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Andrea Zanellati; Daniele Di Mitri; Maurizio Gabbrielli; Olivia Levrini – IEEE Transactions on Learning Technologies, 2024
Knowledge tracing is a well-known problem in AI for education, consisting of monitoring how the knowledge state of students changes during the learning process and accurately predicting their performance in future exercises. In recent years, many advances have been made thanks to various machine learning and deep learning techniques. Despite their…
Descriptors: Artificial Intelligence, Prior Learning, Knowledge Management, Models
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
Kasra Lekan; Zachary A. Pardos – Journal of Learning Analytics, 2025
Choosing an undergraduate major is an important decision that impacts academic and career outcomes. In this work, we investigate augmenting personalized human advising for major selection using a large language model (LLM), GPT-4. Through a three-phase survey, we compare GPT suggestions and responses for undeclared first- and second-year students…
Descriptors: Technology Uses in Education, Artificial Intelligence, Academic Advising, Majors (Students)
Kelli A. Bird; Benjamin L. Castleman; Yifeng Song – Journal of Policy Analysis and Management, 2025
Predictive analytics are increasingly pervasive in higher education. However, algorithmic bias has the potential to reinforce racial inequities in postsecondary success. We provide a comprehensive and translational investigation of algorithmic bias in two separate prediction models--one predicting course completion, the second predicting degree…
Descriptors: Algorithms, Technology Uses in Education, Bias, Racism
Ujjwal Biswas; Samit Bhattacharya – Education and Information Technologies, 2024
The application of machine learning (ML) has grown and is now used to enhance learning outcomes. In blended classroom settings, ML, emerging smartphones and wearable technologies are commonly used to improve teaching and learning. The combination of these advanced technologies and ML plays a crucial role in enhancing real-time feedback quality.…
Descriptors: Artificial Intelligence, Blended Learning, Flipped Classroom, Technology Uses in Education
Mayer, Christian W. F.; Ludwig, Sabrina; Brandt, Steffen – Journal of Research on Technology in Education, 2023
This study investigates the potential of automated classification using prompt-based learning approaches with transformer models (large language models trained in an unsupervised manner) for a domain-specific classification task. Prompt-based learning with zero or few shots has the potential to (1) make use of artificial intelligence without…
Descriptors: Prompting, Classification, Artificial Intelligence, Natural Language Processing
Jian-Wei Tzeng; Nen-Fu Huang; Yi-Hsien Chen; Ting-Wei Huang; Yu-Sheng Su – Educational Technology & Society, 2024
Massive open online courses (MOOCs; online courses delivered over the Internet) enable distance learning without time and place constraints. MOOCs are popular; however, active participation level among students who take MOOCs is generally lower than that among students who take in-person courses. Students who take MOOCs often lack guidance, and…
Descriptors: MOOCs, Artificial Intelligence, Electronic Learning, Student Participation
Alshurideh, Muhammad; Al Kurdi, Barween; Salloum, Said A.; Arpaci, Ibrahim; Al-Emran, Mostafa – Interactive Learning Environments, 2023
Despite the plethora of m-learning acceptance studies, few have tackled the importance of examining the actual use of m-learning systems from the lenses of social influence, expectation-confirmation, and satisfaction. Additionally, most of the prior technology adoption literature tends to use the structural equation modeling (SEM) technique in…
Descriptors: Electronic Learning, Prediction, Least Squares Statistics, Structural Equation Models
Arantes, Janine Aldous – Australian Educational Researcher, 2023
Recent negotiations of 'data' in schools place focus on student assessment and NAPLAN. However, with the rise in artificial intelligence (AI) underpinning educational technology, there is a need to shift focus towards the value of teachers' digital data. By doing so, the broader debate surrounding the implications of these technologies and rights…
Descriptors: Foreign Countries, Elementary Secondary Education, Electronic Learning, Artificial Intelligence
Odiel Estrada-Molina; Juanjo Mena; Alexander López-Padrón – International Review of Research in Open and Distributed Learning, 2024
No records of systematic reviews focused on deep learning in open learning have been found, although there has been some focus on other areas of machine learning. Through a systematic review, this study aimed to determine the trends, applied computational techniques, and areas of educational use of deep learning in open learning. The PRISMA…
Descriptors: Artificial Intelligence, Intelligent Tutoring Systems, Open Education, Educational Trends
Tiffany Wu; Christina Weiland – Society for Research on Educational Effectiveness, 2024
Background/Context: Chronic absenteeism is a serious problem that has been linked to lower academic achievement, diminished socioemotional skills, and an increased likelihood of high school dropout (Allensworth et al., 2021; Gottfried, 2014). As a result, many schools have begun to embrace early warning systems (EWS) as a tool to identify and flag…
Descriptors: Attendance, Early Childhood Education, Intervention, Artificial Intelligence