Development of a Basic Chemistry Conversational Corpus
Maurice HT Ling1*, Syameer Musttakim1 and Poh Nguk Lau1,2
1School of Applied Sciences, Temasek Polytechnic, Singapore
2Learning Academy, Temasek Polytechnic, Singapore
*Corresponding Author: Maurice HT Ling, School of Applied Sciences, Temasek
Polytechnic, Singapore.
Received:
December 31, 2022; Published: January 13, 2023
Abstract
Chatbot technology can be an important tool and supplement to education, leading to explorations in this area. Corpus-based chatbot building has a relatively low entry barrier as it only requires a relevant corpus to train a chatbot engine. The corpus is a set of human-readable questions and answers and may be an amalgamation of existing corpora. However, a suitable chemistry-based chatbot corpus catering for a freshman general chemistry course addressing inorganic and physical chemistry has not been developed. In this study, we present a basic chemistry conversational corpus consisting of 998 pairs of questions and answers, focused on a freshman general chemistry course addressing inorganic and physical chemistry. Ten human raters evaluated the responses of a chatbot trained on the corpus and suggests that the corpus resulted in better response than random (t = 17.4, p-value = 1.86E-53). However, only 20 of the 50 test questions show better responses compared to random (difference in mean score ≥ 1.9, paired t-test p-value ≤ 0.0324), suggesting that the corpus provides better responses to certain questions rather than overall better responses, with questions related to definitions and computational procedures answered more accurately. Hence, this provides a baseline for future corpora development.
Keywords: Chemistry; Conversational Corpus; ChatterBot
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