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Record W4327605576 · doi:10.3389/feduc.2023.979709

Preservice teachers’ science learning and self-efficacy to teach with robotics-based activities: Investigating a scaffolded and a self-guided approach

2023· article· en· W4327605576 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueFrontiers in Education · 2023
Typearticle
Languageen
FieldComputer Science
TopicTeaching and Learning Programming
Canadian institutionsBrock University
FundersBrock University
KeywordsRoboticsArtificial intelligenceCurriculumBachelorEducational roboticsMathematics educationScience educationComputer sciencePsychologyPedagogyRobot

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.790
Threshold uncertainty score0.743

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.014
GPT teacher head0.277
Teacher spread0.263 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it