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Showing 1 to 15 of 37 results Save | Export
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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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Sha, Lele; Rakovic, Mladen; Lin, Jionghao; Guan, Quanlong; Whitelock-Wainwright, Alexander; Gasevic, Dragan; Chen, Guanliang – IEEE Transactions on Learning Technologies, 2023
In online courses, discussion forums play a key role in enhancing student interaction with peers and instructors. Due to large enrolment sizes, instructors often struggle to respond to students in a timely manner. To address this problem, both traditional machine learning (ML) (e.g., Random Forest) and deep learning (DL) approaches have been…
Descriptors: Computer Mediated Communication, Discussion Groups, Artificial Intelligence, Intelligent Tutoring Systems
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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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Jose Barambones; Cristian Moral; Angelica de Antonio; Ricardo Imbert; Loic Martinez-Normand; Elena Villalba-Mora – IEEE Transactions on Learning Technologies, 2024
Before interacting with real users, developers must be proficient in human--computer interaction (HCI) so as not to exhaust user patience and availability. For that, substantial training and practice are required, but it is costly to create a variety of high-quality HCI training materials. In this context, chat generative pretrained transformer…
Descriptors: Artificial Intelligence, Synchronous Communication, Computer Mediated Communication, Man Machine Systems
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Belle Li; Curtis J. Bonk; Chaoran Wang; Xiaojing Kou – IEEE Transactions on Learning Technologies, 2024
This exploratory analysis investigates the integration of ChatGPT in self-directed learning (SDL). Specifically, this study examines YouTube content creators' language-learning experiences and the role of ChatGPT in their SDL, building upon Song and Hill's conceptual model of SDL in online contexts. Thematic analysis of interviews with 19…
Descriptors: Independent Study, Language Acquisition, Artificial Intelligence, 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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Andre, Maverick; Mello, Rafael Ferreira; Nascimento, Andre; Lins, Rafael Dueire; Gasevic, Dragan – IEEE Transactions on Learning Technologies, 2021
Social presence is an essential construct of the well-known Community of Inquiry (CoI) model, which is created to support design, facilitation, and analysis of asynchronous online discussions. Social presence focuses on the extent to which participants of online discussions can see each other as "real persons" in computer-mediated…
Descriptors: Communities of Practice, Interpersonal Relationship, Computer Mediated Communication, Asynchronous 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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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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Neto, Valter; Rolim, Vitor; Pinheiro, Anderson; Lins, Rafael Dueire; Gasevic, Dragan; Mello, Rafael Ferreira – IEEE Transactions on Learning Technologies, 2021
This article investigates the impact of educational contexts on automatic classification of online discussion messages according to cognitive presence, an essential construct of the community of inquiry model. In particular, the work reported in the article analyzed online discussion messages written in Brazilian Portuguese from two different…
Descriptors: Foreign Countries, Computer Mediated Communication, Discussion, Content Analysis
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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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Geller, Shay A.; Gal, Kobi; Segal, Avi; Sripathi, Kamali; Kim, Hyunsoo G.; Facciotti, Marc T.; Igo, Michele; Hoernle, Nicholas; Karger, David – IEEE Transactions on Learning Technologies, 2021
This article provides computational and rule-based approaches for detecting confusion that is expressed in students' comments in couse forums. To obtain reliable, ground truth data about which posts exhibit student confusion, we designed a decision tree that facilitates the manual labeling of forum posts by experts. However, manual labeling is…
Descriptors: Identification, Misconceptions, Student Attitudes, Computer Mediated Communication
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Jin, Sung-Hee – IEEE Transactions on Learning Technologies, 2021
Participation dashboards in online discussions are learning support tools that can have a positive effect on learners' learning outcomes and satisfaction levels, but their effectiveness differs according to how learners recognize and interpret them. However, there is a lack of research investigating the effectiveness of visualization methods…
Descriptors: Asynchronous Communication, Discussion, Computer Mediated Communication, Peer Relationship
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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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Bioglio, Livio; Capecchi, Sara; Peiretti, Federico; Sayed, Dennis; Torasso, Antonella; Pensa, Ruggero G. – IEEE Transactions on Learning Technologies, 2019
In this paper, we address the problem of enhancing young people's awareness of the mechanisms involving privacy in online social networks by presenting an innovative approach based on gamification. In particular, we propose a web application that allows kids and teenagers to experience the typical dynamics of information spread through a realistic…
Descriptors: Privacy, Social Media, Children, Adolescents
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