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Evaluating Information Design for Notification Systems - eScholarship

2002· article· en· W2613342285 sur OpenAlexaboutno aff
C. M. Chewar, D. Scott McCrickard

Notice bibliographique

RevueProceedings of the Annual Meeting of the Cognitive Science Society · 2002
Typearticle
Langueen
DomaineDecision Sciences
ThématiquePersonal Information Management and User Behavior
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésComputer scienceWearable computerVariety (cybernetics)Information systemMobile deviceHuman–computer interactionUbiquitous computingPerceptionWorld Wide WebInternet privacyEngineeringArtificial intelligencePsychology
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Evaluating Information Design for Notification Systems C. M. Chewar (cchewar@cs.vt.edu) D. Scott McCrickard (mccricks@cs.vt.edu) Department of Computer Science, Virginia Polytechnic Institute and State University Blacksburg, VA 24061-0106 USA As computing platforms continuously grow in processing power, diminish in size, and are creatively integrated into every facet of the human experience, popular demand also increases for unfettered access to information of interest, necessitating insightful design for a variety of displays. While engaged in their daily discourse, occupied with activities such as driving, desktop computing, or interacting with others, people often want to remain notified about news items, collaborative efforts, and other changing information. Decision requirements within new settings or situations may prompt immediate interest in accessing related data. Notification systems in the form of ubiquitous computing devices, to include wearable computers, vehicle information systems, and handheld devices, are relied on support these information needs. Desktop computer users also depend on small-sized secondary display applications to provide similar notification information. However, information conveyed through these devices and applications is often perceived with short, discrete attention shifts and glances rather than longer periods of full attention perception that has been considered typical of human-computer interaction. Certainly, this paradigm has implications for information design, rooted in cognitive processing and human attention limitations. Adding to this challenge, user goals are difficult to predict and often conflicting. For example, users may not want to be interrupted from a primary task, although they still wish to maintain awareness of information over a period of time or recognize specific information states. In other usage scenarios, users may wish to be alerted about information and attracted to some interaction. Platform capabilities may also mandate minimalist information representation, presenting an imperative for reevaluation of design guidelines for a wide array of emerging computer interfaces within these constraints. Objectives and Related Work Through empirical study, we seek to understand how various options for information encoding and design, presented within a dual-task situation, simultaneously affect user interruption while enabling reaction and comprehension of notifications. Although much work has been done to understand relative effectiveness and expressiveness of visual primitives within the human- computer interaction field, there are few empirically established design guidelines available for digital displays that are typically not a user’s main attention focus. Cleveland and McGill’s ordering of graph attributes provides guidance for primary task displays (1984), and Cleveland has extended consideration of graphical attribute effectiveness to specific information extraction tasks (1994). However, the dual-task nature of notification systems usage requires evaluation of many other system variables for strong empirical study validity. For example, various combinations of mental and physical workload levels, cross- modal or intramodal presentation of the two tasks, and competing demand for sensory channels and short-term memory (Wickens & Hollands, 2000) will certainly have implications for fulfilling objective information design requirements. Empirical methods allowing reliable replication, measurement, and modeling of these variables are pivotal for creating notification systems guidelines. Continuing Work Initial findings from our work show that Cleveland and McGill’s guidelines for use of visual attributes do not hold for dual-task situations where a distraction to a primary task requiring high attention and manual interaction must be minimized (Tessendorf et al., 2002). Additionally, we have seen evidence that information design for decision-support notification systems is best accomplished with cross-modal representations as a primary task’s visual sensory demand level increases (tasks tested within a CAVE TM virtual environment and on a desktop computer). Continuing studies will lead to development of regression models and tables, supporting rule-based presentation adaptivity, complementary to efforts such as Horvitz’s PRIORITIES system, which makes inferences about a user’s attention state and calculates expected cost of an interruption to determine the most suitable presentation method (Horvitz, Jacobs & Hovel, 1999). References Cleveland, W. S. (1994). The Elements of Graphing Data. Summit, NJ: Hobart Press. Cleveland, W. S., & McGill, R. (1984). Graphical perception: Theory, experimentation, and application to the development of graphical methods. Journal of American Statistical Association, 79(387), 531-554. Horvitz, E., Jacobs, A. & Hoxel, D. (1999). Attention- sensitive alerting. 15 th Conf. on Uncertainty and AI (UAI ’99) (pp. 305-13). San Francisco, CA: Morgan Kaufmann. Tessendorf, D., Chewar, C. M., Ndiwalana, A., Pryor, J., McCrickard, D. S. & North., C. (2002). An ordering of secondary display attributes. Extended Abstracts of CHI2002 (pp. 600-1). New York: ACM Press. Wickens, C. D. & Hollands, J. G. (2000). Engineering Psychology and Human Performance. 3 rd edn. Upper Saddle River, NJ: Prentice Hall.

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,017
score de la tête « metaresearch » (Gemma)0,019
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Qualitatif · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,423
Score d'incertitude au seuil0,989

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0170,019
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,002
Études des sciences et des technologies0,0010,001
Communication savante0,0010,005
Science ouverte0,0020,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,375
Tête enseignante GPT0,437
Écart entre enseignants0,063 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeQualitatif
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2002
Routes d'admission1
Résumé présentoui

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