blog posts and news stories

Considerations for Conducting Research in Digital Learning Platforms

Along with Digital Promise and members of the initial SEERNet research teams, we recently authored a paper illustrating some of the mindset shifts necessary when conducting research using digital learning platforms.

Researchers with traditional backgrounds may need to think flexibly about how to frame their research questions, collaborate closely with developers, identify log data that can inform implementation, and consider iterative study designs.

The paper builds on prior publications and discussions within SEERNet and the broader DLP-as-research infrastructure movement, visit SEERNet.org for more information.

Read the full paper here

Looking Back to Move Forward

We recently published a paper in collaboration with Digital Promise illustrating the historical precedents for the five digital learning platforms that SEERNet comprises. In “Looking Back to Move Forward,” we trace the technical and organizational foundations of the network’s current efforts along four main themes.

By situating this innovative movement alongside its predecessors, we can identify the opportunities for SEERNet and others to progress and sustain the mission of making research more scalable, equitable, and rigorous.

Read the paper here.

Navigating the Tensions: How Could Equity-Relevant Research Also Be Agile, Open, and Scalable?

Our SEERNet partnership with Digital Promise is working to connect platform developers, researchers, and educators to find ways to conduct equity-relevant research using well-used digital learning platforms, and to simultaneously conduct research that is more agile, more open, and more directly applicable at scale. To do this researchers may have to rethink how they plan and undertake their research. We wrote a paper identifying five approaches that could better support this work.

1. Reframe research designs to form smaller, agile cycles that test small changes each time.
2. Researchers could shift from designing new educational resources to determining how well-used resources could be elaborated and refined to address equity issues.
3. Researchers could utilize variables that capture student experiences to investigate equity when they cannot obtain student demographic/identify variables.
4. Researchers could work in partnership with educators on equity problems that educators prioritize and want help in solving.
5. Researchers could acknowledge that achieving equity is not only a technological or resource-design problem, but requires working at the classroom and systems levels too.

We hope that this paper (Navigating the Tensions: How Could Equity-Relevant Research Also Be Agile, Open, and Scalable?) will provide insights and ideas for researchers in the SEERNet community.

Read the paper here.

Instructional Coaching: Positive Impacts on Edtech Use and Student Learning

In 2019, Digital Promise contracted with Empirical Education to evaluate the impact of the Dynamic Learning Project (DLP) on teacher and student edtech usage and on student achievement. DLP provided school-based instructional technology coaches with mentoring and professional developing, with the goal to increase educational equity and impactful use of technology. You may have seen the blog post we published in summer 2020 announcing the release of our design memo for the study. The importance of this project was magnified during the pandemic-induced shift to an increased use of online tools. 

The results of the study are summarized in this research brief published last month. We found evidence of positive impacts on edtech use and student learning across three districts involved in DLP.  

These findings make a contribution to the evidence base for how to drive meaningful technology use in schools. This should continue to be an area of investigation for future studies; districts focused on equity and inclusion must ensure that edtech is adopted broadly across teacher and student populations.

Empirical Describes Innovative Approach to Research Design for Experiment on the Value of Instructional Technology Coaching

Empirical Education (Empirical) is collaborating with Digital Promise to evaluate the impact of the Dynamic Learning Project (DLP) on student achievement. The DLP provides school-based instructional technology coaches to participating districts to increase educational equity and impactful use of technology. Empirical is working with data from prior school years, allowing us to continue this work during this extraordinary time of school closures. We are conducting quasi-experiments in three school districts across the U.S. designed to provide evidence that will be useful to DLP stakeholders, including schools and districts considering using the DLP coaching model. Today, Empirical has released its design memo outlining its innovative approach to combining teacher-level and student-level outcomes through experimental and correlational methods.

Digital Promise— through funding and partnership with Google—launched the DLP in 2017 with more than 1,000 teachers in 50 schools across 18 districts in five states. The DLP expanded in the second year of implementation (2018-2019) with more than 100 schools reached across 23 districts in seven states. Digital Promise’s surveys of participating teachers have documented teachers’ belief in the DLP’s ability to improve instruction and increase impactful technology use (see Digital Promise’s extensive postings on the DLP). Our rapid cycle evaluations will work with data from the same cohorts, while adding district administrative data and data on technology use.

Empirical’s studies will establish valuable links between instructional coaching, technology use, and student achievement, all while helping to improve future iterations of the DLP coaching model. As described in our design memo, the study is guided by Digital Promise’s logic model. In this model, coaching is expected to affect an intermediate outcome, measured in Empirical’s research in terms of patterns of usage of edtech applications, as they implicate instructional practices. These patterns and practices are then expected to impact measurable student outcomes. The Empirical team will evaluate the impact of coaching on both the mediator (patterns and practices) and the student test outcomes. We will examine student-level outcomes by subgroup. The data are currently in the collection process. To view the final report, visit our Digital Promise page.