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Enregistrement W2755229971 · doi:10.18438/b89m14

Usability Study Identifies Vocabulary, Facets, and Education as Primary Primo Discovery System Interface Problems

2017· article· en· W2755229971 sur OpenAlexaffvenue
Ruby Warren

Notice bibliographique

RevueEvidence Based Library and Information Practice · 2017
Typearticle
Langueen
DomaineDecision Sciences
ThématiqueTechnology Adoption and User Behaviour
Établissements canadiensUniversity of Manitoba
Organismes subventionnairesnon disponible
Mots-clésSession (web analytics)UsabilityComputer scienceTest (biology)Task (project management)Interface (matter)World Wide WebLaptopStudy guideVocabularySet (abstract data type)MultimediaHuman–computer interactionEngineering

Résumé

récupéré en direct d'OpenAlex

A Review of: Brett, K. R., Lierman, A., & Turner, C. (2016). Lessons learned: A Primo usability study. Information Technology and Libraries, 35(1), 7-25. https://doi.org/10.6017/ital.v35i1.8965 Abstract Objective – To discover whether users can effectively complete common research tasks in a modified Primo Discovery System interface. Design – Usability testing. Setting – University of Houston Libraries. Subjects – Users of the University of Houston Libraries Ex Libris Primo Discovery System interface. Methods – The researchers used a think aloud usability test methodology, with participants asked to verbalize their thought processes as they completed a set of tasks. Four tasks were developed and divided into two task sets (Test 1 and Test 2), with session facilitators alternating sets for each participant. Tasks were as follows: locating a known article, finding a peer reviewed article on a requested subject, locating a book, and finding a newspaper article on a topic. Tests were conducted in front of the library entrance using a laptop equipped with Morae (screen and audio recording software), and participants were recruited via an assigned “caller” at the table offering library merchandise and food as a research incentive. Users could opt out of having their session recorded, resulting in a total of fifteen sessions completed with fourteen recorded. Thirteen of the fifteen participants were undergraduate students, one was a graduate student, one was a post-baccalaureate student, and there were no faculty participants. Facilitators completed notes on a standard rubric, coding participant responses into successes or failures and noting participant feedback. Main Results – All eight participants assigned Test 1 successfully completed Test 1, Task 1: locating a known article. Participants expressed a need for an author limiter in advanced search, and had difficulty using the citation formatted information to locate materials efficiently. Again, all eight participants found an article on the requested subject in Test 1, Task 2, but two were unable to determine if the article met peer review requirements. One participant used the peer-reviewed journals facet, while the rest attempted to determine this using the item record or with facilitator help. All seven participants in Test 2 were able to locate the book requested in Task 1 via title search, but most had difficulty determining what steps to take to check that book out. Five participants completed Test 2, Task 2 (finding a newspaper article on a topic) unassisted, one completed it with assistance, and one could not complete it at all. Five users did not notice the Newspaper Articles facet, and no participants noticed resource type icons without facilitator prompting. Conclusions – The researchers, while noting that there were few experienced researchers and a narrow scope of disciplines in their sample, concluded that there were a number of clear barriers to successful research in the Primo interface. Participants rarely used post-search facets, although they used pre-search filtering when possible, and ignored links and tabs within search results in favour of clicking on the material’s title. This led to users missing helpful tools and features. They conclude that a number of the usability problems with Primo’s interface are standard discovery systems usability problems, and express concern that this has been inadequately addressed by vendors. They also note that a number of usability issues stemmed from misunderstandings of terminology, such as “peer-reviewed” or “citation”. They conclude that while they have been able to make several improvements to their Primo interface, such as adding an author limiter and changing “Peer-reviewed Journals” to “Peer-reviewed Articles”, further education of users will be the only way to solve many of these usability problems.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,019
score de la tête « metaresearch » (Gemma)0,118
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,019
Score d'incertitude au seuil0,099

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0190,118
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0040,003
Études des sciences et des technologies0,0020,003
Communication savante0,0050,007
Science ouverte0,0010,004
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0030,001

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 Opus0,048
Tête enseignante GPT0,362
Écart entre enseignants0,314 · 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 source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
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

Citations1
Publié2017
Routes d'admission2
Résumé présentoui

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