Preservice teachers’ science learning and self-efficacy to teach with robotics-based activities: Investigating a scaffolded and a self-guided approach
Bibliographic record
Abstract
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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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".