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Record W4318046733 · doi:10.5539/elt.v16n2p67

Objectives and Related Requirements of College English Teaching: A Comparative Textual Analysis of College English Curriculum Requirements and College English Teaching Guidelines (2020 Version)

2023· article· en· W4318046733 on OpenAlexvenueno aff
Qianmei Rao

Bibliographic record

VenueEnglish Language Teaching · 2023
Typearticle
Languageen
FieldComputer Science
TopicEducational Technology and Pedagogy
Canadian institutionsnot available
Fundersnot available
KeywordsCurriculumActive listeningCollege EnglishPsychologyMathematics educationReading (process)Needs analysisTeaching methodValue (mathematics)LiteracyPedagogyComputer scienceLinguistics

Abstract

fetched live from OpenAlex

In order to explore the longitudinal development of the objectives and their related requirements of college English teaching in the last nearly two decades in China, the author adopting the methods of literature reading and textual analysis, draws a diachronic comparison between the College English Curriculum Requirements and the College English Teaching Guidelines(2020 version). Through careful reading and analyzing, the key findings are that at least three-aspect similarities and differences respectively exist in the two documents. For the similarities, the teaching objectives and their related requirements in the two documents both reflect the value orientation of instrumentality, the attention to students’ autonomous learning as well as their comprehensive cultural literacy and the classification of three-level teaching requirements. However, as to the differences, firstly, special attention has been paid to the cultivation of students’ listening and speaking skills in the teaching objectives of the Curriculum Requirements, while humanity in the teaching objectives of the Guidelines(2020 version) has increasingly become a major value orientation; additionally, an overall description of three-level teaching requirements has been made in the Guidelines(2020 version) apart from the individual description of each language skill; lastly, the numbers have been taken full advantage of to quantify English proficiency(five basic language skills) of three levels in teaching requirements of the Curriculum Requirements. Drawing on these findings, some corresponding suggestions are provided with in this paper.

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)0.013
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.184
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.013
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0000.002
Open science0.0010.001
Research integrity0.0000.002
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 head0.029
GPT teacher head0.343
Teacher spread0.314 · 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.

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

Citations0
Published2023
Admission routes1
Has abstractyes

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