Proyecto de gamificación para trabajar la coeducación en el tercer ciclo de la educación primaria
Bibliographic record
Abstract
In the twenty-first century, real equality is presented as an unachieved goal and one that needs to be increasingly addressed. Individuals, since we were born, we experience a process of socialization that reproduces the gender roles and values inculcated by patriarchal society. Despite their role as socializing agents, schools and education are lacking in the treatment of gender equality, ignoring and not paying enough attention to co-education. \nMoreover, the continuing technological advances and the emergence of TICs in society have not left the education system indifferent. Taking into account the advantages that TICs provide and the imperative need to adapt both to the new social context and to the needs and characteristics of its students, the education system opts for their inclusion as a tool in the teaching processes. Along these lines, the growing interest of students in games and video games makes gamification an innovative tool that increases their motivation and interest in the content worked. \nFor this reason, this Master’s Thesis presents a proposal for innovation based on the gamification of a quarter with the aim of working coeducation in the third cycle of primary, seeking the development and promotion of an education based on the principles of equality, respect and freedom.
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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 | 0.003 | 0.004 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".