CHATBOT AS ARTIFICIAL INTELLIGENCE LEARNING IN KNOWLEDGE MANAGEMENT

Ambar Sri Lestari




Abstract

This research aims to create a chatbot as Artificial Intelligence learning in knowledge management.  The participants are teachers or lecturers engaging in the virtual education academic. Using machine learning technology on the https://m.chatboat.university platform, the result chatbot product development includes several steps, including: 1) using chatbot templates, 2) creating a self-contained chatbot. 3) modify the background and short description; 4) add chatbot content (image, text, video); 5) include quizzes and fun facts; and 6) create the chatbot design with thematic discussion. The development of the chatbot to provide students or users with a future learning that includes innovation, knowledge, learning community as displayed on the chatboat. This study has implications for learning innovation based on computational chatbots in interactive conversations as a transformation to support education in the 5.0 era.

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References

Chandra, Y. W., & Suyanto, S. (2019). Indonesian chatbot of University admission using a question answering system based on Sequence-to-Sequence model. Procedia Computer Science, 157, 367–374. https://doi.org/10.1016/j.procs. 2019.08.179

De Carolis, B., De Gemmis, M., & Lops, P. (2015). A multimodal framework for recognizing emotional feedback in conversational recommender systems. ACM International Conference Proceeding series, 2015-September, 11–18.

Dede, C. (2007). Reinventing the role of information and communications technologies in education. Yearbook of the National Society for the Study of Education, 106(2), 11–38. https://doi.org/10.1111/j.1744-7984.2007.00113.x

Eisman, E. M., Navarro, M., & Castro, J. L. (2016). A multiagent conversational system with heterogeneous data sources access. Expert Systems with Applications, 53, 172–191.

Goh, O. S., Fung, C. C., & Depickere, A. (2008). Domain knowledge query conversation bots in instant messaging (IM). Knowledge-Based Systems, 21(7), 681–691. https://doi.org/10.1016/j.knosys.2008.03.055

Graesser, A. C., Lu, S., Jackson, G. T., Mitchell, H. H., Ventura, M., Olney, A., & Louwerse, M. M. (2004). Autotutor: A tutor with dialogue in natural language. Behavior Research Methods, Instruments, & Computers, 36(2), 180–192. https://doi. org/10.3758/BF03195563

Grewal, D., Roggeveen, A. L., & Nordfält, J. (2017). The future of retailing. Journal of Retailing, 93(1), 1–6. Jurafsky, D., & Martin, J. H. (2020). Speech and language processing (3rd ed. Draft). Upper Saddle River, NJ: Prentice Hall.

Iswandi, I., Suwardi, I., & Maulidevi, N. (2013). Penelitian Awal: Otomatisasi Interpretasi Data Berbasis Natural Language Processing. Jurnal Sistem Informasi, (5) 622-628.

Kim, Eunji., Ga-Young Jang & Soo-Hyun Kim (2022): How to Apply Artificial Intelligence for Social Innovations, Applied Artificial Intelligence, DOI: 10.1080/08839514.2022.2031819

Lotfi, Ismail & Abdelhamid El Bouhadi (2021): Artificial Intelligence Methods: Toward a New Decision Making Tool, Applied Artificial Intelligence, DOI: 10.1080/08839514.2021.1992141

Pantano, E., & Pizzi, G. (2020). Forecasting artificial intelligence on online customer assistance: Evidence from chatbot patents analysis. Journal of Retailing and Consumer Services, 55, 102096.

Suartama, I., Setyosari, P., Sulthoni, S., & Ulfa, S. (2020). Development of ubiquitous learning environment based on moodle learning management system.

Schlesinger, A., O’Hara, K. P., & Taylor, A. S. (2018, April). Let’s talk about race: Identity, chatbots, and AI. Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (pp. 1–14).

Vaccaro, K., Agarwalla, T., Shivakumar, S., & Kumar, R. (2018). Designing the future of personal fashion. Conference on human factors in Computing systems - proceedings, 2018-April, 1–11.

Weiser, M. (1999). The computer for the 21st century. ACM SIGMOBILE Mobile Computing and Communications Review, 3(3), 3–11. https://doi.org/10.1145/329124.329126

Wong, B. T. (2018). Success in mobile and ubiquitous learning: Indicators of effectiveness. BRAIN. Broad Research in Artificial Intelligence and Neuroscience, 9, 55–63. https://lumenpublishing.com/journals/index.php/brain/article/ view/2114

Xu, A., Liu, Z., Guo, Y., Sinha, V., & Akkiraju, R. (2017, May). A new chatbot for customer service on social media. Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems (pp. 3506–3510).




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