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Alina Kadluba; Anselm Strohmaier; Christian Schons; Andreas Obersteiner – Educational Studies in Mathematics, 2025
Teachers need technological pedagogical content knowledge (TPACK) for teaching with technology, and its assessment is crucial for research and practice. Previous literature reviews on TPACK assessment were not specific to a content area (e.g., mathematics), although, by definition, the TPACK framework includes content-specific knowledge facets.…
Descriptors: Mathematics Education, Pedagogical Content Knowledge, Technological Literacy, Course Content
Anirudhan Badrinath; Zachary Pardos – Journal of Educational Data Mining, 2025
Bayesian Knowledge Tracing (BKT) is a well-established model for formative assessment, with optimization typically using expectation maximization, conjugate gradient descent, or brute force search. However, one of the flaws of existing optimization techniques for BKT models is convergence to undesirable local minima that negatively impact…
Descriptors: Bayesian Statistics, Intelligent Tutoring Systems, Problem Solving, Audience Response Systems
Kevin Wai Ho Yung; Scarlet Poon – European Journal of Education, 2025
Well-being development in young people's formative years is crucial for their transition to adulthood. While research on well-being in formal education contexts is expanding, little attention has been paid to out-of-school educational settings, particularly supplementary tutoring for disadvantaged students. Adopting Sirgy's concept of positive…
Descriptors: Longitudinal Studies, Economically Disadvantaged, Adolescents, Well Being
Yujie Han; Sumin Hong; Zhenyan Li; Cheolil Lim – TechTrends: Linking Research and Practice to Improve Learning, 2025
This scoping review investigates the roles of intelligent learning companion systems (LCS) within educational settings, as well as the presences artificial intelligence (AI) embodies within these roles, and their application in education. Employing the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines for…
Descriptors: Artificial Intelligence, Definitions, Classification, Technology Uses in Education
J. Weidlich; D. Gaševic; H. Drachsler; P. Kirschner – Journal of Computer Assisted Learning, 2025
Background: As researchers rush to investigate the potential of AI tools like ChatGPT to enhance learning, well-documented pitfalls threaten the validity of this emerging research. Issues of media comparison research, where the confounding of instructional methods and technological affordances is unrecognised, may render effects uninterpretable.…
Descriptors: Artificial Intelligence, Technology Uses in Education, Educational Benefits, Barriers
Anqi Dou; Wei Xu; Ruijia Liu – International Journal of Information and Communication Technology Education, 2025
Artificial intelligence (AI)-based chatbots like ChatGPT represent a promising technological advancement that has the potential to revolutionize the field of education. Therefore, it is imperative to continue exploring and developing such AI-based tools to improve the learning outcomes of students. This study conducted a bibliometric review of…
Descriptors: Foreign Countries, Literature Reviews, Bibliometrics, Artificial Intelligence
Vasiliki Paltsoglou; Kostas Zafiropoulos – Open Education Studies, 2025
The usage of artificial intelligence (AI) in education is quickly growing, with chatbots gaining popularity as potential tools for supporting teaching and learning. This study looks into the elements that influence teachers' willingness to use chatbots in their teaching techniques. Drawing on the Unified Theory of Acceptance and Use of Technology,…
Descriptors: Foreign Countries, Elementary School Teachers, Artificial Intelligence, Natural Language Processing
Fiachra Long – Studies in Philosophy and Education, 2025
Conversation of a particular sort holds the key to learning. I argue here that peer to peer conversation promotes two features that are essential to progressive learning, namely 'contestation' and 'communication.' Traditional learning is principally concerned with whether students have reached a standard of knowledge and skill prescribed by some…
Descriptors: Artificial Intelligence, Natural Language Processing, Intelligent Tutoring Systems, Peer Relationship
Jionghao Lin; Zifei Han; Danielle R. Thomas; Ashish Gurung; Shivang Gupta; Vincent Aleven; Kenneth R. Koedinger – International Journal of Artificial Intelligence in Education, 2025
One-on-one tutoring is widely acknowledged as an effective instructional method, conditioned on qualified tutors. However, the high demand for qualified tutors remains a challenge, often necessitating the training of novice tutors (i.e., trainees) to ensure effective tutoring. Research suggests that providing timely explanatory feedback can…
Descriptors: Artificial Intelligence, Technology Uses in Education, Tutor Training, Trainees
Maria Eleftheriou; Sana Sayed – Composition Forum, 2025
The American University of Sharjah (AUS) Writing Center, one of the first writing centers in the Gulf region, supports a multilingual student body in the transnational context of the United Arab Emirates. The profile gives an account of the Center's history, peer-tutoring program, tutor-training course, and Writing Fellows initiative, with…
Descriptors: Foreign Countries, Writing (Composition), Laboratories, Multilingualism
Søren Christensen; Jason Tan – European Journal of Education, 2025
This paper explores the emergence of new forms of private supplementary classes in Singapore. Specifically, it examines the consolidation of an 'enrichment industry' offering classes in sports, music, performing arts, and extracurricular academic activities. The paper argues that even if such classes do not shadow the school curriculum or prepare…
Descriptors: Tutoring, Private Education, Supplementary Education, Foreign Countries
Marjolein K. Camphuijsen – European Journal of Education, 2025
Private supplementary tutoring has become a widespread global phenomenon, with many schoolteachers providing fee-based tutoring after school hours. This study focuses on the Netherlands, where demand for private tutoring has grown substantially over time. It examines the entry routes, motivations, and experiences of Dutch schoolteachers involved…
Descriptors: Private Education, Tutoring, Teacher Role, Educational Change
Mark Abdelshiheed; Tiffany Barnes; Min Chi – International Journal of Artificial Intelligence in Education, 2024
Two metacognitive knowledge types in deductive domains are procedural and conditional. This work presents a preliminary study on the impact of metacognitive knowledge and motivation on transfer across two Intelligent Tutoring Systems (ITSs), then two experiments on metacognitive knowledge instruction. Throughout this work, we trained students on a…
Descriptors: Metacognition, Intelligent Tutoring Systems, Cognitive Processes, Learning Strategies
A. N. Varnavsky – IEEE Transactions on Learning Technologies, 2024
The most critical parameter of audio and video information output is the playback speed, which affects many viewing or listening metrics, including when learning using tutoring systems. However, the availability of quantitative models for personalized playback speed control considering the learner's personal traits is still an open question. The…
Descriptors: Hierarchical Linear Modeling, Intelligent Tutoring Systems, Individualized Instruction, Electronic Learning
Linda Maria Laaksonen; Sonja Kosunen – Nordic Journal of Studies in Educational Policy, 2024
We examine private supplementary tutoring within the context of Finnish general upper secondary education. Specifically, we focus on profit-driven private preparatory course providers who cater to individual students and their families, aiming to improve applicants' prospects of gaining access to higher education. We examine this during a time…
Descriptors: Tutoring, Secondary School Students, College Admission, Educational Policy

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