What are the current trends and gaps in distance learning data research?

Educational data mining is a field that focuses on analyzing data from educational settings to uncover patterns and trends that can inform teaching and learning processes. It involves using advanced algorithms and data analysis techniques to explore a range of educational data, including student performance, engagement, and behavior. Through this process, we can gain valuable insights that help improve both instructional strategies and student outcomes. The goal is to make data-driven decisions that enhance the learning experience, identify areas for improvement, and predict future student success or challenges. This approach allows for a deeper understanding of how students learn and how different factors influence their progress.

In my experience, this type of multi-layered analysis that merges both quantitative and qualitative data is invaluable in helping faculty advance higher levels of student success. EDM provides a more holistic picture of what works and what is not as effective, especially for community college faculty who teach in open door institutions that do not use selective admissions criteria. Designing courses that will effectively engage diverse learners at various levels of preparedness is complex. EDM can provide critical analysis to guide course design that addresses the diversity of learners and informs both structure and content to successfully engage more learners.

One example of the importance of EDV is the use of dashboards to provide comparisons of both leading and lagging success metrics. Dashboards provide visuals of current data and also allow you to compare data over time, creating quick insight into what interventions work. At our college we also use EDV through dashboards to help us compare traditional versus online course success and to see what clases are working best in an online format. Once we know the online courses with the highest success rates we can dig into why those classes are doing better and use those findings to improve the course design for courses that do not have high success levels.

Word clouds are also powerful in terms of taking qualitative data and transforming it to quickly show trends. You can immediately see what was said must often and quickly dive into that data. The real power of EDV is that it enables us to quickly synthesize data to make better, informed, decisions. It's absolutely critical that EDV is leveraged across platforms and research areas to ensure that people can take away meaningful insights from the data collected. One thing to note about accessibility: although EDV enables a larger group to interpret large sets of data quickly, it may not be accessible to all individuals. It's important to still use captions, proper labels, and alt text (alternative text) to ensure greater accessibility.

Actually I agree that EDV can assist students that require a variety of modalities to understand data. This is especially true in adult education where students need to see their progress visually represented to help them track their own progress in their learning journey. This aids in retention of students as it builds persistence in learners.

I agree. I believe the greatest benefit of EDM and EDV for online learning success is realized when the people analyzing and using the data understand the importance of a culture of curiosity where data provides the basis for more questions. EDM and EDV can help faculty and course designers easily see which online classes are not as successful as traditional seated class options and then they can delve deeper into the data to understand why. The key however is a healthy culture where faculty do not fear their data but rather see data as critical for continuous innovation.

In my experience, transparency and accountability are the two greatest hurdles that can become insurmountable barriers to creating a culture of inquiry or curiosity. Great care must be used to ensure transparent data sharing is positively received as a starting point for achieving greater student success versus being negatively perceived as punitive. Additionally, simply sharing data without the expectation that the data will inform practice and be used for continuous innovation is a waste of time and effort.

The push for data aggregation and visualization will ultimately move distance learning research forward. The gap that exist across institutions (educational and corporate) is simply having systems that lend themselves to extracting meaningful metrics. It's easy to get lost in data, and expecting individuals (faculty, administrators, employees) to extract large data sets and use tools like Python or R (which have a steep learning curve) to visualize data isn't scalable. Instead, institutions need to prioritize getting systems/tools that EDV features -- or, at least, push existing tools to do a better job of presenting data. Make sure you work with stakeholders across the organization to figure out what data they need to filter out the noise!