Integrating Eye Tracking, Feature Use, and Emotional Valence: A Multimodal Approach to Evaluating Search Interfaces
Interactive Information Retrieval (IIR) interfaces are typically evaluated using questionnaires that gather post-task subjective measures such as ease of use, usefulness, satisfaction, and user engagement, along with in-task objective measures derived from log analysis.However, a comprehensive evaluation requires a deeper understanding of user behaviour beyond such traditional measures.Integrating eye tracking data with logged feature use and emotional valence provides a multimodal approach to evaluating a search interface at the feature level.To validate this approach, we examined three search interfaces in a controlled laboratory study focused on exploratory search within the context of digital humanities archives.A key benefit of this multimodal approach is that it allows us to evaluate both traditional interaction with the search interface (looking at a feature, using it, and experiencing an emotional response) as well as passive interaction with the search interface (looking at a feature, choosing not to use it but possibly getting information from it, and experiencing an emotional response).Using this approach, we were able to identify specific features of the interfaces that generated positive and negative emotional valence responses when used, as well as features that generated such emotional valence responses when viewed but not used.Such feature-level assessments would be difficult to capture using other means, providing insight into the nature of the searchers' experiences using the search interfaces.
Authors
- David T. Gleeson (ORCID: https://orcid.org/0000-0002-1592-4201)
- Orland Hoeber (ORCID: https://orcid.org/0000-0003-2875-1132)
- Morgan Harvey (ORCID: https://orcid.org/0000-0001-5504-2089)
- Abbas Pirmoradi Bezanjani (ORCID: https://orcid.org/0000-0001-6493-9285)
- Milad Momeni (ORCID: https://orcid.org/0000-0003-4267-4938)
Institutions
- University of Regina (CA)
- Northumbria University (GB)
- University of Sheffield (GB)
Publication Details
- Published
- 2025-03-24
- DOI
- https://doi.org/10.1145/3698204.3716444
- Citations
- 1
- Primary Topic
- Advanced Text Analysis Techniques
- Type
- article
- Field-Weighted Citation Impact
- 2.48
Funders
- University of Regina
- Natural Sciences and Engineering Research Council of Canada