Differentiated Instruction and Portfolio Assessment: Motivating Young Greek-Romani Students in the English Class
Bibliographic record
Abstract
The socio-cultural changes taking place in Greek classrooms over the last years have rendered the modification and revising of the existing teaching material critical. It is argued that in classes with cultural minorities, students’ needs should be put at the forefront, and teaching objectives should be adapted accordingly. The aim of the present study is to investigate the effectiveness of differentiated instruction and alternative assessment in the teaching of English to diverse population classes within a three-month period. The research focuses on the effect these approaches primarily have on triggering students’ motivation and, secondarily, on their overall linguistic development. In particular, the study examines the outcomes of two groups of diverse population students attending the third grade of primary school. The experimental group was taught through differentiated instruction, while the control group attended the traditional class. The tools employed were a needs analysis questionnaire, a pre- and post-test, portfolio evaluation checklists and semi-structured interviews. The results of the questionnaires showed students’ preference for non-traditional teaching strategies. The findings of the pre- and post-tests revealed that there is a greater progress regarding the skills of the experimental group. However, the statistical analysis (SPSS 26) showed that there are no significant differences. The answers of the portfolio assessment checklists, although scarce, featured the motivating role of portfolios in students’ engagement. The results of the semi-structured interviews showed the student’s positive overall attitude towards the employed strategies. Nevertheless, the wide attendance outflow, the short research period, the limited sample, as well as the lack of equipment provision suggest more extended future research.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".