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Nurassyl Kerimbayev; Karlygash Adamova; Rustam Shadiev; Zehra Altinay – Smart Learning Environments, 2025
This review was conducted in order to determine the specific role of intelligent technologies in the individual learning experience. The research work included consider articles published between 2014 and 2024, found in Web of Science, Scopus, and ERIC databases, and selected among 933 ?articles on the topic. Materials were checked for compliance…
Descriptors: Intelligent Tutoring Systems, Artificial Intelligence, Computer Software, Databases
Minkyoung Kim; Lauren Adlof – TechTrends: Linking Research and Practice to Improve Learning, 2024
ChatGPT, an artificial intelligence (AI) language model, holds significant promise for improving the quality and efficiency of teaching and learning. However, its potential challenges and disruptions in education systems require further investigation for a deeper understanding and mitigation. Given that ChatGPT is already being utilized and…
Descriptors: Computer Software, Computational Linguistics, Intelligent Tutoring Systems, Teaching Methods
Moses Kumi Asamoah; Jessica Amarteifio – Discover Education, 2025
This systematic review explores the use of Intelligent Tutoring Systems (ITS) in fostering creativity, innovation, and personalized learning experiences among university students in Ghana. The review also examines the challenges associated with the implementation of ITS, along with the ethical considerations involved. Employing an interpretive…
Descriptors: Ethics, Barriers, Intelligent Tutoring Systems, Technology Integration
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
Peer reviewedDevika Venugopalan; Ziwen Yan; Conrad Borchers; Jionghao Lin; Vincent Aleven – Grantee Submission, 2025
Caregivers (i.e., parents and members of a child's caring community) are underappreciated stakeholders in learning analytics. Although caregiver involvement can enhance student academic outcomes, many obstacles hinder involvement, most notably knowledge gaps with respect to modern school curricula. An emerging topic of interest in learning…
Descriptors: Homework, Computational Linguistics, Teaching Methods, Learning Analytics
Nikola M. Luburic; Luka Z. Doric; Jelena J. Slivka; Dragan Lj. Vidakovic; Katarina-Glorija G. Grujic; Aleksandar D. Kovacevic; Simona B. Prokic – IEEE Transactions on Learning Technologies, 2025
Software engineers are tasked with writing functionally correct code of high quality. Maintainability is a crucial code quality attribute that determines the ease of analyzing, modifying, reusing, and testing a software component. This quality attribute significantly affects the software's lifetime cost, contributing to developer productivity and…
Descriptors: Intelligent Tutoring Systems, Coding, Computer Software, Technical Occupations
Jonathan Brazil; Suijing Yang; Fabienne van der Kleij – Australian Council for Educational Research, 2025
This document provides guiding principles and practical examples for using AI in teaching and learning. Underpinned by a human-centred approach, the PATH principles serve as key guidance to ensure the ethical and effective integration of AI systems into teaching and learning. The PATH principles are: Promote teaching and learning; Advance…
Descriptors: Artificial Intelligence, Computer Software, Technology Integration, Educational Principles
Phillips, Andrea; Pane, John F.; Reumann-Moore, Rebecca; Shenbanjo, Oluwatosin – Educational Technology Research and Development, 2020
Evidence is emerging that technology-based curricula and adaptive learning systems can personalize students' learning experiences and facilitate development of mathematical skills. Yet, evidence of efficacy in rigorous studies for these blended instructional models is mixed. These studies highlight challenges implementing the systems in…
Descriptors: Intelligent Tutoring Systems, Program Implementation, Computer Software, Mathematics Skills
Phillips, Andrea; Pane, John F.; Reumann-Moore, Rebecca; Shenbanjo, Oluwatosin – Grantee Submission, 2020
Evidence is emerging that technology-based curricula and adaptive learning systems can personalize students' learning experiences and facilitate development of mathematical skills. Yet, evidence of efficacy in rigorous studies for these blended instructional models is mixed. These studies highlight challenges implementing the systems in…
Descriptors: Intelligent Tutoring Systems, Program Implementation, Computer Software, Mathematics Skills
Ig Ibert Bittencourt; Geiser Chalco; Jário Santos; Sheyla Fernandes; Jesana Silva; Naricla Batista; Claudio Hutz; Seiji Isotani – International Journal of Artificial Intelligence in Education, 2024
The unprecedented global movement of school education to find technological and intelligent solutions to keep the learning ecosystem working was not enough to recover the impacts of COVID-19, not only due to learning-related challenges but also due to the rise of negative emotions, such as frustration, anxiety, boredom, risk of burnout and the…
Descriptors: Artificial Intelligence, COVID-19, Pandemics, Computer Software
Janice D. Gobert; Haiying Li; Rachel Dickler; Christine Lott – Grantee Submission, 2024
An intelligent tutoring system (ITS, henceforth) is currently defined as a computer system that delivers personalized instruction to students by using computational techniques to evaluate the learner in a variety of ways, including (but not limited to) their prior knowledge, competency/skill levels, motivation, and affective states. ITSs are…
Descriptors: Artificial Intelligence, Scaffolding (Teaching Technique), Computer Science Education, Teaching Methods
Sue-Jin Lee – CATESOL Journal, 2024
The emergence of AI writing assistants has raised concerns about their potential impact on language diversity, preservation, and education. This paper examines the capabilities and limitations of AI writing assistants in generating dialectic text in response to academic and professional writing prompts. The study uses a concordance tool to conduct…
Descriptors: Writing Assignments, Artificial Intelligence, Computer Software, Intelligent Tutoring Systems
Sanjana Gautam – ProQuest LLC, 2024
Adaptive learning systems aim to emulate how skilled educators provide every student with the best possible learning experience. We investigate how these systems might be enriched by incorporating activities and indicators of social learning, which focus on the influences of learners' social context and interactions. This doctoral research aims to…
Descriptors: Intelligent Tutoring Systems, Artificial Intelligence, Computer Software, Rating Scales
Edwards, John; Hart, Kaden; Shrestha, Raj – Journal of Educational Data Mining, 2023
Analysis of programming process data has become popular in computing education research and educational data mining in the last decade. This type of data is quantitative, often of high temporal resolution, and it can be collected non-intrusively while the student is in a natural setting. Many levels of granularity can be obtained, such as…
Descriptors: Data Analysis, Computer Science Education, Learning Analytics, Research Methodology
del Blanco, Angel; Torrente, Javier; Moreno-Ger, Pablo; Fernandez-Manjon, Baltasar – International Journal of Distance Education Technologies, 2010
The increasing adoption of e-Learning technology is facing new challenges, such as how to produce student-centered systems that can be adapted to each student's needs. In this context, educational video games are proposed as an ideal medium to facilitate adaptation and tracking of students' performance for assessment purposes, but integrating the…
Descriptors: Foreign Countries, Electronic Learning, Intelligent Tutoring Systems, Educational Games
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