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Zara Ersozlu; Sona Taheri; Inge Koch – Education and Information Technologies, 2024
Integrating machine learning (ML) methods in educational research has the potential to greatly impact upon research, teaching, learning and assessment by enabling personalised learning, adaptive assessment and providing insights into student performance, progress and learning patterns. To reveal more about this notion, we investigated ML…
Descriptors: Artificial Intelligence, Educational Research, Data Analysis, Methods
Kamila Misiejuk; Sonsoles López-Pernas; Rogers Kaliisa; Mohammed Saqr – Journal of Learning Analytics, 2025
Generative artificial intelligence (GenAI) has opened new possibilities for designing learning analytics (LA) tools, gaining new insights about student learning processes and their environment, and supporting teachers in assessing and monitoring students. This systematic literature review maps the empirical research of 41 papers utilizing GenAI…
Descriptors: Literature Reviews, Artificial Intelligence, Learning Analytics, Data Collection
Blaizot, Aymeric; Veettil, Sajesh K.; Saidoung, Pantakarn; Moreno-Garcia, Carlos Francisco; Wiratunga, Nirmalie; Aceves-Martins, Magaly; Lai, Nai Ming; Chaiyakunapruk, Nathorn – Research Synthesis Methods, 2022
The exponential increase in published articles makes a thorough and expedient review of literature increasingly challenging. This review delineated automated tools and platforms that employ artificial intelligence (AI) approaches and evaluated the reported benefits and challenges in using such methods. A search was conducted in 4 databases…
Descriptors: Artificial Intelligence, Literature Reviews, Databases, Data Analysis
Jay Fie Paler Luzano – International Journal of Technology in Education, 2025
This study investigated the role of ChatGPT-assisted data analysis in mathematics education research within the post-modern scholarly milieu using a scoping review approach. This examined how ChatGPT contributes to ethical, reliable, rigorous, and context-sensitive data analysis in mathematics education research. The findings reveal five (5)…
Descriptors: Artificial Intelligence, Mathematics Education, Educational Research, Data Analysis
M. Nazir; A. Noraziah; M. Rahmah – International Journal of Virtual and Personal Learning Environments, 2023
An effective educational program warrants the inclusion of an innovative construction that enhances the higher education efficacy in such a way that accelerates the achievement of desired results and reduces the risk of failures. Educational decision support system has currently been a hot topic in educational systems, facilitating the pupil…
Descriptors: Data Analysis, Academic Achievement, Artificial Intelligence, Prediction
Suthinanth Rattanachotithavorn; Pattarawat Jeerapattanatorn – Journal of Education and Learning, 2025
This review article examines the emerging trends in business education to address the rapidly evolving demands of a global, technology-driven economy. The study systematically analyzed 64 research articles from academic databases, of which 28 high-quality studies met the inclusion criteria based on their direct relevance to business education and…
Descriptors: Business Education, Educational Trends, Educational Research, Artificial Intelligence
Lin Lin; Danhua Zhou; Jingying Wang; Yu Wang – SAGE Open, 2024
The rapid development of artificial intelligence has driven the transformation of educational evaluation into big data-driven. This study used a systematic literature review method to analyzed 44 empirical research articles on the evaluation of big data education. Firstly, it has shown an increasing trend year by year, and is mainly published in…
Descriptors: Data Analysis, Educational Research, Geographic Regions, Periodicals
Karimah, Shofiyati Nur; Hasegawa, Shinobu – Smart Learning Environments, 2022
Recognizing learners' engagement during learning processes is important for providing personalized pedagogical support and preventing dropouts. As learning processes shift from traditional offline classrooms to distance learning, methods for automatically identifying engagement levels should be developed. This article aims to present a literature…
Descriptors: Learner Engagement, Automation, Electronic Learning, Literature Reviews
Chen, Xieling; Zou, Di; Cheng, Gary; Xie, Haoran; Jong, Morris – Education and Information Technologies, 2023
Researchers and practitioners are paying increasing attention to blockchain's potential for resolving trust, privacy, and transparency-related issues in smart education. Research on educational blockchain is also becoming an active field of research. Based on 206 studies published from 2017 to 2020, we identify contributors, collaborators,…
Descriptors: Educational Technology, Technology Uses in Education, Artificial Intelligence, Databases
Umer, Rahila; Susnjak, Teo; Mathrani, Anuradha; Suriadi, Lim – Interactive Learning Environments, 2023
Predictive models on students' academic performance can be built by using historical data for modelling students' learning behaviour. Such models can be employed in educational settings to determine how new students will perform and in predicting whether these students should be classed as at-risk of failing a course. Stakeholders can use…
Descriptors: Prediction, Student Behavior, Models, Academic Achievement
Fernández, Antonio; Gómez, Beatriz; Binjaku, Kleona; Meçe, Elinda Kajo – Education and Information Technologies, 2023
Higher Education Institutions (HEIs) are involved in an evolution to a new model of university called "digital university." This model implies not only adopting new technologies but also developing an organizational strategic transformation which includes information, processes, human aspects, and more. Because an organization's digital…
Descriptors: Higher Education, Educational Change, Technology Integration, Educational Technology
Hwang, Gwo-Jen; Tu, Yun-Fang; Tang, Kai-Yu – International Review of Research in Open and Distributed Learning, 2022
This study reviews the journal publications of artificial intelligence-supported online learning (AIoL) in the Web of Science (WOS) database from 1997 to 2019 taking into account the contributing countries/areas, leading journals, highly cited papers, authors, research areas, research topics, roles of AIoL, and adopted artificial intelligence (AI)…
Descriptors: Artificial Intelligence, Electronic Learning, Educational Research, Data Analysis
Kayleigh K. Hyde; Marlena N. Novack; Nicholas LaHaye; Chelsea Parlett-Pelleriti; Raymond Anden; Dennis R. Dixon; Erik Linstead – Review Journal of Autism and Developmental Disorders, 2019
Autism spectrum disorder (ASD) research has yet to leverage "big data" on the same scale as other fields; however, advancements in easy, affordable data collection and analysis may soon make this a reality. Indeed, there has been a notable increase in research literature evaluating the effectiveness of machine learning for diagnosing…
Descriptors: Artificial Intelligence, Autism Spectrum Disorders, Clinical Diagnosis, Intervention
Talan, Tarik; Kalinkara, Yusuf – International Society for Technology, Education, and Science, 2022
With the rapid development of science and technology in recent years, the application areas of fuzzy logic have also gained speed. Fuzzy logic is a frequently preferred approach in the educational process, and it can be said that scientific publications on this topic have recently gained momentum in the literature. In this context, the present…
Descriptors: Databases, Research Reports, Foreign Countries, Universities
Morakinyo Akintolu; Akinpelu A. Oyekunle – Journal of Educators Online, 2025
This paper provides a comprehensive overview of the research on the application of artificial intelligence (AI) in primary education to explore its potential to enhance teaching and learning processes. Through a systematic review of the relevant literature, this study identifies key areas in which AI can significantly impact primary education and…
Descriptors: Data Analysis, Learning Analytics, Artificial Intelligence, Computer Software
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