Exploring the Benefits of Combined Outdoor Adventure Education and Dual-Immersion Short-Term Study Abroad Experiences
Bibliographic record
Abstract
Outdoor adventure education (OAE) and study abroad share many epistemological and pedagogical foundations and have been on parallel tracks for many years yet rarely intersect. This paper has two goals: (a) to invite study abroad researchers and practitioners to consider findings and practices from OAE to further enhance study abroad, and (b) to explore the benefits of combining OAE and study abroad practices by presenting such a model. Three questionnaires (pre, post, and 1-year after) were distributed to 32 students in 2012 and 2015 who participated in a combined OAE and dual-immersion study abroad experience. Responses were analyzed to identify central learning outcomes and critical elements. Overall, the findings affirm that the combined model of OAE and study abroad provided meaningful learning and point to a number of potential benefits of combining study abroad and OAE as an effective means of enhancing shared learning goals. Abstract in Japanese 野外冒険教育（OAE）と留学（スタディアブロード）は認識論的にも教育学的にも、その土台とするところに共通点を持ちながら、これまで互いに関係づけて論じられることがなかった。この論文は次の２つの目標を持つ；１）スタディアブロードの研究者や実践者らが、OAE研究の成果や実践から知見を得ること、２）OAEとスタディアブロードの実践を組み合わせることの利点を、事例から探求すること。本研究では、OAEと二重イマージョンのスタディアブロードを織り交ぜた体験プログラムに2012年と2015年に参加した32人の大学生を対象として、質問用紙が三度（事前、事後、1年後）送られた。収集された回答は、プログラムからの主たる学びは何かと、それにつながった要素を焦点に分析された。その結果、OAEとスタディアブロードを組み合わせたプログラムは、価値ある学びを提供したことが明らかになった。また両者を組み合わせることは、互いに共通する教育目標をより高める効果的なやり方として、いくつもの利点を持つ可能性を示した。
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".