MétaCan
Menu
Back to cohort
Record W4220986308 · doi:10.5539/ies.v15n2p182

Problems of Internship of Professional Experience in Teaching Mathematics

2022· article· en· W4220986308 on OpenAlexvenueno aff
Apantee Poonputta, Autthapon Intasena

Bibliographic record

VenueInternational Education Studies · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicTechnology-Enhanced Education Studies
Canadian institutionsnot available
FundersMahasarakham University
KeywordsInternshipMathematics educationBachelorPsychologyCore-Plus Mathematics ProjectTest (biology)Statistical analysisSample (material)Connected MathematicsMathematicsPedagogyMedical educationMedicineStatisticsChemistry

Abstract

fetched live from OpenAlex

The purposes of the research were (1) to study the problems of internship of teachers in teaching mathematics programs and (2) to compare the problems internship of teachers regarding the classes and educational level. Mixed method research was employed for the study. Quantitative data from 242 sample teachers and interview data from 12 teachers. The research instruments were a questionnaire and an interview form. The statistics used were percentage, mean, standard deviation and t-test. Results of the research were as follows. 1. The research findings showed that the average problem of the teachers about teaching Mathematics was the total and five domains at a moderate level. Whereas, assessment and evaluation at a low level. 2. The findings indicated that the problems of the teachers about teaching Mathematics regarding the secondary school teachers about teaching Mathematics was more than that of the primary school teachers at the .05 level of the statistical significance. Whereas, bachelor degree and post graduate degree was not different.

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)0.002
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 score0.155
Threshold uncertainty score0.321

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.155
GPT teacher head0.511
Teacher spread0.355 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueInternational Education StudiesSame topicTechnology-Enhanced Education StudiesFrench-language works237,207