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Record W2297038623 · doi:10.14288/1.0078361

The investigation of generative themes in E.S.L. needs assessment

2010· article· en· W2297038623 on OpenAlexaboutno aff
Ellen Joanne Millard

Bibliographic record

VenuecIRcle (University of British Columbia) · 2010
Typearticle
Languageen
FieldPsychology
TopicIdentity, Memory, and Therapy
Canadian institutionsnot available
Fundersnot available
KeywordsGenerative grammarComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

This thesis investigates the "generative theme" as the basis for adult ESL needs analysis and curriculum development. Generative themes consist of the relationship between an objective situation and the perceptions held of that situation by the people involved in it. They form the basis for program content in the pedagogical scheme of Brazilian adult literacy educator Paulo Freire. North American ESL practitioners, notably Nina Wallerstein, Deborah Barndt, and the Toronto ESL Core Group, have developed guidelines for ESL teachers to identify students themes and structure the content of lessons around them. However according to Freire, a full-scale interdisciplinary ethnographic study of the students' community is necessary in order to understand their themes. The primary purpose of this investigation was to determine whether an individual ESL teacher could come up with a thematic analysis that would fulfill Freire's criteria, through a participant-observation case study of an adult ESL class. The second purpose was to identify the themes of these particular students in order to gain some insights as to the relevance of generative themes for learning ESL. The students were four Punjabi-speaking immigrant women enrolled in a homefront volunteer tutor ESL program offered by the Candian Farmworkers Union. I taught the twice-weekly classes for five months, taped them and recorded observations, and then conducted a content-analysis of transcriptions of the tapes in order to identify and rank the topic areas of most and least interest to the students according to time spent discussing them. I then analyzed these topic areas qualitatively, according to whether or not they met Freire's criteria for generative themes. From this analysis several possible themes emerged. Students see their position in Canada as one of "strangers in a strange land. The "strangers" area represents all those aspects of the students' traditional culture which, while sources of affirmation and strength to them, are out of place and irrelevant in Candian society. The "strange land" is Canda and the system - including the English language, the medical and legal system, life in a big city - which is foreign, difficult, alienating and hostile. Bridging the gulf between these two, their main source of contact and therefore of tensions . between them, are the family and the language learning process. Curricular recommendations are that ESL content be focussed on family-related learning needs, and that the curriculum take the approach of affirming the cultural themes that are sources of strength and pride while attempting to lessen the ignorance and alienation which characterizes students' perceptions of Canadian society. Several observations are made regarding the feasibility of investigating generative themes for ESL. Some of the problems are logistical and can be addressed by changing the situation: a strategy to combine Freire's four-stage team approach with the parameters of the classroom setting is proposed. Others, such as the difficulty of conducting 'dialogue' in one-word phrases, and the conflict of roles and agenda between the teaching and research aspects of the investigation, are inherent in the attempt to apply Freire's pedagogy to ESL. This attempt is worthwhile and important, however, because this approach is one of the few that takes into account learners' social context in the organization of curriculum, and that acknowledges the relationship between language learning and power in their lives.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.465
Threshold uncertainty score0.929

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.012
GPT teacher head0.232
Teacher spread0.219 · 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 designObservational
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
Published2010
Admission routes1
Has abstractyes

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