Publication Date
| In 2026 | 0 |
| Since 2025 | 155 |
| Since 2022 (last 5 years) | 563 |
| Since 2017 (last 10 years) | 1110 |
| Since 2007 (last 20 years) | 1914 |
Descriptor
Source
Author
Publication Type
Education Level
Location
| Taiwan | 49 |
| China | 46 |
| United Kingdom | 29 |
| Pennsylvania | 27 |
| Germany | 25 |
| Turkey | 24 |
| Canada | 22 |
| Massachusetts | 22 |
| Spain | 22 |
| United States | 16 |
| California | 15 |
| More ▼ | |
Laws, Policies, & Programs
| Every Student Succeeds Act… | 3 |
| Elementary and Secondary… | 2 |
| American Rescue Plan Act 2021 | 1 |
| No Child Left Behind Act 2001 | 1 |
Assessments and Surveys
What Works Clearinghouse Rating
| Meets WWC Standards without Reservations | 4 |
| Meets WWC Standards with or without Reservations | 6 |
| Does not meet standards | 2 |
Hall, Lynne; Tazzyman, Sarah; Hume, Colette; Endrass, Birgit; Lim, Mei-Yii; Hofstede, GertJan; Paiva, Ana; Andre, Elisabeth; Kappas, Arvid; Aylett, Ruth – International Journal of Artificial Intelligence in Education, 2015
Providing opportunities for children to engage with intercultural learning has frequently focused on exposure to the ritual, celebrations and festivals of cultures, with the view that such experiences will result in greater acceptance of cultural differences. Intercultural conflict is often avoided, bringing as it does particular pedagogical,…
Descriptors: Multicultural Education, Intelligent Tutoring Systems, Experiential Learning, Children
Ostrow, Korinn; Donnelly, Christopher; Adjei, Seth; Heffernan, Neil – Grantee Submission, 2015
Student modeling within intelligent tutoring systems is a task largely driven by binary models that predict student knowledge or next problem correctness (i.e., Knowledge Tracing (KT)). However, using a binary construct for student assessment often causes researchers to overlook the feedback innate to these platforms. The present study considers a…
Descriptors: Intelligent Tutoring Systems, Models, Difficulty Level, Scores
Mirzaei, Maryam Sadat; Meshgi, Kourosh – Research-publishing.net, 2019
Many language learners have difficulty practicing listening skills using authentic materials, and thus use captions to map text with speech, and they benefit from reading along while listening to comprehend content. However, many learners over-rely on reading the text and many have difficulty in dividing their attention to the multimodal input. We…
Descriptors: Visual Aids, Second Language Learning, Second Language Instruction, Listening Skills
Aravind, Vasudeva Rao; McConnell, Marcella Kay – World Journal on Educational Technology: Current Issues, 2018
Educating our future citizens in science and engineering is vitally important to ensure future advancement. Presently, in the light of environmental sustainability, it is critical that students learn concepts relating to energy, its consumption and future demands. In this article, we harness the state of the educational technology, namely…
Descriptors: Intelligent Tutoring Systems, Science Instruction, Energy, Instructional Design
Huang, Jin-Xia; Kwon, Oh-Woog; Lee, Kyung-Soon; Kim, Young-Kil – Research-publishing.net, 2018
This paper presents a chatbot for a Dialogue-Based Computer Assisted Language Learning (DB-CALL) system. The chatbot helps users learn language via free conversations. To improve the chatbot performance, this paper adopts a Neural Machine Translation (NMT) engine to combine with an existing search-based engine, and also extracts a small domain…
Descriptors: Computer Assisted Instruction, Second Language Learning, Second Language Instruction, Computer Mediated Communication
Kim, Yanghee; Baylor, Amy L. – International Journal of Artificial Intelligence in Education, 2016
In this paper we review the contribution of our original work titled "Simulating Instructional Roles Through Pedagogical Agents" published in the "International Journal of Artificial Intelligence and Education" (Baylor and Kim in "Computers and Human Behavior," 25(2), 450-457, 2005). Our original work operationalized…
Descriptors: Artificial Intelligence, Intelligent Tutoring Systems, Computer Interfaces, Instructional Design
McManus, Margaret M.; Aiken, Robert M. – International Journal of Artificial Intelligence in Education, 2016
Our original research, to design and develop an Intelligent Collaborative Learning System (ICLS), yielded the creation of a Group Leader Tutor software system which utilizes a Collaborative Skills Network to monitor students working collaboratively in a networked environment. The Collaborative Skills Network was a conceptualization of…
