TY - GEN
T1 - ChatGPT as a Game-Changer for Embedding Emojis in Faculty Feedback
AU - Kupershtein, Ethan
AU - Kumar, Yulia
AU - Manikandan, Anjana
AU - Morreale, Patricia
AU - Li, J. Jenny
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - This study explores the potential of integrating emojis, and digital pictographs, into faculty feedback to augment student learning outcomes. This additional layer of expressiveness, encouragement, and involvement adds a personal touch to the often distant and virtual student-educator communications, fostering motivation. The study focuses on the impact of emojis on the learning process within the scrutinized Computer Science (CS) Department. Capitalizing on the capabilities of OpenAI's Large Language Model (LLM) ChatGPT-4, its Application Programming Interface (API), and associated tools and third-party plugins, a system that translates text into corresponding emojis and vice versa has been developed. The proposed application offers direct benefits to educators by simplifying the provision of detailed and extensive feedback to students. The primary research question is: Can the appropriate use of emojis, matched with the sentiment of the feedback text, contribute to enhanced student learning outcomes, higher retention rates, and boost the reputation of the educators providing it? Two surveys on the impact of emojis across selected course sections were conducted to answer the question: a pre-survey and a post-survey involving 175 active participants. The results were analyzed, and it was concluded that integrating emojis in faculty feedback, particularly when grading student work, could potentially enhance student learning outcomes and their overall course experience.
AB - This study explores the potential of integrating emojis, and digital pictographs, into faculty feedback to augment student learning outcomes. This additional layer of expressiveness, encouragement, and involvement adds a personal touch to the often distant and virtual student-educator communications, fostering motivation. The study focuses on the impact of emojis on the learning process within the scrutinized Computer Science (CS) Department. Capitalizing on the capabilities of OpenAI's Large Language Model (LLM) ChatGPT-4, its Application Programming Interface (API), and associated tools and third-party plugins, a system that translates text into corresponding emojis and vice versa has been developed. The proposed application offers direct benefits to educators by simplifying the provision of detailed and extensive feedback to students. The primary research question is: Can the appropriate use of emojis, matched with the sentiment of the feedback text, contribute to enhanced student learning outcomes, higher retention rates, and boost the reputation of the educators providing it? Two surveys on the impact of emojis across selected course sections were conducted to answer the question: a pre-survey and a post-survey involving 175 active participants. The results were analyzed, and it was concluded that integrating emojis in faculty feedback, particularly when grading student work, could potentially enhance student learning outcomes and their overall course experience.
KW - ChatGPT
KW - computer science education
KW - emojis
KW - Feedback Emojifier
KW - text-to-emoji translation
UR - http://www.scopus.com/inward/record.url?scp=85172278717&partnerID=8YFLogxK
U2 - 10.1109/CSCE60160.2023.00173
DO - 10.1109/CSCE60160.2023.00173
M3 - Conference contribution
AN - SCOPUS:85172278717
T3 - Proceedings - 2023 Congress in Computer Science, Computer Engineering, and Applied Computing, CSCE 2023
SP - 1039
EP - 1046
BT - Proceedings - 2023 Congress in Computer Science, Computer Engineering, and Applied Computing, CSCE 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2023 Congress in Computer Science, Computer Engineering, and Applied Computing, CSCE 2023
Y2 - 24 July 2023 through 27 July 2023
ER -