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Salomons, Nicole – ProQuest LLC, 2022
Robots have shown great promise in being effective tutors for both children and adults. For instance, they have been shown to be successful in math tutoring for children, interruptions training for adults with Autism Spectrum Disorder, and assisting the elderly while exercising. Yet, despite the great potential of tutoring robots, most studies…
Descriptors: Robotics, Intelligent Tutoring Systems, Artificial Intelligence, Technology Uses in Education
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Dimitrova, Vania; Mitrovic, Antonija – International Journal of Artificial Intelligence in Education, 2022
Video-based learning is widely used today in both formal education and informal learning in a variety of contexts. Videos are especially powerful for transferable skills learning (e.g. communicating, negotiating, collaborating), where contextualization in personal experience and ability to see different perspectives are crucial. With the ubiquity…
Descriptors: Artificial Intelligence, Video Technology, Teaching Methods, Transfer of Training
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Kareem, Jacqueline; Mathew, Minu Mary; David, Daliya – International Journal of Virtual and Personal Learning Environments, 2022
Owing to the importance of a subject like mathematics in the teaching and learning of science, self-learning often poses a challenge to the educator. The objective of this study is to analyse the enhancement of the textual and the media form of self-learning modules to teach algebra and geometry to eighth graders considering their retention…
Descriptors: Algebra, Geometry, Mathematics Instruction, Mathematics Achievement
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Singla, Adish; Theodoropoulos, Nikitas – International Educational Data Mining Society, 2022
Block-based visual programming environments are increasingly used to introduce computing concepts to beginners. Given that programming tasks are open-ended and conceptual, novice students often struggle when learning in these environments. AI-driven programming tutors hold great promise in automatically assisting struggling students, and need…
Descriptors: Programming, Computer Science Education, Task Analysis, Introductory Courses
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Renu Balyan; Tracy Arner; Tong Li; Ellen Orcutt; Reese Butterfuss; Panayiota Kendeou; Danielle McNamara – Grantee Submission, 2022
Speech technology (automated speech recognition -- ASR and text-to-speech) offers great promise in the field of automated literacy and reading tutors for children. Students in third and fourth grades struggle with generating longer strings of text on a QWERTY keyboard because they still "hunt and peck" for AQ1 the letters and symbols…
Descriptors: Assistive Technology, Technology Integration, Intelligent Tutoring Systems, Automation
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Hamed Asgari; Georges Antoniadis – International Association for Development of the Information Society, 2022
Mobile artifacts are the objects that increasingly surround us in life. They provide us with the opportunity to engage in activities outside the traditional context and at our own pace. In this article, we present the results of the tests of our mobile application intended for the learning of the French language with the concept of SPOC with a…
Descriptors: French, Second Language Learning, Second Language Instruction, Natural Language Processing
Geoffrey Converse – ProQuest LLC, 2021
In educational measurement, Item Response Theory (IRT) provides a means of quantifying student knowledge. Specifically, IRT models the probability of a student answering a particular item correctly as a function of the student's continuous-valued latent abilities [theta] (e.g. add, subtract, multiply, divide) and parameters associated with the…
Descriptors: Item Response Theory, Test Validity, Student Evaluation, Computer Assisted Testing
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Liang, Jia-Cing; Hwang, Gwo-Jen; Chen, Mei-Rong Alice; Darmawansah, Darmawansah – Interactive Learning Environments, 2023
This study explores the roles and research foci of AILEd (Artificial Intelligence in Language Education). The AILEd studies published from 1990 to 2020 in the WOS (Web of Science) database were included in the present study. Based on the well-recognized Technology-based Learning Review model, several dimensions, such as research methods, research…
Descriptors: Artificial Intelligence, Technology Uses in Education, Second Language Learning, Educational Trends
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Gonulal, Talip – Interactive Learning Environments, 2023
Intelligent personal assistants (IPAs), which are voice-activated agents enabling human--computer interaction, have recently been reported to be pedagogically useful agents in language learning. IPAs use various forms of humor to better communicate with users and to compensate for any performance limitations. In order to understand the IPAs' sense…
Descriptors: Intelligent Tutoring Systems, Second Language Learning, Second Language Instruction, English (Second Language)
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Silvia García-Méndez; Francisco de Arriba-Pérez; Francisco J. González-Castaño – International Association for Development of the Information Society, 2023
Mobile learning or mLearning has become an essential tool in many fields in this digital era, among the ones educational training deserves special attention, that is, applied to both basic and higher education towards active, flexible, effective high-quality and continuous learning. However, despite the advances in Natural Language Processing…
Descriptors: Higher Education, Artificial Intelligence, Computer Software, Usability
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Fancsali, Stephen E.; Yudelson, Michael V.; Berman, Susan R.; Ritter, Steven – International Educational Data Mining Society, 2018
Learners in various contemporary settings (e.g., K-12 classrooms, online courses, professional/vocational training) find themselves in situations in which they have access to multiple technology-based learning platforms and often one or more non-technological resources (e.g., human instructors or on-demand human tutors). Instructors, similarly,…
Descriptors: Intelligent Tutoring Systems, Tutors, Higher Education, Online Courses
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Chaudhry, Ritwick; Singh, Harvineet; Dogga, Pradeep; Saini, Shiv Kumar – International Educational Data Mining Society, 2018
Interactive learning environments facilitate learning by providing hints to fill the gaps in the understanding of a concept. Studies suggest that hints are not used optimally by learners. Either they are used unnecessarily or not used at all. It has been shown that learning outcomes can be improved by providing hints when needed. An effective…
Descriptors: Student Behavior, Prediction, Models, Intelligent Tutoring Systems
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Maniktala, Mehak; Cody, Christa; Isvik, Amy; Lytle, Nicholas; Chi, Min; Barnes, Tiffany – Journal of Educational Data Mining, 2020
Determining "when" and "whether" to provide personalized support is a well-known challenge called the assistance dilemma. A core problem in solving the assistance dilemma is the need to discover when students are unproductive so that the tutor can intervene. Such a task is particularly challenging for open-ended domains, even…
Descriptors: Intelligent Tutoring Systems, Problem Solving, Helping Relationship, Prediction
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Balyan, Renu; McCarthy, Kathryn S.; McNamara, Danielle S. – International Journal of Artificial Intelligence in Education, 2020
For decades, educators have relied on readability metrics that tend to oversimplify dimensions of text difficulty. This study examines the potential of applying advanced artificial intelligence methods to the educational problem of assessing text difficulty. The combination of hierarchical machine learning and natural language processing (NLP) is…
Descriptors: Natural Language Processing, Artificial Intelligence, Man Machine Systems, Classification
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Grubišic, Ani; Žitko, Branko; Stankov, Slavomir – Journal of Technology and Science Education, 2020
In intelligent e-learning systems that adapt a learning and teaching process to student knowledge, it is important to adapt the system as quickly as possible. However, adaptation is not possible until the student model is initialized. In this paper, a new approach to student model initialization using domain knowledge representative subset is…
Descriptors: Electronic Learning, Educational Technology, Models, Intelligent Tutoring Systems
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