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Nehyba, Jan; Štefánik, Michal – Education and Information Technologies, 2023
Social sciences expose many cognitively complex, highly qualified, or fuzzy problems, whose resolution relies primarily on expert judgement rather than automated systems. One of such instances that we study in this work is a reflection analysis in the writings of student teachers. We share a hands-on experience on how these challenges can be…
Descriptors: Models, Language, Reflection, Writing (Composition)
Nayak, Padmalaya; Vaheed, Sk.; Gupta, Surbhi; Mohan, Neeraj – Education and Information Technologies, 2023
Students' academic performance prediction is one of the most important applications of Educational Data Mining (EDM) that helps to improve the quality of the education process. The attainment of student outcomes in an Outcome-based Education (OBE) system adds invaluable rewards to facilitate corrective measures to the learning processes.…
Descriptors: Predictor Variables, Academic Achievement, Data Collection, Information Retrieval
Doleck, Tenzin; Lemay, David John; Basnet, Ram B.; Bazelais, Paul – Education and Information Technologies, 2020
Large swaths of data are readily available in various fields, and education is no exception. In tandem, the impetus to derive meaningful insights from data gains urgency. Recent advances in deep learning, particularly in the area of voice and image recognition and so-called complete knowledge games like chess, go, and StarCraft, have resulted in a…
Descriptors: Learning Analytics, Prediction, Information Retrieval, Accuracy
Bousnguar, Hassan; Najdi, Lotfi; Battou, Amal – Education and Information Technologies, 2022
Forecasting the enrollments of new students in bachelor's systems became an urgent desire in the majority of higher education institutions. It represents an important stage in the process of making strategic decisions for new course's accreditation and optimization of resources. To gain a deep view of the educational forecasting context, the most…
Descriptors: Higher Education, Undergraduate Students, Enrollment Management, Strategic Planning
Nahar, Khaledun; Shova, Boishakhe Islam; Ria, Tahmina; Rashid, Humayara Binte; Islam, A. H. M. Saiful – Education and Information Technologies, 2021
Information is everywhere in a hidden and scattered way. It becomes useful when we apply Data mining to extracts the hidden, meaningful, and potentially useful patterns from these vast data resources. Educational data mining ensures a quality education by analyzing educational data based on various aspects. In this paper, we have analyzed the…
Descriptors: Learning Analytics, College Students, Engineering Education, Data Collection
Adekitan, Aderibigbe Israel; Noma-Osaghae, Etinosa – Education and Information Technologies, 2019
The academic performance of a student in a university is determined by a number of factors, both academic and non-academic. Student that previously excelled at the secondary school level may lose focus due to peer pressure and social lifestyle while those who previously struggled due to family distractions may be able to focus away from home, and…
Descriptors: Foreign Countries, Data Collection, Educational Research, Prediction
Mimis, Mohamed; El Hajji, Mohamed; Es-saady, Youssef; Oueld Guejdi, Abdellah; Douzi, Hassan; Mammass, Driss – Education and Information Technologies, 2019
The educational recommendation system to provide support for academic guidance and adaptive learning has always been an important issue of research for smart education. A bad guidance can give rise to difficulties in further studies and can be extended to school dropout. This paper explores the potential of Educational Data Mining for academic…
Descriptors: Educational Counseling, Guidance, Educational Research, Data Collection