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Record W2784736471 · doi:10.5334/jime.455

Secondary Students’ Perceptions of Open Science Textbooks

2018· article· en· W2784736471 on OpenAlexaboutno aff
Rebecca Morales, Alesha Baker

Bibliographic record

VenueJournal of Interactive Media in Education · 2018
Typearticle
Languageen
FieldComputer Science
TopicOpen Education and E-Learning
Canadian institutionsnot available
Fundersnot available
KeywordsMathematics educationPublishingOpen educational resourcesPsychologyPresentation (obstetrics)MainstreamPerceptionPedagogyQuarter (Canadian coin)Medical educationPolitical scienceGeographyMedicine

Abstract

fetched live from OpenAlex

In an attempt to align instructional resources with new state standards and to increase teacher awareness of these standards, one large suburban public school district piloted the development and adoption of open secondary science textbooks. Open textbooks created by teachers in grades six through nine replaced conventional science textbooks provided by mainstream publishing companies. Therefore, grade nine students were not included in this study. At the end of the first quarter, middle school students (grades six through eight) who used the open textbooks were surveyed. Survey responses required respondents to consider their learning before and during the use of the open textbook. The survey included quality and presentation of content questions, as well as an opportunity for students to explain their responses. There were qualitative and quantitative indications that students’ perceptions of an open textbook in place of a standard textbook are improving students’ attitudes and behaviors toward learning.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesOpen science
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.999
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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.

Opus teacher head0.022
GPT teacher head0.395
Teacher spread0.373 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designObservational
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

Citations18
Published2018
Admission routes1
Has abstractyes

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