Annie: Automated Generation of Adaptive Learner Guidance for Fun Serious Games
Abstract
This paper describes some of the difficulties inherent in building intelligent educational games, specifically the challenge of integrating pedagogy with core game play. We introduce a plan-based knowledge representation that provides a novel framework for infusing the core mechanics of a game with pedagogical content. We describe, in detail, a system that leverages this framework to dynamically adapt a game to individual learners at runtime.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
AI has assisted the integration of the game and knowledge domain, and the further potential is making the game adapt to learners' behaviours and affections dynamically.
“AI has assisted the integration of the game and knowledge domain, and the further potential is making the game adapt to the learners' behaviours and affections dynamically [57].”
From A Review of Artificial Intelligence (AI) in Education from 2010 to 2020 (2021) · cites this paper as [57]
Another ethical debate was conspicuously found in gamification that emphasis should be put on learning and tend to 'suck the fun out' of games, or on gameplay 'suck out the learning'.
“Another ethical debate was conspicuously found in gamification that emphasis should be put on learning and tend to”
From A Review of Artificial Intelligence (AI) in Education from 2010 to 2020 (2021) · cites this paper as [57]
Cites
Vygotsky, L. S. (1964) · Bulletin of the Orton Society · doi:10.1007/bf02928399 · Cited by 20,704 · see citing works
Flow: the psychology of optimal experience
(1990) · Choice Reviews Online · doi:10.5860/choice.28-0597 · Cited by 12,652 · see citing works
Flow: The Psychology of Optimal Experience
Buchanan, R., & Csíkszentmihályi, M. (1991) · Design Issues · doi:10.2307/1511458 · Cited by 9,437 · see citing works
What Video Games Have to Teach Us about Learning and Literacy
(2004) · Education + Training · doi:10.1108/et.2004.00446dae.002 · Cited by 6,674 · see citing works
What video games have to teach us about learning and literacy
Gee, J. P. (2003) · Computers in Entertainment · doi:10.1145/950566.950595 · Cited by 5,735 · see citing works
Rules of Play: Game Design Fundamentals
Salen, K., & Zimmerman, E. (2003) · Medical Entomology and Zoology · Cited by 5,321 · see citing works
STRIPS: A New Approach to the Application of Theorem Proving to Problem Solving
Fikes, R. E., & Nilsson, N. J. (1971) · Artificial Intelligence · doi:10.1016/0004-3702(71)90010-5 · Cited by 4,882 · see citing works
Prensky, M. (2003) · Computers in entertainment · doi:10.1145/950566.950596 · Cited by 3,106 · see citing works
Tatnall, A. (2020) · Encyclopedia of Education and Information Technologies · doi:10.1007/978-3-030-10576-1_300187 · Cited by 2,893 · see citing works
Suits, B. (1978) · University of Toronto Press eBooks · doi:10.3138/9781487574338 · Cited by 1,549 · see citing works
A Theory of Fun for Game Design
Koster, R., & Wright, W. (2004) · Cited by 951 · see citing works
(1984) · Cited by 919 · see citing works
The Behavior of Tutoring Systems
VanLehn, K. A. (2006) · International Journal of Artificial Intelligence in Education · doi:10.3233/irg-2006-16(3)02 · Cited by 821 · see citing works
A Scaffolding Design Framework for Software to Support Science Inquiry
Quintana, C., Reiser, B., Davis, E., Krajcik, J., Fretz, E., Duncan, R., Kyza, E., Edelson, D. C., & Soloway, E. (2004) · The Journal of the Learning Sciences · doi:10.1207/s15327809jls1303_4 · Cited by 667 · see citing works
Andrew Rollings and Ernest Adams on Game Design
Rollings, A., & Adams, E. (2003) · Cited by 524 · see citing works
Technological advances in inquiry learning
de Jong, T. (2006) · Science · doi:10.1126/science.1127750 · Cited by 469 · see citing works
A Large‐Scale Evaluation of an Intelligent Discovery World: Smithtown
Shute, V. J., & Glaser, R. A. (1990) · Interactive Learning Environments · doi:10.1080/1049482900010104 · Cited by 279 · see citing works
Structuring Content in the Façade Interactive Drama Architecture
Mateas, M., & Stern, A. (2005) · Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment · doi:10.1609/aiide.v1i1.18722 · Cited by 217 · see citing works
