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Showing all 15 results Save | Export
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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
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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
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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
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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
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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
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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
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Xu, Zhuojia; Yuan, Hua; Liu, Qishan – IEEE Transactions on Education, 2021
Contribution: This article explored blended learning by implementing a student-centered teaching method based on the flipped classroom and small private online course (SPOC). The impact of general online learning behavior on student performance was analyzed. This work is practical and provides enlightenment for learning analysis and individualized…
Descriptors: Academic Achievement, Blended Learning, Prediction, Performance Factors
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Saqr, Mohammed; Jovanovic, Jelena; Viberg, Olga; Gaševic, Dragan – Studies in Higher Education, 2022
Predictors of student academic success do not always replicate well across different learning designs, subject areas, or educational institutions. This suggests that characteristics of a particular discipline and learning design have to be carefully considered when creating predictive models in order to scale up learning analytics. This study…
Descriptors: Meta Analysis, Learning Analytics, Predictor Variables, Correlation
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Zhang, Jia-Hua; Zou, Liu-cong; Miao, Jia-jia; Zhang, Ye-Xing; Hwang, Gwo-Jen; Zhu, Yue – Interactive Learning Environments, 2020
Extensive studies have been conducted to diagnose and predict students' academic performance by analyzing a large amount of data related to their learning behaviors in a blended learning environment. But there is a lack of research examining how individualized learning interventions could improve students' academic performance in such a learning…
Descriptors: Individualized Instruction, Academic Achievement, Interaction, Blended Learning
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Georgakopoulos, Ioannis; Chalikias, Miltiadis; Zakopoulos, Vassilis; Kossieri, Evangelia – Education Sciences, 2020
Our modern era has brought about radical changes in the way courses are delivered and various teaching methods are being introduced to answer the purpose of meeting the modern learning challenges. On that account, the conventional way of teaching is giving place to a teaching method which combines conventional instructional strategies with…
Descriptors: Academic Failure, Blended Learning, Learner Engagement, Student Participation
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Shabnam Ara S. J.; Tanuja R. – Journal of Education and e-Learning Research, 2024
Understanding the factors that influence students' results in hybrid learning environments is becoming increasingly important in today's educational environment. The goal of this research is to examine factors that influence students' academic performance as well as their level of participation in blended learning environments. A comprehensive…
Descriptors: Academic Achievement, Blended Learning, Learning Analytics, Technology Education
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Han, Feifei; Ellis, Robert – Australasian Journal of Educational Technology, 2020
This study combined the methods from student approaches to learning and learning analytics research by using both self-reported and observational measures to examine the student learning experience. It investigated the extent to which reported approaches and perceptions and observed online interactions are related to each other and how they…
Descriptors: Measurement Techniques, Observation, Learning Analytics, Data Collection
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Kohnke, Lucas; Foung, Dennis; Chen, Julia – SAGE Open, 2022
Blended learning pedagogical practices supported by learning management systems have become an important part of higher education curricula. In most cases, these blended curricula are evaluated through multimodal formative assessments. Although assessments can strongly affect student outcomes, research on the topic is limited. In this paper, we…
Descriptors: Formative Evaluation, Higher Education, Outcomes of Education, Learning Analytics
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Foung, Dennis; Chen, Julia – Electronic Journal of e-Learning, 2019
In recent years, research using learning analytics to predict learning outcomes has begun to increase. This emerging field of research advocates the use of readily-available data to inform teaching and learning. The current case study adopts a learning analytics approach to evaluate the online learning package of an academic English course in a…
Descriptors: Foreign Countries, Blended Learning, Electronic Learning, English for Academic Purposes
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Santiago Berrezueta Ed. – Lecture Notes in Educational Technology, 2023
The proceedings of the 18th edition of Latin American Conference on Learning Technologies (LACLO) demonstrates the developments in the research of learning science, learning resources, challenges and solutions. This Proceedings book showcases a collection of quality articles that explores and discusses trending topics in education in the upcoming…
Descriptors: Educational Technology, Active Learning, Design, Telecommunications