The Teaching and Assessment in Second-Language Context: Assessment of Decoding Differences on Language Speakers.
Bibliographic record
Abstract
The language assessment in second language context is still a gap in Portuguese schools and at research settings. Comprehensive diagnostic procedures are expected to be explanatory and to provide classification about proficiency levels. Proficiency, development and application are three components involved in educational assessment, specifically in second language context. Diagnostic and placement should be responsive to ensure the academic success mainly in the first years of schooling. The current international approaches focused on in-depth and broader assessments with strong theoretical basis. Specifically, our research project is developed maintaining the principles of several benchmarks provided by ALBERTA, TESOL, TOEFL and other testing guides. Despite of Portuguese Second Language context, our sources are mainly American instruments regarding the great scientific evidence available. This study will examine the validity and prevalence of 4 specific tasks to differentiate 108 second language learners, considering the socioeconomic factor determined by current job situation of students’ families. Immigration routes are mostly work related and the professional situation of families is extremely diverse and might have influence in school outcomes of young students experiencing constrained economic environments. All the tasks were developed for the first levels of proficiency (A2-B1, according to European benchmarks), including subtests as main criteria of organization and different types of responses (multiple format), applied to a large sample (oversampling is recommended) of diverse students (with the migratory experience as a condition). Across a small scale exploratory study we will have useful information about the adequacy of the test for school staff members, for students and for specific research in second language. Data will be presented regarding the following items: verbal analogies, semantic associations, picture naming, and morphological extraction. The main focus will be on the evaluation of the cognitive academic language proficiency depending on socioeconomic backgrounds identified through the professional situation of two-parent families and attending to their job skills (graduate and non-graduate). The results confirmed the hypothesis that students from low income immigrant families experienced worst performance in general tasks. Implications will be discussed considering that limited socioeconomic families have more failure to provide their children cognitive stimulating activities inside home routines comparing to more stable immigrant contexts.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".