Suchergebnisse

The provision of public schooling in the United States has primarily been the states' responsibility, but states generally lack the capacity to manage day-to-day school operations. Thus, states delegate responsibility to districts while maintaining some oversight. Forms of oversight include regulations and political and market-based accountability. However, these can only do so much in holding schools accountable for providing high-quality schooling. Administrative accountability based on student outcomes and school process measures presents an alternative to complement other accountability mechanisms. Standardized measures of performance used for administrative accountability can better align curriculum with state standards, improve quality, and signal the skills that society wishes for students to build. However, they can be counterproductive if they are not reliable, valid, or comprehensive. We suggest in this article that no measure is perfect and that the usefulness of test-based accountability depends on whether the measures enhance educational opportunities and reflect shared goals with reliability, validity, and comprehensiveness.

AbstractPeers affect individual's productivity in the workforce, in education, and in other team‐based tasks. Using large‐scale language data from an online college course, we measure the impacts of peer interactions on student learning outcomes and persistence. In our setting, students are quasi‐randomly assigned to peers, and as such, we are able to overcome selection biases stemming from endogenous peer grouping. We also mitigate reflection bias by utilizing rich student interaction data. We find that females and older students are more likely to engage in student interactions. Students are also more likely to interact with peers of the same gender and with peers from roughly the same geographic region. For students who are relatively less likely to be engaged in online discussion, exposure to more interactive peers increases their probabilities of passing the course, improves their grade in the course, and increases their likelihood of enrolling in the following academic term. This study demonstrates how the use of large‐scale, text‐based data can provide insights into students' learning processes.