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Record W2991813755

Inquiry on the “Six Processes Progressive Research-Based Teaching Mode” in Networked Environment

2015· article· en· W2991813755 on OpenAlexvenueno aff
Shangzhi Zou, Lei Deng

Bibliographic record

VenueCross-cultural communication · 2015
Typearticle
Languageen
FieldComputer Science
TopicHigher Education and Teaching Methods
Canadian institutionsnot available
Fundersnot available
KeywordsConstructiveConstruct (python library)Mathematics educationTeaching and learning centerProcess (computing)Computer scienceCognitionTest (biology)Teaching methodMode (computer interface)Knowledge managementPsychologyMultimediaHuman–computer interaction
DOInot available

Abstract

fetched live from OpenAlex

Research-based teaching is a new teaching concept which developed from the constructive learning theory, and guided by the idea “learn by doing, do by learning, learning whilst doing”. In a networked environment, to construct a teaching method consisted of 6 progressive core processes which are “doing”, “observing”, “experimenting”, “inquiring”, “imagining” and “creating”, would not only fully embody the teaching features of information era, but also enrich students’ cognitive tools make teaching circumstances more vivid. Based on the analysis of 624 middle school students’ test results, it could be seen that “six process progressive teaching mode” has significant improving effects on students’ learning interest, studying attitude, collaborative ability, knowledge level, creating and practical capacity.

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)0.005
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.556
Threshold uncertainty score0.934

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
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 head0.221
GPT teacher head0.487
Teacher spread0.265 · 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 designNot applicable
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
Published2015
Admission routes1
Has abstractyes

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