Documenting and Assessing Learning in Informal and Media-Rich Environments
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
An extensive review of the literature on learning assessment in informal settings, expert discussion of key issues, and a new model for good assessment practice. Today educational activities take place not only in school but also in after-school programs, community centers, museums, and online communities and forums. The success and expansion of these out-of-school initiatives depends on our ability to document and assess what works and what doesn't in informal learning, but learning outcomes in these settings are often unpredictable. Goals are open-ended; participation is voluntary; and relationships, means, and ends are complex. This report charts the state of the art for learning assessment in informal settings, offering an extensive review of the literature, expert discussion on key topics, a suggested model for comprehensive assessment, and recommendations for good assessment practices. Drawing on analysis of the literature and expert opinion, the proposed model, the Outcomes-by-Levels Model for Documentation and Assessment, identifies at least ten types of valued outcomes, to be assessed in terms of learning at the project, group, and individual levels. The cases described in the literature under review, which range from promoting girls' identification with STEM practices to providing online resources for learning programming and networking, illustrate the usefulness of the assessment model.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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