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Facilitating the Learning Engineering Process for Educational Conversational Modules Using Transformer-Based Language Models
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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
Where is the Learning in Learning Analytics? A Systematic Literature Review on the Operationalization of Learning-Related Constructs in the Evaluation of Learning Analytics Interventions
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Knobbout, Justian; van der Stappen, Esther – IEEE Transactions on Learning Technologies, 2020
Learning technologies enable interventions in the learning process aiming to improve learning. Learning analytics provides such interventions based on analysis of learner data, which are believed to have beneficial effects on both learning and the learning environment. Literature reporting on the effects of learning analytics interventions on…
Descriptors: Learning Analytics, Intervention, Educational Research, Outcomes of Education
What Do Linguistic Expressions Tell Us about Learners' Confusion? A Domain-Independent Analysis in MOOCs
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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
Data Capture and Multimodal Learning Analytics Focused on Engagement with a New Wearable IoT Approach
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Camacho, Vicente Lopez; de la Guia, Elena; Olivares, Teresa; Flores, M. Julia; Orozco-Barbosa, Luis – IEEE Transactions on Learning Technologies, 2020
Increasing school dropout rates are a problem in many educational systems, with student disengagement being one significant factor. Learning analytics is a new field with a key role in educational institutions in the coming years. It may help make strategic decisions to reduce student disengagement. The use of technology in educational…
Descriptors: Learning Analytics, Learner Engagement, Measurement Equipment, Technology Uses in Education
Automatic Personality Identification Using Students' Online Learning Behavior
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Lai, Song; Sun, Bo; Wu, Fati; Xiao, Rong – IEEE Transactions on Learning Technologies, 2020
Adaptive e-learning can be used to personalize learning environment for students to meet their individual demands. Individual differences depend on the students' personality traits. Numerous studies have indicated that understanding the role of personality in the learning process can facilitate learning. Hence, personality identification in…
Descriptors: Personality Traits, Electronic Learning, Individual Differences, Learning Processes
Mining Social Media Data for Understanding Students' Learning Experiences
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Chen, Xin; Vorvoreanu, Mihaela; Madhavan, Krishna – IEEE Transactions on Learning Technologies, 2014
Students' informal conversations on social media (e.g., Twitter, Facebook) shed light into their educational experiences--opinions, feelings, and concerns about the learning process. Data from such uninstrumented environments can provide valuable knowledge to inform student learning. Analyzing such data, however, can be challenging. The complexity…
Descriptors: Social Media, Data Analysis, Sleep, Engineering Education