Our assessment research suggests that quantitative business courses that rely primarily on algorithmic problem solving may not produce the deep learning required for addressing real-world business problems. This article illustrates a strategy, supported by recent learning theory, for promoting deep learning by moving students gradually from "well-structured" algorithmic problems with single correct answers to "ill-structured" real-world business problems that may have multiple correct answers and require an argument addressed to a specific audience. We show how these scaffolded communication assignments promote deep learning, and suggest ways that interested faculty can adapt the assignments to their own courses.
In the late 1960s and early 1970s the gender divide in American higher education narrowed rapidly as women shifted their aims from homemaking to careers. The dynamic-social-norms hypothesis explains why we observe unexpected and rapid rather than gradual change in women’s education and employment. The explanation draws on a theory of social change developed by Timur Kuran that predicts revolutionary rather than incremental shifts in social norms. Critical to the argument is the claim that in some settings the choices of individuals depend in part on the choices of others. In the presence of interdependencies, the potential exists for unexpected and rapid transformations, such as that occurring in higher education between 1965 and 1975.
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