Unizin Reports

Fall 2023

by | Sep 25, 2023

This report is to be shared by design to communicate the full scope of Unizin impact, work products, and status at your institution.

Three Years Together………..Cathy’s Final Reflection

Through my last three years at Unizin, I’ve witnessed firsthand the power of a nonprofit consortium.  Unizin’s consortium works because of its dedicated campus-based members, strong board leadership, Unizin’s internal staff, and leadership team working together to focus strategically and to adjust based on continuous transparent dialogue.  Member-driven success imperatives were achieved throughout the marked, pandemic-driven shift to online learning and despite challenging budget constraints.  The economic ramifications of an ‘enrollment cliff’ and the rush to online learning underscore Unizin’s strengths.  In this time like no other,  higher education, like no other time, revealed teaching and learning informed by learner and learning environment data.  That data can and has served as an institutional and pedagogical change instrument.  


Unizin provides a holistic model of the Unizin Common Data Model (UCDM) through which cross-platform analytics on teaching and learning behaviors can be performed.  With a strong alignment between engineering know-how and data services & solutions, Unizin members have significantly impacted student success driven by the Unizin Data Platform (UDP). Unizin’s Content Program relentlessly pushes to deliver affordable content to students and aspires to align that content with meaningful analytics.  Most importantly, Unizin includes and is built on an active, focused, and vibrant set of T&L communities. And, yes, Unizin’s consortium size leverages steep eLearning vendor and digital publisher discounts.  These are the tangible, concrete assets Unizin provides, through which consortial product and service achievements can be clearly seen.


Across the last three years, this consortium delivered numerous projects, products, and services that are as much a part of Unizin’s success as the “pillars” referenced above.  These contributions begin with how Unizin met the challenges that all tech companies faced as the pandemic ruptured the workforce and workplace: Due to the “great resignation,” Unizin lost over one-third of its personnel. In late 2021 and early 2022, Unizin hired nine new personnel, constituting 40% of Unizin’s team.  


With fresh eyes on Unizin growth, a new and incredibly talented set of Unizin employees, and a now seasoned leadership team sharing a unified vision, Unizin has soared. Highlighting their student success initiatives and accomplishments at the May 2023 Unizin T&L retreat, Unizin members unanimously affirmed Unizin’s positive growth and impact, and in a way, marking Unizin’s arrival as an organization defined by achievement and delivery of services, not just aspirations.  

  • Bridging the gap – Between Infrastructure and Impact  So much of an institution’s ability to exploit the UDP rests on clearly understanding how the UDP is modeled and how to conduct analytics through the UDP to meet institutional imperatives.  DSS has streamlined and bridged the gap between the UDP and actionable insights on learners at member institutions. Through consultations on member analytics projects, training and assistance in SQL and statistical methods, and building cross-institutional and bespoke data marts to accelerate student success, DSS has energized members toward not just aspiring to use data but to tangibly use UDP data to understand teaching and learning at their institutions better.

  • Breaking down internal silos Great leadership understands the power of collaboration and team building.  Unizin’s leadership team’s commitment to communication, whether building new channels with members or continuing to foster and grow member communities.  Internally, Unizin’s leadership approached and organized its human resources no differently.  New, intra-team collaborations were formed, allowing an agile integration of expertise across the organization.  This builds clear feedback loops between our member engagements and our Engineering roadmap.  

  • Defining and Actualizing Board Priorities:   From building data marts that address primary use cases across the consortium to working with vendor partners to deliver data to the UDP, Unizin teams have worked closely with the Unizin Board to develop pragmatic, member-driven solutions toward student success. Communication and transparency around progress and challenges have been a natural consequence of Unizin’s leadership and Board engagement. Unizin has delivered, implementing a new eReader, building a comprehensive set of data marts that facilitate cross-institutional understanding of student activity and engagement, delivering progress around third-party integrations, making the UDP more flexible/operational, and building a GCP alternative to the UDW.

  • Landing in the Right Marketplace – While time-consuming and often frustrating, the investment made in designing a Google Marketplace offering provided invaluable insight and experience into the potential for an independent UDP offering.  Moving the UDP to a PaaS model (“Private Offers”) gives Unizin the greatest control and IP protection and positions Unizin to address UDP-only institutions with greater clarity and focus when the time arises.    Unizin also tested our deployments and stretched our data and implementation services teams in incredibly beneficial ways to our members.  This benefited the most recent onboarding of the University of California Irvine and Chapman University.  And finally, it provided an opportunity to test a partnership with a deployment partner in Unicon, and productively map D2L Brightspace LMS to the UDP, which will undoubtedly pay dividends with future members who are D2L customers.

