Preservice teachers’ science learning and self-efficacy to teach with robotics-based activities: Investigating a scaffolded and a self-guided approach
Notice bibliographique
Résumé
Introduction Robotics is viewed as a viable pedagogical strategy for STEM learning because it is characterized by many practices common to the STEM disciplines such as engineering design. With many national curricular calling for STEM integration in K-12 formal educational settings, there is a need for empirical evidence about the effectiveness of different pedagogical approaches to teach with robotics-based activities to promote curriculum learning outcomes and teaching practice. This exploratory study investigated the effectiveness of a scaffolded robotics intervention and a self-guided robotics intervention on pre-service teacher knowledge (PST) of science concepts related to gears and on PST self-efficacy to teach with the robotics-based activities. Methods A quasi-experimental, pre-post intervention study was implemented with two non-equivalent groups of elementary preservice teachers (PSTs) in a Bachelor of Education program. PSTs in the self-guided group (n = 11) worked with robotics kits in the library at their own pace. PSTs in the scaffolded intervention group (n = 16) were guided through the activity by the author with instructional scaffolds. IBM SPSS Statistics 27 was used to analyze the data. Results The relationship between intervention type and gains in science knowledge was not statistically significant for the self-guided group but was statistically significant for the scaffolded group suggesting that scaffolding supported PST’s learning of the science concepts. With respect to PST self-efficacy to teach with the robotics-based activity, both intervention types revealed statistically significant gains from pre to post tests, however effect sizes indicated that the scaffolded intervention resulted in greater gains in PST self-efficacy to teach with the robotics-based activities. Discussion The results provide exploratory evidence that the scaffolded robotics approach, modelled for and experienced by the pre-service teachers in this study, was effective for their learning of science curricular concepts related to gears and for developing their self-efficacy for teaching the robotics-based activities. It should be noted that findings may not be generalizable due to the small sample sizes, especially of the self-guided group. Nevertheless, the findings do provide insights for teacher educators incorporating robotics-based activities into curricular courses such as science methods as it provides specific examples of scaffolds that were effective for science learning and for developing PST self-efficacy. The study also contributes to the literature on instructional strategies that promote robotics adoption in K-12 schools to support development of STEM knowledge and skills.
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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 | 0,005 | 0,009 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,002 | 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) | 0,003 | 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 ».