Examining How Expectancies and Values Can Overcome the Costs of Innovation: A Systematic Review of Environments and Approaches
Bibliographic record
Abstract
Making innovation more likely is a common goal of numerous educational initiatives ranging from the makerspace movement to high-skills majors and innovation incubators popping up across Canada. However, there has been limited cross-pollination across different disciplines towards a truly interdisciplinary understanding of what makes innovation more likely. This systematic review study examines the expectancies, values and costs that have been found to be involved in approaches and environments that promote the act of innovating. A systematic approach integrating an all-databases search in EBSCOhost (n=375 databases) yielded 115 full-text papers for data extraction. A majority of papers were found to be from business settings and predominantly using a survey methodology. There were limited considerations for implementation in schooling and education more broadly. Persistent trends for building expectancy tend to be supportive environments or approaches that make it safer for the aspiring innovators to practice and develop self-efficacy. Aspiring innovators tended to find intrinsic and utility value rather than attainment value as their principal task values, which suggests possibilities for maximizing their effect. Costs of innovation followed a similar pattern to costs as noted in other expectancy-value theory (EVT) studies. These findings point to a need for those interested in promoting innovation, especially educators, to focus their energies on creating a supportive environment and a needs-supportive approach.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 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".