  • Unizin’s security program approaches maturity – With the completion and refinement of security policy documents that align with  NIST and CIS security controls, the establishment of policy and documentation, the investment in a complete suite of cloud security tools (daily vulnerability scanning, annual penetration testing, network threat analysis and intrusion detection), completion of a successful set of risk assessments for Arizona State University, the University of Illinois Champaign-Urbana, University of California of Irvine, and Chapman University, all built and predicated on an automated development workflow and robust code review, Unizin’s security team has made literally “night and day” strides toward its security posture maturity. In addition, our recent risk assessment by the University of Florida and previous member risk assessments are essential to Unizin’s security program growth.  

  • Making the UDP and UCDM more flexible – Member engagements, new member implementations, and our Engineering roadmap keep innovation and proactive change moving. Institutionally driven analytics initiatives often involve unique approaches to surfacing analytics, student success, or activity measures, each of which also often entails Unzin DSS and Engineering teams to augment or even rethink current modeling, expanded option sets, or the development of bespoke data marts or data mart logic. New members often introduce unique, home-grown SIS platforms and request to adjust or modify the UCDM with them.  Unizin receives invaluable feedback and input into improving everything from batch ingest to modeling new learner and learning environment representations.

  • Helping third parties deliver data Critical to Unizin’s impact is the expansion of tools conveying data to the UDP – so important that it is a current Board imperative.  While Unizin has little control over third-party priorities and strategy, Unizin leadership has been proactive in collaborating with third-party learning tool producers wherever possible on producing Caliper-compliant events.  Specifically, Unizin successfully partnered with Top Hat on their events stream and are nearly complete with context data (a rarity outside of the realm of LMSs); Ex Libris in the execution of the Caliper Library profile for their reading list application, Leganto; and Packback, are now able to send fully formed events to the UDP.  Other tools are in process. 

  • Transitioning from Canvas data 1 to 2 – In the midst of all of Unizin’s engineering and infrastructure projects and challenges, Instructure’s transition from CD1 to CD2 has been a centerpiece to Unizin’s engineering, outreach, and analytics workflows.  Preparing early and aligning the right people within the organization, Unizin successfully mapped CD2 to the UCDM, developed a pre-ingest stage to transform CD2 for batch ingest, position raw data within member SIT environments, and create a reporting and validation tool for the ingest of CD2 so that members have measurable assurance of data integrity. All of Unizin has made this time-consuming and highly consequential project possible, from early planning to preliminary execution of CD2 modeled with the University of Michigan.  Without the highly collaborative expertise within Unizin, such a project completion in roughly eight months would have been impossible.  We are not there yet but we have had incredible success and planning thus far.  Every indication is that Unizin will deliver a seamless transition to CD2 for all members by the first of the year.

  • Data marts – from POC to pipeline integration – Board-driven, task force imperatives were met around student activity/engagement data marts (and the student, course, and program level). With the five base dashboard data marts made available to members as well, Unizin DSS and Engineering integrated a set of data marts refreshed daily and integrated them within our batch pipeline, automating updates and securing data within each member tenant.  

  • Self-paced training, Synthetic data, and more Unizin Hackathons – While Unizin’s products have been for some time front and center (i.e., the UDP, Engage, or Order Tool), Unizin services have grown significantly over the last three years.  Member analytics engagements, projects, data marts, dashboards, and the full range of data services that look to facilitate the productive use of the UDP for members.  But increasingly, Unizin is looking to evolve these service offerings largely around efficiently modeled data and toward information products.  One addition is the self-paced training DSS created to allow members to work with their institutional data in a guided and structured manner at their own pace.  Building familiarity and facility with UDP is key to developing member engagement and tangible learning analytics success. 


  • Unizin’s synthetic data project is another example of providing a multifaceted tool with various applications and benefits, from data science to security. Synthetic data can be safely used to test research methods, train, and general explore, or allow members and non-members to explore fictitious UDP data without betraying privacy/confidentiality concerns.  In this way, synthetic data is perfect for the upcoming hackathon, whereby Unizin members can safely employ UDP data toward application development and data mart creation.

