TY - GEN
T1 - A Self-Served AI Tutor for Growth Mindset Teaching
AU - Abduljabbar, A.
AU - Gupta, N.
AU - Healy, L.
AU - Kumar, Y.
AU - Li, J. J.
AU - Morreale, P.
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Recommender systems are a part of our everyday life. We are accustomed to see suggestions of what videos to watch, what products to buy, what apps to install, and what food to eat. We assume that these personalized suggestions are accurate because they are based on our personal profile, saved history, location, physical and online activities, and other factors. In this paper, we present an innovative application of a recommender system. We created a self-served AI tutor with recommender technologies that encourages a Growth Mindset when teaching Computer Science to a broader and inclusive audience. The AI tutor uses our in-house AI/ML algorithms to detect and provide constructive, encouraging feedback to facilitate Growth Mindset in students, which in turn yields positive learning outcomes in said students. We trained our app to detect Growth Mindset utilization in Computer Science teaching, through evaluating the Growth Mindset presence in text, audio/video recordings and live speeches. The app was also trained to generate recommendations for improving Computer Science teaching in terms of Growth Mindset. The promotion and widely adaptation of our AI tutor through a free online platform will help Computer Science teachers globally.
AB - Recommender systems are a part of our everyday life. We are accustomed to see suggestions of what videos to watch, what products to buy, what apps to install, and what food to eat. We assume that these personalized suggestions are accurate because they are based on our personal profile, saved history, location, physical and online activities, and other factors. In this paper, we present an innovative application of a recommender system. We created a self-served AI tutor with recommender technologies that encourages a Growth Mindset when teaching Computer Science to a broader and inclusive audience. The AI tutor uses our in-house AI/ML algorithms to detect and provide constructive, encouraging feedback to facilitate Growth Mindset in students, which in turn yields positive learning outcomes in said students. We trained our app to detect Growth Mindset utilization in Computer Science teaching, through evaluating the Growth Mindset presence in text, audio/video recordings and live speeches. The app was also trained to generate recommendations for improving Computer Science teaching in terms of Growth Mindset. The promotion and widely adaptation of our AI tutor through a free online platform will help Computer Science teachers globally.
KW - computer science
KW - embedding features
KW - growth mindset
KW - recommender system
KW - self-served tutor
UR - http://www.scopus.com/inward/record.url?scp=85137081655&partnerID=8YFLogxK
U2 - 10.1109/ICICT55905.2022.00018
DO - 10.1109/ICICT55905.2022.00018
M3 - Conference contribution
AN - SCOPUS:85137081655
T3 - Proceedings - 2022 5th International Conference on Information and Computer Technologies, ICICT 2022
SP - 55
EP - 59
BT - Proceedings - 2022 5th International Conference on Information and Computer Technologies, ICICT 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 5th International Conference on Information and Computer Technologies, ICICT 2022
Y2 - 4 March 2022 through 6 March 2022
ER -