Information Communication Technology (ICT) and Internet Awareness Amongst the College and University Teachers
Bibliographic record
Abstract
The of the paper deals with the brief introduction of ICT, Internet and brief account of the status of Higher Education in India , role of UGC in imparting quality education, and Refresher and Orientation Courses being offered by the Academic Colleges of India with special reference to Himachal Pradesh University, Shimla. Further, described in the paper about the need and purpose of the study, objectives, methodology adopted and finally highlights the important survey findings in respect of ICT Awareness and Internet Use pattern of the participants of the refresher course. Besides this, some suggestions and recommendations have also been enumerated in brief. Information Communication Technology (ICT) is one of the important buzzwords of today's IT world. It has changed the society into information society and our way of life. It has been integrated in every walk of our life. Its impact has been evident in railway, air reservations, banking and insurance sectors, postal services, biotechnology, bioinformatics, biomedical sciences, health care sector, telemedicine, media and communications, teaching -learning, library and information services, printing technology, e-resources, digitization of documents, digital library, library networking, e-commerce, & trade, entertainment, and what not? It has penetrated in everywhere and its makes our life comfortable and easy. Throughout the developed world, changes in technologies are permitting the more extensive use of electronics and telecommunications to access information. The trend in information technology use has been described in a number of ways. In USA it is described as 'Information Superhighway', and in Canada it is termed as 'Information Highway'. The European Commission has adopted the term 'Information Society'- emphasizing that the application and development in information infrastructure will have significant social as well as economic impact (Development of Information Society, 1996) During the last couples of years since 1990s, the university libraries and other institutional libraries in India are coming under the impact of information technology. Since last two decades several initiatives have been taken by the Govt. of India for computerisation and networking of Indian of Indian libraries. Recently a Task Force for quick implementation of National Information Policy has been established and the recommendations of Task Force Committee have already been submitted to the Govt. of India for its quick implementation (Sinha and Satish, 2000).
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.001 |
| 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".