  • Blossoming of member-built analytics tools – As members increasingly incorporate the UDP into analytics and reporting workflows, data analytics projects – as one-time analytics or fully formed student intervention platforms, have begun to form and take shape across the consortium.  Three years ago, only a handful of tools and reports were created by members drawing on UDP data. Now, with increased knowledge and familiarity around the UDP, Unizin DSS training and deep engagements with members, and institutional teams and resources increasingly to learning analytics, new institutional platforms like Learning Activity View for Advisors (LAVA) at the University of Wisconsin and Compass at the University of California Irvine, or Course Insights at the University of Nebraska are being developed to provide avenues for student reflection or to identify students at risk.


  • This trend coincides with the many avenues Unizin has taken to build awareness around and make the UDP more accessible. It is fundamentally a journey from data to information, data marts to applications building on those marts, and simple reporting in Data Studio to sophisticated tableau dashboards launched as an LTI application within Canvas.


  • Content and Content program – RedShelf eReader – allowing Unizin to deliver content efficiently and setting the stage for integrating reading events in the UDP. This new paradigm of vendor-based partnership enables Unizin to provide an up-to-date, modern, and accessible reader efficiently and effectively to our students. 


  • New members, new prospects – As the post-pandemic world has energized learning analytics imperatives, so has institutional interest in Unizin accelerated. With two new members (with a likely third) acquired within a year, Unizin’s value and ability to translate tangible savings (whether through content affordability, vendor contracts, or staff and infrastructure savings seen through the UDP).  Unizin’s value is significantly on the rise. 


Unizin is strong, impactful, and growing.  I have three significant recommendations for the future:

  1.  Unizin is only as strong as its membership involvement. Stay engaged, and move your student success journey forward by continuing to build, implement, refine, and innovate with learner data.  Don’t settle for the impacts that your institution gleans today.  
  2. Unizin as an organization is healthy with dedicated staff and a strong culture of teamwork and transparency.  Encourage that through internal opportunities for growth and innovation. 
  3. Invest in the modernization of the Unizin Content Program with a focus on sharing learner data to diversify learner data and its impact.

I will miss every one of you.  I will miss the continuous opportunities to improve learning within higher education.  However, in my heart, I know that Unizin has everything it takes to soar to new heights.  I also look forward to spending more time with my family, friends, and many hobbies.  Please never be a stranger.  Drop me a line at cathyannobryan@gmail.com  from time to time.


Cathy O'Bryan

Cathy O'Bryan

Chief Executive Officer

Interim Unizin CEO: Bart Pursel

On Friday, September 22, 2023, the Unizin Board appointed Bart Pursel as interim CEO beginning on October 1, 2023.   As CTO across the last 1.75 years, Bart has broadened his existing relationships and understanding of Unizin extensively.  We are very pleased to announce Bart in this important interim role as Unizin continues to innovate for the betterment of our students.

Unizin Hackathon Scheduled for October 26 & 27

The Unizin Application Development community, in collaboration with Colorado State University, is hosting an onsite hackathon on Thursday, October 26th (full day). Friday, 27th (½ day) in Fort Collins, CO. This event is designed to bring Unizin members together to gain hands-on experience working with Unizin and Unizin vendor partner products and services, such as:

  • The UDP and associated data marts
  • Working with Kaltura data
  • Prototyping new application concepts (Canvancements, Denodo/Data Shipping)
  • Expanding upon existing applications created by Unizin members


Unizin is working to have a synthetic data set for different activities, allowing all participants to directly access UDP data without privacy or security concerns. This event is primarily designed with application developers, business analysts, and data scientists in mind, though all Unizin members are welcome to attend.


Participants are welcome to stay at the Hilton Fort Collins, 425 W Prospect Rd. where we have a group rate of $149 per night. Use this link to secure the rate and room. Ten rooms are blocked at this rate until September 29. You can also call 970-482-2626 and ask for the Unizin Hackathon room block with booking code 90N. The other option is the Best Western University Inn which is a 5-10 minute walk to the TILT building where we will be meeting.


Denver International Airport is 65 miles from CSU. Groome Transportation is your best option for a shuttle directly to either Hotel. Book each leg separately since you’ll be leaving on Friday from the CSU Transit Center, a 5-minute walk from where we will meet.


