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A Multimedia Adaptive Tutoring System for Mathematics that Addresses Cognition, Metacognition and Affect
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This article describes research results based on multiple years of experimentation and real-world experience with an adaptive tutoring system named Wayang Outpost. The system represents a novel adaptive learning technology that has shown successful outcomes with thousands of students, and provided teachers with valuable information about students’ mathematics performance. We define progress in three areas: improved student cognition, engagement, and affect, and we attribute this improvement to specific components and interventions that are inherently affective, cognitive, and metacognitive in nature. For instance, improved student cognitive outcomes have been measured with pre-post tests and state standardized tests, and achieved due to personalization of content and math fluency training. Improved student engagement was achieved by supporting students’ metacognition and motivation via affective learning companions and progress reports, measured via records of student gaming of the system. Student affect within the tutor was measured through sensors and student self-reports, and supported through affective learning companions and progress reports. Collectively, these studies elucidate a suite of effective strategies to support advanced personalized learning via an intelligent adaptive tutor that can be tailored to the individual needs, emotions, cognitive states, and metacognitive skills of learners.
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“As far as we can tell, only one paper from 2014 surveyed other aspects of motivation (e.g., self-efficacy) in a more substantial way (Arroyo et al., 2014).”
From Evolution and Revolution in Artificial Intelligence in Education (2016) · cites this paper as Arroyo et al., 2014
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Metadata
- Authors
- Arroyo, I., Woolf, B. P., Burelson, W., Muldner, K., Rai, D., & Tai, M.
- Affiliations
- Worcester Polytechnic Institute (US)
- University of Massachusetts Amherst (US)
- New York University (US)
- Corresponding author
- Arroyo, Ivon
- Venue
- International Journal of Artificial Intelligence in Education
- Publisher
- Elsevier BV
- Published
- 2014-12
- Volume
- 24
- Issue
- 4
- Pages
- 387-426
- ISSN
- 1560-4292 (ISSN-L)
- OpenAlex
- W2094147479
- Cited by
- 263
- References
- 106
- Citations by year
- 2026: 13 · 2025: 36 · 2024: 25 · 2023: 36 · 2022: 31 · 2021: 22 · 2020: 22 · 2019: 18 · 2018: 17 · 2017: 19 · 2016: 11 · 2015: 12 · 2014: 1
- FWCI
- 14.29
- Type
- journal article
- Language
- en
- Update notices
- Open access
- hybrid
- doi.org
- Licence
- Locations
- International Journal of Artificial Intelligence in Education (publishedVersion, cc-by-nc-nd)
- Funders
- National Science Foundation (1324385)
- Office of Naval Research (N0001413C0127)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Social Sciences › Psychology › Developmental and Educational Psychology › Innovative Teaching and Learning Methods
- Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
- Keywords
- adaptive tutoring systems, mathematics education, metacognition, student engagement, student motivation, personalized learning, emotion sensing
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