Using a Blended versus Online Course Design for Teaching Intermediate Accounting - an Empirical Study of the Teaching/Learning Environments
Bibliographic record
Abstract
The increasing importance of technology use in instructional design and delivery suggests significant implications for accounting educators and administrators. This study examines the effect of delivering an Intermediate Accounting course in a fully online format as compared with the effect of delivering the same course in a blended, face-to-face format over two semesters. The quasi- experimental design tests whether use of common course materials and instruction offered concurrently in both formats results in comparable learning and performance outcomes. Initial data collection took place in fall quarter 2012. Preliminary analysis suggests the importance of student computer skills and grade point average to performance. No difference in student performance between the two delivery approaches is noted, probably due to small sample size. To build upon fall quarter 2012 findings, the study was extended to provide for additional observations in the same settings in the spring quarter 2013 just completed. Analysis of spring 2013 data shows students in online mode obtained more accounting knowledge than the blended mode. Students aged younger than 29 perceive the technology application more favorably enhanced their learning than others. Students enrolled in the blended setting indicate they are more willing to use the technology than the online setting. Students with different learning styles perform differently and perceive differently about the amount of computer skills enhanced by taking the blended vs. online courses. The findings in this paper show promise of relevance to administrators for future planning and implementation of technology-based instructional design and delivery, for faculty in their development planning, and for educators who seek to develop a better awareness of student performance and learning preferences in each setting.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".