From the airport: Select Hotels option: Hilton Fort Collins on Prospect

To the airport: Select schools option: CSU Transit Center

Flights on Friday after 4:15 PM are highly recommended and required by Groome for 12:05 pickup time. The scheduled dropoff for that shuttle is 2:05 p.m. If you have an earlier flight, you’ll need to select a 4:15 PM departure time when booking the shuttle. Shuttles are scheduled every hour and require a flight time 4 hours later. If you plan on attending, please let us know by adding your name to this registration form.

Canvas Data 2: What’s Next?

With Canvas Data 2 (CD2) implementation, Instructure is employing an entirely new data schema. This will do away with the dimension and fact tables The first focus for Unizin Engineering, Data Services, and Services teams was to successfully map CD2 to the Unizin Common Data Model (UCDM).  With minimal challenges and some remaining but small modifications to address foreign key relationships, Unizin has successfully made the translation. CD2 data should land successfully modeled within institutional members’ UDP tenants.  Queries and data marts generated through CD1 data will perform seamlessly with CD2 data.


So, what are the next steps?  What are Instructure’s timelines and how do they impact member institution’s transition?  And what about CD2 and the transition out of the UDW in Amazon Cloud?  


Over the next month, Unizin will finalize validation workflows and prepare to move CD2 data into member test environments.  Unizin has begun contacting members to schedule the transition  in October, November, and December.  This stage will focus on moving CD2 data to member SIT (System Integration Testing) environments, validating CD2 data against CD1 data in production, generating and conveying a validation report to members, and then switching CD2 to production. 


Through the SIT environments, both Unizin and member institutions will have working representations of CD2 data to validate existing code and workflows specific to each institution. However certain we believe we are matching CD2 to the UCDM, Unizin will verify the integrity of the data for each member before moving from their test environments to production.


“We intend to have CD2 migrations into member test environments and then again to production in place by the end of the calendar year,” said Bart Pursel, Unizin’s Chief Technology Officer.  “We are also actively engaged with Instructure in the event that we may need some additional time early in 2024 to complete the migration.  Currently, based on our mapping and preliminary work with the University of Michigan in testing CD2 in their SIT environment, we are confident we can implement CD2 for all members by the end of calendar year 2023.”


Another challenge operating in tandem with the CD2 migration is Unizin’s transition of the UDW out of Amazon Redshift and into Google Cloud (Big Query).  While distinct from the CD2  migration, the underlying change is both efficiency and the fact that the raw CD1 data is, of course, going away with CD2.  While members can expect a more efficient and adjacent repository of CD2 data in their Google Cloud Big Query project space, the schema has changed and will have some distinct differences in terms of scope.  For example, the Requests Table (now called “Web Logs”) \ is a massive table of system and user login data that will include only the most recent 30 days of data.  


For some members, the Web Logs table and the legacy UDW had little or no utility other than through usage in MyLA (My Learning Analytics).  MyLA previously depended upon the UDW.  Now that MyLA has fully transitioned \to rely on the UDP, the number of institutions requiring raw Canvas data to support workflows not utilizing modeled UDP data has decreased significantly.  Nonetheless, Unizin believes that providing an option for such data, especially if it is adjacent to modeled UDP data, will allow members to efficiently access raw Canvas data and make the adjustments to the changes Canvas has implemented with the least disruption possible.


There remain some additional unknowns, specifically around the possibilities of deltas or incremental data changes for CD2 data moving to the UDP, as well as what is both possible and practical in terms of the frequency by which the UDP can make an API request for “fresh” data.  According to Instructure, Unizin can expect no more than a four-hour latency for CD2 data.  For such data elements as “assignment_grades,” Unizin would like to eventually address specific tables and/or elements for targeted updates (with even less latency than four hours) without the overhead of a full data transfer. Regardless, Unizin will continue to work closely with members and Instructure to make this significant migration as seamless and transparent as possible.

Unizin Town Hall and BeeKast

Unizin Data Services and Solutions (DSS) completed their fifth DSS Town Hall on August the 8th of this year.  With over 50 in attendance, DSS updated members on a variety of Unizin and DSS-centered topics and projects, but with a twist this year: adding BeeKast survey and interactivity tool to provide real-time and asynchronous feedback on discussion topics.

The first request for feedback focused on privacy.  Unizin, either through security reviews or new member engagements, routinely addresses questions around its role in privacy, the UDP, and member institutional data. While Unizin has limited direct control over privacy policy and practices at member institutions, Unizin has yet to formally document its role in privacy in relation to member institutions. To address this gap, Unizin has drafted for member feedback a  “Unizin Privacy Statement” outlining Unizin’s role in confidentiality and security  (protecting data and the systems that house and process data), member roles in implementing privacy (protecting individuals) such as determining what data elements to convey to the UDP and transparency around the use of learning analytics. This privacy statement will remain “living” and open to modifications based on member input, but serve as Unizin’s and in general member’s roles and responsibilities governing privacy.

