Effects of Instruction-Supported Learning with Worked Examples in Quantitative Method Training
Bibliographic record
Abstract
An experimental field study at a German university was conducted in order to test the effectiveness of an integrated learning environment to improve the acquisition of knowledge about empirical research methods. The integrated learning environment was based on the combination of instruction-oriented and problem-oriented design principles and consisted of twelve worked examples. An elaboration intervention was administered as instructional support. The effectiveness of the learning environment both with and without the elaboration intervention was assessed using knowledge application tasks (near and far transfer), which were applied after the training phase. In addition, student’s self-reports on mindfulness (Salomon & Globerson, 1987) were collected. The training was implemented into the regular curriculum. The participants were advanced students in educational science. Both experimental groups (with elaboration intervention: n = 26; without elaboration intervention n = 27) clearly outperformed the control group (n = 17) in the knowledge application tasks. In order to (successfully) foster transferable applicable knowledge, instructional support provided via the elaboration intervention was in fact necessary. Furthermore, the self-reports of students in the experimental group with elaboration intervention showed higher mindfulness scores than those without it. Our results indicate that the integrated learning environment developed in this study can be implemented to improve the acquisition of knowledge about empirical research methods both effectively and efficiently.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".