Maurice HT Ling¹*, Syameer Musttakim¹ and Poh Nguk Lau^1,2

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

References

1. Adamopoulou E and Moussiades L. “An Overview of Chatbot Technology”. AIAI 2020: Artificial Intelligence Applications and Innovations, eds Maglogiannis I, Iliadis L, Pimenidis E (Springer International Publishing, Cham) (2020): 373-383.
2. Turing AM. “Computing Machinery and Intelligence”. Mind LIX 236 (1950): 433-460.
3. Luo B., et al. “A Critical Review of State‐of‐the‐Art Chatbot Designs and Applications”. WIREs Data Mining and Knowledge Discovery 12 (2022): e1434.
4. Landim ARDB. “Chatbot Design Approaches for Fashion E-commerce: An Interdisciplinary Review”. International Journal of Fashion Design, Technology and Education2 (2022): 200-210.
5. Tjiptomongsoguno ARW. “Medical Chatbot Techniques: A Review”. Software Engineering Perspectives in Intelligent Systems, Advances in Intelligent Systems and Computing., eds Silhavy R, Silhavy P and Prokopova Z. “(Springer International Publishing, Cham) 1294 (2020): 346-356.
6. Okonkwo CW and Ade-Ibijola A. “Chatbots Applications in Education: A Systematic Review”. Computers and Education: Artificial Intelligence 2 (2021): 100033.
7. Yang S and Evans C. “Opportunities and Challenges in Using AI Chatbots in Higher Education”. Proceedings of the 2019 3^rd International Conference on Education and E-Learning (ACM, Barcelona Spain) (2019): 79-83.
8. Hamam D. “The New Teacher Assistant: A Review of Chatbots’ Use in Higher Education”. HCI International 2021 - Posters, Communications in Computer and Information Science., eds Stephanidis C, Antona M, Ntoa S (Springer International Publishing, Cham) 1421 (2021): 59-63.
9. Akinwalere SN and Ivanov V. “Artificial Intelligence in Higher Education: Challenges and Opportunities”. Border Crossing1 (2022): 1-15.
10. Amiri P and Karahanna E. “Chatbot Use Cases in the Covid-19 Public Health Response. Journal of the American Medical Informatics Association5 (2022): 1000-1010.
11. Zhu Y., et al. “It Is Me, Chatbot: Working to Address the COVID-19 Outbreak-Related Mental Health Issues in China. User Experience, Satisfaction, and Influencing Factors”. International Journal of Human-Computer Interaction12 (2022): 1182-1194.
12. Sweidan SZ., et al. “SIAAA‐C: A Student Interactive Assistant Android Application with Chatbot During COVID‐19 Pandemic”. Computer Applications in Engineering Education6 (2021): 1718–1742.
13. Fonna MR and Widyantoro DH. “Tutorial System in Learning Activities Through Machine Learning-Based Chatbot Applications in Pharmacology Education”. 2021 8^th International Conference on Advanced Informatics: Concepts, Theory and Applications (ICAICTA) (IEEE, Bandung, Indonesia) (2019): 1-6.
14. Kovacek D and Chow JCL. “An AI-Assisted Chatbot for Radiation Safety Education in Radiotherapy”. IOP SciNotes3 (2021): 034002.
15. Atmosukarto I., et al. “Enhancing Adaptive Online Chemistry Course with AI-Chatbot”. 2021 IEEE International Conference on Engineering, Technology and Education (TALE) (2021): 838-843.
16. Korsakova E., et al. “Chemist Bot as a Helpful Personal Online Training Tool for the Final Chemistry Examination”. Journal of Chemical Education2 (2022): 1110-1117.
17. Mahroof A., et al. “An AI based Chatbot to Self-Learn and Self-Assess Performance in Ordinary Level Chemistry. 2020 2^nd International Conference on Advancements in Computing (ICAC) (IEEE, Malabe, Sri Lanka) (2020): 216-221.
18. Shawar BAA. “A Corpus Based Approach to Generalise a Chatbot System”. Doctor of Philosophy (University of Leeds, School of Computing) (2005).
19. Shawar BA and Atwell ES. “Using Corpora in Machine-Learning Chatbot Systems”. International Journal of Corpus Linguistics4 (2005): 489-516.
20. Rikters M., et al. “Designing the Business Conversation Corpus”. Proceedings of the 6^th Workshop on Asian Translation (Association for Computational Linguistics, Hong Kong, China), 54-61.
21. Shawar BA and Atwell E. “Using the Corpus of Spoken Afrikaans to Generate an Afrikaans Chatbot”. Southern African Linguistics and Applied Language Studies4 (2003): 283-294.
22. Shawar BA and Atwell E. “Arabic Question-Answering via Instance Based Learning from an FAQ Corpus”. Proceedings of the CL 2009 International Conference on Corpus Linguistics”. UCREL 386 (2016): 1-12.
23. Sim KS and Ling MH. “Installation and Documentation Evaluation of Recent (01 January 2020 to 15 February 2021) Chatbot Engines from Python Package Index (PyPI)”. Acta Scientific Computer Sciences8 (2011): 38-43.
24. Shawar BA and Atwell E. “Different measurements metrics to evaluate a chatbot system”. (Association for Computational Linguistics) (2007): 89-96.
25. Kumar S., et al. “Defining and Measuring Academic Performance of Hei Students - A Critical Review”. Turkish Journal of Computer and Mathematics Education6 (2021): 3091-3105.
26. Alyahyan E and Düştegör D. “Predicting Academic Success in Higher Education: Literature Review and Best Practices”. International Journal of Educational Technology in Higher Education1 (2020): 3.
27. Kim J., et al. “Two-Step Training and Mixed Encoding-Decoding for Implementing a Generative Chatbot with a Small Dialogue Corpus. Proceedings of the Workshop on Intelligent Interactive Systems and Language Generation (2IS and NLG) (Association for Computational Linguistics, Tilburg, the Netherlands) (2018): 31-35.
28. Kowsher Md., et al. “Doly: Bengali Chatbot for Bengali Education”. 2019 1^st International Conference on Advances in Science, Engineering and Robotics Technology (ICASERT) (IEEE, Dhaka, Bangladesh) (2019): 19.
29. Blanc C., et al. “FlauBERT vs. CamemBERT: Understanding Patient’s Answers by a French Medical Chatbot”. Artificial Intelligence in Medicine 127 (2022): 102264.
30. Shawar BAA and Atwell E. “Automatic Extraction of Chatbot Training Data from Natural Dialogue Corpora” (2016): 29-38.
31. Kapočiūtė-Dzikienė J. “A Domain-Specific Generative Chatbot Trained from Little Data”. Applied Sciences7 (2020): 2221.
32. Callejas-Rodríguez Á., et al. “From Dialogue Corpora to Dialogue Systems: Generating a Chatbot with Teenager Personality for Preventing Cyber-Pedophilia. Text, Speech, and Dialogue, Lecture Notes in Computer Science., eds Sojka P, Horák A, Kopeček I, Pala K (Springer International Publishing, Cham) 9924 (2016): 531-539.

Citation

Citation: Maurice HT Ling., et al. “Development of a Basic Chemistry Conversational Corpus". Acta Scientific Nutritional Health 7.2 (2023): 48-54.

Copyright

Copyright: © 2023 Maurice HT Ling., et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.