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Marc Burchart; Joerg M. Haake – IEEE Transactions on Learning Technologies, 2024
In distance education courses with a large number of students and groups, the organization and facilitation of collaborative writing tasks are challenging. Teachers need support for planning, specification, execution, monitoring, and evaluation of collaborative writing tasks in their course. This requires a collaborative learning platform for…
Descriptors: Writing Instruction, Distance Education, Large Group Instruction, Learning Management Systems
Hua Ma; Wen Zhao; Yuqi Tang; Peiji Huang; Haibin Zhu; Wensheng Tang; Keqin Li – IEEE Transactions on Learning Technologies, 2024
To prevent students from learning risks and improve teachers' teaching quality, it is of great significance to provide accurate early warning of learning performance to students by analyzing their interactions through an e-learning system. In existing research, the correlations between learning risks and students' changing cognitive abilities or…
Descriptors: College Students, Learning Analytics, Learning Management Systems, Academic Achievement
Liu, Fang; Zhao, Liang; Zhao, Jiayi; Dai, Qin; Fan, Chunlong; Shen, Jun – IEEE Transactions on Learning Technologies, 2022
Educational process mining is now a promising method to provide decision-support information for the teaching-learning process via finding useful educational guidance from the event logs recorded in the learning management system. Existing studies mainly focus on mining students' problem-solving skills or behavior patterns and intervening in…
Descriptors: Data Use, Learning Management Systems, Problem Solving, Learning Processes
Sonja Kleter; Uwe Matzat; Rianne Conijn – IEEE Transactions on Learning Technologies, 2024
Much of learning analytics research has focused on factors influencing model generalizability of predictive models for academic performance. The degree of model generalizability across courses may depend on aspects, such as the similarity of the course setup, course material, the student cohort, or the teacher. Which of these contextual factors…
Descriptors: Prediction, Models, Academic Achievement, Learning Analytics
Lin, Jian-Wei; Koong Lin, Hao-Chiang; Chen, Hong-Ren – IEEE Transactions on Learning Technologies, 2022
Conventional e-learning platforms require a high self-regulatory learning (SRL) ability to ensure learning effectiveness. However, because not everyone has high autonomy and a high SRL ability, many students quit during the online learning period. To enhance the SRL ability, many studies have developed e-learning platforms based on Zimmerman's SRL…
Descriptors: Metacognition, Role Models, Learning Strategies, Personal Autonomy
Uto, Masaki; Nguyen, Duc-Thien; Ueno, Maomi – IEEE Transactions on Learning Technologies, 2020
With the wide spread large-scale e-learning environments such as MOOCs, peer assessment has been popularly used to measure the learner ability. When the number of learners increases, peer assessment is often conducted by dividing learners into multiple groups to reduce the learner's assessment workload. However, in such cases, the peer assessment…
Descriptors: Item Response Theory, Electronic Learning, Peer Evaluation, Accuracy
Conijn, Rianne; Snijders, Chris; Kleingeld, Ad; Matzat, Uwe – IEEE Transactions on Learning Technologies, 2017
With the adoption of Learning Management Systems (LMSs) in educational institutions, a lot of data has become available describing students' online behavior. Many researchers have used these data to predict student performance. This has led to a rather diverse set of findings, possibly related to the diversity in courses and predictor variables…
Descriptors: Blended Learning, Predictor Variables, Predictive Validity, Predictive Measurement
Ruano, Ildefonso; Gamez, Javier; Dormido, Sebastian; Gomez, Juan – IEEE Transactions on Learning Technologies, 2016
Online laboratories are useful and valuable resources in high education, especially in engineering studies. This work presents a methodology to create effective laboratories for learning that interact with a Learning Management System (LMS) to achieve advanced integration. It is based on pedagogical aspects and considers not only the laboratory…
Descriptors: Management Systems, Laboratories, Teaching Methods, Computer Simulation