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Behzad Mirzababaei; Viktoria Pammer-Schindler – IEEE Transactions on Learning Technologies, 2024
In this article, we investigate a systematic workflow that supports the learning engineering process of formulating the starting question for a conversational module based on existing learning materials, specifying the input that transformer-based language models need to function as classifiers, and specifying the adaptive dialogue structure,…
Descriptors: Learning Processes, Electronic Learning, Artificial Intelligence, Natural Language Processing
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Zheng, Yafeng; Gao, Zhanghao; Shen, Jun; Zhai, Xuesong – IEEE Transactions on Learning Technologies, 2023
A text semantic classification is an essential approach to recognizing the verbal intention of online learners, empowering reliable understanding, and inquiry for the regulations of knowledge construction amongst students. However, online learning is increasingly switching from static watching patterns to the collaborative discussion. The current…
Descriptors: Semantics, Classification, Electronic Learning, Computer Mediated Communication
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Sirinda Palahan – IEEE Transactions on Learning Technologies, 2025
The rise of online programming education has necessitated more effective personalized interactions, a gap that PythonPal aims to fill through its innovative learning system integrated with a chatbot. This research delves into PythonPal's potential to enhance the online learning experience, especially in contexts with high student-to-teacher ratios…
Descriptors: Programming, Computer Science Education, Artificial Intelligence, Computer Mediated Communication
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Giacomo Cassano; Nicoletta Di Blas – IEEE Transactions on Learning Technologies, 2024
In recent years, the world of education has become increasingly hybrid (online/on location) and flexible (synchronous/asynchronous), frequently referred to as HyFlex. One of the risks of these mixed environments is the distance between teacher and students that can make interaction, a crucial component of the teaching/learning process, more…
Descriptors: Electronic Learning, Asynchronous Communication, Teacher Student Relationship, Feedback (Response)
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Atapattu, Thushari; Falkner, Katrina; Thilakaratne, Menasha; Sivaneasharajah, Lavendini; Jayashanka, Rangana – IEEE Transactions on Learning Technologies, 2020
The substantial growth of online learning, and in particular, through massively open online courses (MOOCs), supports research into nontraditional learning contexts. Learners' confusion is one of the identified aspects which impact the overall learning process, and ultimately, course attrition. Confusion for a learner is an individual state of…
Descriptors: Electronic Learning, Online Courses, Psychological Patterns, Learning Processes
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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
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Zheng, Xiao-Lin; Chen, Chao-Chao; Hung, Jui-Long; He, Wu; Hong, Fu-Xing; Lin, Zhen – IEEE Transactions on Learning Technologies, 2015
The needs for life-long learning and the rapid development of information technologies promote the development of various types of online Community of Practices (CoPs). In online CoPs, bounded rationality and metacognition are two major issues, especially when learners face information overload and there is no knowledge authority within the…
Descriptors: Metacognition, Communities of Practice, Computer Mediated Communication, Comparative Analysis
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Alario-Hoyos, Carlos; Pérez-Sanagustin, Mar; Delgado-Kloos, Carlos; Parada G., Hugo A.; Muñoz-Organero, Mario – IEEE Transactions on Learning Technologies, 2014
This paper presents an in-depth empirical analysis of a nine-week MOOC. This analysis provides novel results regarding participants' profiles and use of built-in and external social tools. The results served to detect seven participants' patterns and conclude that the forum was the social tool preferred to contribute to the MOOC.
Descriptors: Profiles, Online Courses, Computer Science Education, Distance Education
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Anwar, M.; Greer, J. – IEEE Transactions on Learning Technologies, 2012
This research explores a new model for facilitating trust in online e-learning activities. We begin by protecting the privacy of learners through identity management (IM), where personal information can be protected through some degree of participant anonymity or pseudonymity. In order to expect learners to trust other pseudonymous participants,…
Descriptors: Computer Mediated Communication, Discussion, Client Server Architecture, Online Courses
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Thoms, Brian – IEEE Transactions on Learning Technologies, 2011
In this research, we examine the design, construction, and implementation of a dynamic, easy to use, feedback mechanism for social software. The tool was integrated into an existing university's online learning community (OLC). In line with constructivist learning models and practical information systems (IS) design, the feedback system provides…
Descriptors: Social Networks, Web Sites, Electronic Publishing, Electronic Learning