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Ani Grubišic; Ines Šaric-Grgic; Angelina Gašpar; Branko Žitko – Journal of Computer Assisted Learning, 2025
Background: Adaptive educational systems have gained increasing attention due to their ability to personalise educational content based on individual learner progress. Prior research highlights that intelligent tutoring systems (ITSs) and adaptive courseware models improve learning outcomes by dynamically adjusting instructional materials.…
Descriptors: Usability, Courseware, Natural Language Processing, Intelligent Tutoring Systems
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Frank Lee; Alex Algarra – Information Systems Education Journal, 2025
This case study examines employee attrition, its detrimental effects on businesses, and the potential of data analytics to address this challenge. By employing Latent Dirichlet Allocation (LDA), a sophisticated NLP technique, we delve into the underlying reasons for employee departures. Additionally, we explore using RapidMiner to develop…
Descriptors: Labor Turnover, Data Analysis, Natural Language Processing, Employees
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Brian Clements; Tamirat T. Abegaz; Bryson Payne – Information Systems Education Journal, 2025
The rise of artificial intelligence (AI) has made life and work easier; however, AI has also made it almost impossible to determine whether the information we consume is legitimate, AI-generated, or AI-manipulated. This paper examines how the use of artificial intelligence, specifically GPT-4, Gemini Advanced, and Claude Opus, can aid a user in…
Descriptors: Artificial Intelligence, Perception, Man Machine Systems, Natural Language Processing
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Luis Eduardo Muñoz Guerrero; Yony Fernando Ceballos; Luis David Trejos Rojas – Contemporary Educational Technology, 2025
Recent progress made in conversational AI lays emphasis on the need for development of language models that possess solid logical reasoning skills and further extrapolated capabilities. An examination into this phenomenon investigates how well the Capybara dataset can improve one's ability to reason using language-based systems. Multiple…
Descriptors: Artificial Intelligence, Logical Thinking, Models, Natural Language Processing
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Michael J. Parker; Caitlin Anderson; Claire Stone; YeaRim Oh – International Journal of Artificial Intelligence in Education, 2025
This paper assesses the potential for the large language models (LLMs) GPT-4 and GPT-3.5 to aid in deriving insight from education feedback surveys. Exploration of LLM use cases in education has focused on teaching and learning, with less exploration of capabilities in education feedback analysis. Survey analysis in education involves goals such…
Descriptors: Artificial Intelligence, Natural Language Processing, Surveys, Feedback (Response)
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Javad Keyhan – International Journal of Technology in Education and Science, 2025
In recent years, remarkable advancements in artificial intelligence technology have created new opportunities for transforming educational systems and enhancing student learning. This study focuses on designing a model for an AI-based intelligent assistant to provide a personalized learning experience in higher education. A qualitative approach…
Descriptors: Individualized Instruction, Artificial Intelligence, Models, Higher Education
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Francesco Contel; Annalisa Cusi – Digital Experiences in Mathematics Education, 2025
We present the results of a study investigating the potential role of the generative AI GPT-4 in scaffolding students' metacognitive activities during problem-solving. The theoretical framework according to which students' interactions with GPT-4 are analysed is based on three main components: the notion of utilisation scheme within the frame of…
Descriptors: Artificial Intelligence, Metacognition, Problem Solving, Technology Uses in Education
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Lord J. Hyeamang; Tejas C. Sekhar; Emily Rush; Amy C. Beresheim; Colleen M. Cheverko; William S. Brooks; Abbey C. M. Breckling; M. Nazmul Karim; Christopher Ferrigno; Adam B. Wilson – Anatomical Sciences Education, 2025
Evidence suggests custom chatbots are superior to commercial generative artificial intelligence (GenAI) systems for text-based anatomy content inquiries. This study evaluates ChatGPT-4o's and Claude 3.5 Sonnet's capabilities to interpret unlabeled anatomical images. Secondarily, ChatGPT o1-preview was evaluated as an AI rater to grade AI-generated…
Descriptors: Artificial Intelligence, Anatomy, Identification, Man Machine Systems
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Ainhoa Berciano; Astrid Cuida; María-Luisa Novo – Education and Information Technologies, 2025
In the last two decades, computational thinking has gained wide relevance in international educational systems. The inclusion of this new type of thinking poses educational challenges with some underlying research questions that need to be answered to meet these challenges with quality. Thus, this study focuses on analyzing the difficulties that…
Descriptors: Coding, Translation, Programming Languages, Sequential Approach
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Fan Zhang; Chenglu Li; Owen Henkel; Wanli Xing; Sami Baral; Neil Heffernan; Hai Li – International Journal of Artificial Intelligence in Education, 2025
In recent years, the pre-training of Large Language Models (LLMs) in the educational domain has garnered significant attention. However, a discernible gap exists in the application of these models to mathematics education. This study aims to bridge this gap by pre-training LLMs on authentic K-12 mathematical dialogue datasets. Our research is…
Descriptors: Artificial Intelligence, Natural Language Processing, Mathematics Education, Elementary Secondary Education
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Hatice Yildiz Durak; Figen Egin; Aytug Onan – European Journal of Education, 2025
Generative artificial intelligence (GenAI) models, such as ChatGPT, Gemini, and BingAI, have become integral to educational sciences, bringing about significant transformations in the education system and the processes of knowledge production. These advancements have facilitated new methods of teaching, learning, and information dissemination.…
Descriptors: Writing (Composition), Discussion, Artificial Intelligence, Natural Language Processing
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Kangkang Li; Chengyang Qian; Xianmin Yang – Education and Information Technologies, 2025
In learnersourcing, automatic evaluation of student-generated content (SGC) is significant as it streamlines the evaluation process, provides timely feedback, and enhances the objectivity of grading, ultimately supporting more effective and efficient learning outcomes. However, the methods of aggregating students' evaluations of SGC face the…
Descriptors: Student Developed Materials, Educational Quality, Automation, Artificial Intelligence
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Atharva Naik; Jessica Ruhan Yin; Anusha Kamath; Qianou Ma; Sherry Tongshuang Wu; R. Charles Murray; Christopher Bogart; Majd Sakr; Carolyn P. Rose – British Journal of Educational Technology, 2025
The relative effectiveness of reflection either through student generation of contrasting cases or through provided contrasting cases is not well-established for adult learners. This paper presents a classroom study to investigate this comparison in a college level Computer Science (CS) course where groups of students worked collaboratively to…
Descriptors: Cooperative Learning, Reflection, College Students, Computer Science Education
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Mohammad Arif Ul Alam; Geeta Verma; Eumie Jhong; Justin Barber; Ashis Kumer Biswas – International Educational Data Mining Society, 2025
The growing demand for microcredentials in education and workforce development necessitates scalable, accurate, and fair assessment systems for both soft and hard skills based on students' lived experience narratives. Existing approaches struggle with the complexities of hierarchical credentialing and the mitigation of algorithmic bias related to…
Descriptors: Microcredentials, Sex, Ethnicity, Artificial Intelligence
Damaris D. E. Carlisle – Sage Research Methods Cases, 2025
This case study explores the use of large language models (LLMs) as analytical partners for data exploration and interpretation. Grounded in original research, it navigates the intricacies of using LLMs for uncovering themes from datasets. The study tackles various methodological and practical challenges encountered during the research process…
Descriptors: Artificial Intelligence, Natural Language Processing, Data Analysis, Data Interpretation
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