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Michael Mindzak – Brock Education: A Journal of Educational Research and Practice, 2024
The integration of artificial intelligence (AI) into education has prompted significant reflection on the nature of work and labour among teachers and students. This essay examines the implications of AI on educational labour, highlighting the distinction between work, encompassing unpaid and broader educational contributions, and labour, defined…
Descriptors: Artificial Intelligence, Technology Uses in Education, Labor, Role
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Melek Gülsah Sahin; Yildiz Yildirim – International Journal of Assessment Tools in Education, 2024
This study aims to generalize the reliability of the GAAIS, which is known to perform valid and reliable measurements, is frequently used in the literature, aims to measure one of today's popular topics, and is one of the first examples developed in the field. Within the meta-analytic reliability generalization study, moderator analyses were also…
Descriptors: Generalization, Meta Analysis, Databases, Research Reports
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Oluwaseyi A. G. Opesemowo; Mdutshekelwa Ndlovu – Journal of Pedagogical Research, 2024
Integrating Artificial Intelligence [AI] into mathematics education offers promising advancements and potential pitfalls. Striking a balance between AI-driven developments and preserving core pedagogical principles is critical in the teaching and learning environment. AI has emerged as a transformative force in various fields, including education.…
Descriptors: Artificial Intelligence, Mathematics Education, Technology Integration, Mathematics Instruction
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Derek C. Briggs – Journal of Educational and Behavioral Statistics, 2024
I consider recent attempts to establish standards, principles, and goals for artificial intelligence (AI) through the lens of educational measurement. Distinctions are made between generative AI and AI-adjacent methods and applications of AI in formative versus summative assessment contexts. While expressing optimism about its possibilities, I…
Descriptors: Artificial Intelligence, Standard Setting, Standards, Measurement
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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
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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
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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
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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
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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
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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
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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
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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
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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
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