Developing a rubric to assess critical thinking in a multidisciplinary context in higher education
Bibliographic record
Abstract
Critical thinking (CT) is a generic attribute that is greatly valued across academic disciplines in higher education, and around the globe. It is also defined as one of the graduate attributes of higher education for the sample private university where this research was conducted, as it is perceived that CT helps the graduate to become ‘engaged citizens’ in the twenty-first century. Despite the well-documented importance of CT, its assessment remains a challenge. This study addresses this challenge through the systematic development and field-testing of a rubric for assessing critical thinking in a multidisciplinary context in higher education. A multidisciplinary group of faculty (i.e. education, nursing, medicine) from the sample university partnered with a policy research group in Canada to translate this plan into action. The development of the assessment tool followed a multi-step process including: (i) identification of the main elements of CT; (ii) choice of a rubric format; (iii) adaptation of the currently available relevant rubrics; and, (iv) field testing and establishment of the reliability of the rubric. The process resulted in the development of a holistic template, the Assessment of Critical Thinking (ACT) rubric. Two versions of the rubric have been field tested on a sample (n=59) of students drawn from different entities of the sample university. The data collected was subjected to psychometric analysis which yielded satisfactory results. This was a modest attempt to develop an assessment tool to guide multidisciplinary faculty members in teaching and assessing CT by assisting them to make decisions about the level of their students’ CT skills through a combination of numerical scores and qualitative description. It may also empower them to make self-initiated, conscious efforts to improve their classroom practice with reference to CT. The ACT rubric provides an anchoring point to start working on the daunting yet doable task of developing and fine-tuning both the assessment measures of CT and interventions to promote CT based on the assessment findings. Future research may not only provide robust evidence of the reliability and validity of the ACT rubric for a larger and varied sample but also help in making informed decisions to enhance teaching and learning of CT across entities of the sample university. How to cite this article: BHUTTA, Sadia Muzaffar; CHAUHAN, Sahreen; ALI, Syeda Kausar; GUL, Raisa; CASSUM, Shanaz; KHAMIS, Tashmin. Developing a rubric to assess critical thinking in a multidisciplinary context in higher education. Scholarship of Teaching and Learning in the South. v. 3, n. 1, p. 6-25, Apr. 2019. Available at: https://sotl-south-journal.net/?journal=sotls&page=article&op=view&path%5B%5D=69&path%5B%5D=34 This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
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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 | 0.029 | 0.084 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".