A Literature Review of Technology‐Related Research in Accounting Education: 2010–2020*
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
ABSTRACT This literature review includes 187 articles with a technology focus that were published during 2010–2020 in seven accounting education journals. We analyze these articles with a goal of identifying the research conducted at the intersection of technology and accounting education. Five accounting education areas of focus emerge, with each having prevalent themes. Within these themes, we identify the technological infusion and how it was applied or related to accounting education. Where feasible, we report information on the target expected use (users) within each of the five accounting focus areas in the article and present any relevant key findings. We conclude by identifying research voids and suggesting potential directions for future research. The analysis should aid current faculty in their efforts to infuse appropriate technology into accounting education with a goal of producing technologically savvy graduates.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.020 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it