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Ibrahim Abba Mohammed; Ahmed Bello; Bala Ayuba – Education and Information Technologies, 2025
In spite of the emergence of studies seeking to integrate chatbot into education, there is a wide literature gap in the Nigerian contexts. While most studies focus on the design and development of chatbots, there exists a very scarce literature on the effect of ChatGPT chatbot on students' achievement. To address this gap, this study checked the…
Descriptors: Natural Language Processing, Artificial Intelligence, Academic Achievement, Computer Science Education
Ke Li; Lulu Lun; Pingping Hu – Education and Information Technologies, 2025
Amid the ongoing discussion about the potential of LLMs (Large Language Models) to facilitate language learning, there has been a broad spectrum of views in academia. However, little is known about the different viewpoints of students and what contributes to these differences. In light of this, this study adopts Q-methodology, a mixed-methods…
Descriptors: Student Attitudes, Language Attitudes, Affordances, Artificial Intelligence
Anna Y. Q. Huang; Jei Wei Chang; Albert C. M. Yang; Hiroaki Ogata; Shun Ting Li; Ruo Xuan Yen; Stephen J. H. Yang – Educational Technology & Society, 2023
To improve students' learning performance through review learning activities, we developed a personalized intervention tutoring approach that leverages learning analysis based on artificial intelligence. The proposed intervention first uses text-processing artificial intelligence technologies, namely bidirectional encoder representations from…
Descriptors: Academic Achievement, Tutoring, Artificial Intelligence, Individualized Instruction
McHugh, David; Shaw, Sarah; Moore, Travis R.; Ye, Leafia Zi; Romero-Masters, Philip; Halverson, Richard – Journal of Research on Technology in Education, 2020
Using a natural language processing tool, this study examined participant discourse in personalized learning schools to better understand what personalized learning looks like in practice. Term frequency-inverse document frequency (tf-idf) was used to identify the significant words and potential emergent themes for 134 interview transcripts. This…
Descriptors: Natural Language Processing, Discourse Analysis, Word Frequency, Identification

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