Practical Steps to Incorporate Analytics and Peer Collaboration to Support Active Learning

Many faculty understand the importance of active learning, but some may struggle to make the transition from less engaging teaching practices. A recent webinar sponsored by Transform Learning and Every Learner Everywhere looked at how data analytics and peer collaboration can be used to support active learning.

Leveraging Learning Analytics and Peer Collaboration explored practical ways to incorporate these practices to enhance student success. It featured presentations from Heidi Echols, an Adaptive Learning Specialist and Instructional Designer at the University of North Carolina at Charlotte, and Jennifer Reed, a Lecturer in the Department of Mathematics and Statistics at the University of North Carolina at Charlotte. The webinar was the second part in a planned series of four about the eight DE-EBTs (digitally enabled, evidence-based teaching practices). In the first of the series, Fostering a Sense of Belonging and Instructional Transparency, presenters Aris Winger and Abbe Herzig explored strengthening student connection and improving instructional transparency.

Peer collaboration leverages active learning to create stronger peer-to-peer connections, develop valuable soft skills, and improve academic performance. Learning analytics offers faculty a data-backed way to improve teaching practices. Both are DE-EBTs featured on Transform Learning, a new resource hub that outlines the research around and dimensions of each practice and lets users submit their own activities to an instructional examples library.

Fostering engagement through peer collaboration

The presenters described how peer collaboration enhances academic performance and promotes essential skills like communication, empathy, and a sense of responsibility. “With generative AI, and all the conversations we’re having around that, the importance of these soft skills has never been higher,” Echols said.

The key to successful peer collaboration starts with group goals in which students collectively work toward shared objectives and individual accountability where every student contributes meaningfully, preventing reliance on others to carry the group.

Echols and Reed presented several digital learning tools that can assist in promoting peer collaboration and individual accountability:

• Online student communities, like InScribe or Piazza, foster a sense of connection, enable peer support and 24/7 engagement, and promote accessibility.
• Brainstorming tools, including whiteboard features on video-conferencing platforms like Zoom, capture and prioritize ideas in real time, enable remote participation, and allow for multimedia integration. Others, like Mural, are purpose-built visual collaboration platforms.
• Collaborative documents on Google Drive or Microsoft OneDrive promote group accountability, streamline the feedback and revision process, simplify version control, and enhance transparency.
• Creative tools, such as Canva or Gamma, offer easy-to-use templates, have multimedia integration, and provide well-designed results.

For Reed, project-based learning is a reliable way to facilitate peer collaboration and active learning. Different project formats can develop specific skills, like using poster sessions to practice data visualization skills or a spreadsheet to work on collaborative calculations. Projects allow students to take ownership with their learning and connect with one another.

“It’s energizing, it’s buzzing, and there’s excitement as they’re getting connected with one another,” Reed said.

Measuring the impact

Digital tools make collecting and analyzing student data easier than ever, but it requires accountability and reflection on the part of faculty.

“It takes some vulnerability,” Echols said. “It means that you’re digging in and looking at your teaching.”

Reasons for collecting and analyzing classroom data include:

• Assessing effectiveness of teaching strategies
• Identifying what works for student success
• Demonstrating improvement over time
• Aligning with institutional goals and standards
• Promoting continuous improvement and growth mindset
• Enhancing faculty reflection and development

Student sentiment and student success are two kinds of data collection that can inform teaching practices. Student sentiment such as polls, student surveys, discussions, and early alerts provide opportunities for support through proactive emails, check-ins, and TA outreaches. Responsive action taken after using learning analytics can include evaluating lessons, scaffolding assignments, or connecting students into study groups.

Echols recommends using a systematic approach to measuring impact:

1. Establishing baseline data — Collect current performance metrics before implementing changes
2. Tracking engagement — Monitor participation rates, time on task, and contributions
3. Gathering student feedback — Use surveys and reflections to assess student experience
4. Iterating and improving — Make data-informed adjustments to enhance effectiveness

Overlapping with active learning

Another of the DE-EBTs covered in depth in the earlier webinar is active learning, and keeping that practice in mind is one way to make peer collaboration and learning analytics manageable.

Echols and Reed suggest starting small by piloting a single 15-minute active learning segment within an existing lesson. It could be facilitating a student-led discussion or working through word problems in small groups. The Transform Learning site has many classroom-tested examples.

Once active learning has been introduced into your classroom, “scaffold” up from there by creating structured digital workspaces that guide collaboration. Integrating reflection deepens the learning experience and provides feedback for the educator.

“We got into teaching through a passion for it,” Echols said, “so having the information to improve your teaching can feel good and really powerful.”