How to prompt training effectiveness? An investigation on achievement goal setting intervention in workplace learning
Notice bibliographique
Résumé
Purpose The purpose of this study is to propose and examine an integrated learning model for improving training effectiveness in workplace learning. Specifically, this study investigated the effect of achievement goal-setting intervention across three groups of new employees from a multinational medical company. During a three-day remote training program, the role of each achievement goal orientation (AGO) in goal setting intervention and their relations with trainees’ applied learning strategies were examined. This study proposed and validated an integrated training model for improving remote workplace learning effectiveness. Design/methodology/approach This study was based on two data sources, the pre- and posttests scores; time on task (deep learning: completing reflective practice) and time on content learning (surface learning: watching tutorials) retrieved from an adaptive learning platform. A total number of 133 participants were recruited in this study, and they were randomly assigned to three interventional groups. The intervention was grounded from the AGO theory and goal setting theory. A series of statistical analysis were conducted to examine the effect of each type of achievement goal setting as a prompt for new employees’ learning behavior and performance. Findings Results indicated that setting mastery goal at the beginning of the training program leads to productive learning outcomes. Compared with the groups being required to set performance goal (final rank) or not to set any goal for the training purpose, trainees’ who were assigned to set a mastery goal (final performance score) performed statistically significantly higher than the other groups. Additionally, learners who set mastery goal spent higher proportion of time on deep learning than learners from the other groups. The results proved mastery goal setting as an effective prompt for boosting workplace learning effectiveness. Practical implications Organizations and institutions can take setting mastery approach goals as a prompt at the beginning of the training to increase learning effectiveness. In this way, trainees are promoted to apply more deep learning strategies and achieve better learning outcomes while setting mastery goal for their training purpose. Originality/value To the best of the authors’ knowledge, this study was the first to combine the intervention of goal setting and types of AGOs into workplace learning. This study adds to previous research on goal setting theory and AGO theory for the practical application and proposes an effective model for learners’ adaptive remote learning. Findings of this study can be used to provide educational psychological insights for training and learning in both industrial and academic settings.
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 | 0,004 | 0,008 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 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 | 0,000 |
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 ».