Enhancing navigation using auditory feedback: a case study of a hierarchical information visualization system
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,008 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,003 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».