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Record W4388798840 · doi:10.5539/ells.v13n4p48

Effects of Mind Map Integrated Project-Based Learning on the Reduction of English Speaking Anxiety on Chinese Undergraduates

2023· article· en· W4388798840 on OpenAlexvenueno aff
Zhinan Li, Samah Ali Mohsen Mofreh, Jiao Chen, Aihua Zhu

Bibliographic record

VenueEnglish Language and Literature Studies · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicTechnology-Enhanced Education Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyAnxietyProject-based learningMind mapVocational educationMathematics educationBusiness EnglishForeign languagePedagogy

Abstract

fetched live from OpenAlex

The problems of English speaking unproficiency, low interest and silent English classrooms among students in Chinese higher vocational colleges have become an issue in recent years in China. Due to the importance of the mind map has become very popular in English language instruction, this paper carries out a study to investigate the effectiveness of Mind Map integrated Project-Based Learning (PjBL) strategy in public English language teaching in one of the Chinese higher vocational colleges and designs an English speaking project on food in the campus cafeteria. Twenty freshman students majoring in preschool education are selected in the experimental group and divided into four sub-groups of five students per group to select their tasks for the project so that they can be stimulated to finish the project independently and cooperatively. The other twenty students of the same major are in the control group to compare. The study uses mixed methods by combining quantitative and qualitative methods through students’ English speaking anxiety tests before and after the project by using Horwitz’s Foreign Language Classroom Anxiety Scale (FLCAS) and a semi-structured interview as a supplement to investigate. It turns out that the Mind Map Integrated Project-Based Learning (PjBL) Strategy reduced students' English speaking anxiety to a certain degree.

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)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.010
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 science0.0000.000
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 head0.011
GPT teacher head0.315
Teacher spread0.304 · 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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