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Jelle Wemmenhove; Dorina Bór; Rianne Conijn; Jim Portegies – Journal of Computer Assisted Learning, 2025
Background: Recently human-centred design plays an increasing role in learning analytics, however this approach is mostly lacking in the design and evaluation of Intelligent Tutoring Systems (ITSs). A potential way to incorporate human-centred design principles in ITS development is by adopting a service design approach. Objectives: This article…
Descriptors: Intelligent Tutoring Systems, Program Evaluation, Design, Stakeholders
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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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Arief Ramadhan; Harco Leslie Hendric Spits Warnars; Fariza Hanis Abdul Razak – Education and Information Technologies, 2024
One of the Information and Communication Technology (ICT) developments used in the learning process is the Intelligent Tutoring System (ITS), and gamification can overcome boredom, lack of interest or motivation, and monotony when using the ITS. In this study, the application of ITS equipped with Gamification is called ITS + G. Currently, several…
Descriptors: Intelligent Tutoring Systems, Gamification, Educational Technology, STEM Education
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Hasnan Baber; Kiran Nair; Ruchi Gupta; Kuldeep Gurjar – Information and Learning Sciences, 2024
This paper aims to present a systematic literature review and bibliometric analysis of research papers published on chat generative pre-trained transformer (ChatGPT), an OpenAI-developed large-scale generative language model. The study's objective is to provide a comprehensive assessment of the present status of research on ChatGPT and identify…
Descriptors: Artificial Intelligence, Intelligent Tutoring Systems, Technology Uses in Education, Bibliometrics
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Ishrat Ahmed; Paul Alvarado; Siddharth Jain; Tracy Arner; Elizabeth Reilley; Danielle S. McNamara – Grantee Submission, 2025
The rapid evolution of artificial intelligence (AI) has created an unprecedented opportunity for innovation across industries, but its complexity often presents a steep learning curve for many (Roberts & Candi, 2024; Gunner, 2025). This highlights the need for user-friendly tools that bridge the gap between AI's potential and its practical…
Descriptors: State Universities, Artificial Intelligence, Usability, Innovation
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Zhu, Xinhua; Wu, Han; Zhang, Lanfang – IEEE Transactions on Learning Technologies, 2022
Automatic short-answer grading (ASAG) is a key component of intelligent tutoring systems. Deep learning is an advanced method to deal with recognizing textual entailment tasks in an end-to-end manner. However, deep learning methods for ASAG still remain challenging mainly because of the following two major reasons: (1) high-precision scoring…
Descriptors: Intelligent Tutoring Systems, Grading, Automation, Models
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Noah L. Schroeder; Robert O. Davis; Eunbyul Yang – Journal of Educational Computing Research, 2025
Pedagogical agents are virtual characters that instructional designers include in learning environments to help students learn. Research in the area has flourished for thirty years, yet there are still critical questions about the efficacy of pedagogical agents for influencing learning and affect. As such, we conducted an umbrella review to…
Descriptors: Educational Technology, Technology Uses in Education, Artificial Intelligence, Intelligent Tutoring Systems
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Hu, Yuanyuan; Donald, Claire; Giacaman, Nasser – International Journal of Artificial Intelligence in Education, 2023
This paper investigates using multi-label deep learning approach to extending the understanding of cognitive presence in MOOC discussions. Previous studies demonstrate the challenges of subjectivity in manual categorisation methods. Training automatic single-label classifiers may preserve this subjectivity. Using a triangulation approach, we…
Descriptors: Classification, MOOCs, Artificial Intelligence, Intelligent Tutoring Systems
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Bai, Xiaoyu; Stede, Manfred – International Journal of Artificial Intelligence in Education, 2023
Recent years have seen increased interests in applying the latest technological innovations, including artificial intelligence (AI) and machine learning (ML), to the field of education. One of the main areas of interest to researchers is the use of ML to assist teachers in assessing students' work on the one hand and to promote effective…
Descriptors: Artificial Intelligence, Intelligent Tutoring Systems, Natural Language Processing, Evaluation
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Elvis Ortega-Ochoa; Marta Arguedas; Thanasis Daradoumis – British Journal of Educational Technology, 2024
Artificial intelligence (AI) and natural language processing technologies have fuelled the growth of Pedagogical Conversational Agents (PCAs) with empathic conversational capabilities. However, no systematic literature review has explored the intersection between conversational agents, education and emotion. Therefore, this study aimed to outline…
Descriptors: Empathy, Artificial Intelligence, Databases, Dialogs (Language)
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M. Anthony Machin; Tanya M. Machin; Natalie Gasson – Psychology Learning and Teaching, 2024
Progress in understanding students' development of psychological literacy is critical. However, generative AI represents an emerging threat to higher education which may dramatically impact on student learning and how this learning transfers to their practice. This research investigated whether ChatGPT responded in ways that demonstrated…
Descriptors: Psychology, Higher Education, Artificial Intelligence, Intelligent Tutoring Systems
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Alexandre Machado; Kamilla Tenório; Mateus Monteiro Santos; Aristoteles Peixoto Barros; Luiz Rodrigues; Rafael Ferreira Mello; Ranilson Paiva; Diego Dermeval – Smart Learning Environments, 2025
Researchers are increasingly interested in enabling teachers to monitor and adapt gamification design in the context of intelligent tutoring systems (ITSs). These contributions rely on teachers' needs and preferences to adjust the gamification design according to student performance. This work extends previous studies on teachers' perception of…
Descriptors: Faculty Workload, Educational Resources, Artificial Intelligence, Technology Uses in Education
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Markus Wolfgang Hermann Spitzer; Miguel Ruiz-Garcia; Korbinian Moeller – British Journal of Educational Technology, 2025
Research on fostering learning about percentages within intelligent tutoring systems (ITSs) is limited. Additionally, there is a lack of data-driven approaches for improving the design of ITS to facilitate learning about percentages. To address these gaps, we first investigated whether students' understanding of basic mathematical skills (eg,…
Descriptors: Mathematics Skills, Fractions, Prediction, Mathematical Concepts
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Scott A. Crossley; Minkyung Kim; Quian Wan; Laura K. Allen; Rurik Tywoniw; Danielle S. McNamara – Grantee Submission, 2025
This study examines the potential to use non-expert, crowd-sourced raters to score essays by comparing expert raters' and crowd-sourced raters' assessments of writing quality. Expert raters and crowd-sourced raters scored 400 essays using a standardised holistic rubric and comparative judgement (pairwise ratings) scoring techniques, respectively.…
Descriptors: Writing Evaluation, Essays, Novices, Knowledge Level
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Markus W. H. Spitzer; Lisa Bardach; Eileen Richter; Younes Strittmatter; Korbinian Moeller – Journal of Computer Assisted Learning, 2025
Background: Many students face difficulties with algebra. At the same time, it has been observed that fraction understanding predicts achievements in algebra; hence, gaining a better understanding of how algebra understanding builds on fraction understanding is an important goal for research and educational practice. Objectives: However, a wide…
Descriptors: Psychological Patterns, Network Analysis, Fractions, Algebra
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