The new IT architecture also requires that tools be able to “work together” to provide better information (analytics) to both faculty and students on their progress and to administrators on their usage. This may mean that data provided by apps is easily made available to an analysis service or even that one tool provides information directly to another tool. For instance, a classroom clicker application might import assessment items created in an LMS and transfer the results data back to the LMS, to a classroom capture system, or to both. An e-textbook application might accept links inserted by the instructor and send data on quiz performance to the LMS and send usage information to the bookstore.
To make the discussion more tangible, Figure 1 shows the types of content, software, and systems that need to be encompassed by the new architecture. In the upper left is the wide variety of learning environments that are today exemplified by the course, LMS, and portal and that in the future will evolve into diverse new forms, such as MOOCs. In the upper right is the growing number of learning tools and content that can be plugged into the learning environments. Such tools can be content-neutral, like a collaboration system, or content-specific, like an adaptive tutoring homework application that goes along with a specific textbook or content area. In the lower right are the other traditionally isolated academic applications, including the new or expanded standalone cloud services that provide specialized learning tools or services, many of which are already in use today. These include library systems, lecture capture, e-portfolio, and assessment systems used by faculty to create, grade, and analyze exams. Though these are typically silo’ed, in the future they will need to be seamlessly integrated for use by faculty and students so that data can be easily exchanged between systems. Finally, in the lower left are the “back office” enterprise systems that typically manage the “system of record.” These enterprise systems are critical in the context of learning analytics, since they provide a wide range of demographic and performance data and can be used to look at how student success changes over time.
The center of Figure 1 highlights some of the key areas of open standards and associated services (web services and application programming interfaces) that the higher education community (colleges and universities and suppliers of all types) must converge on in order to enable low-cost, agile, and seamless integration and data exchange among the four categories of software. This is not an exhaustive list but, rather, is representative of the types of exchanges that enable “connectedness” of applications within the context of an institutional or system-wide IT environment.
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