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Bryan Abendschein; Xialing Lin; Chad Edwards; Autumn Edwards; Varun Rijhwani – Journal of Computer Assisted Learning, 2024
Background: Education is often the primary arena for exploring and integrating new technologies. AI and human-machine communication (HMC) are prevalent in the classroom, yet we are still learning how student perceptions of these tools will impact education. Objectives: We sought to understand student perceptions of credibility related to written…
Descriptors: Students, Student Attitudes, Feedback (Response), Writing (Composition)
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Yang Zhen; Xiaoyan Zhu – Educational and Psychological Measurement, 2024
The pervasive issue of cheating in educational tests has emerged as a paramount concern within the realm of education, prompting scholars to explore diverse methodologies for identifying potential transgressors. While machine learning models have been extensively investigated for this purpose, the untapped potential of TabNet, an intricate deep…
Descriptors: Artificial Intelligence, Models, Cheating, Identification
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Edwin Chng – Journal of Science Education and Technology, 2024
With teachers continuing to report challenges in classroom management and difficulties in implementing scientific inquiry, the current manner in which science practical work is conducted in schools suggests the need for added teacher support. In this regard, we can leverage computer vision to provide instructional support by relieving teachers of…
Descriptors: Artificial Intelligence, Science Education, Computer Uses in Education, Science Teachers
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Yang Zhong; Mohamed Elaraby; Diane Litman; Ahmed Ashraf Butt; Muhsin Menekse – Grantee Submission, 2024
This paper introduces REFLECTSUMM, a novel summarization dataset specifically designed for summarizing students' reflective writing. The goal of REFLECTSUMM is to facilitate developing and evaluating novel summarization techniques tailored to real-world scenarios with little training data, with potential implications in the opinion summarization…
Descriptors: Documentation, Writing (Composition), Reflection, Metadata
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Pan, Yiqin; Wollack, James A. – Journal of Educational Measurement, 2021
As technologies have been improved, item preknowledge has become a common concern in the test security area. The present study proposes an unsupervised-learning-based approach to detect compromised items. The unsupervised-learning-based compromised item detection approach contains three steps: (1) classify responses of each examinee as either…
Descriptors: Test Items, Cheating, Artificial Intelligence, Identification
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Pekrun, Reinhard – British Journal of Educational Psychology, 2023
Background and Aims: Traditionally, research in educational psychology has neglected the physiological foundations of motivation, emotion, engagement, and learning. Recent studies have made substantial progress to more fully consider physiological processes, as documented in the contributions to this special issue. In this commentary, I summarize…
Descriptors: Higher Education, Artificial Intelligence, Publications, Researchers
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Xu, Ying – Child Development Perspectives, 2023
Back-and-forth conversations with others are vital for children's development in the early years. While children's conversation partners have traditionally been their parents, teachers, and peers, recent advances in artificial intelligence have led to the introduction of machines that understand human speech and generate natural responses, and…
Descriptors: Artificial Intelligence, Man Machine Systems, Computer Mediated Communication, Educational Technology
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Nie, Rui; Guo, Qi; Morin, Maxim – Educational Measurement: Issues and Practice, 2023
The COVID-19 pandemic has accelerated the digitalization of assessment, creating new challenges for measurement professionals, including big data management, test security, and analyzing new validity evidence. In response to these challenges, "Machine Learning" (ML) emerges as an increasingly important skill in the toolbox of measurement…
Descriptors: Artificial Intelligence, Electronic Learning, Literacy, Educational Assessment
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Elkhatat, Ahmed M. – International Journal for Educational Integrity, 2023
Academic plagiarism is a pressing concern in educational institutions. With the emergence of artificial intelligence (AI) chatbots, like ChatGPT, potential risks related to cheating and plagiarism have increased. This study aims to investigate the authenticity capabilities of ChatGPT models 3.5 and 4 in generating novel, coherent, and accurate…
Descriptors: Artificial Intelligence, Plagiarism, Integrity, Models
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De Ruyck, Olivia; Conradie, Peter; Van Hove, Stephanie; All, Anissa; Baccarne, Bastiaan; De Marez, Lieven; Saldien, Jelle – International Journal of Technology and Design Education, 2023
Interactions between humans and smart products (i.e. digital components integrated in physical Internet of Things devices) are becoming more complex and less visible. Yet designers lack tools to capture these interactions and incorporate them into their design. In this paper we present the Human-Computer-Context Interaction (HCCI) tool that helps…
Descriptors: Man Machine Systems, Industrial Arts, Design, Internet
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Crescenzi-Lanna, Lucrezia – Journal of Research on Technology in Education, 2023
This paper presents a systematic literature review of artificial intelligence (AI)-supported teaching and learning in early childhood. The focus is on human-machine cooperation in education. International evidence and associated problems with the reciprocal contributions of humans and machines are presented and discussed, as well as future…
Descriptors: Artificial Intelligence, Programming, Educational Technology, Man Machine Systems
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Amane, Meryem; Aissaoui, Karima; Berrada, Mohammed – International Journal of Information and Learning Technology, 2023
Purpose: Together, learning objects (LOs) and e-pedagogical practices have the potential to improve the performance of e-learning systems in several ways. They can make e-learning more personalised and adaptable, providing students with a more engaging and effective learning experience. Design/methodology/approach: The development of LOs and…
Descriptors: Electronic Learning, Resource Units, Metadata, Algorithms
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Francisco Tigre Moura; Chiara Castrucci; Clare Hindley – Journal of Creative Behavior, 2023
This paper presents a study analyzing the perception of artistic products created by or with the support of artificial intelligence (AI). The research builds on previous studies revealing that the output of artificial creativity processes can indeed rival human-made products, satisfy consumer expectations, and derive enjoyment. However, in…
Descriptors: Creativity, Artificial Intelligence, Art, Automation
Ran Tao – ProQuest LLC, 2023
Vision classification tasks, a fundamental and transformative aspect of deep learning and computer vision, play a pivotal role in our ability to understand the visual world. Deep learning techniques have revolutionized the field, enabling unprecedented accuracy and efficiency in vision classification. However, deep learning models, especially…
Descriptors: Classification, Vision, Documentation, Data Collection
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Gerardo Quiroz Vieyra; Luis Fernando Muñoz González – European Journal of Education (EJED), 2023
Learning Management Systems (LMS) or Learning Content Management Systems (LCMS) are the core of e-learning platforms and have evolved according to the development of new information and communication technologies. In this type of software there are many products on the market, some developed by the institutions themselves (in-house), others are…
Descriptors: Online Systems, Electronic Learning, Learning Management Systems, Artificial Intelligence
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