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Ran Jiang – Action, Criticism, and Theory for Music Education, 2025
Artificial Intelligence (AI) technology is reshaping the ways humans study and work across various disciplines. In the field of music, AI technology shows its possibility to empower individuals at diverse levels of musical knowledge in music creation, from novices to experts. In this article, I explore philosophical questions within both AI…
Descriptors: Educational Philosophy, Music Education, Artificial Intelligence, Computer Software
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Bin Liu; Yuanyuan Liao – Education and Information Technologies, 2025
The rapid advancement of generative AI technologies is increasingly accompanied by their broader application across various sectors, particularly within creative industries. In this study, IBM Watson BEAT software, based on generative AI technology, was tested as an educational tool in the process of teaching music composition theory to flute…
Descriptors: Artificial Intelligence, Technology Uses in Education, Technology Integration, Educational Technology
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Minseong Kim; Jihye Kim; Tami L. Knotts; Nancy D. Albers – Education and Information Technologies, 2025
Integrating generative artificial intelligence (AI) tools like ChatGPT into education has reshaped academic practices, offering students innovative ways to engage with learning tasks. This study examines the cognitive, emotional, and behavioral factors influencing undergraduate students' engagement with ChatGPT, guided by the technology acceptance…
Descriptors: Artificial Intelligence, Computer Software, Technology Integration, Factor Analysis
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Longwei Zheng; Anna He; Changyong Qi; Haomin Zhang; Xiaoqing Gu – British Journal of Educational Technology, 2025
In the field of education, the think-aloud protocol is commonly used to encourage learners to articulate their thoughts during the learning process, providing observers with valuable insights into learners' cognitive processes beyond the final learning outcomes. However, the implementation of think-aloud protocols faces challenges such as task…
Descriptors: Protocol Analysis, Learning Experience, Computational Linguistics, Computer Software
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Stefanie Beninger; Alex Reppel; Julie Stanton; Forrest Watson – Journal of Marketing Education, 2025
The emergence of generative AI (GenAI) has illustrated that higher education needs to adapt to the technology. Its speed of evolution requires that we adequately prepare students for an ever-changing landscape. Toward achieving that aim, we draw on the concept of interpretive flexibility, where the interpretations, uses, and outcomes of a new…
Descriptors: Business Education, Marketing, Artificial Intelligence, Computer Software
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Yamauchi, Taisei; Flanagan, Brendan; Nakamoto, Ryosuke; Dai, Yiling; Takami, Kyosuke; Ogata, Hiroaki – Smart Learning Environments, 2023
In recent years, smart learning environments have become central to modern education and support students and instructors through tools based on prediction and recommendation models. These methods often use learning material metadata, such as the knowledge contained in an exercise which is usually labeled by domain experts and is costly and…
Descriptors: Mathematics Instruction, Classification, Algorithms, Barriers
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Snekha, S.; Ayyanathan, N. – Shanlax International Journal of Education, 2023
An educational customer relationship management (CRM) Chatbot is a learner support service automation tool that enhances the human computer interaction and user experience in higher education institutions through effective online conversation and information exchange. The machine with embedded knowledge is trained to identify the sentences and…
Descriptors: Computer Software, Learning Management Systems, Educational Technology, Man Machine Systems
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Gaskins, Nettrice – TechTrends: Linking Research and Practice to Improve Learning, 2023
This paper reviews algorithmic or artificial intelligence (AI) bias in education technology, especially through the lenses of speculative fiction, speculative and liberatory design. It discusses the causes of the bias and reviews literature on various ways that algorithmic/AI bias manifests in education and in communities that are underrepresented…
Descriptors: Algorithms, Bias, Artificial Intelligence, Educational Technology
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Mert Sen; Sevval Nur Sen; Tugrul Gökmen Sahin – Shanlax International Journal of Education, 2023
Today, the use of software in qualitative research analysis is rapidly becoming widespread among researchers. Researchers manage large data sets using features such as editing data, transcribing, creating codes, and searching within data. However, while the data analysis uses software in a format, the analysis of the essence of the data is done by…
Descriptors: Artificial Intelligence, Computer Software, Qualitative Research, Data Analysis
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Shiv K. Tripathi; Wolfgang C. Amann; Agat Stachowicz-Stanusch – International Society for Technology, Education, and Science, 2023
The effective anti-corruption education requires careful understanding of the teaching-learning context. At the different stages of the designing an anti-corruption focuses course, we need to consider factors related to target learning group as well as the respective context in which they are. Learning style versatility is an important factor that…
Descriptors: Artificial Intelligence, Computer Software, Synchronous Communication, Computer Oriented Programs
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Chang Liu; Charles Downing – Journal of Information Systems Education, 2024
This teaching tip describes using Microsoft Power BI Desktop in a class to analyze unstructured data from an exit survey of prior students from a Master of Science in Management Information Systems program. Results from a short survey administered to these students showed that the students, using the no-code Power BI, were able to accomplish their…
Descriptors: Graduate Students, Program Effectiveness, Information Science, Management Information Systems
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Elena Drugova; Irina Zhuravleva; Ulyana Zakharova; Adel Latipov – Journal of Computer Assisted Learning, 2024
Background: Driven by the ongoing need to provide high-quality learning and teaching, universities recently have shown an increased interest in using learning analytics (LA) for improving learning design (LD). However, the evidence of such improvements is scarce, and the maturity of such research is unclear. Objectives: This study is aimed to…
Descriptors: Learning Analytics, Instructional Design, Higher Education, Instructional Improvement
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Md Akib Zabed Khan; Agoritsa Polyzou – Journal of Educational Data Mining, 2024
In higher education, academic advising is crucial to students' decision-making. Data-driven models can benefit students in making informed decisions by providing insightful recommendations for completing their degrees. To suggest courses for the upcoming semester, various course recommendation models have been proposed in the literature using…
Descriptors: Academic Advising, Courses, Data Use, Artificial Intelligence
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Tribikram Budhathoki; Araz Zirar; Eric Tchouamou Njoya; Achyut Timsina – Studies in Higher Education, 2024
The public release of ChatGPT in November 2022 brought excitement and concerns regarding students' use of language models in higher education. However, little research has empirically investigated students' intention to adopt ChatGPT. This study developed a theoretical model based on the Unified Theory of Acceptance and Use of Technology (UTAUT)…
Descriptors: Adoption (Ideas), Anxiety, Computer Attitudes, Artificial Intelligence
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Niklas Humble; Jonas Boustedt; Hanna Holmgren; Goran Milutinovic; Stefan Seipel; Ann-Sofie Östberg – Electronic Journal of e-Learning, 2024
Artificial Intelligence (AI) and related technologies have a long history of being used in education for motivating learners and enhancing learning. However, there have also been critiques for a too uncritical and naïve implementation of AI in education (AIED) and the potential misuse of the technology. With the release of the virtual assistant…
Descriptors: Cheating, Artificial Intelligence, Technology Uses in Education, Computer Science Education
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