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Srikanth Allamsetty; M. V. S. S. Chandra; Neelima Madugula; Byamakesh Nayak – IEEE Transactions on Learning Technologies, 2024
The present study is related to the problem associated with student assessment with online examinations at higher educational institutes (HEIs). With the current COVID-19 outbreak, the majority of educational institutes are conducting online examinations to assess their students, where there would always be a chance that the students go for…
Descriptors: Computer Assisted Testing, Accountability, Higher Education, Comparative Analysis
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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
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Qi Lang; Shengjing Tian; Mo Wang; Jianan Wang – IEEE Transactions on Learning Technologies, 2024
Entrepreneurship education is critical in encouraging students' innovation, creativity, and entrepreneurial spirit. It provides essential skills and knowledge, enabling them to open their creative potential and apply innovative thinking across diverse professional fields. With the widespread application of large language models in education,…
Descriptors: Entrepreneurship, Business Administration Education, Artificial Intelligence, Creativity
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Vo, Thi Ngoc Chau; Nguyen, Phung – IEEE Transactions on Learning Technologies, 2021
A course-level early final study status prediction task is to predict as soon as possible the final success of each student after studying a course. It is significant because each successful course accomplishment is required for a degree. Further, early predictions provide enough time to make necessary changes for ultimate success. This article…
Descriptors: Prediction, Academic Achievement, Data Collection, Learning Processes
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Kim, Hodam; Chae, Younsoo; Kim, Suhye; Im, Chang-Hwan – IEEE Transactions on Learning Technologies, 2023
Owing to the rapid development of information and communication technologies, online or mobile learning content is widely available on the Internet. Unlike traditional face-to-face learning, online learning exhibits a critical limitation: real-time interactions between learners and teachers are generally not feasible in online learning. To…
Descriptors: College Students, Control Groups, Attention, Comprehension
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Xiuyu Lin; Zehui Zhan; Xuebo Zhang; Jiayi Xiong – IEEE Transactions on Learning Technologies, 2024
The attribution of learning success or failure is crucial for students' learning and motivation. Effective attribution of their learning success or failure in the context of a small private online course (SPOC) could generate students' motivation toward learning success while an incorrect attribution would lead to a sense of helplessness. Based on…
Descriptors: Learning Analytics, Learning Processes, Learning Motivation, Attribution Theory
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Jiaqi Yin; Tiong-Thye Goh; Yi Hu – IEEE Transactions on Learning Technologies, 2024
This study aimed to examine sustainable effects of chatbot-based formative feedback on intrinsic motivation, cognitive load, and learning performance. A longitudinal quasi-experimental design with 173 undergraduate students was conducted. The experiment is a between-subject design. Students either received formative feedback from a chatbot or a…
Descriptors: Artificial Intelligence, Synchronous Communication, Feedback (Response), Longitudinal Studies
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Saint, John; Whitelock-Wainwright, Alexander; Gasevic, Dragan; Pardo, Abelardo – IEEE Transactions on Learning Technologies, 2020
The recent focus on learning analytics (LA) to analyze temporal dimensions of learning holds the promise of providing insights into latent constructs, such as learning strategy, self-regulated learning (SRL), and metacognition. These methods seek to provide an enriched view of learner behaviors beyond the scope of commonly used correlational or…
Descriptors: Undergraduate Students, Engineering Education, Learning Analytics, Learning Strategies
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Meng, Lingling; Zhang, Wanxue; Chu, Yu; Zhang, Mingxin – IEEE Transactions on Learning Technologies, 2021
With the rapid advancement of education, personalized learning has gained considerable attention in recent years. Learning path plays an important role in this area and has attracted great concern. Many generating mechanisms have been proposed from different perspectives for assisting learning. Some methods focus on learners' interest, while some…
Descriptors: Educational Diagnosis, Individualized Instruction, Learning Processes, Cognitive Ability
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Wan, Han; Zhong, Zihao; Tang, Lina; Gao, Xiaopeng – IEEE Transactions on Learning Technologies, 2023
Small private online courses (SPOCs) have influenced teaching and learning in China's higher education. Learning management systems (LMSs) are important components in SPOCs. They can collect various data related to student behavior and support pedagogical interventions. This research used feature engineering and nearest neighbor smoothing models…
Descriptors: Online Courses, Learning Management Systems, Higher Education, Student Behavior
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Ueno, Maomi; Miyazawa, Yoshimitsu – IEEE Transactions on Learning Technologies, 2018
Over the past few decades, many studies conducted in the field of learning science have described that scaffolding plays an important role in human learning. To scaffold a learner efficiently, a teacher should predict how much support a learner must have to complete tasks and then decide the optimal degree of assistance to support the learner's…
Descriptors: Scaffolding (Teaching Technique), Prediction, Probability, Comparative Analysis
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Mejia, Carolina; Florian, Beatriz; Vatrapu, Ravi; Bull, Susan; Gomez, Sergio; Fabregat, Ramon – IEEE Transactions on Learning Technologies, 2017
Existing tools aim to detect university students with early diagnosis of dyslexia or reading difficulties, but there are not developed tools that let those students better understand some aspects of their difficulties. In this paper, a dashboard for visualizing and inspecting early detected reading difficulties and their characteristics, called…
Descriptors: Clinical Diagnosis, Dyslexia, Visualization, Metacognition
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Tempelaar, Dirk T.; Rienties, Bart; Nguyen, Quan – IEEE Transactions on Learning Technologies, 2017
Studies in the field of learning analytics (LA) have shown students' demographics and learning management system (LMS) data to be effective identifiers of "at risk" performance. However, insights generated by these predictive models may not be suitable for pedagogically informed interventions due to the inability to explain why students…
Descriptors: Student Behavior, Integrated Learning Systems, Personality, Educational Research
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Ruipérez-Valiente, Jose A.; Muñoz-Merino, Pedro J.; Kloos, Carlos Delgado; Niemann, Katja; Scheffel, Maren; Wolpers, Martin – IEEE Transactions on Learning Technologies, 2016
Self-regulated learning (SRL) environments provide students with activities to improve their learning (e.g., by solving exercises), but they might also provide optional activities (e.g., changing an avatar image or setting goals) where students can decide whether they would like to use or do them and how. Few works have dealt with the use of…
Descriptors: Metacognition, Learning Processes, Case Studies, Learning Activities
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Amelung, M.; Krieger, K.; Rosner, D. – IEEE Transactions on Learning Technologies, 2011
Assessment is an essential element in learning processes. It is therefore not unsurprising that almost all learning management systems (LMSs) offer support for assessment, e.g., for the creation, execution, and evaluation of multiple choice tests. We have designed and implemented generic support for assessment that is based on assignments that…
Descriptors: Learning Processes, Programming Languages, Assignments, Programming
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