Bibliographic record
Abstract
Icinde bulundugumuz bilgi caginda; ogrenciler ogrenme ortaminin merkezine yerlestirilmeye calisilmaktadir. Bu surecte proje tabanli egitimin kullaniminin temel amaci ogrencilerin ogrenmesini saglayarak bilissel, duyussal ve psikomotor gelisimlerine katkida bulunmaktir. Bu baglamda proje tabanli egitimin kullanimiyla ilgili calismalarin incelenmesinin ve sonuclarin degerlendirilmesinin onem tasidigi dusunulmektedir. Bu dusunceden hareketle bu calismada, son yillarda ogrenme-ogretme surecinde proje tabanli egitimin kullanim durumlarinin ele alindigi calismalar incelenerek bir icerik analizi calismasi yapilmistir. Calismada kullanilacak makaleleri belirleyebilmek amaciyla arastirmacilar tarafindan birtakim tarama ve secim olcutleri belirlenmistir. Olcutler belirlendikten sonra, egitimde proje tabanli egitim kullaniminin ingilizce ele alindigi calismalarin yayimlandigi Scopus isimli veri tabaninda yer alan 2012-2016 yillari arasinda yayimlanmis olan sayilari “( title-abs-key ( project based learning ) and title-abs-key ( social sciences ) and title-abs-key ( teacher ) ) and doctype ( ar ) and ( limit-to ( pubyear , 2016 ) or limit-to ( pubyear , 2015 ) or limit-to ( pubyear , 2014 ) or limit-to ( pubyear , 2013 ) or limit-to ( pubyear , 2012 ) )” anahtar sozcukleri temele alinarak taranmistir. Tarama sonucunda belirlenen olcutlere uygun olan 57 makale ve bu makalelerde, “arastirma konusu, calisma grubu buyuklugu, calisma grubu belirleme turu, arastirma turu, veri toplama araclari ve veri analiz yontemleri” bakimindan incelenmistir. Calismanin, ulasilan bulgularla gelecekte yapilacak olan calismalara yol gosterici olabilecegi dusunulmektedir.
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 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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.021 | 0.003 |
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".