The geoscience education research (GER) community of practice: a brief history and implications from a needs assessment survey
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
The geoscience education research (GER) community has evolved and grown over the past several decades. Using Wenger et al.'s Community of Practice (CoP) model (2002), we discuss how the GER CoP (which is broader than the formal discipline of GER) has changed, highlighting noteworthy events and growth points. Trends in community membership and connections are noted. Additionally, we conducted a GER community needs assessment to identify ways in which the CoP could build on its momentum. The survey included questions on CoP member demographics, engagement in GER work, and professional development needs. We received 107 responses, primarily from the United States and from individuals with geology or atmospheric science backgrounds. The survey highlighted the need for intentional outreach to international venues, K-12 teacher audiences, and underrepresented groups in the GER community. The survey also revealed the various ways in which GER CoP members engage in research, teaching, and dissemination activities. The most commonly used resources for increasing GER knowledge were the SERC site and the Journal of Geoscience Education (JGE). Respondents expressed a strong desire for professional development opportunities, including methodological training and community knowledge exchanges. Based on the survey results, recommendations are proposed to enhance the inclusivity, mentorship, and dissemination efforts within the GER community. The findings emphasize the importance of networking, expanding resources, and addressing the needs of diverse members to foster a vibrant and inclusive GER community.
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 | 0.032 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| 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