INFLUENCE OF INFORMATION COMMUNICATION TECHNOLOGY SKILLS ON RESEARCH OUTPUT OF ACADEMIC LIBRARIANS IN ADEKUNLE AJASIN UNIVERSITY LIBRARY, AKUNGBA AKOKO, ONDO STATE
Bibliographic record
Abstract
The study investigated the influence of information communication technology on the research output of Academic Librarians in AAUA Library, Akungba – Akoko, Ondo state. Descriptive survey research design was used for the study. The population of the study was Five academic Librarians in Adekunle Ajasin University Library, Akungba – Akoko, Ondo state. Total enumeration sampling technique was used for the study. Questionnaire was used as the data collection instrument. The collected data were subjected to analysis with the aids of descriptive and inferential statistics. The hypothesis was tested at a 0.05 level of significance. The study found that the research output of the academic librarians in AAU library are grant writing, curricular, project management, literacy instructions and scholarly journal; Information communication technology facilities in AAU library are high speed internet, computers, interactive whiteboard and telecommunication. It also found that the challenges confronting the academic librarians regarding the usage of ICT are financial constraints, lack of ICT skill, inadequate facilities and security threat. The study recommended that academic librarians should engage in a skill acquisition in the area of information communication technology, so as to improve their research output; Information communication technology facilities should be provided in the library to assist the academic librarians in undertaking research functions and Adekunle Ajasin university library should make available to the academic librarians, training and retraining, seminars, workshops and orientation programes to enhance their knowledge of ICT.
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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 | 0.004 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".