Holistic decision-making is essential to improving postsecondary education. As technology enables us to access more data from different sources and systems of record, an intentional data strategy and governance process help ensure the privacy and security of student data. This is where interoperability standards can help.
Data governance is not a one-time task; rather, it is an evolving one. Many institutions consider this a work in progress and, although complex, confirm that it is vital to building and maintaining their data analytics culture. 1EdTech Consortium member organizations involved in data analytics discussions and initiatives agree that building consensus and a robust culture around data use is key to supporting a trusting, successful and secure structure for data consumption and action planning.
“You need to have a culture that believes data can do good and serves student success,” said Bart Pursel, Unizin CEO. “Anxiety can slow down efforts to use data to support teaching and learning, so you need to show others that getting data to people on the front lines to make informed decisions is not only a good thing but also the right thing to do.”
When you build a culture for learning analytics, you need to know what questions you want to ask and what challenges you need to address further with the data—including permission to plan new programs and other resources that rely on data as evidence for the why. If you simply start there, you give your stakeholders time to reflect and make meaning from data to impact change with smaller bites. That's where your journey toward data literacy starts.
For Penn State University's Data Empowered Learning team, the pandemic accelerated their journey toward data literacy.
“As the institution transitioned to full remote learning, it became imperative that we identify students who were no longer engaging in their coursework to help support and retain them,” explained Hannah Williams, Project Manager for the Data Empowered Learning team at Penn State. “Looking at the activity data was a no-brainer, but we needed to combine it with data from multiple systems to make it accessible to advisors.”
“In order to address this challenge, the team created learning analytic tools that combine Canvas course activity data with SIS and academic advising data to deliver real-time insights. Looking at course activity data was a no-brainer, but we needed to combine it with data from multiple systems to make it actionable and accessible to academic advisers and others,” said Williams.
“Beyond the pandemic, these learning analytic tools demonstrated the need to provide real-time data to support proactive academic advising and student success initiatives,” added Ben Hellar, Manager of the Data Empowered Learning team at Penn State. “As word started getting around, more people saw the potential for real-time insights and wanted similar access to serve their population of students.”
Of course, who should have access to what data is a decision each institution needs to make before releasing the information. Bringing together a team to make those decisions can help ensure all needs are considered and your strategy is transparent.
“We work very closely with data stewards, who are experts in regulations, policies and the needs of the individual departments and offices, to determine who should have access to what data,” said Jared Kosanovic, Enterprise Integration Architect for the University of Wisconsin-Madison.
Of course, data is most valuable when those receiving it can quickly understand what the data means and what actions need to be taken. At institutions that are innovatively addressing real-time data needs, it means adding the right resources to support the process.
“There is a reason we’re the data-empowered and not data-driven team,” said Hellar. “We want to empower the decision-making process and give academic advisers and instructors real-time insights during the semester so that they can know when student interventions can be most impactful.”
Of course, gathering all the data and providing insights can take a lot of time and effort unless your systems are interoperable. Open interoperability standards, created, advanced, and certified by 1EdTech Consortium, can help ease the burden of that work so teams can focus on data governance and using the data to address opportunities to grow and improve instead of just using valuable time to stitch the technology together.
“Because learning analytic data combines data from multiple sources, if you want to answer a question that looks at data from six different systems, do you need to get approval from six different people, or is there a single governance process to determine who should have access to that analytic,” said Williams. “Data governance is a constant and ongoing process that requires institutions to be agile and understand how innovation is changing our systems. The speed at which new technologies such as AI and learning analytics are created, compounded by the demographic and financial realities facing higher education institutions, make the need for real-time data insight necessary to support students and institutional business processes.”
There are three big data standards that, when implemented together within your chosen edtech tools, can help you design an end-to-end data pipeline to ingest and normalize data for easy visualization and consumption. They are Caliper Analytics®, Edu-API, and LTI®.
Caliper Analytics enables institutions to collect learning data from digital tools launched by students in different environments.
“If you look at an entire project, if the edtech tools don’t provide data in the same format, 40-50 percent of the work is formatting the data. The Caliper standard solves that and allows us to get the insights quicker,” said Pursel. “For our members, if a vendor has a Caliper-compliant feed, it can take weeks, not months or years, for our members to draw insights from the data.”
One of the newest 1EdTech standards is Edu-API, which will help disparate systems exchange data across the student lifecycle, from admissions to student information systems to learning management systems. This will enable a more scalable approach to consuming data from these systems in a secure and consistent way to enhance holistic decision-making.
“I’m excited for the potential of Edu-API,” said Kosanovic. “I think it's underselling it to say it will save time because I think it has the potential to help people who maybe aren’t as tech-savvy understand the benefits of interoperability and see how much we can get done when the integrations are less complicated.”
Rounding off the big three data standards is LTI (Learning Tools Interoperability®), which has become ubiquitous in higher education and K-12 online learning. All mainstream learning management systems use LTI, and most implementations are certified by 1EdTech to meet the most secure standards and integration protocols.
“LTI tells us what tools are being launched, and Caliper can give us information on the activity that’s taking place inside these tools,” said Hellar. “The minute a vendor supports Caliper or LTI, it's easy for us to bring it into our data ecosystem. We don’t have to start an entirely new project or waste precious time and resources.”
Bringing your data together across multiple systems of record and ensuring its accuracy and security transforms your institution into one of trust and impact. Data available to users via a data governance structure, coupled with easy consumption, provides the biggest benefit to the learners; it helps institutions understand their learners better, and it empowers holistic decisions, leading to more personalized learning.
“We have a substantial data warehouse that stores data from the SIS, the LMS and other data as well, that’s available for analysis, but some data is needed in almost real-time to trigger meaningful action,” said Chris Davis, Vice President of Academic Services and Quality for University of Maryland Global Campus and 1EdTech board member. “These technical standards, especially once Edu-API is available, will make it easier for small institutions or others that haven't already built their own system to get the information.”
1EdTech members interested in data and analytics are encouraged to join our work through one of our leadership groups. Our Learner Success and Data Analytics ILN has been focused on data governance and revisiting our initial guidance document, which this community designed to provide additional information about artificial intelligence and data visualization requirements.
About the Author
Suzanne Carbonaro
Suzanne Carbonaro is the director of higher education programs at 1EdTech Consortium. Suzanne spent much of her career in higher education as a leader of curriculum and assessment, instruction and student success, institutional effectiveness and planning, and accreditation. Over the last five years, Suzanne served as a subject matter expert for two edtech companies and supported the growth of interoperability standards, strategic planning processes, and the Comprehensive Learner Record (CLR) across the colleges and universities she served. Suzanne’s research interests and publications are in the areas of digital credentials and CLR, high-impact practices, co-curricular assessment, and integrated strategic planning.
