An Evaluation of an Innovative In-Service Teacher Training Model in Turkey
Bibliographic record
Abstract
A project, with the support of the UNICEF and the Ministry of National Education in Turkey (MoNE), was carried out to develop and implement an in-service teacher training programme aiming at changing participating teachers’ perceptions and practices regarding inclusive education. Within scope of the programme, ten separate modules were developed, each of which focusing on developing teachers’ skills in certain aspects of inclusive education. Within the project, an in-service teacher training model was developed to guide the design of the ten modules in terms of the process, content and materials utilized. The model encompasses hands-on and inspiring teaching methods, the teachers’ collaboration and flexibility in terms of bringing the teachers’ ideas and experiences to the process. For this study, of these modules, “Teaching and Assessment” was chosen to evaluate the effectiveness of the in-service teacher training model in terms of ensuring teacher change. The module aimed at developing the participating teachers’ pedagogical skills in order for them to carry out differentiated instruction and formative assessment. Approximately eight thousand teachers were trained through the Teaching and Assessment Module across Turkey from September to November in 2018. Data for the present study was collected through focus group discussions (FGD). In total, four FGDs were held with randomly selected 27 teachers who participated in the Teaching and Assessment Module. Content analysis was performed in order to analyse the data obtained from the FGDs. According to the results of the study, it was found that although a “one-shot” in-service training approach was implemented, significant changes occurred both in the teachers’ perceptions, awareness and practices regarding inclusive education. However, it was noted that certain factors such as the organization, in particular the place and time of training sessions could be improved. Furthermore, excessive use of worksheets and lack of subject specific examples were criticised by some FGD participants.
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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 | 0.008 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".