Development and validation of a social media and science learning 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 purpose of this study is to describe the development and validation of a survey that examines science students’ social media learning behaviours. Inherent in critiques regarding ‘digital natives’ is a need to better understand what the current generation of learners actually do in their social media practices for learning. The survey can help us understand how students actually use social media for learning science. Survey development followed an inductive approach [Brinkman, 2013. Qualitative interviewing. Oxford ebook; Mansourian, 2006. Adoption of grounded theory in LIS research. New Library World, 107(9/10), 386–402; Strauss & Corbin, 1998. Basics of qualitative research: Grounded theory procedures and technique (2nd ed.). Newbury Park, CA: Sage], where survey design was informed by results of focus groups with secondary and post-secondary physics students and the survey was iteratively revised after two cycles of administration and validation interviews. The final version of the Social Media and Science Learning Survey can be used by educators and researchers to understand how social media tools can be leveraged in order to allow learning to emerge and to use this knowledge to frame recommendations and methods for integrating these tools into classroom-based environments.
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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 it