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Markov Transition Matrix Analysis of Mathematical Expression Input Models
Computer software interfaces for mathematics collaboration and problem solving rely, as all interfaces do, on user identification and recognition of symbols (via icons and other contextual widgets). In this paper we examine the results of a short study which examined users interacting with mathemati...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7340900/ http://dx.doi.org/10.1007/978-3-030-52200-1_45 |
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author | Quinby, Francis Kim, Seyeon Kang, Sohee Pollanen, Marco Reynolds, Michael G. Burr, Wesley S. |
author_facet | Quinby, Francis Kim, Seyeon Kang, Sohee Pollanen, Marco Reynolds, Michael G. Burr, Wesley S. |
author_sort | Quinby, Francis |
collection | PubMed |
description | Computer software interfaces for mathematics collaboration and problem solving rely, as all interfaces do, on user identification and recognition of symbols (via icons and other contextual widgets). In this paper we examine the results of a short study which examined users interacting with mathematics software (Mathematics Classroom Communicator, MC[Formula: see text]) designed for education, real-time communication and collaboration. Videos were recorded of 14 users working through seven comprehensive problems in the MC[Formula: see text] interface. Extensive second-by-second coding was completed of the user’s actions and status throughout their work, and a set of transition matrices were tabulated, estimating transition probabilities between symbols, operators and other aspects of mathematical expressions. We discuss the results of these matrices, and their implications in the translation of abstract mathematical concepts into software interfaces, and further conclude with a brief discussion of suggestions for mathematical software interface design. This study also has applications in mathematical software usability and accessibility. |
format | Online Article Text |
id | pubmed-7340900 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
record_format | MEDLINE/PubMed |
spelling | pubmed-73409002020-07-08 Markov Transition Matrix Analysis of Mathematical Expression Input Models Quinby, Francis Kim, Seyeon Kang, Sohee Pollanen, Marco Reynolds, Michael G. Burr, Wesley S. Mathematical Software – ICMS 2020 Article Computer software interfaces for mathematics collaboration and problem solving rely, as all interfaces do, on user identification and recognition of symbols (via icons and other contextual widgets). In this paper we examine the results of a short study which examined users interacting with mathematics software (Mathematics Classroom Communicator, MC[Formula: see text]) designed for education, real-time communication and collaboration. Videos were recorded of 14 users working through seven comprehensive problems in the MC[Formula: see text] interface. Extensive second-by-second coding was completed of the user’s actions and status throughout their work, and a set of transition matrices were tabulated, estimating transition probabilities between symbols, operators and other aspects of mathematical expressions. We discuss the results of these matrices, and their implications in the translation of abstract mathematical concepts into software interfaces, and further conclude with a brief discussion of suggestions for mathematical software interface design. This study also has applications in mathematical software usability and accessibility. 2020-06-06 /pmc/articles/PMC7340900/ http://dx.doi.org/10.1007/978-3-030-52200-1_45 Text en © Springer Nature Switzerland AG 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Article Quinby, Francis Kim, Seyeon Kang, Sohee Pollanen, Marco Reynolds, Michael G. Burr, Wesley S. Markov Transition Matrix Analysis of Mathematical Expression Input Models |
title | Markov Transition Matrix Analysis of Mathematical Expression Input Models |
title_full | Markov Transition Matrix Analysis of Mathematical Expression Input Models |
title_fullStr | Markov Transition Matrix Analysis of Mathematical Expression Input Models |
title_full_unstemmed | Markov Transition Matrix Analysis of Mathematical Expression Input Models |
title_short | Markov Transition Matrix Analysis of Mathematical Expression Input Models |
title_sort | markov transition matrix analysis of mathematical expression input models |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7340900/ http://dx.doi.org/10.1007/978-3-030-52200-1_45 |
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