Using Educational Robotics (ER) to Promote STEM Problem-Solving in Preservice Teachers
Why this work is in the frame
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Bibliographic record
Abstract
With the recent emphasis on learning STEM skills across the k-12 curriculum globally, there is need to provide elementary preservice teachers (PTs) with knowledge of what STEM skills are and how to teach STEM problem-solving skills. In many k-12 curricula, the teaching of STEM skills is mainly incorporated into the science and mathematics curricula. The literature suggests that educational robotics (ER) is an instructional activity that can support school students learn STEM skills. This chapter reports on a study that explored how middle school PTs engaged in STEM problem-solving during a robotics activity. A qualitative, comparative case study design was employed. Data sources included a problem-solving worksheet, audio-recordings of group interactions, and video-recordings or photographs of artifacts. The discourse of six PT groups was analyzed using a STEM problem-solving framework. The results provide insights into the STEM problem-solving decisions of PTs during these ER activities such as PTs drawing on mainly everyday, practical experiences and some basic STEM knowledge to frame and plan the problem, and solving through trial-error-trial feedback loops. Recommendations are made for enhancing PTs STEM problem-solving and the design and implementation of ER activities for elementary students.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it