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Fan, Zongwen; Chiong, Raymond – Education and Information Technologies, 2023
Digital capabilities have become increasingly important in this digital age. Within a university setting, digital capability assessment is key to curriculum design and curriculum mapping, given that digital capabilities not only can help students engage and communicate with others but also succeed at work. To the best of our knowledge, however, no…
Descriptors: Course Content, Artificial Intelligence, Technological Literacy, Computer Literacy
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Chen, Zhen; Zhu, Peixi; Qiu, Wei; Guo, Jiajie; Li, Yike – International Journal of Language & Communication Disorders, 2023
Background: Auditory-perceptual assessment of voice is a subjective procedure. Artificial intelligence with deep learning (DL) may improve the consistency and accessibility of this task. It is unclear how a DL model performs on different acoustic features. Aims: To develop a generalizable DL framework for identifying dysphonia using a…
Descriptors: Voice Disorders, Acoustics, Mandarin Chinese, German
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Kim, Jinhee; Lee, Sang-Soog – TechTrends: Linking Research and Practice to Improve Learning, 2023
A growing number of educators expect that artificial intelligence (AI) will augment students' capacities and rapidly transform the teaching and learning practice. However, there is a lack of convincing evidence on the effects of Student-AI Collaboration (SAC) on a learning task's performance. A critical examination of the effects on students'…
Descriptors: Artificial Intelligence, Cooperation, Academic Achievement, Undergraduate Students
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Pan, Yiqin; Wollack, James A. – Educational Measurement: Issues and Practice, 2023
Pan and Wollack (PW) proposed a machine learning method to detect compromised items. We extend the work of PW to an approach detecting compromised items and examinees with item preknowledge simultaneously and draw on ideas in ensemble learning to relax several limitations in the work of PW. The suggested approach also provides a confidence score,…
Descriptors: Artificial Intelligence, Prior Learning, Item Analysis, Test Content
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Tomic, Bojan; Kijevcanin, Anisja; Sevarac, Zoran; Jovanovic, Jelena M. – IEEE Transactions on Learning Technologies, 2023
Soft skills (such as communication and collaboration) are rarely addressed in programming courses, mostly because they are difficult to teach, assess, and grade. A quantitative, modular, AI-based approach for assessing and grading students' collaboration has been examined in this article. The pedagogical underpinning of the approach includes a…
Descriptors: Artificial Intelligence, Grading, Cooperation, Students
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Karatas, Kasim; Arpaci, Ibrahim; Yildirim, Yusuf – Education and Urban Society, 2023
This study aimed to predict the culturally responsive teacher roles based on cultural intelligence and self-efficacy using machine learning classification algorithms. The research group consists of 415 teachers from different branches. The Bayes classifier (NaiveBayes), logistic-regression (SMO), lazy-classifier (KStar), meta-classifier…
Descriptors: Prediction, Culturally Relevant Education, Teacher Role, Cultural Awareness
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Deepak, Gerard; Trivedi, Ishdutt – International Journal of Adult Education and Technology, 2023
Recommender systems have been actively used in many areas like e-commerce, movie and video suggestions, and have proven to be highly useful for its users. But the use of recommender systems in online learning platforms is often underrated and less likely used. But many of the times it lacks personalisation especially in collaborative approach…
Descriptors: Learning Strategies, Artificial Intelligence, Information Systems, Algorithms
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Halaweh, Mohanad – Contemporary Educational Technology, 2023
Since the launch of ChatGPT for public use, educators have expressed a variety of concerns about its integration into educational settings. This paper has been written to provide an indepth examination of these issues and explore the potential use of ChatGPT in educational contexts. Specifically, it aims to (i) present an argument in favor of…
Descriptors: Artificial Intelligence, Technology Uses in Education, Technology Integration, Teaching Methods
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Thompson, Greg; Gulson, Kalervo N.; Swist, Teresa; Witzenberger, Kevin – Learning, Media and Technology, 2023
The use of automated decision-making systems is increasing in education. While the potential impacts of ADM are becoming widely known amongst experts, the perspectives of those impacted by ADM remain peripheral. To broaden expertise and participation, this paper proposes that ADM needs to be considered as a sociotechnical controversy, as part of a…
Descriptors: Automation, Decision Making, Educational Technology, Democracy
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Okubo, Fumiya; Shiino, Tetsuya; Minematsu, Tsubasa; Taniguchi, Yuta; Shimada, Atsushi – IEEE Transactions on Learning Technologies, 2023
In this study, we propose an integrated system to support learners' reviews. In the proposed system, the review dashboard is used to recommend review contents that are adaptive to the individual learner's level of understanding and to present other information that is useful for review. The pages of the digital learning materials that are…
Descriptors: Learning Management Systems, Student Evaluation, Automation, Artificial Intelligence
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Adiguzel, Tufan; Kaya, Mehmet Haldun; Cansu, Fatih Kürsat – Contemporary Educational Technology, 2023
Artificial intelligence (AI) introduces new tools to the educational environment with the potential to transform conventional teaching and learning processes. This study offers a comprehensive overview of AI technologies, their potential applications in education, and the difficulties involved. Chatbots and related algorithms that can simulate…
Descriptors: Artificial Intelligence, Educational Technology, Barriers, Man Machine Systems
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Möller, Annette; George, Ann Cathrice; Groß, Jürgen – International Journal of Research & Method in Education, 2023
Methods based on machine learning have become increasingly popular in many areas as they allow models to be fitted in a highly-data driven fashion and often show comparable or even increased performance in comparison to classical methods. However, in the area of educational sciences, the application of machine learning is still quite uncommon.…
Descriptors: Foreign Countries, Learning Analytics, Classification, Artificial Intelligence
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Álvarez-Álvarez, Carmen; Falcon, Samuel – Educational Technology Research and Development, 2023
University teaching practices impact student interest, engagement, and academic performance. This paper presents a study that uses artificial intelligence (AI) to examine students' preferences for university teaching practices. We asked students in various fields open-ended questions about the best teaching practices they had experienced. Due to…
Descriptors: College Students, Preferences, Teaching Methods, Artificial Intelligence
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Al-Alawi, Lamees; Al Shaqsi, Jamil; Tarhini, Ali; Al-Busaidi, Adil S. – Education and Information Technologies, 2023
This study aims to employ the supervised machine learning algorithms to examine factors that negatively impacted academic performance among college students on probation (underperforming students). We used the Knowledge Discovery in Databases (KDD) methodology on a sample of N = 6514 college students spanning 11 years (from 2009 to 2019) provided…
Descriptors: Artificial Intelligence, Predictor Variables, Academic Achievement, Grade Prediction
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Zhu, Chenjia; Sun, Meng; Luo, Jiutong; Li, Tianyi; Wang, Minhong – Knowledge Management & E-Learning, 2023
Technological advancements, particularly in the field of artificial intelligence (AI) have played an increasingly important role in transforming education. More recently, ground-breaking AI applications like ChatGPT have demonstrated the potential to bring radical changes to the educational landscape due to their capability to understand complex…
Descriptors: Artificial Intelligence, Ethics, Technology Integration, Technology Uses in Education
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