Evaluating Students' Experiences of a Weekly “Hour of Code”
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.
Bibliographic record
Abstract
In the winter semester of 2020 during a multimedia design and production class for pre-service teachers, the students were introduced to basic computer coding concepts such as variables, conditional statements, various expressions, logic, and syntax. For their final project, the students were asked to create an interactive instructional app using MIT App Inventor for their own future students in their teaching subjects (such as social studies, mathematics, science, and language arts). They were expected to integrate technical skills and knowledge of interface design, instructional design, and pedagogical strategies. The instructors examined exit tickets submitted at the end of each hour-of-code lesson and course evaluations at the end of the semester for evidence of threshold concepts, students' learning experiences, and motivation. This brief qualitative study provides a description of the course, coding and computational thinking processes, and the student evaluations. The paper concludes with commentary on lessons learned for teaching coding to pre-service teacher candidates.
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 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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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