The Visual Science Communication Toolkit: Responding to the Need for Visual Science Communication Training in Undergraduate Life Sciences Education
Bibliographic record
Abstract
Visual representations are essential to scientific research and teaching, playing a role in conceptual understanding, knowledge generation, and the communication of discovery and change. Undergraduate students are expected to interpret, use, and create visual representations so they can make their thinking explicit when engaging in discourse with the scientific community. Despite the importance of visualization in the biosciences, students often learn visualization skills in an ad hoc fashion without a clear framework. We used a mixed-methods sequential explanatory study design to explore and assess the pedagogical needs of undergraduate biology students (n = 53), instructors (n = 13), and teaching assistants (n = 8) in visual science communication education. Key themes were identified using inductive grounded theory methods. We found that extrinsic motivations, namely time, financial resources, and grading practices, contribute to a lack of guidance, support, and structure as well as ambiguous expectations and standards perceived by students and instructors. Biology and science visualization instructors cite visual communication assessments as a way of developing and evaluating students’ higher-order thinking skills in addition to their communication competencies. An output of this research, the development of a learning module, the Visual Science Communication Toolkit, is discussed along with design considerations for developing resources for visual science communication education.
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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 | 0.012 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.017 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.003 | 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; both teacher heads agree on what is shown here.
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".