New Trend of Information Literacy from Leisure Reading Behavior and Experiences of Junior High School Students
Bibliographic record
Abstract
Information literacy education in school libraries is based on abilities of personal reading and learning. The research was used semi-structured interview in qualitative research to understand the reading behavior and experiences of junior high school students who are leisure reading lover. The analysis of qualitative data included both hermeneutic phenomenology and axial coding in grounded theory. According to research obtained, leisure reading behavior of junior high school students have several conclusion. First, The interesting content is the main motive. Second, the purposes of leisure reading behavior may divide into the tool goal and the non- tool goal. Third, internet is acting both important information source and channel. The analysis of leisure reading experiences of junior high school students have several conclusions. First, there are three kinds of reading styles that included comprehensive reading, tool reading and the non- tool reading. Second, participants often use internet communication software to exchange their reading information in internet reading. Third, participants often read datas which they searched or browsed, E-mail, internet literature and book description in the internet. According to research conclusions, this article discussed how to develop information literacy in junior high school students. These ways includes that use internet technologies to improve interaction, have library instruction classes depend on reading purposes, integrate reading information in school effectively and promotes software and hardware equipment in school to reduce the imformation divide. Finally, this article thought new trend of information literacy.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".