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Hsi-Hsun Yang – International Review of Research in Open and Distributed Learning, 2024
This study proposes a hypothetical model combining the unified theory of acceptance and use of technology (UTAUT) with self-determination theory (SDT) to explore design professionals' behavioral intentions to use artificial intelligence (AI) tools. Moreover, it incorporates job replacement (JR) as a moderating role. Chinese-speaking design…
Descriptors: Artificial Intelligence, Design, Intention, Models
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Jamey A. Darnell; Shalini Gopalkrishnan – Discover Education, 2024
The use of Artificial Intelligence (AI) software has recently increased exponentially. Generative AI capabilities have moved from fiction to fact. This technology is changing the way we engage in Entrepreneurship, research it, and teach it. The significant impact on Entrepreneurship teaching is the focus of this paper. Any instructor, regardless…
Descriptors: Artificial Intelligence, Entrepreneurship, Technology Uses in Education, Technology Integration
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Ching Sing Chai; Ding Yu; Ronnel B. King; Ying Zhou – SAGE Open, 2024
As artificial intelligence (AI) permeates almost all aspects of our lives, university students need to acquire relevant knowledge, skills, and attitudes to adapt to the challenges it poses. This study reports the development and validation of a scale called the Artificial Intelligence Learning Intention Scale (AILIS). AILIS was designed to measure…
Descriptors: Artificial Intelligence, Intention, Measures (Individuals), Development
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Curby Alexander; Liran Ma; Ze-Li Dou; Zhipeng Cai; Yan Huang – Journal of Cybersecurity Education, Research and Practice, 2024
Recent advances in Artificial Intelligence (AI) have brought society closer to the long-held dream of creating machines to help with both common and complex tasks and functions. From recommending movies to detecting disease in its earliest stages, AI has become an aspect of daily life many people accept without scrutiny. Despite its functionality…
Descriptors: Students, Teachers, Inquiry, Computer Security
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Jody Britten; Paul Atherton – Childhood Education, 2024
Globally, less than 10% of schools are developing uniquely local artificial intelligence (AI) policies and addressing use cases. Policies and guide rails for using AI in education that are in place have rightfully called for us to address the ethical implications and biases that can arise with regard to AI tools and systems. The landscape of what…
Descriptors: Artificial Intelligence, Technology Uses in Education, Faculty Development, Computer Assisted Instruction
Reima Al-Jarf – Online Submission, 2024
This study explores Arab university faculty's views on fully AI-generated assignments and research papers submitted by students, what reasons they give for their stance and how they react in this case. Surveys with a sample of 45 Arab instructors revealed that 98% do not accept AI-generated assignments and research papers from students at all.…
Descriptors: Assignments, Research Papers (Students), Foreign Countries, College Faculty
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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
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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
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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
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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
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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
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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
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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
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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
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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
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