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Halimi, Khaled; Seridi-Bouchelaghem, Hassina – Australasian Journal of Educational Technology, 2021
Traditional content-based assessment systems, which depend on the score as a key criterion for students' evaluation, have proven to have many drawbacks, especially with the development of learning methods in recent years. Based on these developments, there is a need to adopt new assessment methods to assess the actual skills of students in the…
Descriptors: Performance Based Assessment, Learning Analytics, Alternative Assessment, Student Evaluation
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Praharaj, Sambit; Scheffel, Maren; Drachsler, Hendrik; Specht, Marcus – IEEE Transactions on Learning Technologies, 2021
Collaboration is one of the important 21st-century skills. It can take place in remote or co-located settings. Co-located collaboration (CC) is a very complex process that involves subtle human interactions that can be described with indicators like eye gaze, speaking time, pitch, and social skills from different modalities. With the advent of…
Descriptors: Learning Analytics, 21st Century Skills, Learning Modalities, Task Analysis
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Ouyang, Fan; Chen, Si; Li, Xu – British Journal of Educational Technology, 2021
Social learning analytics (SLA) tools are designed to visually demonstrate online discussions with a goal to foster student engagement. However, empirical studies indicate controversial results of the effect of SLA tools on student engagement. This design-based research designs a student-facing SLA tool to demonstrate discussions from three…
Descriptors: Learning Analytics, Visual Aids, Learner Engagement, Discussion
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Tsiakmaki, Maria; Kostopoulos, Georgios; Kotsiantis, Sotiris; Ragos, Omiros – Journal of Computing in Higher Education, 2021
Predicting students' learning outcomes is one of the main topics of interest in the area of Educational Data Mining and Learning Analytics. To this end, a plethora of machine learning methods has been successfully applied for solving a variety of predictive problems. However, it is of utmost importance for both educators and data scientists to…
Descriptors: Active Learning, Predictor Variables, Academic Achievement, Learning Analytics
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Amarasinghe, Ishari; Hernández-Leo, Davinia; Ulrich Hoppe, H. – International Journal of Computer-Supported Collaborative Learning, 2021
Under the notion of "CSCL scripts", different pedagogical models for structuring and supporting collaboration in the classroom have been proposed. We report on a practical experience with scripts based on the Pyramid collaborative learning flow pattern supported by a specific classroom tool and a teacher-facing dashboard that implements…
Descriptors: Cooperative Learning, Computer Assisted Instruction, Scripts, Learning Analytics
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Liu, Min; Pan, Zilong; Li, Chenglu; Han, Songhee; Shi, Yi; Pan, Xin – International Journal on E-Learning, 2021
There has been an increasing interest in learning analytics (LA) research especially in higher education (HE) in recent years. In this study, we conducted a systematic focused review of research, from 2016 to present, on using analytics in HE (specifically system- or user-generated data) to understand in what way such analytics has been…
Descriptors: Learning Analytics, Educational Research, Higher Education, Data Collection
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Yang, Christopher C. Y.; Chen, Irene Y. L.; Ogata, Hiroaki – Educational Technology & Society, 2021
Precision education is now recognized as a new challenge of applying artificial intelligence, machine learning, and learning analytics to improve both learning performance and teaching quality. To promote precision education, digital learning platforms have been widely used to collect educational records of students' behavior, performance, and…
Descriptors: Learning Analytics, Individualized Instruction, Instructional Materials, Books
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Sahin, Muhittin; Ulucan, Aydin; Yurdugül, Halil – Education and Information Technologies, 2021
E-learning environments can store huge amounts of data on the interaction of learners with the content, assessment and discussion. Yet, after the identification of meaningful patterns or learning behaviour in the data, it is necessary to use these patterns to improve learning environments. It is notable that designs to benefit from these patterns…
Descriptors: Electronic Learning, Data Collection, Decision Making, Evaluation Criteria
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Zhao, Fuzheng; Hwang, Gwo-Jen; Yin, Chengjiu – Educational Technology & Society, 2021
Educational data mining and learning analytics have become a very important topic in the field of education technology. Many frameworks have been proposed for learning analytics which make it possible to identify learning behavior patterns or strategies. However, it is difficult to understand the reason why behavior patterns occur and why certain…
Descriptors: Behavior Patterns, Reading, Textbooks, Electronic Learning
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Tetzlaff, Leonard; Schmiedek, Florian; Brod, Garvin – Educational Psychology Review, 2021
Personalized education--the systematic adaptation of instruction to individual learners--has been a long-striven goal. We review research on personalized education that has been conducted in the laboratory, in the classroom, and in digital learning environments. Across all learning environments, we find that personalization is most successful when…
Descriptors: Individualized Instruction, Instructional Effectiveness, Instructional Design, Student Characteristics
Majumdar, Rwitajit; Bakilapadavu, Geetha; Majumder, Reek; Chen, Mei-Rong Alice; Flanagan, Brendan; Ogata, Hiroaki – Research and Practice in Technology Enhanced Learning, 2021
This study investigates learner's reading behaviors in a critical reading task in humanities course using learning analytics techniques. "A Critical Analysis of Literature and Cinema" course was selected as a context. The course activities evolved over 10 years, and for this instance, some face-to-face classroom critical reading…
Descriptors: Learning Analytics, Humanities, Critical Reading, Electronic Publishing
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Mahmoud, Mai; Dafoulas, Georgios; Abd ElAziz, Rasha; Saleeb, Noha – International Journal of Information and Learning Technology, 2021
Purpose: The objective of this paper is to present a comprehensive review of the literature on learning analytics (LA) stakeholders' expectations to reveal the status of ongoing research in this area and to highlight gaps in research. Design/methodology/approach: Conducting a literature review is a well-known method to establish knowledge and…
Descriptors: Learning Analytics, Stakeholders, Expectation, Higher Education
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Tsutsumi, Emiko; Kinoshita, Ryo; Ueno, Maomi – International Educational Data Mining Society, 2021
Knowledge tracing (KT), the task of tracking the knowledge state of each student over time, has been assessed actively by artificial intelligence researchers. Recent reports have described that Deep-IRT, which combines Item Response Theory (IRT) with a deep learning model, provides superior performance. It can express the abilities of each student…
Descriptors: Item Response Theory, Prediction, Accuracy, Artificial Intelligence
Grace Jackson – ProQuest LLC, 2021
Higher education institutions (HEIs) implementing learning analytics (LA) use student data to improve the learning experience. The problem for LA implementation originates from individuals responsible for analytic programs from different institutional departments and the lack of a framework for communication and productive dialogue about usages of…
Descriptors: Higher Education, Educational Research, Learning Analytics, Program Implementation
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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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