Beyond the privacy statement,  DSS shifted to the first real-time survey question exploring the formation of a privacy-focused working group.  Based on the variety of challenges and perspectives across the consortium and the impact these privacy positions have on the implementation and use of the UDP by member institutions, DSS wants to understand whether or not a new T&L group around privacy would be useful to members.

Would you be in favor of participating in or supporting the existence of a Unizin Working Group on Privacy, sharing common practices and challenges, and helping develop policy and/or practices that would facilitate the effective and ethical use of UDP data?

While many felt that they were not the best person at their institution to weigh in on such a group, the results were largely positive, with almost 70% at least “somewhat interested.”

Very Interested


Somewhat interested


Somewhat disinterested


Not interested



The next steps will involve articulating the need for such a T&L group to the Unizin Board, developing a charter, and seeking membership.

The second Survey centered on Canvas Data 2 (CD2) and particular areas of concern to members.  While there are specific areas that must be addressed as priorities (mapping, validation, migration to production) the feedback we received helps us better prepare from a service delivery perspective to address particular pain points or areas of concern.  Areas of concern included:

Data Latency – 4 hours


Hosted solution for raw Canvas Data 2


Query Rewriting CD1 -> CD2




Support (or lack of support) for New Quizzes


Reliance on the API


Operationalizing weblogs table



The third and final survey question centered on our Synthetic data update. In the previous two DSS Town Halls, Sara discussed in some detail how DSS constructs synthetic or “fake” data derived from randomized distributions and census data to achieve representations of learner and learning environments.  Sara underscored that, while maintaining the rational shape of the data, synthetic data has no connection to an actual individual, course, or faculty member and no connection to anonymized data.  Synthetic data differs significantly from anonymized or de-personalized data in that it looks broadly at distributions of data and generates randomized, fictitious values based on generalized patterns found across all member institutions, for data such as course enrollments or grades, for example. Anonymized data involves simply the removal of identifiers from real data, preserving the integrity of the record while protecting the identity of the individual.

The synthetic data “word cloud” question allowed participants to candidly enter words or phrases in response to the prompt “What are some questions/concerns you have around synthetic UDP data?  Responses included:

  • Much needed!
  • Control of parameters
  • Bias
  • Algorithm for data construction
  • Accuracy of representation of events
  • Authenticity
  • Ask my privacy, legal office
  • Ability to represent a diversity
  • Is it institution specific?
  • Properly authorized by each institution
  • Volume of data meets dashboard needs
  • Non-identifiable institutions
  • Did you already test its validity?
  • Exclude inappropriate data
  • When will it be available?
  • Varied LMS usage patterns
  • Representation of submission times
  • Who needs to vett this?

The above feedback and associated comments that accompanied some of the responses underscore the need for data that can be used in multiple ways (safely introduce the UDP to new members or newly introduced existing members; training and institutional course work; proof of concepts for research or new implementations, etc.), and verification around methods used to generate synthetic data, and institutional review and validation of the data itself.

Meeting the Board Imperatives: New learning tool integration with Packback

Across the last eight months, the Unizin integrations team (a collaborative effort between Engineering and Data Services and Solutions) has worked steadily over the past eight months with Packback to deliver Caliper-compliant events to the UDP.  Diligence and collaboration have led to success.  Packback provides a single resource for guiding and assessing writing assignments (including plagiarism detection), employing AI to provide students with immediate, meaningful feedback while they write. 

The new events leverage the Caliper Forum profile, providing metadata around students posting to Packback. The focus of these collaborations centers on key identifiers positioned in the correct format in the expected location of the event.  For example, it is critical to be able to identify from which course an event was launched.  Within Caliper, a “federated_session” block reflects the LTI launch from Canvas to Packback (or any third-party tool).  In this way, LMS IDs that the UDP uses to identify courses are passed through to the LTI application, and this pass-through should have consistent representation and positioning within the event. 

With data from a continually growing number of tools, members now have a new data stream that can easily be integrated into student activity analytics work, providing additional data that helps to more accurately represent individual student activity within a course, across a semester, or throughout an entire degree program. 

