What makes informal education programs successful? (Total Solar Eclipse 2001 – live from Africa)
Bibliographic record
Abstract
“Total Solar Eclipse 2001” - live from Africa Abstract: Evaluation and assessments of informal education programs have been challenging because of the diverse nature of objectives, setups, and expected outcomes of these programs. Almost all institutions that develop and present such programs include evaluation specialists in their staff. However, for very large public outreach efforts, large evaluation groups/institutions can contribute more objective and extensive evaluation and assessment instruments that will help to identify whether the program was successful and if the learning objectives were achieved. Approximately 42,000 people participated in “Total Solar Eclipse 2001” at 164 public venues, including 21 museums internationally, science centers, and planetariums. We will expand further on the properties of this program that help to determine whether it was successful or not. Success can be affected by such issues as personal interest in the content, publicity, connectivity to a group, educational as well as entertainment value, and the challenges of using high technology. Introduction Informal education can be defined as the overlap between formal education (i.e., K-14 curriculum development, educator workshops, and links to systemic reforms) and public outreach (i.e., Internet, popular science articles, educational TV, radio programs). Informal education combines educational substance with public outreach, but without the pressure of examinations and assessment. More explicitly, it includes museum exhibits, science center programs, and planetarium shows. It can include educational activities carried out by community organizations such as scouts, girls and boys clubs, 4H, and other youth groups. It engages students, educators, and the general public in settings away from the classroom; provides learning opportunities, and motivates further learning and lifelong interest (Morrow, 2000).
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 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".