Emotion Regulation in Intelligent Tutoring Systems: A Systematic Literature Review

Khadimallah, Rihab; Abdelkefi, Mouna; Kallel, Ilhem

doi:10.1109/tale48869.2020.9368372

Cited by 4 publications

(2 citation statements)

References 42 publications

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“…According to this ZPD principle, the tutoring component classically integrates a performance threshold principle for exercise difficulty shift (often chosen around 70%) to maintain an average optimal learning trajectory (Seitz (2018)). Several signals or performance dimensions can be used to guide the generation of a curriculum: some ITS are interested in using an optimal emotional level (Khadimallah, Abdelkefi, and Kallel (2020)) or learning progress (Clement, Roy, Oudeyer, and Lopes (2013), Ma, Adesope, Nesbit, and Liu (2014)) or both (Oudeyer, Kaplan, and Hafner (2007)).…”

Section: Insights From Its Researchmentioning

confidence: 99%

Exploring the Potential of Artificial Intelligence in Individualized Cognitive Training: a Systematic Review

Adolphe,

Pech,

Sawayama

et al. 2023

Preprint

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To tackle the challenge of responders heterogeneity, Cognitive Training (CT) research currently leverages AI Techniques for providing individualized curriculum rather than one-size-fits-all designs of curriculum. Our systematic review explored these new generations of adaptive methods in computerized CT and analyzed their outcomes in terms of learning mechanics (intra-training performance) and effectiveness (near, far and everyday life transfer effects of CT). A search up to June 2023 with multiple databases selected 19 computerized CT studies using AI techniques for individualized training. After outlining the AI-based individualization approach, this work analyzed CT setting (content, dose, etc), targeted population, intra-training performance tracking, and pre-post-CT effects. Half of selected studies employed a macro-adaptive approach mostly for multiple-cognitive domain training while the other half used a micro-adaptive approach with various techniques, especially for single-cognitive domain training. Two studies emphasized the favorable influence on CT effectiveness, while five underscored its capacity to enhance the training experience by boosting motivation, engagement, and offering diverse learning pathways. Methodological differences across studies and weaknesses in their design (no control group, small sample, etc.) were observed. Despite promising results in this new research avenue, more research is needed to fully understand and empirically support individualized techniques in cognitive training.

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Section: Insights From Its Researchmentioning

confidence: 99%

Exploring the Potential of Artificial Intelligence in Individualized Cognitive Training: a Systematic Review

Adolphe,

Pech,

Sawayama

et al. 2023

Preprint

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show abstract

“…Education researchers are now incorporating emotion recognition into intelligent tutoring systems to gauge student engagement, frustration, and mental health (Khadimallah et al, 2020;Newton, 2021). Chinese educators are experimenting with realtime monitoring of students' faces in the classroom to generate an engagement dashboard for the teacher (Waltz, 2020).…”

Section: Robots and Social-emotional Labormentioning

confidence: 99%

Deskilling of Teaching and the Case for Intelligent Tutoring Systems

Hughes

2021

J. Eth. Emerg. Tech.

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This essay describes trends in the organization of work that have laid the groundwork for the adoption of interactive AI-driven instruction tools, and the technological innovations that will make intelligent tutoring systems truly competitive with human teachers. Since the origin of occupational specialization, the collection and transmission of knowledge have been tied to individual careers and job roles, specifically doctors, teachers, clergy, and lawyers, the paradigmatic knowledge professionals. But these roles have also been tied to texts and organizations that can disseminate knowledge independently from professionals. Professionals and organizations turn knowledge into texts and tools that enable lay people to access knowledge without the intermediation of professionals or organizations. In the 21st century, one emerging tool for transmitting knowledge is the intelligent tutoring system. This paper examines how technological, epistemic, and economic trends in education are supporting the routinization, proletarianization, and automation of the occupation of teaching, leading to the increasing substitution of intelligent tutoring systems for human instruction. Some trends, such as standardized curricula and testing, both restrict teachers’ professional autonomy and facilitate the creation of pedagogical tools. Other trends reduce teachers’ ability to resist automation. The growth of adjunct teaching and paraprofessional roles in higher education allows organizations to take over and rationalize parts of the traditional teacher role. Faculty evaluations and learning outcomes assessment weaken professional claims to be the sole arbiters of instructional quality and student learning. The widespread use of intelligent tutoring systems also depends on the sophistication of software capable of performing the social-emotional and cognitive roles that educators perform. Eventually, pedagogical software will be able to interactively individualize curricula to the needs and interests of every learner, more cheaply, quickly, and accurately than any human teacher. Assessment of learning will be continuous, and certification of learning will be for specific skills instead of broad area competencies. Intelligent tutoring systems will help transition education from its medieval and industrial-era model to more accessible and flexible continuing education for employment and life enrichment.

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Association Rules Mining for Reducing Items from Emotion Regulation Questionnaires

Khadimallah

Kallel

Drira

2022

Intelligent Data Engineering and Automated Learning – IDEAL 2022

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Emotion Regulation in Intelligent Tutoring Systems: A Systematic Literature Review

Cited by 4 publications

References 42 publications

Exploring the Potential of Artificial Intelligence in Individualized Cognitive Training: a Systematic Review

Exploring the Potential of Artificial Intelligence in Individualized Cognitive Training: a Systematic Review

Deskilling of Teaching and the Case for Intelligent Tutoring Systems

Association Rules Mining for Reducing Items from Emotion Regulation Questionnaires

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