TY - GEN
T1 - Optimize Student Learning via Random Forest-Based Adaptive Narrative Game
AU - Hare, Ryan
AU - Tang, Ying
AU - Cui, Wei
AU - Liang, Joleen
N1 - Funding Information:
This work was supported in part by the National Science Foundation under Grant 1913809 and Grant 1610164.
Publisher Copyright:
© 2020 IEEE.
PY - 2020/8
Y1 - 2020/8
N2 - This paper presents an adaptive narrative game system that focuses on sequential logic design. The system adapts a random forest machine learning model to estimate a student's current level of domain knowledge relative to the problem presented to him through his game-playing behavior data, such as time taken to find solutions, errors in solutions, and emotional indicators. Hints, prompts, and/or individualized lessons are then offered to the player to guide their learning in a positive and productive direction. Our preliminary pilot study demonstrates that the model can make accurate classifications, from which proper assistance can then be provided to individual students as they play.
AB - This paper presents an adaptive narrative game system that focuses on sequential logic design. The system adapts a random forest machine learning model to estimate a student's current level of domain knowledge relative to the problem presented to him through his game-playing behavior data, such as time taken to find solutions, errors in solutions, and emotional indicators. Hints, prompts, and/or individualized lessons are then offered to the player to guide their learning in a positive and productive direction. Our preliminary pilot study demonstrates that the model can make accurate classifications, from which proper assistance can then be provided to individual students as they play.
UR - http://www.scopus.com/inward/record.url?scp=85094123624&partnerID=8YFLogxK
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U2 - 10.1109/CASE48305.2020.9217020
DO - 10.1109/CASE48305.2020.9217020
M3 - Conference contribution
AN - SCOPUS:85094123624
T3 - IEEE International Conference on Automation Science and Engineering
SP - 792
EP - 797
BT - 2020 IEEE 16th International Conference on Automation Science and Engineering, CASE 2020
PB - IEEE Computer Society
T2 - 16th IEEE International Conference on Automation Science and Engineering, CASE 2020
Y2 - 20 August 2020 through 21 August 2020
ER -