Done in 60 minutes! Best practices, crowdsourcing, co-creation, and design principals of educational chatbots

Henderson, James; Pears, Matthew; Konstantinidis, Stathis

Abstract

Unlike banking, hospitality, and travel, the education sector is lacking in prolific and effective uses of chatbots for learning. Expert- and research- driven recommendations, online tools, and workshops for contemporary approaches are slim. This workshop is based on the experiences and knowledge gained from several teams in developing chatbots within the scope of the Erasmus+ project- Chatbots Enhance Personalised European Healthcare Curricula (CEPEH). The aim is to demonstrate how novel techniques and frameworks have been blended for efficient co-creation with stakeholders (learners, educators, learning technologists) for all healthcare topic which meet the design criteria. The project consortium has developed high quality chatbots following an adaptive ASPIRE framework as a participatory approach to creating online reusable learning resources. The ASPIRE framework emphasises inclusion of learners and scaffolds significant development stages; Aims, Storyboarding, Population, Implementation, Release and Evaluation.

Specifically, the workshop will provide a short overview of the educational chatbots, a few technical notions such as how entities, intents, and actions are implemented. Participants will be informed of the advantages of co-creation with stakeholders through demonstration of design processes for several artificial intelligence natural language conversational agents.

The focus will also be on a recently created chatbot design tool which participants will interact with. This tool is evidence for the benefits in co-creation through crowd-based data collection. It will showcase how participants can use and transform such methods and techniques discussed for their own conversational agent creation. Hands-on engagement will be through the participatory design of a chatbot using storyboarding and a recently developed online chatbot design application that all participants will use in real-time to define a topic, collect data, and execute the final chatbot for demonstration.

Key takeaway points from the workshop include: 1) benefits and techniques to increase collaboration between stakeholders, 2) understanding the role of the chatbot in healthcare education and training, 3) improving chatbot accuracy and efficacy for healthcare topics, and 4) methods for reducing time and resources for chatbot implementation.

Acknowledgement
This work is supported by the ERASMUS+ Strategic Partnership in Higher Education “Chatbot Enhance Personalise European Healthcare Curricula (CEPEH)” (www.cepeh.eu) (2019-1-UK01- KA203-062091) project of the European Union.


Bibliography
Pears, M., Henderson, J., Tsoupouroglou, I., Bamidis, P. D., Schiza, E., Pattichis, C. S., ... & Konstantinidis, S. T. (2022, March). Prototype for Crowd-based Co-creation of Artificial Intelligence Natural Language Conversational Agents. In 2022 IEEE Global Engineering Education Conference (EDUCON) (pp. 2013-2021). IEEE. https://doi.org/10.1109/EDUCON52537.2022.9766698

Pears, M., Henderson, J., & Konstantinidis, S. T. 2021. Repurposing Case-Based Learning to a Conversational Agent for Healthcare Cybersecurity. Proc. of MIE 202, pp. 1066-1070. IOS Press. https://doi.org/10.3233/SHTI210348.

Pears, M., Henderson, J., et al., 2021. Co-Creation Of Chatbots As An Educational Resource-Training The Trainers Workshop. In INTED2021 Proceedings, pp. 7808-7815. IATED. https://doi.org/10.21125/inted.2021.1570.

Citation

Henderson, J., Pears, M., & Konstantinidis, S. (2022, September). Done in 60 minutes! Best practices, crowdsourcing, co-creation, and design principals of educational chatbots. Presented at ALT Annual Conference 2022, Manchester, UK

• Presentation Conference Type: Other
• Conference Name: ALT Annual Conference 2022
• Start Date: Sep 6, 2022
• End Date: Sep 8, 2022
• Deposit Date: Nov 4, 2022
• Keywords: Co-creation, Chatbots, Crowdsourcing, Education, Healthcare
• Public URL: https://nottingham-repository.worktribe.com/output/13179986
• Related Public URLs: https://altc.alt.ac.uk/2022/