La Alfabetización Cuantitativa en estudiantes de Tercer Grado de Primaria a través de un Juego Serio
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
The last results of national and international evaluations, show that learning math is complex for Mexican students. Different plans and techniques have been implemented to counter this problem, one of them is the use of different technology in the classroom. During the last two decades, the videogame industry in Mexico has gained great traction among children, teenagers and young people, which is why the advantages of these kind of technologic tools must be harnessed. In this paper, we present a serious game to improve quantitative literacy in children studying the third grade of primary school. To design it, an iterative design model that contemplates four stages was use: planification, development, evaluation and improvement; emphasizing the instruction design. Through a quasi-experiment during a two-month period, the game was tested in a class of 33 morning shift third-grade students. The results obtained demonstrated quantitatively an increase in the students’ skills. It was shown, that out of the three subconstructs that constitute quantitative literacy, two of those (natural numbers and mathematical operations) showed significant improvement after treatment. The students enjoyed and engaged with the serious game, which is why it is expected to use this tool in the future in different Mexican communities.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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