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Yuan Chih Fu; Jin Hua Chen; Kai Chieh Cheng; Xuan Fen Yuan – Higher Education: The International Journal of Higher Education Research, 2024
Using data from approximately 342,000 course-taking records collected from 4406 college students enrolled at Taipei Tech during the 2009-2012 academic years, we examine the impact of multidisciplinarity on students' academic performance. Our study contributes to the literature in three ways. First, by applying natural language processing (NLP), we…
Descriptors: College Students, Interdisciplinary Approach, Academic Achievement, Natural Language Processing
Tianlong Zhong; Gaoxia Zhu; Chenyu Hou; Yuhan Wang; Xiuyi Fan – Education and Information Technologies, 2024
The significance of interdisciplinary learning has been well-recognized by higher education institutions. However, when teaching interdisciplinary learning to junior undergraduate students, their limited disciplinary knowledge and underrepresentation of students from some disciplines can hinder their learning performance. ChatGPT's ability to…
Descriptors: Influences, Artificial Intelligence, Natural Language Processing, Technology Uses in Education
Bauer, Elisabeth; Greisel, Martin; Kuznetsov, Ilia; Berndt, Markus; Kollar, Ingo; Dresel, Markus; Fischer, Martin R.; Fischer, Frank – British Journal of Educational Technology, 2023
Advancements in artificial intelligence are rapidly increasing. The new-generation large language models, such as ChatGPT and GPT-4, bear the potential to transform educational approaches, such as peer-feedback. To investigate peer-feedback at the intersection of natural language processing (NLP) and educational research, this paper suggests a…
Descriptors: Peer Relationship, Feedback (Response), Artificial Intelligence, Natural Language Processing
Dianova, Vera G.; Schultz, Mario D. – Industry and Higher Education, 2023
This comment builds on the example of chat generative pretrained transformer (ChatGPT) to discuss the implications of generative AI on industry and higher education, underlining the need for more transdisciplinary digital literacy education. The release of ChatGPT has generated significant academic and professional interest and instigated a…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Industry
Qinggui Qin; Shuhan Zhang – Education and Information Technologies, 2025
Artificial Intelligence (AI) plays a vital role in the growth and progress of education. Therefore, there is a need to scientifically explore the application of Artificial Intelligence in Education (AIED) and systematically analyze the development trends and research hotspots of AIED to provide reference for researchers. In this study, 1356…
Descriptors: Artificial Intelligence, Knowledge Level, Visual Aids, Concept Mapping
Danielle S. McNamara; Tracy Arner; Reese Butterfuss; Debshila Basu Mallick; Andrew S. Lan; Rod D. Roscoe; Henry L. Roediger; Richard G. Baraniuk – Grantee Submission, 2022
The learning sciences inherently involve interdisciplinary research with an overarching objective of advancing theories of learning and to inform the design and implementation of effective instructional methods and learning technologies. In these endeavors, learning sciences encompass diverse constructs, measures, processes, and outcomes…
Descriptors: Artificial Intelligence, Learning Processes, Learning Motivation, Educational Research
Hanbing Xue; Weishan Liu – SAGE Open, 2025
The application of natural language processing (NLP) technology in the field of education has attracted considerable attention. This study takes 716 articles from the Web of Science database from 1998 to 2023 as its research sample. Using bibliometrics as the theoretical foundation, and employing methods such as literature review and knowledge…
Descriptors: Bibliometrics, Natural Language Processing, Technology Uses in Education, Educational Trends
Baskara, Risang; Mukarto – Indonesian Journal of English Language Teaching and Applied Linguistics, 2023
Recent developments in natural language processing have led to the creation of large language models, such as ChatGPT, which could generate human-like text. In this paper, we explore the potential implications of ChatGPT for language learning in higher education. We first provide an overview of ChatGPT and discuss its capabilities and limitations.…
Descriptors: Artificial Intelligence, Second Language Learning, Second Language Instruction, Teaching Methods
Odden, Tor Ole B.; Marin, Alessandro; Rudolph, John L. – Science Education, 2021
For well over a century, the journal "Science Education" has been publishing articles about the teaching and learning of science. These articles represent more than just a repository of past work: they have the potential to offer insights into both the history of science education as well as well as the dynamics of field-specific change.…
Descriptors: Science Education, Periodicals, Literature Reviews, Natural Language Processing
Heather Catherine Thompson – ProQuest LLC, 2024
This study investigates the instructional practices of a chemistry professor during an immersion summer program, with a focus on employing multimodal discourse within a studio-based learning environment. For this study, multimodal discourse includes natural language, gestures, mathematical expressions, symbolic visual representations, and manual…
Descriptors: Teaching Methods, Design, Chemistry, Summer Programs
Ahmed Tlili; Michael Agyemang Adarkwah; Chung Kwan Lo; Aras Bozkurt; Daniel Burgos; Curtis J. Bonk; Eamon Costello; Sanjaya Mishra; Christian M. Stracke; Ronghuai Huang – Journal of Learning for Development, 2024
The development, use, and timely promotion of Open Education (OE) has been effective in addressing myriad educational concerns, including inclusivity, accessibility and learning achievement, among many others. However, limited information exists in the literature concerning how OE could enhance Generative Artificial Intelligence (GenAI), which is…
Descriptors: Open Education, Instructional Effectiveness, Safety, Artificial Intelligence
Vittorini, Pierpaolo; Menini, Stefano; Tonelli, Sara – International Journal of Artificial Intelligence in Education, 2021
Massive open online courses (MOOCs) provide hundreds of students with teaching materials, assessment tools, and collaborative instruments. The assessment activity, in particular, is demanding in terms of both time and effort; thus, the use of artificial intelligence can be useful to address and reduce the time and effort required. This paper…
Descriptors: Artificial Intelligence, Formative Evaluation, Summative Evaluation, Data
Goren, Heela; Yemini, Miri; Maxwell, Claire; Blumenfeld-Lieberthal, Efrat – Review of Research in Education, 2020
This chapter presents an innovative, cross-disciplinary methodological approach to systematically reviewing and comparing large bodies of literature using big data, Natural Language Processing, network analysis, and supplementary qualitative analysis. The approach is demonstrated through an analysis of the literature surrounding four common…
Descriptors: Educational Research, Scholarship, Literature Reviews, Research Methodology
Tafazoli, Dara; María, Elena Gómez; Huertas Abril, Cristina A. – International Journal of Information and Communication Technology Education, 2019
Intelligent computer-assisted language learning (ICALL) is a multidisciplinary area of research that combines natural language processing (NLP), intelligent tutoring system (ITS), second language acquisition (SLA), and foreign language teaching and learning (FLTL). Intelligent tutoring systems (ITS) are able to provide a personalized approach to…
Descriptors: Intelligent Tutoring Systems, Computer Assisted Instruction, Teaching Methods, Interdisciplinary Approach
West, Jason – Curriculum Journal, 2017
Interdisciplinarity requires the collaboration of two or more disciplines to combine their expertise to jointly develop and deliver learning and teaching outcomes appropriate for a subject area. Curricula and assessment mapping are critical components to foster and enhance interdisciplinary learning environments. Emerging careers in data science…
Descriptors: Curriculum Development, Validity, Data Analysis, Interdisciplinary Approach
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