Teaching students to explain the pathophysiology of diseases to lay audiences with a scaffold that supports student choice
| Autor: | Louise Lexis, Brian L Grills, Brianna L. Julien, Debbi Weaver |
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| Rok vydání: | 2021 |
| Předmět: | |
| Zdroj: | Advances in Physiology Education. 45:281-289 |
| ISSN: | 1522-1229 1043-4046 |
| DOI: | 10.1152/advan.00016.2020 |
| Popis: | Expert educators in science argue that science graduates are often lacking skills in effectively communicating scientific information to lay audiences. To address this, we designed a project, Communicating Disease, for final-year undergraduate human pathophysiology students. Students chose a disease, a relevant nonscientific target audience, and a mode of communication and produced a communiqué designed to educate the audience on the pathophysiology of the disease. Separately, students justified their choice of disease and target audience. Upon completion of the project, students completed an anonymous questionnaire, and their submitted work was analyzed. Our study demonstrated that students thought it was important to learn how to effectively communicate science to a lay audience and felt that the project had supported them in developing knowledge and skills that enabled them to do so. Students were adequately challenged, and most students gave their best effort to the project, indicating a high level of engagement. Evaluation of student performance was consistent with the students’ own perceptions and showed that most students communicated the pathophysiology effectively to the target audience and appropriately justified their choice of disease and target audience. Nevertheless, opportunities for improvement with some aspects of communication, production quality, and creativity were evident. This model is suitable for a range of scientific disciplines to engage students in developing their ability to communicate scientific information to lay audiences—a skill that it can be argued is vital for improving the scientific literacy of our community at large. |
| Databáze: | OpenAIRE |
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