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Natural Language Communication with a Teachable Agent

Rachel Love, Edith Law, Philip R. Cohen, Dana Kulić

TL;DR

This work investigates the effect of teaching modality when interacting with a virtual agent, via the web-based teaching platform, the Curiosity Notebook, and indicates that teaching via paraphrasing and text input has a positive effect on learning outcomes for the material covered, and also on aspects of affective engagement.

Abstract

Conversational teachable agents offer a promising platform to support learning, both in the classroom and in remote settings. In this context, the agent takes the role of the novice, while the student takes on the role of teacher. This framing is significant for its ability to elicit the Protégé effect in the student-teacher, a pedagogical phenomenon known to increase engagement in the teaching task, and also improve cognitive outcomes. In prior work, teachable agents often take a passive role in the learning interaction, and there are few studies in which the agent and student engage in natural language dialogue during the teaching task. This work investigates the effect of teaching modality when interacting with a virtual agent, via the web-based teaching platform, the Curiosity Notebook. A method of teaching the agent by selecting sentences from source material is compared to a method paraphrasing the source material and typing text input to teach. A user study has been conducted to measure the effect teaching modality on the learning outcomes and engagement of the participants. The results indicate that teaching via paraphrasing and text input has a positive effect on learning outcomes for the material covered, and also on aspects of affective engagement. Furthermore, increased paraphrasing effort, as measured by the similarity between the source material and the material the teacher conveyed to the robot, improves learning outcomes for participants.

Natural Language Communication with a Teachable Agent

TL;DR

This work investigates the effect of teaching modality when interacting with a virtual agent, via the web-based teaching platform, the Curiosity Notebook, and indicates that teaching via paraphrasing and text input has a positive effect on learning outcomes for the material covered, and also on aspects of affective engagement.

Abstract

Conversational teachable agents offer a promising platform to support learning, both in the classroom and in remote settings. In this context, the agent takes the role of the novice, while the student takes on the role of teacher. This framing is significant for its ability to elicit the Protégé effect in the student-teacher, a pedagogical phenomenon known to increase engagement in the teaching task, and also improve cognitive outcomes. In prior work, teachable agents often take a passive role in the learning interaction, and there are few studies in which the agent and student engage in natural language dialogue during the teaching task. This work investigates the effect of teaching modality when interacting with a virtual agent, via the web-based teaching platform, the Curiosity Notebook. A method of teaching the agent by selecting sentences from source material is compared to a method paraphrasing the source material and typing text input to teach. A user study has been conducted to measure the effect teaching modality on the learning outcomes and engagement of the participants. The results indicate that teaching via paraphrasing and text input has a positive effect on learning outcomes for the material covered, and also on aspects of affective engagement. Furthermore, increased paraphrasing effort, as measured by the similarity between the source material and the material the teacher conveyed to the robot, improves learning outcomes for participants.
Paper Structure (30 sections, 6 figures, 4 tables)

This paper contains 30 sections, 6 figures, 4 tables.

Table of Contents

  1. Introduction
  2. Related Work
  3. Educational Teachable Agents
  4. Teaching via Natural Language
  5. Curiosity Notebook
  6. Student Engagement and Learning Outcomes
  7. Summary
  8. Methodology
  9. Curiosity Notebook Interface
  10. Teaching via Sentence Selection
  11. Teaching via Text Input
  12. Mixed-Initiative Interaction
  13. Agent Utterances
  14. Teaching Modality User Study
  15. Participants
  16. ...and 15 more sections

Figures (6)

  • Figure 1: Illustration to show the roles in an interaction with a teachable agent. The user takes on the roles of teaching for their own learning. Images via Vecteezy (https://www.vecteezy.com/)
  • Figure 2: The Curiosity Notebook interface, in the sentence selection condition. The user has clicked on the highlighted sentence, and it is available to teach
  • Figure 3: A sample of initiative modes, each begins with the agent thanking the user for their teaching. User initiated action (top), agent initiated action and user rock selection (middle), agent initiated action and rock selection (bottom)
  • Figure 4: Sample utterances from each agent asking for information from the user, for Alpha (top) and Gamma (bottom)
  • Figure 5: Participant responses to survey questions comparing Alpha and Gamma on preference in teaching, helpfulness for their learning, and which they would like to interact with in future. Results are given as a percentage of participants
  • ...and 1 more figures