- Year 2019
- NSF Noyce Award # 1758419
- First Name Paul
- Last Name Heideman
- Institution College of William & Mary
- Role/Position Professor of Biology
- Workshop Category Track 1: Scholarships and Stipends
- Workshop Disciplines Audience Biological
- Target Audience Noyce Master Teachers, Noyce Teaching Fellows, Undergraduate and/or Graduate Noyce Scholars
- Topics STEM Content Area and/or Convergent Discipline Skills Development
- Session Length 45 minutes
Goals
1. Gain an entry into the research literature on sketching and visualization for STEM learning.
2. Practice a method to teach students sketching skills and visualization skills, with the opportunity to self-assess how students might respond to the instruction and the methods, while also learning how to gain feedback from students on their understanding and ability.
3. Practice a method to engage students in developing their own hypotheses and predictions using model-based reasoning from sketching and/or visualization while providing feedback to their teachers.
Evidence
Drawing and visualization are ubiquitous in STEM disciplines. There exists a substantial literature on drawing-to-learn and on visualization as powerful tools for learning. But the same literature also documents challenges in teaching students how to use drawing/sketching and visualization. Many students resist learning and applying these methods. The approaches from this workshop apply R. E. Mayer’s principles of multimedia learning as part of their theoretical framework (Mayer, 2019. Multimedia Learning, 2nd Ed), along with recent literature on model-based reasoning in relation to drawing-to-learn (e.g., Quillin and Thomas 2015, CBE Life Sciences Education 14:es2). The workshop presenter has published research results on drawing to learn (Heideman et al., 2017, CBE Life Sciences Education 16:ar28), and also has experience in applying information from the research literature in courses. He has ongoing research on use of sketching for learning and model-based reasoning both at the level of college freshmen and high school biology students. In addition, the presenter has received feedback from G6-12 teachers who have applied these methods in their classrooms. This workshop could be presented in abbreviated form as a 30 minute session; for the highly interactive version with multiple opportunities for participants to practice, it would require 60 or 75 minutes. Any of these time lengths could be accommodated for the workshop.
Proposal
Students struggle to replace learning methods that have low effectiveness, such as rereading or reviewing, with effective active learning methods that help build recall and build problem-solving skills. This workshop will explore ways to apply two methods that can help students understand, recall, and reason in science (and perhaps in mathematics). Drawing, sketching, and visualization have extensive evidence from the research literature for effectiveness as a tool for understanding and reasoning, but are known to be challenging for students to learn and adopt for learning and problem solving. For both of these, guided instruction and practice can help students apply these tools effectively for reasoning. The workshop will begin with a brief introduction and rationale from the research literature on drawing to learn and visualization. The workshop will take participants through examples that apply drawing as brief, minimalist sketches that require no artistic expertise, and also through a visualization approach, eyes-closed exercises, both of which help students focus on essentials. Both methods also provide ways for teachers to gain feedback from students. The workshop will include opportunities for small-group and full-group applications followed by Q&A on potential problems. Participants will also work in small groups to practice a method to build student skills for model-based reasoning and problem solving: so-called ‘Change-one-thing – What-would-be-different?’ problems that are based on sketched or visualized models. Both methods can be taught to students as a mechanism to understand hypotheses and make predictions.
