How Influential Are Mental Models on Interaction Performance? Exploring the Gap between Users’ and Designers’ Mental Models through a New Quantitative Method
The objective of this study is to investigate the effect of the gap between two different mental models on interaction performance through a quantitative way. To achieve that, an index called mental model similarity and a new method called path diagram to elicit mental models were introduced. There...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Wiley
2017-01-01
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| Series: | Advances in Human-Computer Interaction |
| Online Access: | http://dx.doi.org/10.1155/2017/3683546 |
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| _version_ | 1832559792769466368 |
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| author | Bingjun Xie Jia Zhou Huilin Wang |
| author_facet | Bingjun Xie Jia Zhou Huilin Wang |
| author_sort | Bingjun Xie |
| collection | DOAJ |
| description | The objective of this study is to investigate the effect of the gap between two different mental models on interaction performance through a quantitative way. To achieve that, an index called mental model similarity and a new method called path diagram to elicit mental models were introduced. There are two kinds of similarity: directionless similarity calculated from card sorting and directional similarity calculated from path diagram. An experiment was designed to test their influence. A total of 32 college students participated and their performance was recorded. Through mathematical analysis of the results, three findings were derived. Frist, the more complex the information structures, the lower the directional similarity. Second, directional similarity (rather than directionless similarity) had significant influence on user performance, indicating that it is more effective in eliciting mental models using path diagram than card sorting. Third, the relationship between information structures and user performance was partially mediated by directional similarity. Our findings provide practitioners with a new perspective of bridging the gap between users’ and designers’ mental models. |
| format | Article |
| id | doaj-art-d255c3cb22ea448bbe50015ad08a5cfc |
| institution | Kabale University |
| issn | 1687-5893 1687-5907 |
| language | English |
| publishDate | 2017-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Human-Computer Interaction |
| spelling | doaj-art-d255c3cb22ea448bbe50015ad08a5cfc2025-02-03T01:29:14ZengWileyAdvances in Human-Computer Interaction1687-58931687-59072017-01-01201710.1155/2017/36835463683546How Influential Are Mental Models on Interaction Performance? Exploring the Gap between Users’ and Designers’ Mental Models through a New Quantitative MethodBingjun Xie0Jia Zhou1Huilin Wang2Department of Industrial Engineering, Chongqing University, Chongqing 400044, ChinaDepartment of Industrial Engineering, Chongqing University, Chongqing 400044, ChinaDepartment of Industrial Engineering, Chongqing University, Chongqing 400044, ChinaThe objective of this study is to investigate the effect of the gap between two different mental models on interaction performance through a quantitative way. To achieve that, an index called mental model similarity and a new method called path diagram to elicit mental models were introduced. There are two kinds of similarity: directionless similarity calculated from card sorting and directional similarity calculated from path diagram. An experiment was designed to test their influence. A total of 32 college students participated and their performance was recorded. Through mathematical analysis of the results, three findings were derived. Frist, the more complex the information structures, the lower the directional similarity. Second, directional similarity (rather than directionless similarity) had significant influence on user performance, indicating that it is more effective in eliciting mental models using path diagram than card sorting. Third, the relationship between information structures and user performance was partially mediated by directional similarity. Our findings provide practitioners with a new perspective of bridging the gap between users’ and designers’ mental models.http://dx.doi.org/10.1155/2017/3683546 |
| spellingShingle | Bingjun Xie Jia Zhou Huilin Wang How Influential Are Mental Models on Interaction Performance? Exploring the Gap between Users’ and Designers’ Mental Models through a New Quantitative Method Advances in Human-Computer Interaction |
| title | How Influential Are Mental Models on Interaction Performance? Exploring the Gap between Users’ and Designers’ Mental Models through a New Quantitative Method |
| title_full | How Influential Are Mental Models on Interaction Performance? Exploring the Gap between Users’ and Designers’ Mental Models through a New Quantitative Method |
| title_fullStr | How Influential Are Mental Models on Interaction Performance? Exploring the Gap between Users’ and Designers’ Mental Models through a New Quantitative Method |
| title_full_unstemmed | How Influential Are Mental Models on Interaction Performance? Exploring the Gap between Users’ and Designers’ Mental Models through a New Quantitative Method |
| title_short | How Influential Are Mental Models on Interaction Performance? Exploring the Gap between Users’ and Designers’ Mental Models through a New Quantitative Method |
| title_sort | how influential are mental models on interaction performance exploring the gap between users and designers mental models through a new quantitative method |
| url | http://dx.doi.org/10.1155/2017/3683546 |
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