The Use of Mother Language Instruction in Enhancing Reading Skills to Public Pre-Primary Children in Rural Tanzania
Bibliographic record
Abstract
Reading skills are a significant schooling issue in Tanzania and other developing nations.Tanzanian rural public primary school pupils to which pre-primary classes are attached have poor reading literacy.The present study investigated the use of the mother language to enhance reading skills in pre-primary children and primary teachers in rural areas.Specifically, the study examined public primary teacher perceptions of using mother language instructions to teach pre-primary classes.The study also assessed pre-primary teachers' perceptions of using the mother language in enhancing reading skills.Interdependence and sociocultural theories (Cummins, 1979;Vygotsky, 1978) guided the study.The study adopted a quantitative approach with a descriptive design.The study involved 226 out of 550 primary teachers who attended the December 2023 face-to-face Diploma in Primary Teacher Education at The Open University of Tanzania from five centres.In Tanzania, the primary teachers are the ones who teach pre-primary classes, and the information was collected using a structured questionnaire with four Likert scale intervals.Data analysis was done using SPSS version 23.Mean and standard deviation were computed.The findings revealed that primary teachers disagree with using the mother language when teaching pre-primary classes.However, the findings showed that most teachers felt that the mother language would easily improve pre-primary children's reading ability.In conclusion.Mother language is essential in enhancing reading skills in preprimary classes.The study recommends the establishment and implementation of a language policy that would mandate the use of both the mother tongue and Kiswahili in the instruction of pre-primary classes.
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.
How this classification was reachedexpand
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".