Using Qualitative Data from Targeted Interviews to Inform Rapid AIED Development

Jaclyn Ocumpaugh, Stephen Hutt, Juliana Ma Alexandra L. Andres, Ryan S. Baker, Gautam Biswas, Nigel Bosch, Luc Paquette, Anabil Munshi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper examines how interviews with students—at critical moments of the learning process—may be leveraged to improve the design of educational software. Specifically, we discuss iterative work to improve the design of a pedagogical agent in the Betty’s Brain learning environment, Mr. Davis. Students interacted with the pedagogical agent in Betty’s Brain during two separate studies, two months apart. During study one, qualitative interviews were prompted by student actions within the system and theoretically aligned sequences of educationally relevant affective states (as detected by previously validated models). Facilitaed by an app called the Quick Red Fox (QRF), these in situ interviews were then used to identify ways to rapidly improve Mr. Davis’ design, investigated in study two. Results indicate that changes designed to make Mr. Davis more empathetic correlate with improved learning outcomes. We also discuss the potential for rapidly collected qualitative data in future developments.

Original languageEnglish (US)
Title of host publication29th International Conference on Computers in Education Conference, ICCE 2021 - Proceedings
EditorsMaria Mercedes T. Rodrigo, Sridhar Iyer, Antonija Mitrovic, Hercy N. H. Cheng, Dan Kohen-Vacs, Camillia Matuk, Agnieszka Palalas, Ramkumar Rajenran, Kazuhisa Seta, Jingyun Wang
PublisherAsia-Pacific Society for Computers in Education
Pages69-74
Number of pages6
ISBN (Electronic)9789869721479
StatePublished - Nov 22 2021
Event29th International Conference on Computers in Education Conference, ICCE 2021 - Virtual, Online
Duration: Nov 22 2021Nov 26 2021

Publication series

Name29th International Conference on Computers in Education Conference, ICCE 2021 - Proceedings
Volume1

Conference

Conference29th International Conference on Computers in Education Conference, ICCE 2021
CityVirtual, Online
Period11/22/2111/26/21

Keywords

  • Affective computing
  • data-driven design
  • learning by teaching
  • pedagogical agents

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Education

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