Designing Websites for Learning and Enjoyment: A study of museum experiences
Bibliographic record
Abstract
This study reports on an exploratory research study that examined the design of websites that encourage both learning and enjoyment. This study examines museum websites that offer educational materials. As part of their mission, most museums provide the general public educational materials for study and enjoyment. Many museums use the Internet in support of their mission. Museum websites offer excellent opportunity to study learning environments designed for enjoyment. Computer-supported learning of various types has been studied over the years, including computer-aided learning, computer-aided instruction, computer-managed learning, and more recently, learning via the Internet. However, the concept of online learning for enjoyment – specifically when learning is not part of a formal instructional undertaking – has not been well studied and thus is not well understood. Some relevant work appears in the literature on pleasure (Telfer, 1980), happiness (Perry, 1967; Veenhoven, 1984), playfulness (Lieberman, 1977; Webster & Martocchio, 1992), and flow (Csikszentmihalyi, 1990; Pace, 2004). The study reported here seeks to redress this gap in the literature, specifically ‘learning for enjoyment,’ by reporting on a number of semi-structured in-depth interviews with museum and educational experts in Taiwan. Our study identified a number of characteristics required of online learning websites, and we conclude some suggested guidelines for developing an online learning website for enjoyment.
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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 | 0.002 | 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 | 0.000 | 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".