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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
Jiayi Zhang; Conrad Borchers; Vincent Aleven; Ryan S. Baker – International Educational Data Mining Society, 2024
Think-aloud protocols are a common method to study self-regulated learning (SRL) during learning by problem-solving. Previous studies have manually transcribed and coded students' verbalizations, labeling the presence or absence of SRL strategies and then examined these SRL codes in relation to learning. However, the coding process is difficult to…
Descriptors: Artificial Intelligence, Technology Uses in Education, Protocol Analysis, Self Management
Rashid, M. Parvez; Xiao, Yunkai; Gehringer, Edward F. – International Educational Data Mining Society, 2022
Peer assessment can be a more effective pedagogical method when reviewers provide quality feedback. But what makes feedback helpful to reviewees? Other studies have identified quality feedback as focusing on detecting problems, providing suggestions, or pointing out where changes need to be made. However, it is important to seek students'…
Descriptors: Peer Evaluation, Feedback (Response), Natural Language Processing, Artificial Intelligence
Manaf Al-Okaily – Education and Information Technologies, 2025
ChatGPT a state-of-the-art language model created by Open Artificial Intelligence (AI), can revolutionize education by improving student engagement and making learning more personalized. Consequently, the study's purpose is to evaluate the antecedent factors that the influence usage and continuance usage of a recently introduced AI-based tool…
Descriptors: Artificial Intelligence, Technology Uses in Education, Educational Resources, Educational Technology
Wilson, Joseph; Pollard, Benjamin; Aiken, John M.; Lewandowski, H. J. – Physical Review Physics Education Research, 2022
Surveys have long been used in physics education research to understand student reasoning and inform course improvements. However, to make analysis of large sets of responses practical, most surveys use a closed-response format with a small set of potential responses. Open-ended formats, such as written free response, can provide deeper insights…
Descriptors: Natural Language Processing, Science Education, Physics, Artificial Intelligence
Meddeb, Ons; Maraoui, Mohsen; Zrigui, Mounir – International Journal of Web-Based Learning and Teaching Technologies, 2021
The advancement of technologies has modernized learning within smart campuses and has emerged new context through communication between mobile devices. Although there is a revolutionary way to deliver long-term education, a great diversity of learners may have different levels of expertise and cannot be treated in a consistent manner.…
Descriptors: Educational Technology, Semitic Languages, Natural Language Processing, Internet
Silvia García-Méndez; Francisco de Arriba-Pérez; Francisco J. González-Castaño – International Association for Development of the Information Society, 2023
Mobile learning or mLearning has become an essential tool in many fields in this digital era, among the ones educational training deserves special attention, that is, applied to both basic and higher education towards active, flexible, effective high-quality and continuous learning. However, despite the advances in Natural Language Processing…
Descriptors: Higher Education, Artificial Intelligence, Computer Software, Usability
Chengyuan Jia; Khe Foon Hew; Mingting Li – Computer Assisted Language Learning, 2025
Listening is a major challenge for many English-as-a-foreign language (EFL) learners. Decoding training, which helps learners develop the ability to recognize words from speech, is frequently used to assist EFL learners. Although recent empirical studies on decoding training have provided positive evidence on its effectiveness in improving EFL…
Descriptors: Flipped Classroom, Second Language Learning, Second Language Instruction, Teaching Methods
Sanchez-Ferreres, Josep; Delicado, Luis; Andaloussi, Amine Abbab; Burattin, Andrea; Calderon-Ruiz, Guillermo; Weber, Barbara; Carmona, Josep; Padro, Lluis – IEEE Transactions on Learning Technologies, 2020
The creation of a process model is primarily a formalization task that faces the challenge of constructing a syntactically correct entity, which accurately reflects the semantics of reality, and is understandable to the model reader. This article proposes a framework called "Model Judge," focused toward the two main actors in the process…
Descriptors: Models, Automation, Validity, Natural Language Processing
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
Braasch, Jason L. G.; Kessler, Erica D. – Discourse Processes: A Multidisciplinary Journal, 2021
Comprehension substantially benefits from attending to, thinking about, and mentally representing the sources of any presented information. Such processes require mental effort and unfortunately people do not always engage in such activities. The current article presents a nascent, evolving model of discourse comprehension that formalizes…
Descriptors: Language Processing, Reading Comprehension, Discourse Analysis, Prediction
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
Belda-Medina, Jose; Kokošková, Vendula – International Journal of Educational Technology in Higher Education, 2023
Recent advances in Artificial Intelligence (AI) have paved the way for the integration of text-based and voice-enabled chatbots as adaptive virtual tutors in education. Despite the increasing use of AI-powered chatbots in language learning, there is a lack of studies exploring the attitudes and perceptions of teachers and students towards these…
Descriptors: Technology Integration, Technology Uses in Education, Artificial Intelligence, Man Machine Systems
Rybinski, Krzysztof; Kopciuszewska, Elzbieta – Assessment & Evaluation in Higher Education, 2021
This article presents the first-ever big data study of the student evaluation of teaching (SET) using artificial intelligence (AI). We train natural language processing (NLP) models on 1.6 million student evaluations from the US and the UK. We address two research questions: (1) are these models able to predict student ratings from the student…
Descriptors: Artificial Intelligence, Technology Uses in Education, Student Evaluation of Teacher Performance, Natural Language Processing
Fernández-López, María; Marcet, Ana; Perea, Manuel – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2019
In past decades, researchers have conducted a myriad of masked priming lexical decision experiments aimed at unveiling the early processes underlying lexical access. A relatively overlooked question is whether a masked unrelated wordlike/unwordlike prime influences the processing of the target stimuli. If participants apply to the primes the same…
Descriptors: Priming, Decision Making, Language Processing, Bayesian Statistics

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