Think-aloud protocols in research on essay rating: An empirical study of their veridicality and reactivity
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
Think-aloud protocols (TAPs) are frequently used in research on essay rating processes. However, there are very few empirical studies of the completeness of TAP data and the effects of this technique on rater performance (i.e., rating processes and outcomes). This study aims to start to address this research gap. As part of a larger study on rater decision-making behaviors, 11 novice and 14 experienced raters rated, both analytically and holistically, a sample of ESL essays silently and while thinking aloud. The raters were then interviewed about their perceptions of thinking aloud and its effects. Essay scores were submitted to FACETS analyses, while TAP and interview data were analyzed qualitatively. Score and qualitative data analyses provided evidence and explanations concerning the veridicality and reactivity of TAPs across rater groups (novice vs. experienced) and rating scales (holistic vs. analytic). The paper concludes with several theoretical and methodological implications and questions for future studies using TAPs to build models of and compare essay rating processes across individuals, groups and contexts.
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 | 0.006 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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