineering course. The research used learning analytics captured from pre-recorded lecture videos, course grade data, and student surveys. Results revealed positive correlations between lecture video viewership and course…
Descriptors: Blended Learning, Advanced Courses, Engineering Education, Undergraduate Students
Yang, Christopher C. Y.; Ogata, Hiroaki – Educational Technology & Society, 2023
Blended learning (BL) is regarded as an effective strategy for combining traditional face-to-face classroom activities with various types of online learning tools (e.g., e-books). An effective feature of e-books is the ability to use digital notes. When e-books are used in BL, the strategic adoption of note-taking provides benefits that influence…
Descriptors: Blended Learning, Sequential Approach, Notetaking, Electronic Publishing
Wu, Xinli; Chang, Jie; Lian, Fei; Jiang, Liheng; Liu, Juntong; Yasrab, Robail – International Journal of Information and Communication Technology Education, 2022
The rapid development of big data technology has attracted a variety of sectors, including tertiary education. The purpose of this paper is to construct a precision teaching mode based on big data technology in order to improve teaching quality and further promote education and teaching reform. The proposed mode, based on the theory of precision…
Descriptors: Precision Teaching, Learning Analytics, Teacher Evaluation, Programming Languages