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Dazhen Tong; Yang Tao; Kangkang Zhang; Xinxin Dong; Yangyang Hu; Sudong Pan; Qiaoyi Liu – Asia Pacific Education Review, 2024
Artificial intelligence (AI) technologies have been consistently influencing the progress of education for an extended period, with its impact becoming more significant especially after the launch of ChatGPT-3.5 at the end of November 2022. In the field of physics education, recent research regarding the performance of ChatGPT-3.5 in solving…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Performance
Susan Shurden; Mike Shurden – Journal of Instructional Pedagogies, 2024
Artificial Intelligence (AI) is taking the world by storm. Higher education is not immune to this phenomenon and has many challenges in embracing AI. Much has been written lately concerning the typical application of AI in higher education, as well as in the classroom itself. The purpose of this paper is to gather information from students to…
Descriptors: Artificial Intelligence, Higher Education, College Students, Student Attitudes
Matthew T. McCrudden; Linh Huynh; Bailing Lyu; Jonna M. Kulikowich; Danielle S. McNamara – Grantee Submission, 2024
Readers build a mental representation of text during reading. The coherence building processes readers use to build a mental representation during reading is key to comprehension. We examined the effects of self- explanation on coherence building processes as undergraduates (n =51) read five complementary texts about natural selection and…
Descriptors: Reading Processes, Reading Comprehension, Undergraduate Students, Evolution
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
Hao Zhou; Wenge Rong; Jianfei Zhang; Qing Sun; Yuanxin Ouyang; Zhang Xiong – IEEE Transactions on Learning Technologies, 2025
Knowledge tracing (KT) aims to predict students' future performances based on their former exercises and additional information in educational settings. KT has received significant attention since it facilitates personalized experiences in educational situations. Simultaneously, the autoregressive (AR) modeling on the sequence of former exercises…
Descriptors: Learning Experience, Academic Achievement, Data, Artificial Intelligence
Sina Rismanchian; Eesha Tur Razia Babar; Shayan Doroudi – Annenberg Institute for School Reform at Brown University, 2025
In November 2022, OpenAI released ChatGPT, a groundbreaking generative AI chatbot backed by large language models (LLMs). Since then, these models have seen various applications in education, from Socratic tutoring and writing assistance to teacher training and essay scoring. Despite their widespread use among high school and college students in…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Undergraduate Students
Emiko Tsutsumi; Yiming Guo; Ryo Kinoshita; Maomi Ueno – IEEE Transactions on Learning Technologies, 2024
Knowledge tracing (KT), the task of tracking the knowledge state of a student over time, has been assessed actively by artificial intelligence researchers. Recent reports have described that Deep-IRT, which combines item response theory (IRT) with a deep learning method, provides superior performance. It can express the abilities of each student…
Descriptors: Item Response Theory, Academic Ability, Intelligent Tutoring Systems, Artificial Intelligence
Jia Tracy Shen; Michiharu Yamashita; Ethan Prihar; Neil Heffernan; Xintao Wu; Sean McGrew; Dongwon Lee – Grantee Submission, 2021
Educational content labeled with proper knowledge components (KCs) are particularly useful to teachers or content organizers. However, manually labeling educational content is labor intensive and error-prone. To address this challenge, prior research proposed machine learning based solutions to auto-label educational content with limited success.…
Descriptors: Mathematics Education, Knowledge Level, Video Technology, Educational Technology
Andrew Kelly; Miriam Sullivan; Katrina Strampel – Journal of University Teaching and Learning Practice, 2023
The global higher education sector has been significantly disrupted by the proliferation of generative artificial intelligence tools such as ChatGPT, especially in relation to its implications for assessment. However, few studies to date have explored student perspectives on these tools. This article reports on one of the first large-scale…
Descriptors: Artificial Intelligence, Student Attitudes, Foreign Countries, Technology Uses in Education
Ting-Ting Wu; Hsin-Yu Lee; Pei-Hua Chen; Chia-Ju Lin; Yueh-Min Huang – Journal of Computer Assisted Learning, 2025
Background: Science, Technology, Engineering, and Mathematics (STEM) education in Asian universities struggles to integrate Knowledge, Skills, and Attitudes (KSA) due to large classes and student reluctance. While ChatGPT offers solutions, its conventional use may hinder independent critical thinking. Objectives: This study introduces PA-GPT,…
Descriptors: Peer Evaluation, Artificial Intelligence, Natural Language Processing, Technology Uses in Education
Manik R. Reddy; Nils G. Walter; Yulia V. Sevryugina – Journal of Chemical Education, 2024
The effective and responsible educational application of ChatGPT and other generative artificial intelligence (GenAI) tools constitutes an active area of exploration. This study describes and assesses the implementation of a structured, GenAI-assisted scientific essay writing assignment in nucleic acid biochemistry. Briefly, students created,…
Descriptors: Artificial Intelligence, Technology Uses in Education, Writing Assignments, Biochemistry
Erika Lundquist; Brit Henderson; Sophia Sutcliffe; Laura Cojocaru; Kasey Eickmeyer; Annabel Utz; Sufiyan Syed; Audrey Yu – MDRC, 2025
Since 2019, high school seniors from low-income households in the state of Washington have received guidance from OtterBot, an interactive chatbot texting tool with artificial intelligence (AI) capabilities. The chatbot, designed by the Washington Student Achievement Council (WSAC), provides information to simplify the complex processes involved…
Descriptors: Artificial Intelligence, Natural Language Processing, Man Machine Systems, Financial Aid Applicants
Haesol Bae; Jaesung Hur; Jaesung Park; Gi Woong Choi; Jewoong Moon – Online Learning, 2024
This study examined pre-service teachers' perspectives on integrating generative AI (GenAI) tools into their own learning and teaching practices. Discussion posts from asynchronous online courses on ChatGPT were analyzed using the Diffusion of Innovations framework to explore awareness, willingness to apply ChatGPT to instruction, and potential…
Descriptors: Preservice Teachers, Teacher Attitudes, Artificial Intelligence, Technology Uses in Education
Carmen Köhler; Johannes Hartig – Contemporary Educational Technology, 2024
Since ChatGPT-3.5 has been available to the public, the potentials and challenges regarding chatbot usage in education have been widely discussed. However, little evidence exists whether and for which purposes students even apply generative AI tools. The first main purpose of the present study was to develop and test scales that assess students'…
Descriptors: Artificial Intelligence, College Students, Natural Language Processing, Technology Uses in Education
Charlotte N. Gunawardena; Yan Chen; Nick Flor; Damien Sánchez – Online Learning, 2023
Gunawardena et al.'s (1997) Interaction Analysis Model (IAM) is one of the most frequently employed frameworks to guide the qualitative analysis of social construction of knowledge online. However, qualitative analysis is time consuming, and precludes immediate feedback to revise online courses while being delivered. To expedite analysis with a…
Descriptors: Models, Learning Processes, Knowledge Level, Online Courses
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