The Power of a Higher Education Consortium

The next generation digital learning environment (NGDLE) presents many challenges for institutions because it’s a dramatically new approach to teaching and learning. It means no longer building tools that meet local, often narrow, purposes. It demands that leadership consider scale, new architectures, and confederation of systems.

The days of building and solving unique problems are not over, nor are the days of building and integrating applications. The days of building infrastructure, however, are swiftly shifting to cloud tools and vendors. Technologists who previously wrote code to produce applications from scratch must now build skills to assess tools and the tools’ role in an ecosystem, as well as strong relationships with vendors. The future requires having a keen eye for truly differentiated needs and opportunities and the ability to move with agility in and out of those spaces. It means knowing that evolving digital workflows might require changes in governance, processes, or pedagogy, and the value of extensions to infrastructure.

Taking on these challenges individually through internal innovation and external contracting has some pluses and minuses, as does working in a consortium. This truth is captured in the African proverb: “If you want to go fast, go alone. If you want to go far, go together.”

The Power of a Consortium

As with many challenging initiatives, one potential path to success is collaboration. For some, sharing the risk minimizes downsides so they are no longer barriers to advancement. For others, pooling resources with like-minded institutions catalyzes a significant burst in capacity, especially in challenging spaces like data management. And for others yet, collaboration is an economic decision, if not an imperative. Given these potentially disparate motivations, what role does a consortium play in encouraging progress toward the next digital learning environment?

The NGDLE approach encompasses many aspects of the teaching and learning ecosystem. For one campus to successfully execute all aspects of the approach would require considerable financial resources and time. It requires a different approach to technology, security, and pedagogy than traditionally used. And the leader in this space is charting new ground; going forward without allies makes the transformation even more complex. Therefore, working together as a consortium allows a group of leaders to pool resources to share risk.

A core part of the NGDLE are the innovative vendors constantly inventing important components. These vendors are sometimes unsure of the market value of their solution or, sometimes more dangerously, overconfident of their solution’s market value. In either case, working together with the vendor yields a better result for both the consortium and the vendor. Consortia can better advocate for those issues that impact not only them but all of higher education.

The relationships between consortia and vendors will be made much more efficient and effective as universities work together to assure the tools and services they select adhere to open standards. For example, IMS Global advocates for the use of standards. Not only do they help define standards for educational technologies, they invite and encourage participation from vendors. This partnership, forged early, leads to tools and services that are born interoperable.

Even beyond the promotion and adoption of standards, the collective reach of large collaboratives incentivizes vendors to enhance tools where they might not otherwise feel compelled to do so. As an example, Unizin institutions collectively expressed the need and worked with Instructure to bring real-time interaction data from the Canvas Learning Management System into being. Unizin staff also led the effort to work directly with Instructure to extend the quantity and quality of data in Canvas.¹ As Canvas made more of its data available to users of its LMS, many users began creating a “wish list” of what other data they would like to get out of Canvas. Instructure knew of these requests and sought a partner with whom to push forward.

Rather than try to rationalize dozens of voices, a consortium can provide a vendor a single, strong, and specific constituent to do the most good for the most people. Working collaboratively, Unizin staff and Instructure partnered to make module data available to all Canvas customers in the Canvas Data function. This data service includes information about modules, module items, module content, completion requirements, and other functions. Modules are critical because they allow more customization and flexibility as the curriculum becomes more personalized. Modules can also capture instructional design and intent in a course. This extended data surpasses what was previously available for learners in Canvas while providing greater context about the course. True to both organizations’ shared philosophy of openness, this data extension is now available to all Canvas customers.

An infrastructure that can effectively ingest, aggregate, and store data can greatly support an institution as it moves toward the NGDLE. This infrastructure need not be unique; in fact, in many ways, including adhering to the vision of the NDGLE, it’s best if it isn’t unique. A data management approach that facilitates integration with multiple systems for data ingestion and outputs data in standard formats for data reporting or analysis is critical to core capabilities needed for a robust data ecosystem: data access and research support. Again, while individual institutions might solve these challenges, the solutions are fundamentally identical. It is exponentially more efficient for a single consortium to deliver and manage those solutions, while providing flexibility for local modification.

The Power of Analytics

The aim of analytics is to better understand empirically how people learn and, ultimately, to improve student outcomes. Learning analytics — ”the measurement, collection, analysis, and reporting of data about learners and their contexts, for purposes of understanding and optimizing learning and the environments in which it occurs”² — is relatively new.

Part of the value of the NGDLE is a data-source agnostic platform for the rigorous management of teaching and learning data to support learning analytics, early warning systems, and in-class visibility for faculty and students. This collection of highly automated processes must be executed continuously (meaning, data needs to be collected as quickly as possible and made available immediately upon processing) to provide timely teaching and learning information to users, applications, and other systems. There are tremendous efficiencies in institutions focusing their efforts on the use of this data, rather than exerting independent efforts to wrangle it.

The other aspect of analytics is supporting research to improve student outcomes. A consortium can create rich and broad collections of curated data across multiple universities as the data set for learner analytics. This research-focused data pool must manage data deliveries for teaching and learning research. The data is contextualized by three important vectors: the course, the pedagogical approach, and outcomes. At the center of the research database is the student, who will be de-identified for privacy and in some risk scenarios fully, irreversibly anonymized. This requires aggregating data from a variety of data sources,including institutions and public, generally available sources. Only a consortium can build a cross-institutional, secure data enclave to house sensitive student data for member institutions. Access to an institution's data must remain wholly under the institution’s control, but the consortial data pool could provide a place to safely store a wide variety of student-related data and a growing set of integration and analytic services.

