Enhancing navigation using auditory feedback: a case study of a hierarchical information visualization system
Bibliographic record
Abstract
Interaction with information systems today mostly consists of a user's unimodal interaction with a text-based or visual information system. However, human-computer interaction studies have illustrated that information can be successfully conveyed through different sensory modalities. This research focuses on the enhancement of the user experience using auditory feedback for the specific case of a 3D-visualized hierarchical information system, by representing some of the structural and navigational cues using nonspeech sounds. It is hypothesized that engaging the auditory modality may aid in navigation tasks, improve users' affective reactions and consequently enhance the overall user experience. The research involves two studies. In the first study, a user-centred semiotic sound design methodology is used, based on a methodology originally used on visually-impaired users. Three panels of end-users are employed to design the required nonspeech sounds. Based on the results of this study, recommendations are made for extending the sound design method to novel interfaces and sighted users. The second study is a controlled experiment that compares user experience with the visualization system and with the auditory-feedback enhanced system. The goal is to evaluate the effect of the auditory feedback on user experience. This effect is measured using a measurement model which draws on concepts derived from three conceptual frameworks, based in Human-Computer Interaction (HCI), Information Science (IS) and auditory interface studies. A combination of measures is examined, including utilitarian variables such as time taken on hierarchy navigation and information retrieval tasks, and accuracy of the answers. Hedonic variables, which influence the affective reactions, were also examined. These include preference, perceived ease of use, usefulness and ease of learning, and user engagement and satisfaction. We observed that 79% of the participants preferred the audio-visual system to the visual-only system. The audio-visual system was also perceived as easier to use and received higher ratings in terms of aesthetic appeal and perceived usability, which are attributes of user engagement. Furthermore, the audio-visual system was often perceived as being faster and more engaging even though no significant differences were observed in terms of utilitarian variables of task times and accuracy. Findings suggest hedonic variables play an important role in enhancing user experience when interacting with information systems. This research contributes to the field of information science by showcasing that designing multimodal information systems with a focus on the user has the potential to improve user experience. Our findings also provides evidence that utilitarian variables need not be the principle focus of user experience enhancement in information navigation and retrieval tasks, as preference appears to be linked to hedonic variables.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".