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Leslie Valiant – Princeton University Press, 2024
We are at a crossroads in history. If we hope to share our planet successfully with one another and the AI systems we are creating, we must reflect on who we are, how we got here, and where we are heading. "The Importance of Being Educable" puts forward a provocative new exploration of the extraordinary facility of humans to absorb and…
Descriptors: Education, Cognitive Processes, Brain, Information Literacy
Alexander Skulmowski – Educational Psychology Review, 2024
Generative AIs have been embraced by learners wishing to offload (parts of) complex tasks. However, recent research suggests that AI users are at risk of failing to correctly monitor the extent of their own contribution when being assisted by an AI. This difficulty in keeping track of the division of labor has been shown to result in placebo and…
Descriptors: Artificial Intelligence, Cognitive Processes, Difficulty Level, Epistemology
Janice Leigh Klima – ProQuest LLC, 2024
This qualitative descriptive case study explores how genealogists describe the mechanism of epistemic change in their research, highlighting the roles of epistemological doubt, epistemological volition, and resolution strategies. It explores the integration of digital technologies in genealogical practices in the United States and their…
Descriptors: Genealogy, Epistemology, Beliefs, Cognitive Processes
Yongtian Cheng; K. V. Petrides – Educational and Psychological Measurement, 2025
Psychologists are emphasizing the importance of predictive conclusions. Machine learning methods, such as supervised neural networks, have been used in psychological studies as they naturally fit prediction tasks. However, we are concerned about whether neural networks fitted with random datasets (i.e., datasets where there is no relationship…
Descriptors: Psychological Studies, Artificial Intelligence, Cognitive Processes, Predictive Validity
Yoon Lee; Gosia Migut; Marcus Specht – British Journal of Educational Technology, 2025
Learner behaviours often provide critical clues about learners' cognitive processes. However, the capacity of human intelligence to comprehend and intervene in learners' cognitive processes is often constrained by the subjective nature of human evaluation and the challenges of maintaining consistency and scalability. The recent widespread AI…
Descriptors: Artificial Intelligence, Cognitive Processes, Student Behavior, Cues
Helene Ackermann; Anja Henke; Johann Chevalère; Hae Seon Yun; Verena V. Hafner; Niels Pinkwart; Rebecca Lazarides – npj Science of Learning, 2025
Rising interest in artificial intelligence in education reinforces the demand for evidence-based implementation. This study investigates how tutor agents' physical embodiment and anthropomorphism (student-reported sociability, animacy, agency, and disturbance) relate to affective (on-task enjoyment) and cognitive (task performance) learning within…
Descriptors: Artificial Intelligence, Intelligent Tutoring Systems, Animals, Human Body
Varghese Panthalookaran – Higher Education for the Future, 2025
Unlike other technologies that augment human physical skills and abilities, artificial intelligence (AI) technologies interact with human thinking skills nurtured through various educational processes. Hence, advances in these technologies challenge the education sector to reimagine the suitable intellectual formation of students in the AI age. It…
Descriptors: Taxonomy, Artificial Intelligence, Thinking Skills, Educational Objectives
Sven Banisch; Hawal Shamon – Sociological Methods & Research, 2025
We combine empirical experimental research on biased argument processing with a computational theory of group deliberation to overcome the micro-macro problem of sociology and to clarify the role of biased processing in debates around energy. We integrate biased processing into the framework of argument communication theory in which agents…
Descriptors: Persuasive Discourse, Energy, Group Dynamics, Opinions
Yannik Fleischer; Susanne Podworny; Rolf Biehler – Statistics Education Research Journal, 2024
This study investigates how 11- to 12-year-old students construct data-based decision trees using data cards for classification purposes. We examine the students' heuristics and reasoning during this process. The research is based on an eight-week teaching unit during which students labeled data, built decision trees, and assessed them using test…
Descriptors: Decision Making, Data Use, Cognitive Processes, Artificial Intelligence
Ann Musgrove; Jillian Powers; Mohammad Azhar; Cristine Yao – Contemporary Issues in Technology and Teacher Education (CITE Journal), 2024
This study examined how an online instructional module that included an unplugged robot design activity integrated computational thinking (CT), assistive technology (AT), and universal design principles into a preservice teacher education class. The research focused on how this module shaped understanding, attitudes, and comfort levels about…
Descriptors: Preservice Teacher Education, Preservice Teachers, Artificial Intelligence, Cognitive Processes
Stefan Depeweg; Contantin A. Rothkopf; Frank Jäkel – Cognitive Science, 2024
More than 50 years ago, Bongard introduced 100 visual concept learning problems as a challenge for artificial vision systems. These problems are now known as Bongard problems. Although they are well known in cognitive science and artificial intelligence, only very little progress has been made toward building systems that can solve a substantial…
Descriptors: Visual Learning, Problem Solving, Cognitive Science, Artificial Intelligence
Unggi Lee; Yeil Jeong; Junbo Koh; Gyuri Byun; Yunseo Lee; Hyunwoong Lee; Seunmin Eun; Jewoong Moon; Cheolil Lim; Hyeoncheol Kim – Smart Learning Environments, 2024
This preliminary study explores how GPT-4 Vision (GPT-4V) technology can be integrated into teacher analytics through observational assessment, aiming to improve reflective teaching practice. Our study develops a Video-based Automatic Assessment System (VidAAS) powered by GPT-4V. This approach uses Generative Artificial Intelligence (GenAI) to…
Descriptors: Observation, Teaching Methods, Artificial Intelligence, Behavior
Jennifer Gunn – English in Texas, 2024
This paper considers the impact of technological processes on human thought, specifically the implications of artificial intelligence (AI) on writing instruction. The main purpose of this paper is to present instructional considerations that will elevate human voice and reduce student temptations to turn to AI unreasonably to produce a piece of…
Descriptors: Artificial Intelligence, Technology Uses in Education, Writing Instruction, Developmental Studies Programs
Sijia Chen; Jan-Louis Kruger – Interpreter and Translator Trainer, 2024
Following a preliminary study that examined the potential effectiveness of a computer-assisted consecutive interpreting (CACI) mode, this paper presents a further trial of the CACI workflow. The workflow involves respeaking using speech recognition (SR) in phase I and production assisted by the SR text and its machine translation (MT) output in…
Descriptors: Computer Assisted Instruction, Artificial Intelligence, Translation, Speech Communication
Leveraging Large Language Models to Generate Course-Specific Semantically Annotated Learning Objects
Dominic Lohr; Marc Berges; Abhishek Chugh; Michael Kohlhase; Dennis Müller – Journal of Computer Assisted Learning, 2025
Background: Over the past few decades, the process and methodology of automatic question generation (AQG) have undergone significant transformations. Recent progress in generative natural language models has opened up new potential in the generation of educational content. Objectives: This paper explores the potential of large language models…
Descriptors: Resource Units, Semantics, Automation, Questioning Techniques