Decline of Reading Culture among Students in Higher Education Institutions: A Survey of Juja and Thika Towns, Kenya
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
Primary school education is intended to inculcate in the learner basic literacy skills of reading, writing and simple arithmetic.The next level which is secondary education is aimed at identifying the career path the learner should pursue based on his/her ability and endowment.This ability is what informs the course the learner will pursue at the tertiary level of education.Higher education as contextualized in this paper is synonymous with tertiary education and refers to learning undertaken after secondary school be it in a college, TVET institution or university.The Study adopted the descriptive survey design.The location of the Study was Juja and Thika towns and their environs in Kenya for having a higher concentration of colleges and universities in Kenya when compared with other regions in the country.Triangulation of sampling techniques was used.The Study found out that less than 50% of students did not visit a library outside their institution to study or buy a personal book for the course they were undertaking.Further, over 50% of the students accessed the internet for non-academic content and went to the library only to study for examinations and not gain wide knowledge.The Study established causes for the decline of the reading culture that included poor foundation in high school and misuse of A.I. Finally, the Study recommended measures to redress the poor reading culture e.g policy changes on evaluation and regulating the use of A.I.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 it