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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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du Boulay, Benedict – International Journal of Artificial Intelligence in Education, 2021
Mark and Greer's ("International Journal of Artificial Intelligence in Education," 4(2/3), 129-153, 1993) review was very influential in setting out effective goals and methods for evaluating adaptive educational systems of all kinds. A later review brought the story up to date (Greer, "International Journal of Artificial…
Descriptors: Artificial Intelligence, Computer Uses in Education, Evaluation Methods, Student Satisfaction
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Valdés Aguirre, Benjamín; Ramírez Uresti, Jorge A.; du Boulay, Benedict – International Journal of Artificial Intelligence in Education, 2016
Sharing user information between systems is an area of interest for every field involving personalization. Recommender Systems are more advanced in this aspect than Intelligent Tutoring Systems (ITSs) and Intelligent Learning Environments (ILEs). A reason for this is that the user models of Intelligent Tutoring Systems and Intelligent Learning…
Descriptors: Intelligent Tutoring Systems, Models, Open Source Technology, Computers
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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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du Boulay, Benedict; Luckin, Rosemary – International Journal of Artificial Intelligence in Education, 2016
Our original paper tried to characterize the richness of the teaching repertoire of expert human teachers and to give a sense of how far there still was to go in the development of pedagogic expertise in AIED systems. It considered three ways in which more expert teaching strategies and tactics might be developed. These were via (i) the…
Descriptors: Intelligent Tutoring Systems, Artificial Intelligence, Teaching Methods, Educational Strategies
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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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du Boulay, Benedict; Avramides, Katerina; Luckin, Rosemary; Martinez-Miron, Erika; Rebolledo-Mendez, Genaro; Carr, Amanda – International Journal of Artificial Intelligence in Education, 2010
This paper describes a Conceptual Framework underpinning "Systems that Care" in terms of educational systems that take account of motivation, metacognition and affect, in addition to cognition. The main focus is on "motivation," as learning requires the student to put in effort and be engaged, in other words to be motivated to learn. But…
Descriptors: Learning Motivation, Metacognition, Affective Behavior, Schemata (Cognition)