Reviewing Digitally Simulated Learning Environments and Cross-Curricular Competencies in Kinematics Education
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Research has shown that students studying kinematics struggle with foundational concepts, such as the idea of constant vertical acceleration due to gravity. One of the strategies teachers have used to engage students in progressing towards normative scientific conceptions is the use of digitally simulated science laboratory (DSSL) environments. In addition to canonical conceptual learning, educational bodies are also increasingly focused on how acts of disciplinary doing should guide learning experiences. These are expressed in curricula through competencies such as scientific inquiry, critical thinking, and problem-solving. However, it can be challenging to operationalize and assess these competency indicators within disciplinary contexts. The purpose of this literature review is to assist in the development of a theoretical framework to operationalize the teaching and assessment of these competencies in a DSSL environment, specifically in the context of kinematics education. Our literature review is framed by four main topics: student conceptions of projectile motion, the role and impact of DSSL environments in physics instruction, the types of performance assessments used in kinematics, and how cross-curricular competencies may be defined in the context of kinematics, offering an exemplar of a framework for how contemporary curricular reforms can be meaningfully achieved in a disciplinary context.
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.
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 | 0.002 | 0.001 |
| 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 | 0.001 |
| 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 it