Organizational learning and benchmarking in university technology courses
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
Purpose The purpose of this paper is to analyze the management practices that contribute to single and double cycles of organizational learning in the vocational education of the Brazilian higher education technology courses (HETC), and to study the learning outcomes that result through the Brazilian Ministry of Education SINAES indicators. Design/methodology/approach It consisted in both participant observation and quantitative phases. The participant observation phase included a benchmarking activity at École de Technologie Supérieure (ÉTS) de Montréal, to analyze and delimitate their practices for the preparation of the second phase, test the hypotheses by means of modeling of structural equations. Findings The key practices that contribute to organizational learning in the Brazilian HETC were identified through a benchmark activity at ÉTS by using a quantitative research scheme of single cycles of organizational learning, and further in correspondence with the Brazilian criteria (SINAES-Ministry of Education). Research limitations/implications The extent of the sample is concentrated in the southern region of Brazil (Rio Grande do Sul, Santa Catarina and Paraná), limiting its representativeness to a regional basis. Practical implications Practices that contribute to organizational learning are a counterpoint and a complement of the Brazilian Ministry of Education SINAES indicators, which value the formalization of those courses and the future actions in the Brazilian universities. Social implications The study re-inforces the importance of organizational learning for the development of excellence in Brazilian HETC. Originality/value The results contribute to build analysis frameworks on the relationships between management practices, organizational learning, benchmarking and organizational outcomes, particularly in the management of the technology courses and for Brazilian universities.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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