# Implementing a Chatbot Solution for Learning Management System

arXiv: https://arxiv.org/abs/2206.13187 · HTML: https://mlsanity.com/paper/2206.13187/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 4 of its 63 references that are in the map.
- First posted on arXiv 27 Jun 2022.

## Builds on (most cited first, 4 of 4)

- [Recipes for building an open-domain chatbot](https://mlsanity.com/paper/2004.13637/) (2020)
- [Towards a Human-like Open-Domain Chatbot](https://mlsanity.com/paper/2001.09977/) (2020)
- [The Ubuntu Dialogue Corpus: A Large Dataset for Research in Unstructured Multi-Turn Dialogue Systems](https://mlsanity.com/paper/1506.08909/) (2015)
- [A Literature Survey of Recent Advances in Chatbots](https://mlsanity.com/paper/2201.06657/) (2022)

## Abstract (arXiv)

Innovation is a key component in trying new solutions for the students to learn efficiently and in ways that correspond to their own experience, where chatbots are one of these new solutions. One of the main problem that chatbots face today is to mimic human language, where they try to find the best answer to an input, which is not how a human conversation usually works, rather taking into account the previous messages and building onto them. Extreme programming methodology was chosen to use integrate ChatterBot, Pyside2, web scraping and Tampermonkey into Blackboard as a test case. Problems occurred with the bot and more training was needed for the bot to work perfectly, but the integration and web scraping worked, giving us a chatbot that was able to talk with. We showed the plausibility of integrating an AI bot in an educational setting.