Stockdill, Aaron, Stapleton, Gem, Raggi, Daniel, Jamnik, Mateja, GarciaGarcia, Grecia and Cheng, Peter C H (2022) Examining experts’ recommendations of representational systems for problem solving. 2022 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC), Rome, Italy, 12 Sep 2022 - 16 Sep 2022. Published in: 2022 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC). 1-6. IEEE ISSN 1943-6106 ISBN 9781665442145

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Abstract

Pólya and others recognised that an appropriate representation of a problem is key for enabling us to solve it. But choosing the right representation is a problem that novice problem solvers find difficult, so must turn to experts for guidance. In this paper, we present a study that examines how human experts recommend representations. We asked high school mathematics teachers to order representational systems based on their suitability generally, and with respect to a student profile. We found the teachers updated their recommendations based on the problem and student profile, but were inconsistent with each other. This inconsistency highlights a need for more training and support in representational system selection.

Item Type:	Conference Proceedings
Additional Information:	© 20XX IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works
Schools and Departments:	School of Engineering and Informatics > Informatics
SWORD Depositor:	Mx Elements Account
Depositing User:	Mx Elements Account
Date Deposited:	14 Nov 2022 11:25
Last Modified:	15 Nov 2022 09:53
URI:	http://sro.sussex.ac.uk/id/eprint/109055

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