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Record W4402045086 · doi:10.5539/ells.v14n3p59

Designing Classroom Activities for Senior English Reading: A Case Study from a High School in China

2024· article· en· W4402045086 on OpenAlexvenueno aff
Bo Zhao

Bibliographic record

VenueEnglish Language and Literature Studies · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicTechnology-Enhanced Education Studies
Canadian institutionsnot available
Fundersnot available
KeywordsGeneralizability theoryCompetence (human resources)Status quoReading (process)Class (philosophy)CurriculumMathematics educationPsychologyComputer sciencePedagogyMedical educationMedicinePolitical scienceDevelopmental psychology

Abstract

fetched live from OpenAlex

Reading class is one of the basic courses of English teaching, and activity design is an important tool for improving students' reading competence. The New English Curriculum highlights the subjectivity and initiative of students in English reading classes, so the design of activities in senior English reading class should be student-centered and achieve full advantage of these activities to improve students' reading ability. This study aims to investigate the status quo of activity design in senior English reading class, to explore the problems existing in the teachers' activity design, and to provide suggestions for effective reading activity design. This study, conducted at Jiangsu Province Zhenjiang No.1 High School, China, targeted ten teachers and fifty students from grade ten through questionnaires and interviews, and thirty classes were observed. Based on analysis of the qualitative and quantitative data, to effectively design reading activities and to promote the efficiency of English reading teaching, this research suggests a layered design of activities aimed at enhancing classroom participation and improving students' overall reading competence in English. This research offers insights into designing activities for senior English reading classes, emphasizing that each stage of reading requires activities tailored to its specific objectives. However, the limited number of participants in the study may impact the generalizability of the findings. In the future study, the targeted participants could be enlarged to increase the variety of data sources.

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)0.004
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 score0.051
Threshold uncertainty score0.862

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.013
GPT teacher head0.332
Teacher spread0.320 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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