Managing interaction between users and agents in a multi-agent storytelling environment
Riedl, M., Saretto, C. J., & Young, R. M. (2003) · Adaptive Agents and Multi-Agents Systems · doi:10.1145/860575.860694 · Cited by 205 · see citing works
Self-citationKambhampati, S., Knoblock, C. A., & Yang, Q. (1995) · Artificial Intelligence · doi:10.1016/0004-3702(94)00076-d · Cited by 178 · see citing works
Interacting with virtual characters in interactive storytelling
Cavazza, M., Charles, F., & Mead, S. J. (2002) · doi:10.1145/544741.544819 · Cited by 169 · see citing works
Unscripted narrative for affectively driven characters
Aylett, R. S., Louchart, S., Dias, J., Paiva, A., Vala, M., Woods, S. N., & Hall, L. E. (2006) · IEEE Computer Graphics and Applications · doi:10.1109/mcg.2006.71 · Cited by 124 · see citing works
Toward Measuring and Maintaining the Zone of Proximal Development in Adaptive Instructional Systems
Murray, T., & Arroyo, I. (2002) · Lecture notes in computer science · doi:10.1007/3-540-47987-2_75 · Cited by 119 · see citing works
Decomposition and causality in partial-order planning
Young, R. M., Pollack, M. E., & Moore, J. D. (1994) · Cited by 115 · see citing works
Self-citationProbabilistic Student Modelling to Improve Exploratory Behaviour
Bunt, A., & Conati, C. (2003) · User Modeling and User-Adapted Interaction · doi:10.1023/a:1024733008280 · Cited by 89 · see citing works
Mott, B., & Lester, J. C. (2006) · Adaptive Agents and Multi-Agents Systems · doi:10.1145/1160633.1160808 · Cited by 79 · see citing works
Game writing : Narrative skills for videogames
Bateman, C., Adams, E., Boon, R. T., et al. (2007) · Cited by 65 · see citing works
Wide Ruled: A Friendly Interface to Author-Goal Based Story Generation
Skorupski, J., Jayapalan, L., Marquez, S., et al. (2007) · Springer eBooks · doi:10.1007/978-3-540-77039-8_3 · Cited by 39 · see citing works
A Comparison of Decision-Theoretic, Fixed-Policy and Random Tutorial Action Selection
Murray, R. C., & VanLehn, K. A. (2006) · Lecture notes in computer science · doi:10.1007/11774303_12 · Cited by 25 · see citing works
Game Writing: Narrative Skills for Videogames (Charles River Media Game Development (Paperback))
Bateman, C. (2006) · Charles River Media, Inc. eBooks · Cited by 18 · see citing works
A Web Services Approach to Generating and Using Plans in Configurable Execution Environments
Vernieri, T. M. (2006) · NCSU Libraries Repository (North Carolina State University Libraries) · Cited by 10 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
A Review of Artificial Intelligence (AI) in Education from 2010 to 2020
Zhai, X., Chu, X., Chai, C. S., Jong, M. S. Y., Istenic, A., Spector, M., Liu, J.-B., Yuan, J., & Li, Y. (2021) · Complexity · doi:10.1155/2021/8812542 · Cited by 1,364 · see citing works
“Another ethical debate was conspicuously found in gamification that emphasis should be put on learning and tend to “suck the fun out” of games, or on gameplay “suck out the learning” [57].”
BackgroundInfluentialArtificial Intelligence in Health Professions Education
Shankar, P. R. (2022) · Archives of Medicine and Health Sciences · doi:10.4103/amhs.amhs_234_22 · Cited by 40 · see citing works
- Authors
- Thomas, J. M., & Young, R. M.
- Affiliations
- North Carolina State University (US)
- Venue
- IEEE Transactions on Learning Technologies
- Published
- 2010-10
- Volume
- 3
- Issue
- 4
- Pages
- 329-343
- ISSN
- 1939-1382 (ISSN-L)
- OpenAlex
- W2129194012
- Cited by
- 48
- References
- 31
- Citations by year
- 2023: 2 · 2022: 4 · 2021: 6 · 2020: 3 · 2019: 3 · 2018: 4 · 2017: 3 · 2016: 3 · 2015: 3 · 2014: 4 · 2013: 7 · 2012: 4
- FWCI
- 4.40
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Transactions on Learning Technologies (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Social Sciences › Psychology › Developmental and Educational Psychology › Educational Games and Gamification
- Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence in Games
- Keywords
- serious games, game mechanics, personalized learning
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review