Exploration of Teaching Reform Path Based on OBE Concept—Taking Online Marketing Course as an Example
Bibliographic record
Abstract
This paper, taking the course of "Network Marketing" as an example, explores the teaching reform path based on the OBE (Outcome-Based Education) concept. Firstly, it analyzes the core content and characteristics of the OBE concept, pointing out that it focuses on cultivating students' comprehensive qualities and abilities, and pays attention to their actual needs and future development. Then, from the aspects of teaching content, teaching methods, evaluation methods, etc., it proposes the teaching reform path based on the OBE concept, including: 1) Optimizing the curriculum design and clarifying the teaching objectives; 2) Using diversified teaching methods to improve students' learning interest and initiative; 3) Implementing project-based teaching to cultivate students' practical ability and innovative spirit; 4) Establishing a diversified evaluation system to focus on students' all-round development. Finally, it summarizes the teaching reform based on the OBE concept, emphasizes the key role of teachers in the reform, and puts forward further research directions.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".