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Lanqin Zheng; Yunchao Fan; Bodong Chen; Zichen Huang; LeiGao; Miaolang Long – Education and Information Technologies, 2024
Online collaborative learning has been broadly applied in higher education. However, learners face many challenges in collaborating with one another and coregulating their learning, leading to low group performance. To address the gaps, this study proposed an artificial intelligence (AI)-enabled feedback and feedforward approach that not only…
Descriptors: Artificial Intelligence, Feedback (Response), Electronic Learning, Cooperative Learning
Ryan Hare; Ying Tang; Sarah Ferguson – IEEE Transactions on Education, 2024
Contribution: A general-purpose model for integrating an intelligent tutoring system within a serious game for use in higher education. Additionally, this article also offers discussions of proper serious game design informed by in-classroom observations and student responses. Background: Personalized learning in higher education has become a key…
Descriptors: Intelligent Tutoring Systems, Game Based Learning, Gamification, Student Attitudes
Eyüp Yurt; Ismail Kasarci – International Journal of Technology in Education, 2024
This study introduces the Questionnaire of AI Use Motives (QAIUM), an instrument designed to measure motivation levels in individuals using artificial intelligence (AI) applications. Building on a theoretical framework that emphasizes motivation over dispositions and defines motivation as expectancy/value, the QAIUM aims to fill a research gap in…
Descriptors: Artificial Intelligence, Foreign Countries, College Students, Student Attitudes
K. I. Senadhira; R. A. H. M. Rupasingha; B. T. G. S. Kumara – Education and Information Technologies, 2024
The majority of educational institutions around the world have switched to online learning due to the COVID-19 pandemic. Since continuing education has become important during the pandemic as well, academics and students have recognized the value of online learning to avoid their challenges. The objective of this study is to categorize peoples'…
Descriptors: Classification, Artificial Intelligence, Social Media, Electronic Learning
Ishanti Gangopadhyay; Daniel Fulford; Kathleen Corriveau; Jessica Mow; Pearl Han Li; Sudha Arunachalam – Cognitive Science, 2024
Understanding cognitive effort expended during assessments is essential to improving efficiency, accuracy, and accessibility within these assessments. Pupil dilation is commonly used as a psychophysiological measure of cognitive effort, yet research on its relationship with effort expended specifically during language processing is limited. The…
Descriptors: Vocabulary, Difficulty Level, Motor Reactions, Cognitive Ability
Jill Fenton Taylor; Ivana Crestani – Qualitative Research Journal, 2024
Purpose: This paper aims to explore how an academic researcher and a practitioner experience scepticism for their qualitative research. Design/methodology/approach: The study applies Olt and Teman's new conceptual phenomenological polyethnography (2019) methodology, a hybrid of phenomenology and duoethnography. Findings: For the…
Descriptors: Qualitative Research, Phenomenology, Ethnography, Bias
Ana Fernández-Mera; José Antonio Hinojosa; Jon Andoni Duñabeitia – Electronic Journal of Research in Educational Psychology, 2024
Introduction: This study investigated the possible existence of differences in several domains or traits of the general construct of emotional intelligence between highly able children and their normotypically developing peers. Method: A group of children with high abilities and a group of children with average intellectual development completed…
Descriptors: Emotional Intelligence, Gifted, Foreign Countries, Preadolescents
A Method for Generating Course Test Questions Based on Natural Language Processing and Deep Learning
Hei-Chia Wang; Yu-Hung Chiang; I-Fan Chen – Education and Information Technologies, 2024
Assessment is viewed as an important means to understand learners' performance in the learning process. A good assessment method is based on high-quality examination questions. However, generating high-quality examination questions manually by teachers is a time-consuming task, and it is not easy for students to obtain question banks. To solve…
Descriptors: Natural Language Processing, Test Construction, Test Items, Models
Muhammad Imran; Norah Almusharraf – Smart Learning Environments, 2024
This emerging technology report discusses Google Gemini as a multimodal generative AI tool and presents its revolutionary potential for future educational technology. It introduces Gemini and its features, including versatility in processing data from text, image, audio, and video inputs and generating diverse content types. This study discusses…
Descriptors: Artificial Intelligence, Computer Software, Educational Technology, Technology Uses in Education
Louis Volante; Don A. Klinger; Christopher DeLuca – Phi Delta Kappan, 2024
The promotion and measurement of standards in compulsory education systems has been a prominent feature of Western education systems for centuries. But the COVID-19 pandemic and the rise of artificial intelligence (AI) have made the limits of current standards-based approaches to assessment more evident. Louis Volante, Don A. Klinger, and…
Descriptors: Educational Change, Academic Standards, Compulsory Education, COVID-19
Violet Leticia Vera-Gutierrez – ProQuest LLC, 2024
Emotional intelligence equips leaders to exercise self-management, self-awareness, social awareness and manage relationships. Furthermore, emotional intelligence skills correlate with various leadership skills. Emotional intelligence supports their ability to develop trusting relationships that inspire others to perform collaboratively. It also…
Descriptors: Superintendents, Emotional Intelligence, Leadership Styles, Disproportionate Representation
Mohammad Mohi Uddin – Discover Education, 2024
The abrupt evolution of Artificial Intelligence (AI) in academia has spurred a complex debate regarding its rejection or integration in academia. This study aims to portray a comparative analysis of the risks associated with the integration of AI and the missed opportunities in the absence of AI in academic settings. Utilizing the economic theory…
Descriptors: Artificial Intelligence, Technology Uses in Education, Higher Education, Risk
Wangqian Fu; Huixing Chen; Yawen Xiao; Cui Yin – International Journal of Developmental Disabilities, 2024
Background: Little is known about the categorization ability of children with intellectual disabilities (ID) in China, which is critical in guiding teaching practice and learning support strategies for those students. The study has aimed to explore the characteristics of categorization ability of children with ID. Method: This study used an…
Descriptors: Foreign Countries, Moderate Intellectual Disability, Classification, Children
Joan Li; Nikhil Kumar Jangamreddy; Ryuto Hisamoto; Ruchita Bhansali; Amalie Dyda; Luke Zaphir; Mashhuda Glencross – Australasian Journal of Educational Technology, 2024
Generative artificial intelligence technologies, such as ChatGPT, bring an unprecedented change in education by leveraging the power of natural language processing and machine learning. Employing ChatGPT to assist with marking written assessment presents multiple advantages including scalability, improved consistency, eliminating biases associated…
Descriptors: Higher Education, Artificial Intelligence, Grading, Scoring Rubrics
Laura M. Bernhardt – New Directions for Teaching and Learning, 2024
This essay uses an example of a library instruction exercise in which otherwise competent online searching goes wrong as a springboard for reconceptualizing digital literacy as an environmental ethics of information. This reconceptualization is presented as a corrective measure for teachers and students grappling with the uses and misuses of AI…
Descriptors: Digital Literacy, Ethics, Library Instruction, Online Searching

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