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Predictive Model to Analyze Real and Synthetic Data for Learners' Performance Prediction Using Regression Techniques
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Shabnam Ara S. J.; Tanuja Ramachandriah; Manjula S. Haladappa – Online Learning, 2025
Predicting learner performance with precision is critical within educational systems, offering a basis for tailored interventions and instruction. The advent of big data analytics presents an opportunity to employ Machine Learning (ML) techniques to this end. Real-world data availability is often hampered by privacy concerns, prompting a shift…
Descriptors: Learning Analytics, Privacy, Artificial Intelligence, Regression (Statistics)
The Growth of Contemporary Music Subject and the Reform of Music Teaching in Universities
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Binbin Zhao; Rim Razzouk – International Journal of Web-Based Learning and Teaching Technologies, 2024
In order to promote the growth of contemporary music and the reform of music, this article designs an improved collaborative filtering (CF) algorithm to solve the problem of sparse matrix in traditional recommendation algorithms. The data matrix is dimensionally reduced to find the nearest neighbor, so as to realize personalized recommendation of…
Descriptors: Music Education, Higher Education, Teaching Methods, Matrices
Multimodal Learning Analytics and Neurofeedback for Optimizing Online Learners' Self-Regulation
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Han, Insook; Obeid, Iyad; Greco, Devon – Technology, Knowledge and Learning, 2023
This report describes the use of electroencephalography (EEG) to collect online learners' physiological information. Recent technological advancements allow the unobtrusive collection of live neurosignals while learners are engaged in online activities. In the context of multimodal learning analytics, we discuss the potential use of this new…
Descriptors: Learning Analytics, Diagnostic Tests, Metacognition, Brain Hemisphere Functions
Artificial Intelligence Applications in Education: Natural Language Processing in Detecting Misconceptions
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Yunus Kökver; Hüseyin Miraç Pektas; Harun Çelik – Education and Information Technologies, 2025
This study aims to determine the misconceptions of teacher candidates about the greenhouse effect concept by using Artificial Intelligence (AI) algorithm instead of human experts. The Knowledge Discovery from Data (KDD) process model was preferred in the study where the Analyse, Design, Develop, Implement, Evaluate (ADDIE) instructional design…
Descriptors: Artificial Intelligence, Misconceptions, Preservice Teachers, Natural Language Processing
Design Analytics for Mobile Learning: Scaling up the Classification of Learning Designs Based on Cognitive and Contextual Elements
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Pishtari, Gerti; Prieto, Luis P.; Rodriguez-Triana, Maria Jesus; Martinez-Maldonado, Roberto – Journal of Learning Analytics, 2022
This research was triggered by the identified need in literature for large-scale studies about the kinds of designs that teachers create for mobile learning (m-learning). These studies require analyses of large datasets of learning designs. The common approach followed by researchers when analyzing designs has been to manually classify them…
Descriptors: Scaling, Classification, Context Effect, Telecommunications
Bring It On! Challenges Encountered While Building a Comprehensive Tutoring System Using "Readerbench"
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Marilena Panaite; Mihai Dascalu; Amy Johnson; Renu Balyan; Jianmin Dai; Danielle S. McNamara; Stefan Trausan-Matu – Grantee Submission, 2018
Intelligent Tutoring Systems (ITSs) are aimed at promoting acquisition of knowledge and skills by providing relevant and appropriate feedback during students' practice activities. ITSs for literacy instruction commonly assess typed responses using Natural Language Processing (NLP) algorithms. One step in this direction often requires building a…
Descriptors: Intelligent Tutoring Systems, Artificial Intelligence, Algorithms, Decision Making
Increasing Computational Protein Design Literacy through Cohort-Based Learning for Undergraduate Students
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Erin C. Yang; Robby Divine; Christine S. Kang; Sidney Chan; Elijah Arenas; Zoe Subol; Peter Tinker; Hayden Manninen; Alicia Feichtenbiner; Talal Mustafa; Julia Hallowell; Isiac Orr; Hugh Haddox; Brian Koepnick; Jacob O'Connor; Ian C. Haydon; Karla-Luise Herpoldt; Kandise Van Wormer; Celine Abell; David Baker; Alena Khmelinskaia; Neil P. King – Journal of Chemical Education, 2022
Undergraduate research experiences can improve student success in graduate education and STEM careers. During the COVID-19 pandemic, undergraduate researchers at our institution and many others lost their work-study research positions due to interruption of in-person research activities. This imposed a financial burden on the students and…
Descriptors: Undergraduate Students, Teaching Methods, COVID-19, Pandemics