The JNGI APC is different than most every other form of analytics-based effort in the current higher education student success environment in four main ways.
1) While it provides tools and dashboards, it treats analytics first and foremost as an engaging, evidence-based pedagogy that can positively, and measurably, influence teaching and shape learning.
2) Treating analytics as an engaging pedagogy requires a professional development process for instructors and those who support instruction in the course(s). The APC provides this through a combination of face-to-face and virtual meetings. These meetings are all about helping faculty and others rethink the way that their courses are taught and students learn through the application of analytics data that the APC gives them.
3) As the previous statements makes clear, it involves faculty – an often neglected group in the current analytics movement; and,
4) Its focus is on applying analytics to inform teaching and student learning within courses and the curriculum of which those courses are a part.
The APC does this with the help of an intentionally structured community that aims to address the fuzzy definitions, high cost and low application issues associated with analytics in gateway courses and the curriculum of which they are a part. It places a specific framework around the use of analytics within higher education; providing that framework at an accessible, non-profit fee; and providing support for faculty and others in their adoption and continuous application of analytics in teaching and learning.
Click here for a scholarship based overview of the issues addressed by the APC.
The JNGI APC includes four key components. These include:
Learning Analytics Readiness Instrument
Through the use of an adapted version of the Learning Analytics Readiness Instrument (LARI; Arnold, Lonn, & Pistilli, 2014), the JNGI’s APC will strive to help campuses identify areas that could be addressed in order to create the most optimal environment possible for the application of analytics in teaching and learning in gateway courses.
Historic Data Analytics (Longitudinal Trend Reporting)
JNGI APC participants will have access to the Gardner institute’s Gateway Course Success Analytics Inventory – a tool that puts data into the hands of faculty and staff working to transform gateway courses. The historic data-including many forms of aggregated and disaggregated data on student and institutional performance in gateway courses-shines a bright light on why changes in teaching and learning are necessary and for whom they are most necessary.
Predictive Analytics Models & Dashboards
The JNGI APC includes both predictive analytics models and dashboards that display prediction outcomes. These models predict the probability of success in a gateway course. Unlike for-profit proprietary approaches that do not reveal their models’ formulas, any participant in the non-profit JNGI APC may see the models and, if they so desire, work with them outside the live system.
Support for Building and Scaling Analytics Capacity to Use Analytics in Teaching
The process of implementing analytics is not a one-time thing or an overnight activity; rather, it requires persistence, dedication, and energy focused on not only implementing something but also continuously nurturing a process over the course of time. The JNGI APC includes a process for facilitating the adoption and high use of analytics within courses including an APC Launch Meeting [February 26, 2017, in Las Vegas, NV] as well as ongoing virtual meetings of the APC community members.
Our experience has led us to believe that when it comes to learning analytics, many institutions-especially those who teach the courses-struggle with similar issues, encounter comparable roadblocks, and need to address concerns regarding how to adopt and scale the use of analytics in teaching and learning. We believe that there is a real void in the educational space on how to even think about analytics, much less having capacity to build or scale an effort. The JNGI APC seeks to fill this space for those institutions willing to embark on using analytics as a tool to inform scholarly teaching and to do so through a supported cooperative, low cost and mutually beneficial manner.
The APC fee has been structured to make the process and tools accessible to institutions of any size. The fee structure is based on institutional undergraduate enrollment. For information on fees contact Drew Koch at firstname.lastname@example.org.
Visit the APC web-based platform to create an account and start an application.
Contact Drew Koch at email@example.com.