Atlas use in teaching geography in higher education in the U.S. and Canada
Bibliographic record
Abstract
Skills in map use and interpretation are important in geography education. Atlases represent special collections of maps that can be beneficial for developing map use and interpretation and spatial analysis skills in geography students. In this study, we examine the utilization of atlases in geographic coursework. We surveyed 295 geography instructors in the U.S.and Canada about their usage of both print and digital atlases in geography courses of different level. The survey generated 54 responses. The findings indicated that about 39 percent of instructors use atlases in instruction, most of those use print atlases rather than digital atlases. It was found that most of the instructors who use atlases in their instruction teach upper-level Human Geography courses. Some other general courses, in which atlases were used are: Introduction to GIS, Remote Sensing, World Regional Geography, and Introduction to Physical Geography. As indicated by the survey responses, atlases are widely used in special topic courses such as World Forests, Geography of North America, Research Methods in Geography, Natural Hazards, Geography of Europe, History and Theory of Geography, Current World Affairs, Geography of Pennsylvania, Political Geography, Geography of Russia, North American House Types, and Geography of Consumption. In addition to analyzing the survey responses, we also provide examples of atlas use in a variety of courses. We conclude that atlases are useful for studies of spatial associations and geographic patterns, as a background information or context resource, as a source that helps to learn geographic locations, and to learn cartographic methods and map design.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 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".