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Record W3215717296

Teaching Mode of C Language as a Common Course in Local Application-oriented College

2015· article· en· W3215717296 on OpenAlexvenueno aff
Nan Li

Bibliographic record

VenueMicrocomputer applications · 2015
Typearticle
Languageen
FieldComputer Science
TopicHigher Education and Teaching Methods
Canadian institutionsnot available
Fundersnot available
KeywordsComputer scienceMathematics educationActive listeningComprehensionComputational thinkingMode (computer interface)Teaching methodMultimediaHuman–computer interactionArtificial intelligencePsychologyProgramming language
DOInot available

Abstract

fetched live from OpenAlex

C-language is a required computer common course for science students in local application-oriented college. By the way of a questionnaire survey to both teachers and students, it is found that there are huge differences of the students in learning foundation, initiative and individuals in local application-oriented college. From both aspects of teaching and learning, this paper analyzes these problems and discusses the solutions, and then it discusses the teaching thoughts which use computational thinking as the guide. After that, it improves awareness of self-directed learning by the multimedia and multilevel teaching method, and improves interests by the combination of participation, teaching and discussion. In addition, the otherness of comprehension on teachers’ teaching contents can be solved by group lesson preparation, mutual listening and evaluation.

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)0.000
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: Methods · Consensus signal: none
Teacher disagreement score0.737
Threshold uncertainty score0.672

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.012
GPT teacher head0.348
Teacher spread0.336 · 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
GenreMethods

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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