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Laura E. Matzen; Zoe N. Gastelum; Breannan C. Howell; Kristin M. Divis; Mallory C. Stites – Cognitive Research: Principles and Implications, 2024
This study addressed the cognitive impacts of providing correct and incorrect machine learning (ML) outputs in support of an object detection task. The study consisted of five experiments that manipulated the accuracy and importance of mock ML outputs. In each of the experiments, participants were given the T and L task with T-shaped targets and…
Descriptors: Artificial Intelligence, Error Patterns, Decision Making, Models
Why Explainable AI May Not Be Enough: Predictions and Mispredictions in Decision Making in Education
Mohammed Saqr; Sonsoles López-Pernas – Smart Learning Environments, 2024
In learning analytics and in education at large, AI explanations are always computed from aggregate data of all the students to offer the "average" picture. Whereas the average may work for most students, it does not reflect or capture the individual differences or the variability among students. Therefore, instance-level…
Descriptors: Artificial Intelligence, Decision Making, Predictor Variables, Feedback (Response)
Sonsoles Lopez-Pernas; Kamila Misiejuk; Rogers Kaliisa; Mohammed Saqr – IEEE Transactions on Learning Technologies, 2025
Despite the growing use of large language models (LLMs) in educational contexts, there is no evidence on how these can be operationalized by students to generate custom datasets suitable for teaching and learning. Moreover, in the context of network science, little is known about whether LLMs can replicate real-life network properties. This study…
Descriptors: Students, Artificial Intelligence, Man Machine Systems, Interaction
Aaron Wolf – Educational Theory, 2025
Much has been written about how to improve the fairness of AI tools for decision-making but less has been said about how to approach this new field from the perspective of philosophy of education. My goal in this paper is to bring together criteria from the general algorithmic fairness literature with prominent values of justice defended by…
Descriptors: Algorithms, Artificial Intelligence, Technology Uses in Education, Educational Philosophy
Mark Johnson; Rafiq Saleh – Interactive Learning Environments, 2024
Educational assessment is inherently uncertain, where physiological, psychological and social factors play an important role in establishing judgements which are assumed to be "absolute". AI and other algorithmic approaches to grading of student work strip-out uncertainty, leading to a lack of inspectability in machine judgement and…
Descriptors: Artificial Intelligence, Evaluation Methods, Technology Uses in Education, Man Machine Systems
André Markus; Maximilian Baumann; Jan Pfister; Andreas Hotho; Astrid Carolus; Carolin Wienrich – Discover Education, 2025
Intelligent Voice Assistants (IVAs) have become integral to many users' daily lives, using advanced algorithms to automate various tasks. Nevertheless, many users do not understand the underlying algorithms and how they work, posing potential risks to the competent and self-determined use of IVAs. This work develops three online training modules…
Descriptors: Algorithms, Digital Literacy, Training, Artificial Intelligence
Sarah Jerasa; Sarah K. Burriss – English Teaching: Practice and Critique, 2024
Purpose: Artificial intelligence (AI) has become increasingly important and influential in reading and writing. The influx of social media digital spaces, like TikTok, has also shifted the ways multimodal composition takes place alongside AI. This study aims to argue that within spaces like TikTok, human composers must attend to the ways they…
Descriptors: Artificial Intelligence, Social Media, Algorithms, Writing (Composition)
Cingillioglu, Ilker – International Journal of Information and Learning Technology, 2023
Purpose: With the advent of ChatGPT, a sophisticated generative artificial intelligence (AI) tool, maintaining academic integrity in all educational settings has recently become a challenge for educators. This paper discusses a method and necessary strategies to confront this challenge. Design/methodology/approach: In this study, a language model…
Descriptors: Artificial Intelligence, Essays, Integrity, Cheating
Kasra Lekan; Zachary A. Pardos – Journal of Learning Analytics, 2025
Choosing an undergraduate major is an important decision that impacts academic and career outcomes. In this work, we investigate augmenting personalized human advising for major selection using a large language model (LLM), GPT-4. Through a three-phase survey, we compare GPT suggestions and responses for undeclared first- and second-year students…
Descriptors: Technology Uses in Education, Artificial Intelligence, Academic Advising, Majors (Students)
Jun Liu – Education and Information Technologies, 2025
Learners of Japanese as a second language (JSL) find it difficult to learn various sentence patterns. To assist JSL learners with their study of Japanese sentence patterns (JSPs), this paper constructs a human-machine collaborative framework that combines artificial intelligence (AI) techniques with the users' active participation for Japanese…
Descriptors: Artificial Intelligence, Technology Uses in Education, Man Machine Systems, Second Language Learning
Kotlyar, Igor; Sharifi, Tina; Fiksenbaum, Lisa – International Journal of Artificial Intelligence in Education, 2023
Teamwork skills are commonly evaluated by human assessors, which can be logistically challenging and resource intensive. Technological advancements provide an opportunity for a new assessment method -- virtual behavioural simulations with self-scoring algorithms. This study explores whether a rule-based algorithm can match human assessors at…
Descriptors: Algorithms, Undergraduate Students, Computer Simulation, Evaluation
Bahar Memarian; Tenzin Doleck – Education and Information Technologies, 2024
A key feature of embodied education is the participation of the learners' body and mind with the environment. Yet, little work has been done to review the state of embodied education with Artificial Intelligence (AI). The goal of this systematic review is to examine the state of human and AI's triad engagement in education, that is the mind, body,…
Descriptors: Artificial Intelligence, Cognitive Processes, Human Body, Technology Uses in Education
Aras Bozkurt; Ramesh C. Sharma – Asian Journal of Distance Education, 2024
This study explores the transformative potential of Generative AI (GenAI) and ChatBots in educational interaction, communication, and the broader implications of human-GenAI collaboration. By examining the related literature through data mining and analytical methods, the paper identifies three main research themes: the revolutionary role of…
Descriptors: Algorithms, Artificial Intelligence, Man Machine Systems, Technology Uses in Education
Huixiao Le; Yuan Shen; Zijian Li; Mengyu Xia; Luzhen Tang; Xinyu Li; Jiyou Jia; Qiong Wang; Dragan Gaševic; Yizhou Fan – British Journal of Educational Technology, 2025
Understanding learners' preferences in educational settings is crucial for optimizing learning outcomes and experience. As artificial intelligence (AI) becomes increasingly integrated into educational contexts, it is crucial to understand learners' preferences between AI and human tutors to support their learning. While AI demonstrates growing…
Descriptors: Student Attitudes, Preferences, Electronic Learning, Artificial Intelligence
Graham B. Slater – Review of Education, Pedagogy & Cultural Studies, 2024
Accelerating digitization, algorithmic computation, artificial intelligence, and machine learning, along with the increasing automation of work, communication, and everyday life, are central to critical studies of technology and political economy, as well as to public discourse concerning technology's role in creating futures. Ongoing…
Descriptors: Algorithms, Anxiety, Artificial Intelligence, Man Machine Systems
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