Pre-Service Teachers’ Assessment of 7th-Grade Students’ Social Studies Learning
Bibliographic record
Abstract
The purpose of this study was to examine how 52 pre-service teachers (PSTs) assessed 7 th -grade students’ learning of social studies lessons they planned and taught. The PSTs provided assessment artifacts on 312 students, along with explanations for how they assessed and graded each student. Of the 429 coded assessment explanations, 240 (56%) related directly to students’ social studies achievement, 141 (33%) related to non-achievement factors, and 48 (11%) related to achievement factors not connected with social studies. Consistent with previous research on the assessment practices of in-service teachers, the pre-service teachers in this study used a combination of student achievement, effort, behavior, and ability to make their grading judgments. Assessment of student learning is taking a greater role in education today, and much of the burden for helping new teachers to improve their assessment practices will fall on teacher educators, who should integrate explicit coursework on assessment with authentic field experiences for PSTs to practice planning and teaching lessons, as well as assessing and grading students.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".