Adaptive Narrative Game for Personalized Learning

Y. Tang, R. Hare

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In recent years, engineering educators have begun to focus more on new learning methods that allow students to better understand and practice their subject matter. However, these approaches are not ideal for every student, and can be costly or time consuming to educators and institutions. Instead, a more individualized approach to learning is needed. This paper addresses this challenge through a narrative game system. Building on top of a previously created narrative game, the system utilizes metacognitive strategies (Roadmap, What I Know-What I Want to Know-What I Have Solved, and Think-Aloud-Share-Solve) and a random forest machine learning model to model a student's learning process. Based on data collected from the student, including emotional state, time, and errors in solutions, the system can estimate the current stage in the learning process. The student can then be offered prompts or hints to guide learning in a positive and productive direction, dynamically correcting misconceptions and allowing the student to learn at his/her own pace in a stress-free environment.

Original languageEnglish (US)
Title of host publicationProceedings - IEEE International Conference on Service Operations and Logistics, and Informatics 2019, SOLI 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages175-180
Number of pages6
ISBN (Electronic)9781728128535
DOIs
StatePublished - Nov 2019
Event2019 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2019 - Zhengzhou, China
Duration: Nov 6 2019Nov 7 2019

Publication series

NameProceedings - IEEE International Conference on Service Operations and Logistics, and Informatics 2019, SOLI 2019

Conference

Conference2019 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2019
CountryChina
CityZhengzhou
Period11/6/1911/7/19

All Science Journal Classification (ASJC) codes

  • Management Science and Operations Research
  • Strategy and Management
  • Artificial Intelligence
  • Information Systems
  • Information Systems and Management

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