Using Data in Practice: What Does It Look Like and What Does It Take?
Posted by Laura McLoughlin on November 17, 2021 in categoryFacts & Research

The Research Digest in the current issue of Adult Literacy Education: The International Journal of Literacy, Language, and Numeracy reviews research and theory on how outcomes data is used in adult literacy. 

The authors then make suggestions for how practitioners can effectively use data within their programs. This includes training staff how to use data and using data to motivate learners as well as funders. 

Read an excerpt from “Using Data in Practice: What Does It Look Like and What Does It Take?” below: 

Little rigorous research has been done on the effects of using data to improve learner outcomes; what does exist was conducted in K-12 settings and has shown mixed or null results. However, a small number of promising findings have emerged. For example, May and Robinson (2007) found that providing secondary students with detailed performance information led to greater persistence and improved performance in retaking the state’s graduation test. An additional suggestion based on a systematic evidence review is to create a "cycle of inquiry" to help learners use formative data to reflect on their progress and become their own data-driven decision makers (Hamilton et al., 2009).1 These findings are tempered, however, by another evidence review which suggests that providing learners with timely, individualized, and ongoing qualitative feedback such as immediate identification and explanation of errors—and especially feedback that is presented within the context of a learner’s goal—is more useful than sharing only test scores (National Research Council, 2012). 

Several others have tested the guided use of formative or interim assessments to inform instruction and found positive effects on learning at the elementary and secondary levels (Carlson et al., 2011; Supovitz et al., 2018). However, impacts in one study were found only for schools with a high level of readiness to implement a data-based intervention (West et al., 2016). These findings echo the guiding frameworks described previously and reinforce the idea that there are important contextual factors to consider in using data effectively.

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