Event Date & Time
Solving problems using data analysis and logical reasoning is one of the primary goals of a science-based education. One evidence-based tool used to support student learning of this goal is the case-study, where students build and rationalize hypotheses grounded in experimental data. This approach allows students to analyze data, and to practice making logical connections. On the other hand, since different datasets require different hypotheses, students often struggle to improve on their performance from one case to the next, and to generalize their understanding of what makes a “good” hypothesis. As an instructor, it can be difficult to decide what method of support is most effective in helping students learn in this context and over time. In this talk, we present three different approaches to supporting student learning of hypothesis-building in a third-year biology course, tried over three consecutive years. In each year, students were presented with four unrelated case studies throughout the term. During class, students worked in groups to analyze data, and to generate a hypothesis with a supporting rationale. In the first year of our study, a traditional model was used: students submitted work and were provided with instructor feedback on each case. In the second year, students were given a worksheet, which provided scaffolding for the first case study; this scaffolding was gradually removed in subsequent case studies. In the third year, rather than scaffolding, students were given several examples of hypotheses and rationales for the first case study. They were asked to grade this writing, prior to building their own hypotheses in subsequent case studies. From each year of the study, we have collected data on student perspectives, and quality of their written work. In this session, we will compare student outcomes from each of the three approaches, and discuss the broader pedagogical implications.
Robin Young, Instructor, Botany
Miranda Meents, Teaching Assistant, Botany