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Jennifer J. Chen; Jasmine C. Lin – Contemporary Issues in Early Childhood, 2024
Advances in artificial intelligence (AI) over the last few decades are transforming the world, pervading nearly all sectors of society, including education, and many aspects of life. In the education discourse, interest in artificial intelligence has sparked various reactions and controversies--everything from appreciation for AI's capabilities to…
Descriptors: Artificial Intelligence, Technological Advancement, Technology Uses in Education, Early Childhood Education
Xiaojing Duan; Bo Pei; G. Alex Ambrose; Arnon Hershkovitz; Ying Cheng; Chaoli Wang – Education and Information Technologies, 2024
Providing educators with understandable, actionable, and trustworthy insights drawn from large-scope heterogeneous learning data is of paramount importance in achieving the full potential of artificial intelligence (AI) in educational settings. Explainable AI (XAI)--contrary to the traditional "black-box" approach--helps fulfilling this…
Descriptors: Academic Achievement, Artificial Intelligence, Prediction, Models
D. Joel Whalen; Charles Drehmer; Andrew Cavanaugh – Business and Professional Communication Quarterly, 2024
Artificial intelligence assignments lead this article's 11 teaching innovations selected from the "My Favorite Assignments" presented at the 2023 Association for Business Communication's (ABC's) 88th Annual International Conference held in the Mile-High City: Denver, Colorado, USA. Pedagogy presented here also includes ideas to enhance…
Descriptors: Business Communication, Business Education, Artificial Intelligence, Assignments
Robert J. Sternberg – Gifted Child Quarterly, 2024
This article proposes a duplex model for understanding giftedness. The first part of the duplex is the set of gifted skills and attitudes that one possesses as a result of heredity, the environment, and their interaction. It is the input that one has acquired from one's life experiences. The second part of the duplex is the utilization or…
Descriptors: Gifted, Individual Characteristics, Ability, Models
Zachary K. Collier; Minji Kong; Olushola Soyoye; Kamal Chawla; Ann M. Aviles; Yasser Payne – Journal of Educational and Behavioral Statistics, 2024
Asymmetric Likert-type items in research studies can present several challenges in data analysis, particularly concerning missing data. These items are often characterized by a skewed scaling, where either there is no neutral response option or an unequal number of possible positive and negative responses. The use of conventional techniques, such…
Descriptors: Likert Scales, Test Items, Item Analysis, Evaluation Methods
Youmi Suk; Kyung T. Han – Journal of Educational and Behavioral Statistics, 2024
As algorithmic decision making is increasingly deployed in every walk of life, many researchers have raised concerns about fairness-related bias from such algorithms. But there is little research on harnessing psychometric methods to uncover potential discriminatory bias inside decision-making algorithms. The main goal of this article is to…
Descriptors: Psychometrics, Ethics, Decision Making, Algorithms
S. Siva Shankar; Bui Thanh Hung; Prasun Chakrabarti; Tulika Chakrabarti; Gayatri Parasa – Education and Information Technologies, 2024
Modern life is increasingly influenced by networks, making cybersecurity a crucial area of study. However, due to their few resources and varied makeup, they are more vulnerable to a wide range of cyber-attacks. Such risks result in sensitive information being stolen as well as financial and reputational harm to firms. How far malicious detection…
Descriptors: Learning Processes, Artificial Intelligence, Information Security, Computer Security
Wei Zhang; Mingxuan Cai; Hong Joo Lee; Richard Evans; Chengyan Zhu; Chenghan Ming – Education and Information Technologies, 2024
Artificial Intelligence (AI) is transforming healthcare and shows considerable promise for the delivery of medical education. This systematic review provides a comprehensive analysis of the global situation, effects, and challenges associated with applying AI at the different stages of medical education. This review followed the PRISMA guidelines,…
Descriptors: Artificial Intelligence, Medical Education, Content Analysis, Teaching Methods
Bambang Sulistio; Arief Ramadhan; Edi Abdurachman; Muhammad Zarlis; Agung Trisetyarso – Education and Information Technologies, 2024
Computer science development, especially machine learning, is a thriving innovation essential for education. It makes the process of teaching and learning more accessible and manageable and also promotes equality. The positive influence of machine learning can also be felt in Islamic studies, particularly in Hadith studies. This literature review…
Descriptors: Electronic Learning, Artificial Intelligence, Computer Uses in Education, Islam
Xiao-Fan Lin; Yue Zhou; Weipeng Shen; Guoyu Luo; Xiaoqing Xian; Bo Pang – Education and Information Technologies, 2024
K-12 artificial intelligence (AI) education requires cultivating students' computational thinking in the school curriculum so as to transfer their computational thinking to diverse problems and authentic contexts. However, students may be limited by traditional computational thinking development activities because they may have a lower degree of…
Descriptors: Secondary School Students, Artificial Intelligence, Foreign Countries, Computation
Herut, Adane Hailu; Muleta, Habtamu Disassa; Lebeta, Mulugeta Fufa – Online Submission, 2024
In education, understanding the determinants of learners' achievement is crucial. This study aimed to explore the correlation between emotional intelligence (EI) and academic achievement in primary schools. Using Goleman's Emotional Intelligence Assessment Scale adapted for local use, 444 primary school students were assessed via random sampling.…
Descriptors: Foreign Countries, Emotional Intelligence, Prediction, Academic Achievement
Jiahong Su; Weipeng Yang – Journal of Computer Assisted Learning, 2024
Background: The number of artificial intelligence (AI) literacy studies in K-12 education has recently increased, with most research focusing on primary and secondary education contexts. Little research focuses on AI literacy programs in early childhood education. Objectives: The aim of this mixed-methods study is to examine the feasibility of an…
Descriptors: Foreign Countries, Artificial Intelligence, Kindergarten, Young Children
Chih-Hsuan Chen; Chia-Ru Chung; Hsuan-Yu Yang; Shih-Ching Yeh; Eric Hsiao-Kuang Wu; Hsin-Jung Ting – IEEE Transactions on Learning Technologies, 2024
Possible symptoms of intellectual disability (ID) include delayed physical development that becomes more pronounced as the disability progresses, delayed development of gross and fine motor skills, sensory perception problems, and difficulty grasping the integrity of objects. Although there is no cure or reversal, research has shown that extensive…
Descriptors: Intellectual Disability, Disability Identification, Simulated Environment, Computer Simulation
Felipe de Morais; Patricia A. Jaques – IEEE Transactions on Learning Technologies, 2024
Emotion detection through sensors is intrusive and expensive, making it impractical for many educational settings. As an alternative, sensor-free affect detection, which relies solely on interaction log data for machine learning models, has been explored. However, sensor-free emotion detectors have not significantly improved performance when…
Descriptors: Psychological Patterns, Personality Traits, Artificial Intelligence, Models
Danial Hooshyar – Education and Information Technologies, 2024
Neural and symbolic architectures are key techniques in AI for learner modelling, enhancing adaptive educational services. Symbolic models offer explanation and reasoning for decisions but require significant human effort. On the other hand, neural architectures demand less human input and yield better predictions, yet lack interpretability. Given…
Descriptors: Artificial Intelligence, Modeling (Psychology), Learner Engagement, Achievement

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