Improving Project Management Teaching Using Scaffolding Based on Cladistics Parsimony Analysis
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
There are numerous educational paradigms each with their advocates and critics. The cognitive science approach is based on modelling memory as short term and long term each with their different characteristics. All learning consists of an iterative cycle of assimilate and retrieve between these two types of memory. The objective is the construction of an ordered mental structure called a schema in long term memory. With this approach it is possible to define schemas according to an optimal learning sequence. An optimum sequence has minimal cognitive load and hence the ideal teaching sequence. Previous work has clearly demonstrated that this method may be applied to network technology education. This paper applies the same method of teaching financial instruments in project management. Results to date demonstrate that scaffolding, based on cladistics parsimony analysis is a generic method and can be applied to different disciplines. Using this method an optimal learning sequence for project management financial instruments may be produced.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 it