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Support How-To Instruction Following via Conversational Agent

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Collaboration Technologies and Social Computing (CollabTech 2023)

Abstract

People indispensably use instructions shared by one another to work on unfamiliar tasks in daily or professional life. However, personally shared tutorials are often based on personal experiences and represent a collective overview of past encounters, which can be misaligned with the specific work context during the re-enacting time. Drawing inspiration from the effective dynamics observed in conversational instruction-giving and -following between experts and novices, we propose a chatbot system that delivers archived how-to tutorials by providing necessary information in a just-in-time manner, tailored to the needs of the instruction-follower. Our aim is to transform unaided instruction reading activities into conversational instruction-following experiences. We implemented a chatbot system and evaluated it through a between subject study. The results demonstrate a promise of leveraging human-chatbot interaction to support actionable instruction-following.

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Notes

  1. 1.

    Sufficient resource is available sharing platforms, such as wikiHow, eHoweHow.

  2. 2.

    https://manychat.com/.

  3. 3.

    https://flask.palletsprojects.com/en/2.0.x/.

  4. 4.

    https://www.python.org/.

  5. 5.

    https://www.teamviewer.com/en-us/.

  6. 6.

    11 males, 14 females, and 1 unknown.

  7. 7.

    Researchers addressed logistic questions while avoiding affecting users’ behaviors.

  8. 8.

    Cronbach’s alpha reported earlier indicates the reliability to derive an average score.

  9. 9.

    Some factors that can cause failure include skipping steps, missing information, execution errors, and other related issues.

  10. 10.

    LMER(actionability_score \(\sim \) assistance_level \(+\) computer_skill_level \(+\) (1 \(\Vert \) uuid)).

  11. 11.

    LMER(situational_awareness \(\sim \) conversational_instruction_following_assistance_level + computer_skill_level + \(1 \Vert uuid\) ), we exclude interaction variable between instruction following condition and computer skill level due to loss of freedom.

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Correspondence to Qingxiaoyang Zhu .

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Zhu, Q., Lee, YC., Wang, HC. (2023). Support How-To Instruction Following via Conversational Agent. In: Takada, H., Marutschke, D.M., Alvarez, C., Inoue, T., Hayashi, Y., Hernandez-Leo, D. (eds) Collaboration Technologies and Social Computing. CollabTech 2023. Lecture Notes in Computer Science, vol 14199. Springer, Cham. https://doi.org/10.1007/978-3-031-42141-9_19

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  • DOI: https://doi.org/10.1007/978-3-031-42141-9_19

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-42140-2

  • Online ISBN: 978-3-031-42141-9

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