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Showing 1 to 15 of 21 results Save | Export
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Darvishi, Ali; Khosravi, Hassan; Sadiq, Shazia; Weber, Barbara – International Journal of Artificial Intelligence in Education, 2022
The use of neurophysiological measurements to advance the design, development, use, acceptance, influence and adaptivity of information systems is receiving increasing attention. Within the field of education, neurophysiological measurements have commonly been used to capture a learner's psychological constructs such as cognitive load, attention…
Descriptors: Neurology, Physiology, Measurement, Information Systems
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Rebolledo-Mendez, Genaro; Huerta-Pacheco, N. Sofia; Baker, Ryan S.; du Boulay, Benedict – International Journal of Artificial Intelligence in Education, 2022
Many previous studies have highlighted the influence of learners' affective states on learning with tutoring systems. However, the associations between learning and learners' meta-affective capability are still unclear. The goal of this paper is to analyse meta-affective capability and its influence on learning outcomes as well as the dynamics of…
Descriptors: Affective Behavior, Intelligent Tutoring Systems, Mathematics Education, Secondary School Students
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Lewis, Armanda; Stoyanovich, Julia – International Journal of Artificial Intelligence in Education, 2022
Although an increasing number of ethical data science and AI courses is available, with many focusing specifically on technology and computer ethics, pedagogical approaches employed in these courses rely exclusively on texts rather than on algorithmic development or data analysis. In this paper we recount a recent experience in developing and…
Descriptors: Statistics Education, Ethics, Artificial Intelligence, Compliance (Legal)
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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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Matsuda, Noboru; Weng, Wenting; Wall, Natalie – International Journal of Artificial Intelligence in Education, 2020
The effect of metacognitive scaffolding for learning by teaching was investigated and compared against learning by being tutored. Three versions of an online learning environment for learning algebra equations were created: (1) APLUS that allows students to interactively teach a synthetic peer with a goal to have the synthetic peer pass the quiz…
Descriptors: Metacognition, Scaffolding (Teaching Technique), Tutoring, Intelligent Tutoring Systems
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Taub, Michelle; Azevedo, Roger – International Journal of Artificial Intelligence in Education, 2019
The goal of this study was to use eye-tracking and log-file data to investigate the impact of prior knowledge on college students' (N = 194, with a subset of n = 30 for eye tracking and sequence mining analyses) fixations on (i.e., looking at) self-regulated learning-related areas of interest (i.e., specific locations on the interface) and on the…
Descriptors: Prior Learning, Eye Movements, Metacognition, Learning Processes
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McCarthy, Kathryn S.; Likens, Aaron D.; Johnson, Amy M.; Guerrero, Tricia A.; McNamara, Danielle S. – International Journal of Artificial Intelligence in Education, 2018
Research suggests that promoting metacognitive awareness can increase performance in, and learning from, intelligent tutoring systems (ITSs). The current work examines the effects of two metacognitive prompts within iSTART, a reading comprehension strategy ITS in which students practice writing quality self-explanations. In addition to comparing…
Descriptors: Metacognition, Difficulty Level, Prompting, Intelligent Tutoring Systems
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Perikos, Isidoros; Grivokostopoulou, Foteini; Hatzilygeroudis, Ioannis – International Journal of Artificial Intelligence in Education, 2017
Logic as a knowledge representation and reasoning language is a fundamental topic of an Artificial Intelligence (AI) course and includes a number of sub-topics. One of them, which brings difficulties to students to deal with, is converting natural language (NL) sentences into first-order logic (FOL) formulas. To assist students to overcome those…
Descriptors: Intelligent Tutoring Systems, Feedback (Response), Natural Language Processing, Logical Thinking
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Porayska-Pomsta, Kaska – International Journal of Artificial Intelligence in Education, 2016
Evidence-based practice (EBP) is of critical importance in education where emphasis is placed on the need to equip educators with an ability to independently generate and reflect on evidence of their practices in situ--a process also known as "praxis." This paper examines existing research related to teachers' metacognitive skills and,…
Descriptors: Evidence Based Practice, Artificial Intelligence, Metacognition, Praxis
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du Boulay, Benedict; del Soldato, Teresa – International Journal of Artificial Intelligence in Education, 2016
This paper describes the development and evaluation of a system called MORE (Motivational Reactive Plan) in the 1990s, designed with an explicit strategy to manage the learner's motivation on a minute-by-minute basis. Progress since the system was evaluated is outlined and our current thinking on the larger issues of the role that the learner's…
Descriptors: Intelligent Tutoring Systems, Artificial Intelligence, Student Motivation, Values
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Conati, Cristina – International Journal of Artificial Intelligence in Education, 2016
This paper is a commentary on "Toward Computer-Based Support of Meta-Cognitive Skills: a Computational Framework to Coach Self-Explanation", by Cristina Conati and Kurt Vanlehn, published in the "IJAED" in 2000 (Conati and VanLehn 2010). This work was one of the first examples of Intelligent Learning Environments (ILE) that…
Descriptors: Metacognition, Intelligent Tutoring Systems, Skill Development, Artificial Intelligence
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Aleven, Vincent; Roll, Ido; McLaren, Bruce M.; Koedinger, Kenneth R. – International Journal of Artificial Intelligence in Education, 2016
Help seeking is an important process in self-regulated learning (SRL). It may influence learning with intelligent tutoring systems (ITSs), because many ITSs provide help, often at the student's request. The Help Tutor was a tutor agent that gave in-context, real-time feedback on students' help-seeking behavior, as they were learning with an ITS.…
Descriptors: Intelligent Tutoring Systems, Artificial Intelligence, Help Seeking, Feedback (Response)
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Chou, Chih-Yueh; Chan, Tak-Wai – International Journal of Artificial Intelligence in Education, 2016
"Reciprocal tutoring," as reported in "Exploring the design of computer supports for reciprocal tutoring" (Chan and Chou 1997), has extended the meaning and scope of "intelligent tutoring" originally implemented in stand alone computers. This research is a follow-up to our studies on a "learning companion…
Descriptors: Peer Teaching, Tutoring, Cognitive Processes, Difficulty Level
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Luckin, Rosemary; du Boulay, Benedict – International Journal of Artificial Intelligence in Education, 2016
In 1999 we reported a study that explored the way that Vygotsky's Zone of Proximal Development could be used to inform the design of an Interactive Learning Environment called the Ecolab. Two aspects of this work have subsequently been used for further research. Firstly, there is the interpretation of the ZPD and its associated theory that was…
Descriptors: Sociocultural Patterns, Metacognition, Goal Orientation, Student Motivation
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Suleman, Raja M.; Mizoguchi, Riichiro; Ikeda, Mitsuru – International Journal of Artificial Intelligence in Education, 2016
Negotiation mechanism using conversational agents (chatbots) has been used in Open Learner Models (OLM) to enhance learner model accuracy and provide opportunities for learner reflection. Using chatbots that allow for natural language discussions has shown positive learning gains in students. Traditional OLMs assume a learner to be able to manage…
Descriptors: Metacognition, Intelligent Tutoring Systems, Natural Language Processing, Models
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