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Showing 1 to 15 of 190 results Save | Export
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Allie Michael; Abdullah O. Akinde – Assessment Update, 2024
Open-ended responses to surveys can be highly beneficial to higher education institutions, providing clarity and context that quantitative data can sometimes lack. However, analyzing open-ended responses typically takes time and manpower most institutional assessment offices do not have to spare. This study focused on finding a potential solution…
Descriptors: Artificial Intelligence, Natural Language Processing, Student Surveys, Feedback (Response)
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Atharva Naik; Jessica Ruhan Yin; Anusha Kamath; Qianou Ma; Sherry Tongshuang Wu; R. Charles Murray; Christopher Bogart; Majd Sakr; Carolyn P. Rose – British Journal of Educational Technology, 2025
The relative effectiveness of reflection either through student generation of contrasting cases or through provided contrasting cases is not well-established for adult learners. This paper presents a classroom study to investigate this comparison in a college level Computer Science (CS) course where groups of students worked collaboratively to…
Descriptors: Cooperative Learning, Reflection, College Students, Computer Science Education
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Chelsea Chandler; Rohit Raju; Jason G. Reitman; William R. Penuel; Monica Ko; Jeffrey B. Bush; Quentin Biddy; Sidney K. D’Mello – International Educational Data Mining Society, 2025
We investigated methods to enhance the generalizability of large language models (LLMs) designed to classify dimensions of collaborative discourse during small group work. Our research utilized five diverse datasets that spanned various grade levels, demographic groups, collaboration settings, and curriculum units. We explored different model…
Descriptors: Artificial Intelligence, Models, Natural Language Processing, Discourse Analysis
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Valentine Joseph Owan; Ibrahim Abba Mohammed; Ahmed Bello; Tajudeen Ahmed Shittu – Contemporary Educational Technology, 2025
Despite the increasing interest in artificial intelligence technologies in education, there is a gap in understanding the factors influencing the adoption of ChatGPT among Nigerian higher education students. Research has not comprehensively explored these factors in the Nigerian context, leaving a significant gap in understanding technology…
Descriptors: Student Behavior, Foreign Countries, Artificial Intelligence, Natural Language Processing
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Laura Schmidt; Niklas Obergassel; Julian Roelle – Applied Cognitive Psychology, 2025
Recent meta-analyses indicate that learning with ChatGPT improves academic performance but reveals substantial heterogeneity in effect sizes. The present study sheds light on one theoretically plausible moderator of the benefits of learning with ChatGPT: the goal structure of the learning task. For this purpose, in an experiment, university…
Descriptors: Artificial Intelligence, Academic Achievement, Natural Language Processing, College Students
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Wali Khan Monib; Atika Qazi; Malissa Maria Mahmud – Education and Information Technologies, 2025
ChatGPT has emerged as a transformative technology with its remarkable ability to generate human-like responses, propelling its widespread adoption. While prior research has investigated the general landscape of AI-driven tools such as ChatGPT, the current study focuses specifically on exploring learners' experiences and perceptions regarding the…
Descriptors: Student Attitudes, Student Experience, Artificial Intelligence, Natural Language Processing
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Abdulrahman M. Al-Zahrani – SAGE Open, 2025
This study examines the impact of Artificial Intelligence (AI) chatbots on the loss of human connection and emotional support among higher education students. To do so, a quantitative research design is employed. An online survey questionnaire is distributed to a sample of 819 higher education students, assessing concerns about human connection,…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, College Students
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Yang Zhong; Mohamed Elaraby; Diane Litman; Ahmed Ashraf Butt; Muhsin Menekse – Grantee Submission, 2024
This paper introduces REFLECTSUMM, a novel summarization dataset specifically designed for summarizing students' reflective writing. The goal of REFLECTSUMM is to facilitate developing and evaluating novel summarization techniques tailored to real-world scenarios with little training data, with potential implications in the opinion summarization…
Descriptors: Documentation, Writing (Composition), Reflection, Metadata
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Qinghao Guan; Yangxi Han – Innovations in Education and Teaching International, 2025
As generative AI (GenAI) continues to permeate academia, distinguishing between student-authored essays and those by Large Language Models (LLMs) becomes crucial for maintaining academic integrity. This study conducted a survey on the ethical awareness of using generative AI tools among a group of STEM students (n=156). Also, we empirically…
Descriptors: Foreign Countries, College Students, Artificial Intelligence, Intelligent Tutoring Systems
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Faiz Subhani; Subayal Aftab Khan; Maqsood Ahmad Sandhu; Muhammad Farrukh Shahzad – TechTrends: Linking Research and Practice to Improve Learning, 2025
The adoption of generative AI in education has revolutionized science by producing human-like texts through contextual understanding, as OpenAI ChatGPT shows. OpenAI's widely used large language model, such as ChatGPT, has become quite popular, especially in higher education. This study examines different factors influencing the adoption and…
Descriptors: Artificial Intelligence, Higher Education, Foreign Countries, College Students
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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
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Abdulkadir Kara; Zeynep Avinç Kara; Serkan Yildirim – International Journal of Assessment Tools in Education, 2025
In measurement and evaluation processes, natural language responses are often avoided due to time, workload, and reliability concerns. However, the increasing popularity of automatic short-answer grading studies for natural language responses means such answers can now be measured more quickly and reliably. This study aims to build models for…
Descriptors: Scoring, Automation, Artificial Intelligence, Natural Language Processing
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Nisar Ahmed Dahri; Noraffandy Yahaya; Waleed Mugahed Al-Rahmi – Education and Information Technologies, 2025
Enhancing student academic success and career readiness is important in the rapidly evolving educational field. This study investigates the influence of ChatGPT, an AI tool, on these outcomes using the Stimulus-Organism-Response (SOR) theory and constructs from the Technology Acceptance Model (TAM). The aim is to explore how ChatGPT impacts…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Career Readiness
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Muhammad Farrukh Shahzad; Shuo Xu; Hira Zahid – Education and Information Technologies, 2025
Artificial Intelligence (AI) technologies have rapidly transformed the education sector and affect student learning performance, particularly in China, a burgeoning educational landscape. The development of generative artificial intelligence (AI) based technologies, such as chatbots and large language models (LLMs) like ChatGPT, has completely…
Descriptors: Artificial Intelligence, Technology Uses in Education, Academic Achievement, Self Efficacy
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Elisabeth Bauer; Constanze Richters; Amadeus J. Pickal; Moritz Klippert; Michael Sailer; Matthias Stadler – British Journal of Educational Technology, 2025
This study explores whether AI-generated adaptive feedback or static feedback is favourable for student interest and performance outcomes in learning statistics in a digital learning environment. Previous studies have favoured adaptive feedback over static feedback for skill acquisition, however, without investigating the outcome of students'…
Descriptors: Artificial Intelligence, Technology Uses in Education, Feedback (Response), Statistics Education
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