BASIE is a framework for interpreting impact estimates from evaluations. It is an alternative to null hypothesis significance testing. This guide walks researchers through the key steps of applying BASIE, including selecting prior evidence, reporting impact estimates, interpreting impact estimates, and conducting sensitivity analyses. The guide…

Digital skills are increasingly important for labour market outcomes and social participation. Do they also matter for academic performance? This paper investigates the effects of digital literacy on educational outcomes by merging data from the Italian National Assessment in secondary schools with an original data-set on performance tests of…

Individuals have difficulty changing their causal beliefs in light of contradictory evidence. We hypothesized that this difficulty arises because people facing implausible causes give greater consideration to causal alternatives, which, because of their use of a positive test strategy, leads to differential weighting of contingency evidence.…

For students to be successful in STEM, they need "statistical literacy," the ability to interpret, evaluate, and communicate statistical information (Gal 2002). The science and engineering practices dimension of the "Next Generation Science Standards" ("NGSS") highlights these skills, emphasizing the importance of…

There is extensive research on the benefits of making data-informed decisions, but research also contains evidence many educators incorrectly interpret student data. Meanwhile, the types of detailed labeling on over-the-counter medication have been shown to improve use of non-medication products, as well. However, data systems most educators use…

Current educational reform calls for increased integration between science and mathematics to overcome the shortcomings in students' quantitative skills. Data Nuggets (free online resource, http://datanuggets.org) are worksheets that bring data into the classroom, repeatedly guiding students through the scientific method and making claims…

Confidence intervals (CIs) and effect sizes are essential to encourage meta-analytic thinking and to accumulate research findings. CIs provide a range of plausible values for population parameters with a degree of confidence that the parameter is in that particular interval. CIs also give information about how precise the estimates are. Comparison…