An Investigation into Assurance of Learning in an Introductory Financial Accounting Course
Bibliographic record
Abstract
This study investigates assurance of learning for an introductory financial accounting course at a large Canadian university. This university is considering AACSB accreditation. To measure student learning, exam questions, the sole method of assessment, were mapped to the learning objectives of the course. Student results, by question, were collected in order to assess the extent to which course objectives were being met. The course objectives were then linked to program and university learning outcomes and applicable AACSB standards. A conceptual framework situating introductory financial accounting within the program and university environment is constructed. This framework can be applied by universities pursuing or supporting AACSB accreditation using a course-embedded approach. This paper contributes to the accounting education literature by providing a case study of the early stages of implementing assurance of learning in an accounting course. It describes an approach for determining the achievement of course objectives and provides a framework for the development of course objectives that support program and university-wide learning outcomes and AACSB accreditation standards.
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.
How this classification was reachedexpand
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.004 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".