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Héctor J. Pijeira-Díaz; Sophia Braumann; Janneke van de Pol; Tamara van Gog; Anique B. H. Bruin – British Journal of Educational Technology, 2024
Advances in computational language models increasingly enable adaptive support for self-regulated learning (SRL) in digital learning environments (DLEs; eg, via automated feedback). However, the accuracy of those models is a common concern for educational stakeholders (eg, policymakers, researchers, teachers and learners themselves). We compared…
Descriptors: Computational Linguistics, Independent Study, Secondary School Students, Causal Models
Eeshan Hasan; Erik Duhaime; Jennifer S. Trueblood – Cognitive Research: Principles and Implications, 2024
A crucial bottleneck in medical artificial intelligence (AI) is high-quality labeled medical datasets. In this paper, we test a large variety of wisdom of the crowd algorithms to label medical images that were initially classified by individuals recruited through an app-based platform. Individuals classified skin lesions from the International…
Descriptors: Algorithms, Human Body, Classification, Knowledge Level
Jiangang Hao; Alina A. von Davier; Victoria Yaneva; Susan Lottridge; Matthias von Davier; Deborah J. Harris – Educational Measurement: Issues and Practice, 2024
The remarkable strides in artificial intelligence (AI), exemplified by ChatGPT, have unveiled a wealth of opportunities and challenges in assessment. Applying cutting-edge large language models (LLMs) and generative AI to assessment holds great promise in boosting efficiency, mitigating bias, and facilitating customized evaluations. Conversely,…
Descriptors: Evaluation Methods, Artificial Intelligence, Educational Change, Computer Software
Bin Tan; Hao-Yue Jin; Maria Cutumisu – Computer Science Education, 2024
Background and Context: Computational thinking (CT) has been increasingly added to K-12 curricula, prompting teachers to grade more and more CT artifacts. This has led to a rise in automated CT assessment tools. Objective: This study examines the scope and characteristics of publications that use machine learning (ML) approaches to assess…
Descriptors: Computation, Thinking Skills, Artificial Intelligence, Student Evaluation
Abdulkadir Kara; Eda Saka Simsek; Serkan Yildirim – Asian Journal of Distance Education, 2024
Evaluation is an essential component of the learning process when discerning learning situations. Assessing natural language responses, like short answers, takes time and effort. Artificial intelligence and natural language processing advancements have led to more studies on automatically grading short answers. In this review, we systematically…
Descriptors: Automation, Natural Language Processing, Artificial Intelligence, Grading
Marco Lünich; Birte Keller; Frank Marcinkowski – Technology, Knowledge and Learning, 2024
Artificial intelligence in higher education is becoming more prevalent as it promises improvements and acceleration of administrative processes concerning student support, aiming for increasing student success and graduation rates. For instance, Academic Performance Prediction (APP) provides individual feedback and serves as the foundation for…
Descriptors: Predictor Variables, Artificial Intelligence, Computer Software, Higher Education
Archana Praveen Kumar; Ashalatha Nayak; Manjula Shenoy K.; Chaitanya; Kaustav Ghosh – International Journal of Artificial Intelligence in Education, 2024
Multiple Choice Questions (MCQs) are a popular assessment method because they enable automated evaluation, flexible administration and use with huge groups. Despite these benefits, the manual construction of MCQs is challenging, time-consuming and error-prone. This is because each MCQ is comprised of a question called the "stem", a…
Descriptors: Multiple Choice Tests, Test Construction, Test Items, Semantics
Mostafa Nazari; Golsa Saadi – Discover Education, 2024
The escalating integration of artificial intelligence (AI) technologies, particularly the widespread use of ChatGPT in higher education, necessitates a profound exploration of effective communication strategies. This paper addresses the critical role of prompt development as a skill essential for university instructors engaging with ChatGPT. While…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Communication Strategies
Helen Crompton; Mildred V. Jones; Diane Burke – Journal of Research on Technology in Education, 2024
Artificial Intelligence in Education (AIEd) has experienced a rapid rise in the past decade. This systematic review is the first examining the use of AIEd in K-12 including 169 extant studies from 2011 to 2021. This study provides contextual information from the research, such as the educational disciplines, educational levels, research purposes,…
Descriptors: Elementary Secondary Education, Artificial Intelligence, Barriers, Affordances
Brady L. Nash – Reading Research Quarterly, 2024
Generative artificial intelligence (GAI) programs such as ChatGPT and other large language models are designed to engage in complex, responsive dialogues that feel like human interactions. The dialogic and responsive nature of GAI signals the potential for users to form relationships with GAI platforms or digital personalities created on these…
Descriptors: Intimacy, Interpersonal Relationship, Epistemology, Artificial Intelligence
Keunjae Kim; Kyungbin Kwon – Education and Information Technologies, 2024
The popularity of artificial intelligence (AI) has highlighted the necessity of K-12 AI education, particularly at the elementary level. However, the lack of a comprehensive and age-appropriate AI curriculum integrated into school subjects, along with the abstract and complex nature of AI concepts, exacerbates student inequalities. Researchers…
Descriptors: Artificial Intelligence, Curriculum Development, Program Effectiveness, Elementary School Students
Adil Baqach; Amal Battou – Education and Information Technologies, 2024
Nowadays, e-learning is a significant learning option, especially in light of the COVID-19 pandemic. However, it is a very challenging task because, in online courses, tutors have no direct interaction with students, which causes most of them to lose interest and ultimately drop out of their studies. In regular classes, teachers can see how each…
Descriptors: MOOCs, Student Attitudes, Student Reaction, Tutors
Hilal Yilmaz – Online Submission, 2024
Artificial intelligence, also known as machine intelligence, is defined as the intelligence demonstrated by machines or computers. Artificial intelligence tools are increasingly being used in early childhood education to support learning and development for young children. Therefore, it is considered important to understand how children perceive…
Descriptors: Foreign Countries, Preschool Children, Childrens Attitudes, Early Childhood Education
Ibrahim Talaat Ibrahim; Najeh Rajeh Alsalhi; Atef F. I. Abdelkader; Nidal Alzboun; Abdellateef Alqawasmi – Eurasian Journal of Applied Linguistics, 2024
Artificial intelligence (AI) has become an integral component of human existence, with individuals employing AI tools in various facets of life. Among the most significant applications of AI is its role in facilitating communication among humans. The present study focuses on the use of AI in translating a crucial type of text that falls within the…
Descriptors: Artificial Intelligence, Translation, Geography, Politics
A Systematic Review of VR/AR Applications in Vocational Education: Models, Affects, and Performances
Yingjie Liu; Qinglong Zhan; Wenping Zhao – Interactive Learning Environments, 2024
This paper presents a systematic review of the application models, affects, and performance outcomes of VR/AR in vocational education. The analysis is based on journal articles retrieved from renowned databases such as Web of Science, Scopus, and EBSCO, spanning from January 2000 to January 2022. It highlights the pedagogical value of VR/AR in…
Descriptors: Computer Simulation, Artificial Intelligence, Vocational Education, Technology Uses in Education

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