Addressing bias in our systematic review of STEM research

 
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Research is a conversation. Researchers attempt to answer a study question, and then other groups of researchers support, contest or expand on those findings. Over the years, this process produces a body of evidence representing the scientific community’s conversation on a given topic. But what did those research teams have to say? What did they determine is the answer to the question? How did they arrive at that answer?

That is where a systematic review enters the conversation. We know, for example, that a significant amount of research exists exploring gender differences in mathematics achievement, but it is unclear how girls’ math identity contributes to or ameliorates this disparity. In response, we are conducting a systematic review to understand how improving girls’ math identity supports their participation, engagement and achievement in math. This review will assist us in moving from a more subjective understanding of the issue to a rigorous and unbiased assessment of the current evidence to date.

Developing a systematic review protocol requires thoughtful decision-making about how to reduce various forms of bias at each stage of the process. Below we discuss some of the decisions made to reduce bias in our systematic review exploring girls’ math identity, in the hopes that it will inform others undertaking similar efforts.

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Gearing up to enhance college readiness for underserved students: Insights from a capacity building workshop

 
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I was fortunate to attend the National Council for Community and Education Partnerships (NCCEP)/ Gaining Early Awareness and Readiness for Undergraduate Programs (GEAR UP) 2018 Capacity Building Workshop in Las Vegas, Nevada. The three-day workshop brought together GEAR UP community partners, school and district administrators, and researchers from across the country for professional learning.

Each day of the workshop began with a keynote address. Linda Cliatt-Wayman, principal and renowned school-turnaround expert, spoke of her motivational story to transform Philadelphia schools on the Persistently Dangerous List. Greg Simon, President of the Biden Cancer Initiative, stressed the importance of communication, shared data, and coming together to share practices and strategies. Natalie Spiro, Founder and President of Drum Café West Coast, led the audience through an interactive drumming performance illustrating GEAR UP’s collective voice and unity of purpose. Even an Elvis impersonator came to liven things up!

But what I found most informative and inspiring were the seminars after each keynote. It was during these sessions that peers from various disciplines from across the country could discuss their successes and difficulties, share strategies and practices, and more importantly share alternate perspectives on common issues and topics. In this post, I share some of my personal insights from those discussions.

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Strengthening capacity to track, store and use data effectively at Catholic and independent schools

 
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I’ll be the first to confess that my research most often focuses on the public school system, with the inherent but weak assumption that strong practices and strategies in public schools can loosely apply to non-public schools (i.e., Catholic and independent schools). But as an education researcher, I’m intimately aware that setting and populations matter and just because an intervention works in a public school doesn’t mean it will work in a nearby independent school.

So, I was pleasantly surprised when I and a few of my colleagues recently had the opportunity to work with a network of Catholic and independent schools in Minnesota to 1) support the integration of assessment data into ongoing school improvement processes, and 2) promote best practices in data collection, assessment and use. I was excited to be able to directly apply my experience and learn about their data issues and concerns. Below I highlight some of my lessons learned in working with the schools and across the network, in the hopes that it will assist other Catholic and independent schools as they seek to use data to inform their practice.

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Investigating STEM and the importance of girls’ math identity

 
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Despite significant progress in closing the gender gap in science, technology, engineering and math (also known as STEM), inequities in girls’ and women’s participation and persistence in math and across STEM education and careers remain. According to the U.S. Census Bureau, women make up nearly half of the U.S. workforce but just 26 percent of STEM workers, as of 2011. Within STEM, the largest number of new jobs are in the computer science and math fields; however, the gender gap in these careers has increased rather than decreased, with female representation decreasing since 2000.

While much of the current STEM research has focused heavily on the barriers and reasons why there aren’t more girls or women in STEM-related fields, here we argue that future research must focus on how to design and develop effective approaches, practices, situations, tools, and materials to foster girls’ interest and engagement.

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7 takeaways from changes in US education grant programs

 
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I recently had the opportunity to attend a workshop on the U.S. Department of Education’s (ED) new Education Innovation and Research (EIR) grant competition. EIR is the successor to the Investing in Innovation (i3) grant program, which invested approximately $1.4 billion through seven competitions from 2010 to 2016 to develop, validate and scale-up evidence-based programs in education. Like i3, EIR implements a tiered award structure to support programs at various levels of development. This blog post summarizes my seven takeaway points from the workshop. These seven points highlight the main changes in the transition from i3 to EIR.

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Gearing up to address attrition: Cohort designs with longitudinal data

 
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As education researchers we know that one of the greatest threats to our work is sample attrition – students dropping out of a study over time. Attrition plays havoc with our carefully designed studies by threatening internal validity and making our results uncertain. To gear up for our evaluation of the Pennsylvania State Gaining Early Awareness and Readiness for Undergraduate Programs (GEAR UP), we designed a three-pronged approach to handling sample attrition. We describe it here in case it can be helpful to others.

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