With Packback events now fully and consistently landing in the UDP, Unizin has begun announcing the availability of event data from Packback for those member institutions who have Packback adoptions at their institution. In addition to spotlighting this new tool at the August DSS Town Hall, Unizin will also reach out to institutional data stewards to inform them of this new application’s data moving to their respective UDP tenant.

Increasing the Diversity of Learning Tool Data in the UDP  (and working with vendors to configure and stream event data from their learning tools) is one of three Board priorities for 2023. Unizin’s work with third parties – particularly Packback and Ex Libris – to deliver consistently formed events is critical to this Board imperative and continues to enrich the learning tool data modeled and available for research through the UDP.

Leganto - Almost There!

As discussed in our spring Unizin Report, Shane Nackerud and Kirsten Clark at the University of Minnesota, in addition to other member stakeholders and Unizin, have collaborated extensively with Ex Libris to deliver events generated through their Leganto (delivered through LTI in Canvas) reading list platform to the Unizin Data Platform (UDP). These events will reflect navigation to Leganto, reading list view, item access, and whether or not the content was downloaded. Employing the Caliper Library profile through Leganto moves us a step closer to incorporating resources originating from Library collections, providing a launchpad into what content students are viewing and potentially aligning these content actions with course contexts and behaviors broadly within the LMS.

The first run of test events was conveyed to the UDP in March, and DSS reviewed and conveyed changes around the needed location of Caliper objects and properly formatted identifiers.  The second set of events was sent in early July, with most of the required changes implemented.  Small changes around consistent identifiers that link events to Canvas courses are needed to complete fully formed Caliper events from Leganto – we are almost there, adding yet another tool’s unique representation of learner data to the UDP.

UDP Implementation Updates: UCI, Chapman & UM: Flint

With new members, the UDP is exposed to additional member campuses.  New UDP implementations are underway. Unizin is excited to work with our new members and campuses on successful UDP implementations, as well as steward existing members that do not yet have a UDP, on different pathways forward to bring a UDP to life to quickly realize new insights from the learner and learning environment data.  

  • UCI status – With a full SIS mapping all but complete, the University of California Irvine is poised to move from their SIT (System Integration Testing) environment to production.  Since late March, Unizin has worked with an amazing UCI team to map and align institutional SIS entities and elements to the Unizin Common Data Model (UCDM). In parallel, UCI has been developing a strategy for a learning analytics platform utilizing the UDP, and will “hit the ground running” once their UDP is migrated fully to production.
  • Chapman – next steps – Unizin held an initial introduction and resources meeting with key Chapman stakeholders in early August.  Next, Unizin Services and DSS will initiate an onboarding meeting with Chapman that will look to implement Canvas context and event data as part of phase 1 of their UDP implementation.  Parallel to this first phase will be to implement the three or four high-value SIS entities, with additional entities added iteratively over the next year.

University of Michigan Flint update – with a primary focus on implementing My Learning Analytics (MyLA) at the University of Michigan Flint campus, collaborating with the Ann Arbor campus, the University of Michigan, Flint, is nearly ready to deploy its UDP into production.

Content Program Update: 2022-2023 Wrap-Up

Spring term billing activities wrapped up in April for late starting spring courses, which allows us to close out the books for the 2022-2023 academic year.  Unizin. We closed the year strong. Student Savings spring totaled $21.1M.  Unizin’s number of billable enrollments was 471K. This was a record high for the 22-23 academic year, as well as a record low for opt-out percentage, 0.58%!  *The graphic below also includes the summer term data).

Unizin Dashboard demonstrating the savings and enrollments numbers for 2022-2023

Instructor Analytics Dashboard (Beta) Released

On September 12th, Unizin released a Beta version of an Instructor Analytics Dashboard, that visualizes student reading events that take place in RedShelf, easily allowing instructors to better understand student reading behaviors. Before Unizin’s adoption of the RedShelf eReader, instructors had access to something similar in the retired Engage eReader. 

These visualizations can be used in multiple ways, such as helping instructors identify students who aren’t engaged in reading activities early in a semester, as well as using reading behavior data to inform what topics are important to emphasize in any given course meeting. The reading events that Unizin uses to power the dashboard are also available in a member’s Unizin Data Platform (UDP) event store, allowing for integration into larger analytics efforts to paint a more complete picture of student activity within a course. Unizin’s Resource Site contains information on how to best utilize the visualization.