Using Bloom’s Taxonomy to Gauge Students’ Reading Comprehension Performance
Bibliographic record
Abstract
Assessment is an essential part of the teaching-learning process. Students’ learning can be measured by different procedures. Despite a significant increase in test procedures, numerous issues surrounding testing of comprehension remain unresolved. This paper investigates the relationship between the level of thinking processes in comprehension questions and the students` performance. The findings indicate that the level of questions designed according to Bloom’s Taxonomy influence the students’ performance in answering comprehension questions. The findings conclude that there’s a relationship between the level of thinking processes needed and the students’ ability to answer these questions correctly. This paper provides a common base for further discussionsont the undergraduates’ competence in English Language as well as the recommendations on the techniques that could be used to handle higher order level questions. Keywords: Level of thinking process; Reading Comprehension Questions; Performance; Bloom’s Taxonomy; Multiple choice questions (MCQs) Resume: L'evaluation est une partie essentielle du processus de l'enseignement-apprentissage. L'apprentissage des eleves peut etre mesure par des procedures differentes. Malgre un accroissement significatif dans les procedures de test, de nombreuses questions concernant les tests de comprehension restent non resolues. Cet article etudie la relation entre le niveau des processus de pensee dans les questions de comprehension et de la performance des etudiants. Les resultats indiquent que le niveau de questions concues selon la taxonomie de Bloom influence sur la performance des eleves dans leurs reponses aux questions de comprehension. Les resultats concluent qu'il y a une relation entre le niveau de processus de pensee necessaire et la capacite des eleves a repondre a ces questions correctement. Ce document fournit une base commune pour des discussions plus approfondies sur la competence de l'anglais des eleves de premier cycle, ainsi que les recommandations sur les techniques qui pourraient etre utilisees pour traiter des questions d'un plus haut niveau.Mots-cles: niveau de processus de pensees; questions sur la comprehension ecrite; performance; taxonomie de Bloom; questions de choix multiple (MCQs)
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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 | 0.008 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".