Designing Metadata Surrogates for Search Result Interfaces of Learning Object Repositories: Linear versus Clustered Metadata Design

This study reports the findings of a usability test conducted to examine users’ interaction with two different learning object metadata-driven search result interfaces. The first was a clustered metadata surrogate interface (where metadata elements were divided into sections), and the second a linear or single metadata surrogate interface (where all metadata elements were listed in a single record). The objectives of this research were: firstly, to investigate the time needed by learners to identify a relevant learning object, using both interfaces; secondly, to examine learners’ subjective satisfaction for both interfaces; and finally, to study the impact of task complexity on users’ interaction with both interfaces. To facilitate the objectives of the study, twelve postgraduate students participated in a user study which employed a multi-method approach and involved observation of users’ interactions, subjective satisfaction questionnaires and semi-structured interviews. Data collected included the time needed for users to identify relevant learning objects in both interfaces and the rating of users’ subjective satisfaction. In addition, qualitative data were collected based on interviews and the think aloud protocol. Parametric analysis (ANOVA tests) was conducted to identify statistically significant differences between the two interfaces in terms of time, user satisfaction and the impact of task complexity. The data analysis revealed that users needed less time to perform the tasks using the clustered metadata surrogate interface. This difference, however, was not significant. In addition, there was no significant impact of task complexity on user’s performance. In terms of subjective satisfaction, however, the participants perceived the clustered metadata surrogate interface to be significantly more satisfying, stimulating and easy to use (F=89.690, p.<0.01). The findings of this study provide useful recommendations for the design of search result interfaces in learning object repositories.