Textbooks and Teaching Materials in Rural Schools: A Systematic Review
Bibliographic record
Abstract
This paper presents the results of a research project whose main purpose is to analyse the concept of multigrade teaching resources and the teaching materials used by teachers in rural schools, in particular the role of textbooks. The use and dimensions of teaching materials are studied in order to promote inclusion and learning in multigrade classrooms with children of different ages mixed together. The present systematic review aims to identify and analyse all of the research papers published internationally on teaching resources in rural schools for the Web of Science and Scopus databases (from 1992 to 2021) and Google Scholar (between 2010 and February 2021). Due to the dearth of publications focused on the topic of study, the reviewed articles have broad inclusion and exclusion criteria. This gives relevance and an innovative character to the research, allowing us to objectify the state of the question on multigrade didactic materials and their relation to teaching-learning processes. From a total of 332 research papers in the field of rural multigrade teaching identified for further analysis, only papers that met the inclusion and exclusion criteria and passed all phases of the PRISMA flow diagram were used (N = 33). Some research publications contributed to identifying opportunities and needs, and to suggesting criteria to be taken into account for the selection and creation of materials to promote inclusion and active learning methodologies. The first results show the need to create one's own materials that analyse the reality of these schools, as well as the need to personalise and adapt printed or digital textbooks and other teaching materials in order to involve the students actively in the learning process and to respond to the needs of rural students in multigrade classrooms.
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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 | 0.014 | 0.055 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.019 | 0.021 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".