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Record W4401053158 · doi:10.5539/jel.v13n5p260

Students Learning Achievement and Satisfaction of Chinese Proficiency Test (HSK1) Reading Courses on the Udemy Platform

2024· article· en· W4401053158 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Education and Learning · 2024
Typearticle
Languageen
FieldComputer Science
TopicEnglish Language Learning and Teaching
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyTest (biology)Mathematics educationReading (process)Chinese languageBlended learningLanguage proficiencyEducational technologyMedical educationMedicineLinguistics

Abstract

fetched live from OpenAlex

This study aimed to explore the effectiveness of learning the Chinese Proficiency Test (HSK) 1 reading course through the Udemy platform and assess the learner’s satisfaction with learning the Chinese course on the Udemy platform. The participants were 30 zero-foundation learners with minimal exposure to basic Chinese expressions and were randomly selected from those enrolled in the Chinese course on Udemy. The pretest and post-test were designed for this study, and the researchers sent the satisfaction survey to the Chinese language learners to investigate the learners’ satisfaction. The findings revealed that the students’ post-test scores were significantly higher than the pretest scores; the current online Chinese language courses benefit students in learning the language. The satisfaction survey results showed that learners were satisfied with learning Chinese courses on the Udemy platform.

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.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.247
Threshold uncertainty score0.402

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 communication0.0000.000
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 head0.011
GPT teacher head0.309
Teacher spread0.298 · 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