Ultimately, the creation of any cross-institutional data pool to benefit teaching and learning as well as research has three objectives:

1. Leverage economies of scale in a secure data enclave governed by the member institutions.
2. Evolve common data integration standards and practices from multiple data sources tied to student learning outcomes (e.g., student information system, learning management system, admission data) in ways that are open to inspection rather than relying on black box proprietary solutions.
3. Participate in the creation of the world's largest learning laboratory at a pace that matches institutional desire and readiness. Many questions cannot be answered within the context of a single institution. The data pool would allow institutions to take a scholarly and practical approach to critical questions around student performance.

Financial Power of a Consortium

A consortium is often the most cost-effective means to explore the opportunities the NGDLE offers. The three main ways in which collaboration can result in more economical progress are vendor negotiations, opportunity costs, and innovations.

Vendor Negotiations

The most obvious financial benefit to working as a consortium comes with group purchasing power. This happens all around us at universities every day, from buying health insurance to the laptops on which we spend much of our working day. There are opportunities to jointly engage with vendors as well. For vendors, the benefit is twofold: (1) they can get access to a large potential customer base, and (2) their sales cycle shortens considerably. Participants in the consortium have an opportunity to get pricing on necessary tools and services that wouldn’t be possible for a single institution.

Opportunity Costs

Working alone has unseen but expensive opportunity costs. Using the example of working with vendors, many steps have to happen on a campus to acquire a tool or service. This includes the due diligence that would require a review of the tool’s accessibility, the vendor’s security policies, references, and on and on. Today, this happens dozens if not hundreds of times for almost every enterprise vendor tool used on campus. And in most cases, the rubrics used to asses these tools are similar if not identical. But imagine if each member of a large consortium took turns doing the review. In a 10-institution collaborative effort, this reduces the effort needed on one campus to review a collection of tools by nine-tenths if not more. That’s time staff have to perform other value-add activities.

Another example of this lost opportunity cost arises with data management. The technical architecture for data management will be similar at many institutions. In fact, TinCan or xAPI, an established standard designed to record learner experiences in educational tools, has already defined a standard Learning Record Store, though it is merely a set of requirements that each institution has to then interpret, design, build, test, and deploy individually, all to achieve the same objective. Unizin also has defined a data platform that will be identical among all members. Conservatively, we have spent thousands of hours on this platform and will invest thousands more to expand it, modify it per our members’ needs, and keep up with new standards and technologies. Those thousands of hours we’ve spent aren’t wasted, though — we see these as thousands of hours we have saved, and will save, each of our members. The people who would be working on a similar initiative in their proverbial silos can instead provide greater value to their institutions by work with the data, not working on the data.

Innovations

Finally, working as part of a consortium can lead to discovery of and investments in innovations that wouldn’t be possible alone. One example where vendor relationships and innovations have come together is the new inclusive model being adopted by many publishers. The inclusive model offers a way for students to access digital course materials on the first day of class, at a cost often a fraction of the list price. Publishers can still offer faculty the same choices as in print.

Indiana University is a leader using this model. They worked with publishers to find pricing for their materials under an agreement that provided value to students, faculty, and the publishers themselves. Indiana also found a solution, now called Unizin Engage, to facilitate delivery and management of the inclusive model. By working with publishers and not building their own e-text reader, Indiana University has saved their students more than $3.5 million dollars in the 2016–17 academic year. This initiative has also led to opportunities for research to further support this model. Because of Indiana’s innovative partnerships, this big idea that started as a small project is now being adopted by dozens of publishers and hundreds of schools.

Facilitating Emergence of the NGDLE

The NGDLE approach seeks to meet the rapidly changing needs of higher education. The path for that approach is neither easy nor simple. The emerging ecosystem will offer learners

• access to and interaction with content;
• the ability to collaborate with peers, faculty, and industry leaders; and
• a space in which they can create new ideas, products, and artifacts that reflect the processing of knowledge and application of understanding.

Meeting this vision will require collaboration to collectively control and govern resources and provide the infrastructure needed to enable innovation and serve each university’s mission.

The NDGLE presumes that the deep personalization of student education is essential to tackling our enormous educational challenges and only possible through a digital transformation in education. The NGDLE represents an ecosystem model for technology — heterogeneous apps and services built on common technical “Legos,” standards, and services — and the optimal way to create and deliver personalized education with technology.

A consortium of like-minded colleges and universities committed to public steering of the teaching and learning mission is best positioned to facilitate the emergence of an NGDLE.

The activities of such a consortium break down into three large categories:

• Technology: an ecosystem resulting from building technology at the levels of common infrastructure, platform capabilities, and tools
• Economics: an economic actor changing the market dynamics currently governing how vendors deliver technology and services to meet the needs of a changing teaching and learning mission
• Culture: an agent of institutional collaboration and change accelerating institutional orientation to the NGDLE model

A consortial approach to teaching and learning can ensure that colleges and universities control the direction of their missions by leading in these three areas. Working as a consortium has allowed Unizin member institutions and their faculties a renewed, action-oriented, collective voice in this vital conversation. This consortium provides a means to reframe and focus our attention on independence, dependence, and intentional interdependence as each of us navigates the transformative changes occurring within higher education.

Notes

1. Unizin, Ltd. is a nonprofit consortium of universities dedicated to promoting affordability, access, and learner success in digital education.
2. George Siemens, "Learning and Academic Analytics" [http://www.learninganalytics.net/?p=131], Stanford Learning Analytics Summer Institute, August 5, 2011.

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Robin Littleworth is the chief operating officer of Unizin.

Amin Qazi is the chief executive officer of Unizin.