A Formative Assessment Example: Word Association Test
Bibliographic record
Abstract
This research was carried out to determine the effectiveness and functionality of the word association test (WAT), which is a formative assessment tool that is frequently emphasized on today’s modern education systems. The study group consisted of 60 students in a public school in Kocaeli in the school year 2018-2019. Participants were identified using convenience sampling technique. The data of the study were obtained by using pre-test and post-test quasi-experimental design with no control group. The data were categorized by subjecting to content analysis. The findings were tabulated using the cut-off technique and analyzed using the Wilcoxon signed-rank test. When the results of the study were examined, it was concluded that conceptual change and development occurred in participants’ minds and there was a significant difference in the results of the Wilcoxon test performed before and after the implementation. It was observed that the students wrote 1669 words before the implementation, and the number increased to 2193 after it. This shows that the students associate the key concept of “migration” with more words after the implementation and thus there is a wider connotation related to migration in their minds. In addition, the results of this research reveal that the WAT is suitable for formative assessment and can be used in educational studies.
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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 | 0.006 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".