Descriptors: Cooperative Learning, Artificial Intelligence, Intelligent Tutoring Systems, Sentences
George, Sébastien; Michel, Christine; Ollagnier-Beldame, Magali – Interactive Learning Environments, 2016
During learning activities, reflexive processes allow learners to realise what they have done, understand why, decide on new actions and gain motivation. They help learners to regulate their actions by themselves, that is, to develop metacognitive regulation skills. Computer environments can support reflexive processes to support human learning,…
Descriptors: Reflection, Metacognition, Technology Uses in Education, Educational Technology
Bull, Susan – Research and Practice in Technology Enhanced Learning, 2016
Today's technology-enabled learning environments are becoming quite different from those of a few years ago, with the increased processing power as well as a wider range of educational tools. This situation produces more data, which can be fed back into the learning process. Open learner models have already been investigated as tools to promote…
Descriptors: Educational Technology, Electronic Learning, Models, Computer Assisted Instruction
Fouh, Eric; Farghally, Mohammed; Hamouda, Sally; Koh, Kyu Han; Shaffer, Clifford A. – International Educational Data Mining Society, 2016
We present an analysis of log data from a semester's use of the OpenDSA eTextbook system with the goal of determining the most difficult course topics in a data structures course. While experienced instructors can identify which topics students most struggle with, this often comes only after much time and effort, and does not provide real-time…
Descriptors: Item Response Theory, Data Analysis, Mathematics, Intelligent Tutoring Systems
Hutt, Stephen; Mills, Caitlin; White, Shelby; Donnelly, Patrick J.; D'Mello, Sidney K. – International Educational Data Mining Society, 2016
Mind wandering (MW) is a ubiquitous phenomenon characterized by an unintentional shift in attention from task-related to task-unrelated thoughts. MW is frequent during learning and negatively correlates with learning outcomes. Therefore, the next generation of intelligent learning technologies should benefit from mechanisms that detect and combat…
Descriptors: Attention, Intelligent Tutoring Systems, Eye Movements, Biology
McCarthy, Kathryn S.; Soto, Christian Marcelo; Gutierrez de Blume, Antonio P.; Palma, Diego; González, Jordan Ignacio; McNamara, Danielle S. – International Journal of Computer-Assisted Language Learning and Teaching, 2020
iSTART-E is a web-based intelligent tutor developed for Spanish-speaking students to improve their reading comprehension through self-explanation strategy training. This study examined the effects of a blended comprehension strategy intervention on students' reading comprehension skill. Chilean high school students (N = 22) completed nine iSTART-E…
Descriptors: Reading Comprehension, High School Students, Computer Assisted Instruction, Teaching Methods
Acharya, Anal; Sinha, Devadatta – Journal of Educational Computing Research, 2017
The aim of this article is to propose a method for development of concept map in web-based environment for identifying concepts a student is deficient in after learning using traditional methods. Direct Hashing and Pruning algorithm was used to construct concept map. Redundancies within the concept map were removed to generate a learning sequence.…
Descriptors: Intelligent Tutoring Systems, Web Based Instruction, Concept Mapping, Learning Problems
Mostafavi, Behrooz; Barnes, Tiffany – International Journal of Artificial Intelligence in Education, 2017
Deductive logic is essential to a complete understanding of computer science concepts, and is thus fundamental to computer science education. Intelligent tutoring systems with individualized instruction have been shown to increase learning gains. We seek to improve the way deductive logic is taught in computer science by developing an intelligent,…
Descriptors: Artificial Intelligence, Problem Solving, Educational Technology, Technology Uses in Education
Thompson, Nik; McGill, Tanya Jane – Educational Technology Research and Development, 2017
This paper details the design, development and evaluation of an affective tutoring system (ATS)--an e-learning system that detects and responds to the emotional states of the learner. Research into the development of ATS is an active and relatively new field, with many studies demonstrating promising results. However, there is often no practical…
Descriptors: Intelligent Tutoring Systems, Electronic Learning, Psychological Patterns, Affective Measures

Peer reviewed
Direct link
