1EdTech: 6 Keys to Effective Learning Analytics

• By Rhea Kelly
• 08/11/25

1EdTech Consortium has released a free report offering six steps to implementing learning analytics effectively in higher education. Based on insights from institutions within the 1EdTech community and its Learning Analytics Builders Coalition (LAB-C), "Six Steps for Effective Learning Analytics Implementation in Postsecondary Education" offers "a phased approach designed to foster data-informed decision-making and improved student outcomes," according to a news announcement.

LAB-C originally formed at the 2024 1EdTech Learning Impact conference, to collaborate on learning analytics discussions and pilots in an effort to scale use of the technology to impact personalized learning and achievement. The report gleaned six foundational steps from those best practices:

1) Create an internal committee or council.

Convene faculty, institutional researchers, instructional designers, academic advisers, IT staff, and student success leaders to define institutional goals for learning analytics, set governance policies, and ensure alignment with institutional mission and accreditation requirements.

2) Involve external stakeholders.

To expand the impact and credibility of analytics initiatives, engage with external partners such as accreditation bodies, ed tech provides, and employers, the report advised. Such partnerships can help ensure that analytics platforms and metrics are interoperable with external systems, highlight workforce-aligned competencies to guide curriculum refinement, and more.

3) Create a taxonomy.

"A clear taxonomy of learning data elements (e.g., engagement metrics, course-level outcomes, demographic factors) ensures consistency and clarity across analytics dashboards and reports," the report stated. It should be tied to institutional goals, aligned with open standards, and include definitions for key student success indicators.

4) Start small.

The report advised focusing on a defined goal in a targeted pilot project within one department or a few courses.

5) Focus on ideation and continuous improvement.

It's important to regularly analyze data as well as feedback from students and instructors — and utilize those results to inform decision-making, the report emphasized.

6) Choose a platform that aligns with standards.

Key features to look for in an analytics solution include interoperability and integration with an institution's learning management system, student information system, advising platform, and other relevant platforms; accessibility; ethical data use; and customizable dashboards for various user types.

"We know from evidence in the field that learning analytics has the potential to transform how we support our students, but only if it's implemented with intention and purpose," said Suzanne Carbonaro, vice president of Postsecondary Education & Workforce Programs at 1EdTech, in a statement. "This report captures lessons learned and effective strategies that any institution can implement to get started, or evolve their current analytics efforts, through a trusted network of peers."

"LAB-C is a catalyst for change, uniting institutions, associations, edtech providers, and educators in a shared mission to accelerate student success through data-informed practice," added Kevin Corcoran, assistant vice provost, Center for Distributed Learning at the University of Central Florida. "By fostering scalable collaboration, ethical data use, and inclusive innovation like those highlighted in this report, LAB-C is reshaping the learning analytics landscape and empowering higher education and EdTech to build more responsive, personalized, and effective learning ecosystems."

The full report, including examples from specific universities, is available on the 1EdTech site here.