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Jinhee Kim; Seongryeong Yu; Rita Detrick; Na Li – Education and Information Technologies, 2025
The rapid development of generative artificial intelligence (GenAI), including large language models (LLM), has merged to support students in their academic writing process. Keeping pace with the technical and educational landscape requires careful consideration of the opportunities and challenges that GenAI-assisted systems create within…
Descriptors: Student Attitudes, Artificial Intelligence, Technology Uses in Education, Natural Language Processing
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Terry L. Howard; Gregory W. Ulferts – Research in Higher Education Journal, 2025
Artificial Intelligence (AI) is profoundly reshaping higher education by introducing innovative tools and systems that enhance learning outcomes, streamline administrative processes, and address global educational challenges. This white paper examines AI's transformative impact on higher education, drawing on a comprehensive analysis of empirical…
Descriptors: Artificial Intelligence, Higher Education, Computer Software, Policy Formation
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Andrew Runge; Sarah Goodwin; Yigal Attali; Mya Poe; Phoebe Mulcaire; Kai-Ling Lo; Geoffrey T. LaFlair – Language Testing, 2025
A longstanding criticism of traditional high-stakes writing assessments is their use of static prompts in which test takers compose a single text in response to a prompt. These static prompts do not allow measurement of the writing process. This paper describes the development and validation of an innovative interactive writing task. After the…
Descriptors: Material Development, Writing Evaluation, Writing Assignments, Writing Skills
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Xie, Tao; Liu, Ruobin; Chen, Yijin; Liu, Geping – IEEE Transactions on Learning Technologies, 2021
The use of conversational agents in computer-supported collaborative learning (CSCL) has been identified as a useful tactic for motivational intervention. The purpose of the current study was to design and implement a conversational agent called a motivational online conversational agent (MOCA) that incorporated motivational interviewing (MI) and…
Descriptors: Learner Engagement, Cooperative Learning, Intelligent Tutoring Systems, Student Motivation
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Sychev, Oleg; Penskoy, Nikita; Anikin, Anton; Denisov, Mikhail; Prokudin, Artem – Education Sciences, 2021
Intelligent tutoring systems have become increasingly common in assisting students but are often aimed at isolated subject-domain tasks without creating a scaffolding system from lower- to higher-level cognitive skills, with low-level skills often neglected. We designed and developed an intelligent tutoring system, CompPrehension, which aims to…
Descriptors: Intelligent Tutoring Systems, Comprehension, Undergraduate Students, Computer Science Education
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Badrinath, Anirudhan; Wang, Frederic; Pardos, Zachary – International Educational Data Mining Society, 2021
Bayesian Knowledge Tracing, a model used for cognitive mastery estimation, has been a hallmark of adaptive learning research and an integral component of deployed intelligent tutoring systems (ITS). In this paper, we provide a brief history of knowledge tracing model research and introduce pyBKT, an accessible and computationally efficient library…
Descriptors: Models, Markov Processes, Mathematics, Intelligent Tutoring Systems
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Kochmar, Ekaterina; Vu, Dung Do; Belfer, Robert; Gupta, Varun; Serban, Iulian Vlad; Pineau, Joelle – International Journal of Artificial Intelligence in Education, 2022
Intelligent tutoring systems (ITS) have been shown to be highly effective at promoting learning as compared to other computer-based instructional approaches. However, many ITS rely heavily on expert design and hand-crafted rules. This makes them difficult to build and transfer across domains and limits their potential efficacy. In this paper, we…
Descriptors: Intelligent Tutoring Systems, Automation, Feedback (Response), Dialogs (Language)
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Rebolledo-Mendez, Genaro; Huerta-Pacheco, N. Sofia; Baker, Ryan S.; du Boulay, Benedict – International Journal of Artificial Intelligence in Education, 2022
Many previous studies have highlighted the influence of learners' affective states on learning with tutoring systems. However, the associations between learning and learners' meta-affective capability are still unclear. The goal of this paper is to analyse meta-affective capability and its influence on learning outcomes as well as the dynamics of…
Descriptors: Affective Behavior, Intelligent Tutoring Systems, Mathematics Education, Secondary School Students
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Dutt, Sarthika; Ahuja, Neelu Jyothi; Kumar, Manoj – Education and Information Technologies, 2022
Several studies have investigated the need for learning difficulties identification specifically Dyslexia, Dysgraphia and Dyscalculia. The identification of these difficulties among children is a multiple screening process under psychologist's supervision. Learning difficulties identification is a difficult task; it affects the learning process…
Descriptors: Intelligent Tutoring Systems, Special Education, Learning Disabilities, Students with Disabilities
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Nguyen, Hanh thi; Choe, Ann Tai; Vicentini, Cristiane – Classroom Discourse, 2022
To inform pedagogical decisions about using technology, it is important to understand from the ground up how technology is utilised during language learning activities. This paper takes an ethnomethodological conversation analytic approach to examine a learner's participation in epistemic management actions and its consequences for second language…
Descriptors: Second Language Learning, Online Searching, Intelligent Tutoring Systems, Videoconferencing
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Schmucker, Robin; Wang, Jingbo; Hu, Shijia; Mitchell, Tom M. – Journal of Educational Data Mining, 2022
We consider the problem of assessing the changing performance levels of individual students as they go through online courses. This student performance modeling problem is a critical step for building adaptive online teaching systems. Specifically, we conduct a study of how to utilize various types and large amounts of log data from earlier…
Descriptors: Academic Achievement, Electronic Learning, Artificial Intelligence, Predictor Variables
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Shakya, Anup; Rus, Vasile; Venugopal, Deepak – International Educational Data Mining Society, 2023
Understanding a student's problem-solving strategy can have a significant impact on effective math learning using Intelligent Tutoring Systems (ITSs) and Adaptive Instructional Systems (AISs). For instance, the ITS/AIS can better personalize itself to correct specific misconceptions that are indicated by incorrect strategies, specific problems can…
Descriptors: Equal Education, Mathematics Education, Word Problems (Mathematics), Problem Solving
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Vassoyan, Jean; Vie, Jill-Jênn – International Educational Data Mining Society, 2023
Adaptive learning is an area of educational technology that consists in delivering personalized learning experiences to address the unique needs of each learner. An important subfield of adaptive learning is learning path personalization: it aims at designing systems that recommend sequences of educational activities to maximize students' learning…
Descriptors: Reinforcement, Networks, Simulation, Educational Technology
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Caspari-Sadeghi, Sima – Journal of Educational Technology Systems, 2023
Intelligent assessment, the core of any AI-based educational technology, is defined as embedded, stealth and ubiquitous assessment which uses intelligent techniques to diagnose the current cognitive level, monitor dynamic progress, predict success and update students' profiling continuously. It also uses various technologies, such as learning…
Descriptors: Artificial Intelligence, Educational Technology, Computer Assisted Testing, Barriers
Husni Almoubayyed; Stephen E. Fancsali; Steve Ritter – Grantee Submission, 2023
Adaptive educational software is likely to better support broader and more diverse sets of learners by considering more comprehensive views (or models) of such learners. For example, recent work proposed making inferences about "non-math" factors like reading comprehension while students used adaptive software for mathematics to better…
Descriptors: Reading Ability, Computer Software, Mathematics Education, Intelligent Tutoring Systems
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