For decades, national reports have emphasized the importance of quantitative reasoning as a foundational science practice in undergraduate STEM education. Assessment of students’ quantitative reasoning, and other science practices, is critical to demonstrate what students know and are able to do with knowledge. The Vision and Change in Undergraduate Biology Education and the Four-dimensional Ecology Education (4DEE) Framework reports emphasize multidimensional learning as a means of helping instructors define what they want students to learn (core ideas), what they want students to do with their knowledge (science practices), and how they want students to focus their knowledge through multiple lenses (crosscutting concepts). How will we know that students have developed a useful and coherent understanding of ecology? What evidence should inform our instructional designs to help students develop deep and robust understandings of ecology, in this case, the ability to use quantitative reasoning? Quantitative skills include the ability to use quantitative reasoning (QR) and the ability to use modeling. The ‘ability to use’ is the key phrase that sets the benchmark for what is characterized for quantitative skills. This implies that merely adding equations, statistics, and computational tools to our existing courses is not adequate. Yes, we want to teach science as science is practiced, but just adding tools may result in students’ approaching quantitative tasks algorithmically, so they merely plug away without building deep understanding of the concepts. Rather, instruction should provide appropriate scaffolds and conceptual supports that promote quantitative reasoning for all students.
Results/Conclusions
Following Long (2020), we proposed three strategies to implement this type of instruction: (1) immersing in data by collecting visualizing, and interpreting; (2) identifying examples where QR promotes understanding about the underlying core concepts of ecology/biology, and (3) taking time to unpack the reasoning and scaffold strategically. Assessment of learning along the way is critical. We used the Three-Dimensional Learning Assessment Protocol (3D-LAP) to characterize assessments tasks on mathematics and computational thinking and developing and using models that focus on what students are explicitly asked to do. This tool helps instructors develop or modify existing assessment tasks so that they have the potential to elicit evidence of students engaging with three dimensions plus the human-environment interactions of the 4DEE. These assessments, in turn, provide data about students’ achievement of learning objectives that also should promote multidimensional learning using quantitative reasoning.