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Record W3127210656 · doi:10.29173/iasl7625

Study on the Prospect of Library Resources Utilization Education Based on the Results of Short Thesis Writing Competitions

2021· article· en· W3127210656 on OpenAlexvenueno aff
Su Mei Cheng, Albert T. Wang, Yuan-Ling Lai

Bibliographic record

VenueIASL Annual Conference Proceedings · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicLibrary Science and Information Literacy
Canadian institutionsnot available
Fundersnot available
KeywordsReading (process)Christian ministryMathematics educationCompetition (biology)Object (grammar)PsychologyPedagogyMedical educationComputer sciencePolitical scienceMedicine

Abstract

fetched live from OpenAlex

In 2004,Taiwan’s Ministry of Education initiated the first Short Thesis Competition for Senior High School Students for the purpose of helping them cultivate reading and researching skills as well as guiding them to make use of library resources and services to do research.Mingdao High School has been practicing a program called “Learning to Learn”, in an attempt to make students, by using various learning strategies, think and learn for themselves so as to adapt themselves to the constantly changing society. To ensure the success of this program, the school library offered courses in short thesis writing, and encouraged students to participate in the island-wide Short Thesis Competitions. To Mingdao High School’s satisfaction, the contestants’ theses were all highly rated.The object of this study is, through an analysis of the results of the short thesis competitions, to understand the efficiency of Mingdao High school’s current education on students’ application of the library’s resources. In addition, we also want to share our experience about how we lead students to write their theses, hoping it will serve as a reference for other senior high schools. The research method this study adopts is called the content-analysis approach. In this paper, the award-winning short theses of the previous years are analyzed, including the types of topics chosen and how reference books are cited. A questionnaire is also used to help us understand how short thesis writing helps students learn.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.338
Threshold uncertainty score0.421

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.003
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.066
GPT teacher head0.312
Teacher spread0.247 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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