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Record W2541744554 · doi:10.5539/jel.v5n4p291

Reflections on a School Teaching: An Exemplary Teaching about Primary Productivity & Energy Flow in Natural Ecosystems

2016· article· en· W2541744554 on OpenAlexvenueno aff
Maria Kalathaki

Bibliographic record

VenueJournal of Education and Learning · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Sustainability and Education
Canadian institutionsnot available
Fundersnot available
KeywordsWorksheetMathematics educationPleasurePsychologyTeaching methodPedagogyChemistry

Abstract

fetched live from OpenAlex

<p>The research has been carried out in the material that Biologist teacher have prepared for the students and teachers, focusing mostly on the sub-query of teacher’s self-assessment, since teacher had written a self-assessment, a reflection, upon differentiation points from an ordinary teaching, with a structured way. This paper searches on the reflections on a school exemplary teaching of Biology about primary productivity & energy flow in natural ecosystems.</p><p>Graduated students of Lyceum were asked to answer a questionnaire on how they felt during the lesson and how they assessed themselves toward the teaching, in relation to the content taught, the methodology followed, their performance and the degree of involvement with a students’ Evaluation Sheet.</p><p>In a self-assessment process, the teacher asked to reflect where this exemplary teaching is differentiated from the ordinary. A content analysis was held in the material that Biologist teacher had prepared to satisfy the demands of the exemplary teaching. This material was given to the students in the beginning of the teaching, consisted of a multipage printed document with the flow diagram, the worksheet, the parallel texts for home study and the self-evaluation sheet.</p><p>The statistical analysis of the replies of the Students’ Evaluation Sheet revealed the feeling of pleasure experienced by students and success of teacher. All data, when analyzed carefully, enables teacher’s self-assessment for further improvement.</p>

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.557
Threshold uncertainty score0.310

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.012
GPT teacher head0.300
Teacher spread0.288 · 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 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

Citations1
Published2016
Admission routes1
Has abstractyes

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