Usability of a classroom response system in an online course: Testing of a smartphone-downloadable technology enhanced learning tool for distance education
Notice bibliographique
Résumé
Background and objective: Classroom response systems (CRS) have been used in higher education since the 1990s to enhance student learning and engagement. It began with portable “TV remote control-looking” devices that students used in class to answer questions posed by the professor. Aggregated responses are available instantaneously and projected on the screen to serve as a feedback mechanism for the professor and students to gauge learning, potentially prompt further review of the topics, or inspire further discussion. Companies which produce CRS tools are beginning to develop apps to allow students to use their own technology mobile devices during similar learning activities. Many educational institutions are increasingly offering distance education courses and programs, yet little is currently known about the effectiveness of CRS integration into online courses. This usability study was conducted to determine whether a technology enhanced learning tool, specifically a CRS that can be downloaded to one’s smartphone, would be suitable for adoption in online classes in one particular suburban university in New York.Methods: The study is a mixed method, one group, pretest/posttest descriptive design. Convenience sampling (n = 48) was used to engage students enrolled in an online nursing course during their first semester in a master’s degree program. A five-point Likert scale was designed for respondents to rate 21 statements in terms of their degree of agreement (with 5 being “strongly agree” and 1 being “strongly disagree”). The statements included descriptors of the three usability domains (functionality, support and effectiveness) selected to evaluate the smartphone-based CRS app. Open-ended questions were included to provide contextual perspectives on these criteria.Results: T-tests demonstrated an improvement in student ratings of agreement with the evaluative criteria for this CRS smartphone app when comparing pre- and post-implementation survey data. This includes agreement with the CRS’s functionality (p = .001), support (p = .004) and effectiveness (p = .189) at α = 0.05, as well as overall usability across criteria domains (p = .000 at α = 0.05). Respondents additionally suggested that specific features be changed or added to the current design to make it easier to navigate.Conclusions: For educational apps to achieve optimal use and effectiveness, iterative design assessments should continue until the end-users truly benefit from the technology enhanced learning tool. This smartphone-downloadable CRS app proved to be a useful adjunctive tool for enhancing student learning in an online class. Yet there were numerous design recommendations provided by students that could further improve its usability.
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 | 0,008 | 0,026 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
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.
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 ».