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Jamiu Adekunle Idowu – International Journal of Artificial Intelligence in Education, 2024
This systematic literature review investigates the fairness of machine learning algorithms in educational settings, focusing on recent studies and their proposed solutions to address biases. Applications analyzed include student dropout prediction, performance prediction, forum post classification, and recommender systems. We identify common…
Descriptors: Algorithms, Dropouts, Prediction, Academic Achievement
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Yuanlan Jiang; Jian-E Peng – Computer Assisted Language Learning, 2025
Language learner engagement, which is receiving increased attention, has predominantly focused on offline classroom contexts, while learner engagement in language Massive Open Online Courses (LMOOCs) remains under-explored. This study was conducted on a College English MOOC with the purpose of examining learner engagement and its relations with…
Descriptors: Learner Engagement, Personal Autonomy, Second Language Learning, Second Language Instruction
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Tran, Tuan M.; Hasegawa, Shinobu – International Association for Development of the Information Society, 2022
A learner model reflects learning patterns and characteristics of a learner. A learner model with learning history and its effectiveness plays a significant role in supporting a learner's understanding of their strengths and weaknesses of their way of learning in order to make proper adjustments for improvement. Nowadays, learners have been…
Descriptors: Markov Processes, Learning Processes, Models, Scores
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Sanguino, Juan; Manrique, Rubén; Mariño, Olga; Linares-Vásquez, Mario; Cardozo, Nicolas – International Educational Data Mining Society, 2022
Recommender systems in educational contexts have proven effective to identify learning resources that fit the interests and needs of learners. Their usage has been of special interest in online self-learning scenarios to increase student retention and improve the learning experience. In current recommendation techniques, and in particular, in…
Descriptors: Data Analysis, Learning Analytics, Student Interests, Student Needs
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Arslanbay, Goshnag; Ersanli, Ceylan Yangin – Journal on English Language Teaching, 2023
Data-Driven Learning (DDL) is a method for learning languages that involves analyzing language usage trends and finding patterns in language data, utilizing technology and statistics. One of the key benefits of DDL is that it allows students to focus on the most relevant and useful language data for their needs. Data-driven learning is an…
Descriptors: English (Second Language), English for Academic Purposes, Second Language Learning, Second Language Instruction
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Chen, Qinghua; Lin, Angel M. Y. – Pedagogies: An International Journal, 2022
Translanguaging and trans-semiotizing research has problematized the static view of language and argued that meaning making is a dynamic, material, social, and historical process across multiple timescales in complex eco-social systems. The second author proposed the concept of trans-semiotizing as an alternative lens to study language teaching…
Descriptors: Semiotics, Code Switching (Language), Language Usage, Video Technology
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Annika Rigole; Sonakshi Sharma; Jessica Bergmann – UNICEF Innocenti - Global Office of Research and Foresight, 2023
Recognizing that children's learning outcomes generally remain low, in its recent 2017--2021 Education and Skills Sector Plan (ESSP) the Government of Zambia prioritized improving learning outcomes through strategies that addressed gaps in education system quality, access, equity and efficiency. What resources and contextual factors are associated…
Descriptors: School Effectiveness, Outcomes of Education, Educational Strategies, Access to Education