Work in progress: The impact of using LATEX for academic writing: A Peruvian engineering students' perspective
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
This study shows the benefits of using the typesetting software LATEX in research courses of two engineering programs from the Sciences and Humanities University (UCH) in Lima, Peru. In several universities worldwide, this software is used to write diverse types of academic documents (e.g., theses, scientific papers and books). Some of the many advantages of LATEX is the easiness of writing mathematical equations and also dealing with different citation styles such as APA, IEEE and Vancouver. Moreover, the documents produced with this software possess an impeccable professional layout. Thus, during the second semester of the year 2019 and the first semester of the year 2020, a group of systems and electronic engineering students from research courses at the UCH were introduced to LATEX and were surveyed to find out their perspectives with regards to the use of this software. By means of a self-administered questionnaire, a general consensus could be seen among the students that LATEX is far better to write academic documents than other typesetting software. Hence, starting the second semester of 2020 we have encouraged its use in other research courses and suggested as well to the head of the engineering department at the UCH to make use of this tool a compulsory one in all such courses.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it