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Elisabeth Bauer; Michael Sailer; Frank Niklas; Samuel Greiff; Sven Sarbu-Rothsching; Jan M. Zottmann; Jan Kiesewetter; Matthias Stadler; Martin R. Fischer; Tina Seidel; Detlef Urhahne; Maximilian Sailer; Frank Fischer – Journal of Computer Assisted Learning, 2025
Background: Artificial intelligence, particularly natural language processing (NLP), enables automating the formative assessment of written task solutions to provide adaptive feedback automatically. A laboratory study found that, compared with static feedback (an expert solution), adaptive feedback automated through artificial neural networks…
Descriptors: Artificial Intelligence, Feedback (Response), Computer Simulation, Natural Language Processing
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Brian W. Stone – Teaching of Psychology, 2025
Background: Students in higher education are using generative artificial intelligence (AI) despite mixed messages and contradictory policies. Objective: This study helps answer outstanding questions about many aspects of AI in higher education: familiarity, usage, perceptions of peers, ethical/social views, and AI grading. Method: I surveyed 733…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Technology Uses in Education
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Mia Allen; Usman Naeem; Sukhpal Singh Gill – IEEE Transactions on Education, 2024
Contributions: In this article, a generative artificial intelligence (AI)-based Q&A system has been developed by integrating information retrieval and natural language processing techniques, using course materials as a knowledge base and facilitating real-time student interaction through a chat interface. Background: The rise of advanced AI…
Descriptors: Artificial Intelligence, Technology Uses in Education, Information Retrieval, Natural Language Processing
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Dorottya Demszky; Jing Liu; Heather C. Hill; Dan Jurafsky; Chris Piech – Educational Evaluation and Policy Analysis, 2024
Providing consistent, individualized feedback to teachers is essential for improving instruction but can be prohibitively resource-intensive in most educational contexts. We develop M-Powering Teachers, an automated tool based on natural language processing to give teachers feedback on their uptake of student contributions, a high-leverage…
Descriptors: Online Courses, Automation, Feedback (Response), Large Group Instruction
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Bünyami Kayali; Mehmet Yavuz; Sener Balat; Mücahit Çalisan – Australasian Journal of Educational Technology, 2023
The purpose of this study was to determine university students' experiences with the use of ChatGPT in online courses. The sample consisted of 84 associate degree students from a state university in Turkey. A multi-method approach was used in the study. Although quantitative data were collected using the Chatbot Usability Scale, qualitative data…
Descriptors: Student Experience, Artificial Intelligence, Natural Language Processing, Electronic Learning
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Alex Rister; Meghan Velez – Communication Teacher, 2025
This article explores the value of generative AI (genAI) tools for much-needed support for instructors in higher education in the realm of course design. Two authors detail their experiences partnering with two distinct tools, ChatGPT and Bard (now known as Gemini), for communication course development, emphasizing iterative collaboration with…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Communications
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Colin Green; Eric Brewe; Jillian Mellen; Adrienne Traxler; Sarah Scanlin – Physical Review Physics Education Research, 2024
This project aims to understand physics faculty responses to transitioning to online teaching during the COVID-19 pandemic. We surveyed 662 physics faculty from the United States following the Spring 2020 term; of these, 258 completed a follow-up survey after the Fall 2020 term. We used natural language processing to measure the sentiment scores…
Descriptors: Teacher Attitudes, Online Courses, Physics, Science Instruction
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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
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Sheri Conklin; Tom Dorgan; Daisyane Barreto – Discover Education, 2024
We investigated the utility of ChatGPT 3.5 in the creation of a fully online asynchronous higher education course. Our collaborative effort with ChatGPT resulted in developing a Master's level course on Trends and Issues in Instructional Design using the Backward Design Model. Throughout this process, we recognized the critical role of precise…
Descriptors: Design, Technology Uses in Education, Artificial Intelligence, Instructional Design
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Jiménez, Haydée G.; Casanova, Marco A.; Finamore, Anna Carolina; Simões, Gonçalo – International Educational Data Mining Society, 2021
Sentiment Analysis is a field of Natural Language Processing which aims at classifying the author's sentiment in text. This paper first describes a sentiment analysis model for students' comments about professor performance. The model achieved impressive results for comments collected from student surveys conducted at a private university in…
Descriptors: Natural Language Processing, Data Analysis, Classification, Student Surveys
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George Hanshaw; Joanna Vance; Craig Brewer – Open Praxis, 2024
This study examines the impact of AI course assistants on student learning experiences in online undergraduate courses at Los Angeles Pacific University. A controlled experiment involving 92 students across treatment and control groups was conducted to evaluate the effectiveness of AI assistants developed by Nectir. The treatment group had access…
Descriptors: Instructional Effectiveness, Artificial Intelligence, Student Experience, Undergraduate Students
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Lee, Jeonghyun; Soleimani, Farahnaz; Irish, India; Hosmer, John, IV; Soylu, Meryem Yilmaz; Finkelberg, Roy; Chatterjee, Saurabh – Online Learning, 2022
In this study, we work towards a strategy to measure and enhance the quality of interactions in discussion forums at scale. We present a machine learning (ML) model which identifies the phase of cognitive presence exhibited by a student's post and suggest future applications of such a model to help online students develop higher-order thinking. We…
Descriptors: Online Courses, Models, Thinking Skills, Computer Mediated Communication
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Degraeuwe, Jasper; Goethals, Patrick – Research-publishing.net, 2022
This paper presents a reflection on the design of an Intelligent Computer-Assisted Language Learning (ICALL) 'ecosystem', integrated into an online learning environment for Spanish as a Foreign Language (SFL). The innovative dimension of the ecosystem lies in its triple focus: apart from enabling users to create and use intelligent language…
Descriptors: Computer Assisted Instruction, Second Language Learning, Second Language Instruction, Spanish
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Bosch, Nigel; Crues, R. Wes; Shaik, Najmuddin; Paquette, Luc – Grantee Submission, 2020
Online courses often include discussion forums, which provide a rich source of data to better understand and improve students' learning experiences. However, forum messages frequently contain private information that prevents researchers from analyzing these data. We present a method for discovering and redacting private information including…
Descriptors: Privacy, Discussion Groups, Asynchronous Communication, Methods
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Huang, Eddie; Valdiviejas, Hannah; Bosch, Nigel – Grantee Submission, 2019
Metacognition is a valuable tool for learning, since it is closely related to self-regulation and awareness of one's own affect. However, methods for automatically detecting and studying metacognition are scarce. Thus, in this paper we describe an algorithm for automatic detection of metacognitive language in writing. We analyzed text from the…
Descriptors: Metacognition, Mathematics, Language Usage, Writing (Composition)
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