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Emphasizing Equity: SEERNet’s Reflections on IES’s New SEER Standard for Equity

A focus on equity ensures that research is not conducted “simply for the sake of science.” That’s why SEERNet welcomes IES’s addition of an equity statement to the SEER principles.

Our work to define equity runs through the core of Digital Promise’s work. 

When Digital Promise was launched at the White House in 2011, Secretary of Education Arne Duncan said, “Digital Promise … will help spur breakthrough learning technologies. And it will help make sure Americans of all ages and races, regions and backgrounds can benefit from them.” 

More recently, Digital Promise’s equity statement makes clear our belief that given our position at the intersection of educators, researchers, and developers we hold a “significant responsibility to influence systems, practices, and policies to ensure all learners the opportunity to achieve their highest human potential”, especially those who have been historically and systematically excluded.

Equity Standards

As network lead for SEERNet, it has always been our intent to focus on diversity, equity, inclusion, and access goals, not only for educators and students engaged in the learning technologies, but also for the researchers studying the impact.  When Mark Schneider announced at the spring 2022 IES PI meeting that there would be a new SEER Standard for equity, we were excited to have not only a grounding philosophy in equity but also a standard with associated recommendations. Our digital learning platforms (DLPs) responded similarly. Debshila Basu Mallick, Director of Research at OpenStax, said, “Fairness, Ethics, Accountability, and Transparency (FEAT) have been a cornerstone of the design and implementation of OpenStax Kinetic, and promoting equity and inclusion is a large part of FEAT. The SEER Equity Principle acknowledges that inequities exist and that we must actively work toward diminishing them by improving learners’ outcomes and access to resources and educational opportunities.” 

Following the National Academies’s use of the definition from the Executive Order, we define equity as:

the consistent and systematic fair, just, and impartial treatment of all individuals, including individuals who belong to underserved communities that have been denied such treatment, such as Black, Latino, and Indigenous and Native American persons, Asian Americans and Pacific Islanders and other persons of color; members of religious minorities; lesbian, gay, bisexual, transgender, and queer (LGBTQ+) persons; persons with disabilities; persons who live in rural areas; and persons otherwise adversely affected by persistent poverty or inequality.

(Exec. Order No. 13985, 2021)

Ensuring Equity within Research Practice

When equity is the goal, researchers must consider how it is integrated into the decisions they make at each step of the research process (e.g., design, sample, measure, analysis, and reporting). Additionally, when considering efficacy, the success of an intervention should be defined not only as overall improvements, but also as a decrease in equity gaps related to populations of interest. This requires thinking about measures of equity beyond achievement tests, such as formative assessment data, data on student interactions with and responses to content, and affective and attitudinal measures.  DLPs can offer these types of timely and relevant data. It also requires methods that examine subgroups and intersectionality of race and gender, language background, socioeconomic class, and ability status. To illustrate this within a DLP, Cristina Heffernan, Executive Director of the ASSISTments Foundation said, “A researcher using E-TRIALS might conceptualize educational equity by making sure that the sample of students who have been a part of their study comes from a variety of schools and that the analysis makes sure to take into consideration all the students in the sample in subgroups not just on average.” 

The student-level data needed to disaggregate study data by equity-relevant factors can be harder to generate, and that is an ongoing discussion within SEERNet. Debshila stated, 

Within Kinetic, we are engaging diverse learners and researchers to understand their goals, educational or research contexts, and how we may bring value to both our user groups. We are securely collecting sociodemographic information to enable researchers to diagnose inequities in order to formulate effective systemic remediation. As part of the SEERNet community, we are collectively devising ways in which we can responsibly impact the education system to support our learners’ success in achieving their educational and career goals.

Debshila Basu Mallick, Director of Research at OpenStax

April Murphy, Senior Learning Engineer, Carnegie Learning also shared her hopes that the addition of this standard would enable DLPs to work together to develop best practices to address equity in research conducted across the different platforms. She explained, “For instance, are some platforms better-positioned to address specific equity concerns than others? How might platforms learn from one another in terms of supporting equity in terms of learner-specific demographics, study designs, population recruitment, and communication?”

Learn more about the promise and challenges of equity-centered research in our latest white paper, Navigating the Tensions: How Could Equity-relevant Research Also Be Agile, Open, and Scalable?