Good Problems within and Across Disciplines

Daniel Reinholz,Sam Pazicni,Tara Slominski,Chris Rasmussen,Timothy A French,Bradley Mccoy

doi:10.51355/jstem.2018.34

Abstract

This paper focuses on the question of what makes a good disciplinary or interdisciplinary problem. We draw from literature across the STEM disciplines and two conference sessions to provide insight into what makes a good problem within a specific discipline and across the disciplines. We use various frameworks to analyze a variety of problems that were nominated as exemplars by STEM education research experts. Common features identified include real-world connections, reinforcement of conceptual understanding, a low floor and high ceiling, multiple solutions paths, and building dispositions of professionals in the discipline. While a good problem need not have all of these features, in general, good problems have more of these features. We also recognize that these problems are context-specific, as what may be considered a problem for one learner could be a trivial exercise for another. We discuss some of the challenges of designing good interdisciplinary problems and identify some features that can make a problem interdisciplinary, including use of cross-cutting concepts and drawing on the specific expertise of each discipline.

Highlights

This paper addresses the question: what makes a problem good? Thinking beyond problems generally, what makes a problem good for biology, physics, math, engineering, computer science, or chemistry? What are the implications for interdisciplinary problems? In this paper, we discuss a variety of frameworks for thinking about good problems, both within and across disciplines
STEM Discipline Based Education Research (DBER) scholars across their disciplines have spent a considerable amount of time thinking about problems, but there is certainly no consensus across the disciplines
Mathematics educators use the idea of cognitive demand to describe what type of thinking a task requires, whereas biologists have taken up Bloom’s taxonomy

Summary

Introduction

The emphasis on multiple solution paths is pervasive in mathematics education (e.g., National Council of Teachers of Mathematics, 2000), because it allows students to compare and contrast their solutions to develop deeper knowledge Taken together, these problem features are valuable because they support learning across a variety of students in heterogeneous environments (Cohen & Lotan, 1997), which is a real pedagogical challenge. Values / Implications Reasoning from evidence Coordinating macro, submicro, and symbolic Guiding field work Articulation of physical laws Creating tools Real-world solutions Theory building This is not to say that each discipline has only one core practice or type of problem. The Science Education Framework has three major areas of focus for student understanding: disciplinary practices, crosscutting concepts, and core disciplinary ideas (NRC, 2011) Practices are things such as developing and using models, analyzing and interpreting data, or explaining and justifying one’s ideas, that are key to doing the work of STEM professionals. It could be a good disciplinary problem, and a multidisciplinary problem, but not a good multidisciplinary problem because it does not help build core ideas or practices in multiple disciplines

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Discussion