Design Parameters for Online Psychometrics

  • Shiny Verghese

Student thesis: Doctoral Thesis


In contemporary society, where technology is rapidly spreading, the traditional method of (offline) testing through pen(cil) and paper is being converted to online psychometric test administration. There is a plethora of research available on the advantages of online administration of questionnaires. However, much of this work addresses comparisons between online and offline administration, factual questionnaires rather than psychometric questionnaires or online psychometric questionnaires without addressing presentation- or interaction design. In human-computer interaction online psychometric questionnaires are, for example, used to measure customers’ perceived quality of (online or offline) services and to measure users’ interaction experience with a Web site in terms of flow experience. Compared to the popularity of web-based surveys, there is little research available to aid the design of online psychometric questionnaires and to ensure sound measurement. Because psychometric questionnaires do not measure factual information, it is more likely that the responses given are influenced by external factors, such as the presentation design of the particular questionnaire that is being administered. Research reports that reading speed is affected by font size which (in turn) could apply for online psychometrics in terms of completion time of questionnaires. It is essential to further develop the scientific understanding of how presentation-design factors affect people’s responses in psychometric measurement and design guidance. The aims of this research are to develop a technical system to support the required research, gather data for online psychometrics with manipulation of design parameters, provide empirical evidence of the effect of design parameters on online psychometric measurement and finally provide design guidance for online psychometrics. The results could be extended to various other settings such as educational assessments.
Date of AwardOct 2019
Original languageEnglish
Awarding Institution
  • Teesside University
SupervisorPaul Van Schaik (Supervisor) & Chris Wilson (Supervisor)

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