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Il Do Ha – Measurement: Interdisciplinary Research and Perspectives, 2024
Recently, deep learning has become a pervasive tool in prediction problems for structured and/or unstructured big data in various areas including science and engineering. In particular, deep neural network models (i.e. a basic core model of deep learning) can be viewed as an extension of statistical models by going through the incorporation of…
Descriptors: Artificial Intelligence, Statistical Analysis, Models, Algorithms
A Method for Generating Course Test Questions Based on Natural Language Processing and Deep Learning
Hei-Chia Wang; Yu-Hung Chiang; I-Fan Chen – Education and Information Technologies, 2024
Assessment is viewed as an important means to understand learners' performance in the learning process. A good assessment method is based on high-quality examination questions. However, generating high-quality examination questions manually by teachers is a time-consuming task, and it is not easy for students to obtain question banks. To solve…
Descriptors: Natural Language Processing, Test Construction, Test Items, Models
Zhaozhen Xu; Amelia Howarth; Nicole Briggs; Nello Cristianini – International Journal of Artificial Intelligence in Education, 2024
Questions have a critical role in learning and teaching. People ask questions to obtain information and express interest in ideas. The Bristol scientific centre "We The Curious" launched "Project What If" in 2017 to inspire residents of Bristol to record their questions and pursue their curiosities. Researching these questions…
Descriptors: Questioning Techniques, Science Teaching Centers, Museums, Science Education
Radek Pelánek – International Journal of Artificial Intelligence in Education, 2025
While the potential of personalized education has long been emphasized, the practical adoption of adaptive learning environments has been relatively slow. Discussion about underlying reasons for this disparity often centers on factors such as usability, the role of teachers, or privacy concerns. Although these considerations are important, I argue…
Descriptors: Educational Environment, Modeling (Psychology), Barriers, Adjustment (to Environment)
George Veletsianos; Shandell Houlden; Nicole Johnson – TechTrends: Linking Research and Practice to Improve Learning, 2024
Much of the literature on artificial intelligence (AI) in education imagines AI as a tool in the service of teaching and learning. Is such a one-way relationship all that exists between AI and learners? In this paper we report on a thematic analysis of 92 participant responses to a story completion exercise which asked them to describe a classroom…
Descriptors: Artificial Intelligence, Technology Uses in Education, Man Machine Systems, Interaction
Glenn Hardaker; Liyana Eliza Glenn – International Journal of Information and Learning Technology, 2025
Purpose: The purpose of this systematic literature review is to identify the antecedents that have enabled the adoption of artificial intelligence (AI) in Higher Education (HE) institutions at both a macro and micro level. The term adoption is in reference to the diffusion of technology that is actively chosen for use by the targeted demographic.…
Descriptors: Artificial Intelligence, Individualized Instruction, Technology Uses in Education, Higher Education
Alexis Lebis; Jérémie Humeau; Anthony Fleury; Flavien Lucas; Mathieu Vermeulen – International Journal of Artificial Intelligence in Education, 2024
The personalization of curriculum plays a pivotal role in supporting students in achieving their unique learning goals. In recent years, researchers have dedicated efforts to address the challenge of personalizing curriculum through diverse techniques and approaches. However, it is crucial to acknowledge the phenomenon of student forgetting, as…
Descriptors: Individualized Instruction, Curriculum Development, Curriculum Implementation, Memory
Adil Baqach; Amal Battou – Education and Information Technologies, 2024
Nowadays, e-learning is a significant learning option, especially in light of the COVID-19 pandemic. However, it is a very challenging task because, in online courses, tutors have no direct interaction with students, which causes most of them to lose interest and ultimately drop out of their studies. In regular classes, teachers can see how each…
Descriptors: MOOCs, Student Attitudes, Student Reaction, Tutors
Justin Edwards; Andy Nguyen; Joni Lämsä; Marta Sobocinski; Ridwan Whitehead; Belle Dang; Anni-Sofia Roberts; Sanna Järvelä – British Journal of Educational Technology, 2025
Socially shared regulation of learning (SSRL) is a crucial process for groups of learners to successfully collaborate. Detecting and supporting SSRL is a challenge, especially in real time, but hybrid intelligence approaches such as Artificial Intelligence (AI) agents may make this possible. Leveraging the concept of trigger events which invite…
Descriptors: Artificial Intelligence, Computer Software, Technology Uses in Education, Metacognition
S. Siva Shankar; Bui Thanh Hung; Prasun Chakrabarti; Tulika Chakrabarti; Gayatri Parasa – Education and Information Technologies, 2024
Modern life is increasingly influenced by networks, making cybersecurity a crucial area of study. However, due to their few resources and varied makeup, they are more vulnerable to a wide range of cyber-attacks. Such risks result in sensitive information being stolen as well as financial and reputational harm to firms. How far malicious detection…
Descriptors: Learning Processes, Artificial Intelligence, Information Security, Computer Security
Hugo-Henrik Hachem; Fredrik Heintz – International Journal of Lifelong Education, 2024
AI's opportunities and potential high-risk consequences for individuals and societies render mass AI literacy imperative. MOOCs are one effective conduit for its provision. However, MOOCs remain epistemologically one-sided when lifelong learning steadily shifts towards a reflexive epistemology whereby subjectivities and expert knowledge intersect,…
Descriptors: Artificial Intelligence, MOOCs, Technological Literacy, Reflection
Deliang Wang; Gaowei Chen – IEEE Transactions on Education, 2024
Contributions: To address the interpretability issues in artificial intelligence (AI)-powered classroom discourse models, we employ explainable AI methods to unpack classroom discourse analysis from deep learning-based models and evaluate the effects of model explanations on STEM teachers. Background: Deep learning techniques have been used to…
Descriptors: Artificial Intelligence, STEM Education, Learning Processes, Technology Uses in Education
Carvalho, Floran; Henriet, Julien; Greffier, Francoise; Betbeder, Marie-Laure; Leon-Henri, Dana – Journal of Education and e-Learning Research, 2023
This research is part of the Artificial Intelligence Virtual Trainer (AI-VT) project which aims to create a system that can identify the user's skills from a text by means of machine learning. AI-VT is a case-based reasoning learning support system can generate customized exercise lists that are specially adapted to user needs. To attain this…
Descriptors: Learning Processes, Algorithms, Artificial Intelligence, Programming Languages
Siren, Anni; Tzerpos, Vassilios – IEEE Transactions on Learning Technologies, 2022
Learning paths are curated sequences of resources organized in a way that a learner has all the prerequisite knowledge needed to achieve their learning goals. In this article, we systematically map the techniques and algorithms that are needed to create such learning paths automatically. We focus on open educational resources (OER), though a…
Descriptors: Open Educational Resources, Artificial Intelligence, Instructional Materials, Educational Technology
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