Perilaku Pencarian Informasi Mahasiswa Jurusan Teknologi Pendidikan Tahun 2016 di Perpustakaan Universitas Negeri Padang
Bibliographic record
Abstract
AbstractThis paper discusses the 2016 information seeking behavior of Education Technology Department students at the Padang State University Library. The purpose of writing this paper is to describe: (1) information seeking behavior of 2016 Education Technology students at the Padang State University Library; (2) obstacles in conducting information searches at the Padang State University Library; (3) efforts that can be made to overcome obstacles in conducting information searches at the Padang State University Library. Data collection is done through questionnaires or questionnaires. Based on the results of the study concluded as follows: (1) information seeking behavior of Education Technology Department students in 2016 from the front information seeking behavior of students gave a positive response, (2) obstacles encountered in conducting information searches among them: (a) no information they need ; (b) the incomplete collection needed; (c) there are difficulties in finding collections because they are on different shelves than the OPAC system; (d) inadequate internet network; (e) the service of librarians who are unfavorable and unwise, (3) efforts that can be made to overcome obstacles in seeking information are: (a) providing and completing collections according to the needs of students and lecturers; (b) compile a collection rack that is compatible with the OPAC search engine, so that users can easily find the information they need; (c) improving internet network facilities so that they are not slow, because most students often use the internet to find information they need; (d) as a librarian, it is better to serve the user well and wisely so that they can help the users who find it difficult to find the information needed.Keywords: behavior, information, students, librarians.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.022 | 0.004 |
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".