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Quiet interfaces that help students think

Published: 15 October 2006 Publication History

Abstract

As technical as we have become, modern computing has not permeated many important areas of our lives, including mathematics education which still involves pencil and paper. In the present study, twenty high school geometry students varying in ability from low to high participated in a comparative assessment of math problem solving using existing pencil and paper work practice (PP), and three different interfaces: an Anoto-based digital stylus and paper interface (DP), pen tablet interface (PT), and graphical tablet interface (GT). Cognitive Load Theory correctly predicted that as interfaces departed more from familiar work practice (GT > PT > DP), students would experience greater cognitive load such that performance would deteriorate in speed, attentional focus, meta-cognitive control, correctness of problem solutions, and memory. In addition, low-performing students experienced elevated cognitive load, with the more challenging interfaces (GT, PT) disrupting their performance disproportionately more than higher performers. The present results indicate that Cognitive Load Theory provides a coherent and powerful basis for predicting the rank ordering of users' performance by type of interface. In the future, new interfaces for areas like education and mobile computing could benefit from designs that minimize users' load so performance is more adequately supported.

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cover image ACM Conferences
UIST '06: Proceedings of the 19th annual ACM symposium on User interface software and technology
October 2006
354 pages
ISBN:1595933131
DOI:10.1145/1166253
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 15 October 2006

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Author Tags

  1. e-learning and education
  2. handheld and mobile
  3. input and interaction technologies
  4. pen-based interfaces
  5. performance metrics
  6. universal (or disability access)

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Overall Acceptance Rate 561 of 2,567 submissions, 22%

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  • (2023)Extended Control With Hybrid Gaze-BCI for Multi-Robot System Under Hands-Occupied Dual-TaskingIEEE Transactions on Neural Systems and Rehabilitation Engineering10.1109/TNSRE.2023.323497131(829-840)Online publication date: 2023
  • (2022)Reducing the Cognitive Load of Playing a Digital Tabletop Game with a Multimodal InterfaceProceedings of the 2022 CHI Conference on Human Factors in Computing Systems10.1145/3491102.3502062(1-13)Online publication date: 29-Apr-2022
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  • (2020)Digital Pen Features Predict Task Difficulty and User Performance of Cognitive TestsProceedings of the 28th ACM Conference on User Modeling, Adaptation and Personalization10.1145/3340631.3394839(23-32)Online publication date: 7-Jul-2020
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  • (2018)Dynamic Handwriting Signal Features Predict Domain ExpertiseACM Transactions on Interactive Intelligent Systems10.1145/32133098:3(1-21)Online publication date: 24-Jul-2018
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