Student learning during a project based unit in a secondary classroom
Bibliographic record
Abstract
Project based learning (PBL) is recognized as a student-centred instructional model that focuses on student collaboration to solve a real world question that results in the creation of a final product (Kokotsaki, Menzies, & Wiggins, 2016). While literature reviews of PBL reveal that teachers perceive students to be more motivated, more collaborative, and more successful when PBL is used in the classroom, the majority of research focuses only on perceptions rather than measures of student learning. Using a mixed methods triangulation-convergence design (Creswell & Plano Clark, 2007) this study gathered detailed classroom observations, one-on-one student interviews, and student surveys to examine what, if any, student learning occurred. In addition, levels of student engagement, during both a PBL and non-PBL unit, were measured. These measures aimed to improve the validity of research that reports on student learning and engagement in relation to PBL in the secondary classroom. Key recommendations are included to help teachers, administrators, and policy advocates regarding the use of PBL opportunities to develop students
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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".