research-article

Computational Model of the Transition from Novice to Expert Interaction Techniques

Authors:

Mehdi Khamassi,

Benoît GirardAuthors Info & Claims

ACM Transactions on Computer-Human Interaction, Volume 30, Issue 5

Article No.: 66, Pages 1 - 33

https://doi.org/10.1145/3505557

Published: 23 September 2023 Publication History

Abstract

Despite the benefits of expert interaction techniques, many users do not learn them and continue to use novice ones. This article aims at better understanding if, when and how users decide to learn and ultimately adopt expert interaction techniques. This dynamic learning process is a complex skill-acquisition and decision-making problem. We first present and compare three generic benchmark models, inspired by the neuroscience literature, to explain and predict the learning process for shortcut adoption. Results show that they do not account for the complexity of users’ behavior. We then introduce a dedicated model, Transition, combining five cognitive mechanisms: implicit and explicit learning, decay, planning and perseveration. Results show that our model outperforms the three benchmark models both in terms of model fitting and model simulation. Finally, a post-analysis shows that each of the five mechanisms contribute to goodness-of-fit, but the role of perseveration is unclear regarding model simulation.

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Index Terms

Computational Model of the Transition from Novice to Expert Interaction Techniques
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. HCI theory, concepts and models

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cover image ACM Transactions on Computer-Human Interaction

ACM Transactions on Computer-Human Interaction Volume 30, Issue 5

October 2023

593 pages

ISSN:1073-0516

EISSN:1557-7325

DOI:10.1145/3623487

Editors:
Kristina Höök
KTH Royal Institute of Technology, Sweden
,
Kasper Hornbæk
University of Copenhagen, Denmark

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Publication History

Published: 23 September 2023

Online AM: 24 February 2022

Accepted: 09 December 2021

Revised: 06 December 2021

Received: 29 June 2021

Published in TOCHI Volume 30, Issue 5

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Qian WGao CSathya ASuzuki RNakagaki K(2024)SHAPE-IT: Exploring Text-to-Shape-Display for Generative Shape-Changing Behaviors with LLMsProceedings of the 37th Annual ACM Symposium on User Interface Software and Technology10.1145/3654777.3676348(1-29)Online publication date: 13-Oct-2024
https://dl.acm.org/doi/10.1145/3654777.3676348
Cunha JRenguette CSingh NStella LMcmahon MJin HKleinberger R(2024)Ellie Talks About the Weather: Toward Evaluating the Expressive and Enrichment Potential of a Tablet-Based Speech Board in a Single Goffin’s CockatooProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3643654(1-16)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3643654
Khamassi MMirolli MWallraven C(2023)Editorial: Neurorobotics explores the human sensesFrontiers in Neurorobotics10.3389/fnbot.2023.121487117Online publication date: 22-May-2023
https://doi.org/10.3389/fnbot.2023.1214871

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