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Using Educational Escape Room Activities to Teach Teamwork Skills and Build Effective Teams

2019· article· en· W3173798267 sur OpenAlexaff
John Kelly, Nicole Campbell

Notice bibliographique

RevueThe FASEB Journal · 2019
Typearticle
Langueen
DomaineEngineering
ThématiqueBiomedical and Engineering Education
Établissements canadiensWestern University
Organismes subventionnairesnon disponible
Mots-clésTeamworkSession (web analytics)Set (abstract data type)Medical educationThematic analysisPsychologyWork (physics)Mathematics educationComputer scienceEngineeringMedicineQualitative research

Résumé

récupéré en direct d'OpenAlex

Teamwork involves a set of skills used by a group of people who are working together towards a common goal. It is one of the most important skill sets for many careers; however, undergraduate students report that opportunities to develop teamwork skills are limited. Additionally, knowing the criteria that should be used to build effective teams of students can be challenging for instructors. In response to these problems, our aim was to develop and evaluate a low‐stakes team‐based activity that provides students with an opportunity to practice and develop teamwork skills. We also used the activity to investigate the criteria required to select effective student teams. To do this, we collaborated with a local escape room design team to develop a novel educational escape room activity (escape activity) that could be implemented in upper year science laboratory courses. Briefly, the activity requires students to work in teams and consists of various thematic challenges, such as visual and numerical puzzles. It requires collaboration amongst team members, each with their own strengths and perspectives, to solve a series of challenges and “break‐in” to the box within a limited amount of time. Currently, a longitudinal study approved by our institutional review board is being completed in a fourth‐year undergraduate laboratory course, which requires students to work in teams throughout the semester on a research project. The escape activity was run during the first lab session and students were randomly placed in small groups. Following the activity, students completed a validated self‐efficacy of teamwork skills survey and reported on their past research experiences. The results of the surveys allowed us to build teams that had strengths in teamwork skills, research experience, or both. When building teams, we ensured that they all represented a diversity of skills so that no teams were disadvantaged. An additional survey on self and peer evaluations of teamwork behaviours will also be administered at the end of the semester to evaluate the effectiveness of these teams. This will be done using a t‐distribution test on the teams' scores. The results of these surveys could inform the criteria that are used to select effective student teams in the future. Individual and group‐based reflections completed after the activity and at the end of the semester will be analyzed to identify themes related to teamwork concepts that students learned and compared to surveys on past teamwork experiences. These will assess the students' development of teamwork skills and their perceptions of its importance throughout the semester, which could inform the effectiveness of the escape activity as a pedagogical tool to teach teamwork skills. The data is in the process of being collected and analyzed. The escape activity is generalizable to any course or discipline. Thereby, validation of the escape activity as an effective pedagogical tool to teach teamwork skills could provide educators with an innovative opportunity to address the lack of opportunities for teamwork development in the undergraduate curriculum. It could also enhance students' self‐efficacy of teamwork skills which could provide educators with criteria to develop more effective student teams. Support or Funding Information Western CTL This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

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)0,003
score de la tête « metaresearch » (Gemma)0,006
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
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 enseignants0,006
Score d'incertitude au seuil0,020

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0030,006
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0000,001
Bibliométrie0,0010,000
Études des sciences et des technologies0,0010,001
Communication savante0,0020,002
Science ouverte0,0020,004
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0060,002

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 Opus0,004
Tête enseignante GPT0,223
Écart entre enseignants0,220 · 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'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
Publié2019
Routes d'admission1
Résumé présentoui

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