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Record W2945989398 · doi:10.29173/iasl7890

A Critical Evaluation of Year 7 Students’ Reflections on the Use of Information Skills when Completing a Curriculum Related Project

2021· article· en· W2945989398 on OpenAlexvenueno aff
James E. Herring

Bibliographic record

VenueIASL Annual Conference Proceedings · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicLibrary Science and Information Literacy
Canadian institutionsnot available
Fundersnot available
KeywordsInformation literacyMathematics educationCurriculumPsychologyRelation (database)Process (computing)Computer scienceMedical educationPedagogy

Abstract

fetched live from OpenAlex

While there have been a large number of books, articles and reports on information literacy in schools, there is a lack of empirical evidence in relation to the use of information literacy models in schools, Wolf (2003) and Herring, Tarter and Naylor (2000 and 2002) being exceptions. The purpose of this pilot study was to examine students’ reflections on the information skills process following the use of an information skills scaffold (the PLUS model) during the completion of an assignment in a secondary school in the UK. The study takes a constructivist approach and data was gathered via a post-assignment questionnaire given to students. Results show that students’ confidence was variable at the start of the assignment; that students found the completion of a concept map to be generally helpful; that almost 50% of students found that completing a concept map made them more confident; that students used the concept map when searching for information; that students used a range of print and electronic sources of information; that students’ preferences for using particular types of resources included both print and electronic sources; that students found the PLUS model to be helpful with their project; and that most students were prepared to consider using the model when completing future assignments.

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)0.002
metaresearch head score (Gemma)0.007
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 score0.288
Threshold uncertainty score0.828

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.011
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 head0.128
GPT teacher head0.403
Teacher spread0.276 · 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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