Enhancing tree testing analysis to improve the usability evaluation of websites.
Tree testing is a technique used in the early stages of Information Architecture to design the structure and navigation of a web application. It can also be used in later stages to evaluate navigational trees or the navigation map of existing web applications. Although Tree Testing is used frequentl...
| Publicado en: | Behaviour & Information Technology Vol. 45; no. 6; pp. 1117 - 1136 |
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| Autores principales: | , |
| Formato: | pictorial research tables/charts Journal Article |
| Publicado: |
Taylor & Francis Ltd
Apr2026
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=192771839&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 192771839 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 0144929X B6Q jtl: Behaviour & Information Technology issn: 0144929X maglogo: Y pubinfo: dt: Apr2026 vid: 45 iid: 6 pid: 377 pub: Taylor & Francis Ltd place: Philadelphia, Pennsylvania artinfo: ui: 192771839 187447271 192771839 192771839 10.1080/0144929X.2025.2546971 192771839 ppf: 1117 ppct: 19 formats: tig: atl: Enhancing tree testing analysis to improve the usability evaluation of websites. aug: au: Callejo, Adrián Macías, José A. affil: Escuela Politécnica Superior, Universidad Autónoma de Madrid, Madrid, Spain sug: subj: World Wide Web Decision Making, Computer Assisted Software Design Computer Systems Evaluation User-Computer Interface Human Funding Source Male Female Adolescence Adult Middle Age Usability Study Information Systems Program Evaluation Data Analysis, Statistical Confidence Intervals Qualitative Studies Benchmarking Website Development Machine Learning Cluster Analysis Decision Support Systems, Clinical Adolescent: 13-18 years Adult: 19-44 years Middle Aged: 45-64 years Male Female ab: Tree testing is a technique used in the early stages of Information Architecture to design the structure and navigation of a web application. It can also be used in later stages to evaluate navigational trees or the navigation map of existing web applications. Although Tree Testing is used frequently, its use and adoption are still largely handmade, using handcraft or spreadsheets to carry it out. This makes it challenging to perform benchmarking and comparative evaluations to assess the quality of navigational content and compare different website designs. Although some tools to assist evaluators exist, they are mainly based on standard metrics, lacking advanced representation and the possibility to compare and benchmark different evaluation projects. This paper presents a systematic solution to improve Tree Testing analysis through advanced visual, statistical, and machine-learning techniques that facilitate decision-making. Our solution includes a tool created to support evaluators and participants, featuring advanced techniques to extract and represent knowledge not included in other existing tools. This facilitates decision-making in the early (analysis) and advanced (evaluation) stages of web-content development. The tool has been evaluated with target users, obtaining successful results related to usefulness, satisfaction, ease of learning, and ease of use. pubtype: Academic Journal doctype: pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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