This study examines the efficacy of blended learning – an approach that combines in-class and online methods in a way that leverages the strengths of both – using a field experiment spanning 16 weeks. An information-processing model of learning suggests that learners will weigh the cost of information accessibility against its value in ways that will impact their interactions with the available information sources, which will consequently affect learning outcomes. Results of our study suggest that such an assessment did indeed occur and that it impacted learning performance. Specifically, our results support the idea that providing high-value content in both settings – the classroom (rich, yet high cost) and online (efficient, yet low cost), enhances performance. The largest gains in performance were seen by those who used the blended learning system the most, with the lowest gains by those who did not use the system at all (i.e. the control group).

The Differential File Architecture (DFA) has been previously proposed as a physical database design which confines the volatility of a large database into a small, more manageable file. Although this approach affords many advantages, the use of dual files often results in two accesses to secondary storage. The response performance of the DFA is therefore a key issue, yet the only predictive performance model currently in existence assumes an ideal environment. This paper represents a preliminary step toward developing a general model of DFA performance, applicable to realistic settings in which the distribution of key accesses and the hashing distribution of keys to filter switches are non-uniform. In support of a regression approach to the problem, a metric is developed and tested for suitability as a predictor of non-uniformity effects.