Preparing Teachers For Success In Plug-And-Play Ecosystems

Preparing Teachers For Success In Plug-And-Play Ecosystems
Summary: How do we support teachers in plug-and-play? Choosing from among hundreds of apps to plug into a Learning Management System can be a challenge. Interoperability and data standards pave a technical pathway. Modular curricula design and process-oriented analytics can help instructors walk it.

Plug-And-Play: What A Teacher Says

With over 100 apps to choose from in the EduApp Center, as an instructor using UC Berkeley’s Canvas Learning Management System, I have seemingly limitless options in creating my blended learning course. I can explore the apps I want by category in a product matrix like this one from EdSurge, and simply “plug” them into my institution’s Learning Management System in a custom configuration perfectly tailored to my instructional needs. As Learning Management System designs have moved from all-in-one monoliths to flexible, multi-sided Lego blocks, we have seen instructors and developers at the bleeding edge of this trend create a rich tapestry of learning experiences and tools, showcasing the real potential for plug-and-play to personalize and enhance learning. But has the promise of plug-and-play truly arrived?

For the majority of instructors who are not power users with tech, navigating hundreds of apps with inconsistent integrations with the Learning Management System, as well as data silos locked down by proprietary interests, still represent significant barriers to more widespread adoption of plug-and-play principles. Interoperability and learning analytics are key tenets of the Next Generation Digital Learning Environments (NGDLE) (see more on NGDLE here). They were also two of the most discussed themes at IMS Global’s 2016 Learning Impact Leadership Institute (LILI 2016). Adherence by edTech vendors to developer standards, such as Learning Tools Interoperability (LTI) and Caliper (read more on Caliper Learning Measurement Framework here), offers technical pathways to optimizing plug-and-play that would no doubt have a positive impact on ease of use. As so often the case, however, a technical solution requires a complementary social solution -a mindset shift and knowledge domain acquisition- in order to truly effect change.

The Pedagogy In Interoperabilty

The majority of instructors I work with don’t use the specific term "interoperability". However, in my workshops and sessions with them, instructors often describe their reluctance in sending students “outside” the Learning Management System. They want to use apps that feel connected to the Learning Management System, and that can easily map onto other tools they are already using. For all of their amazing innovation, the explosion of edTech startups has also resulted in extraordinary fragmentation; a symptom of an unstable marketplace of soon-to-be-acquired apps with varied user authentications, redundant features, locked-down content, and worrisome privacy policies around student (and instructor) data.

A vibrant marketplace of tech innovation is not a bad thing, but I also think it becomes more and more necessary to focus professional learning with new technologies on product-agnosticism as much as possible. Too often, our time supporting instructors is spent introducing them to a new product, instead of allowing them to explore tools and features that would be useful to solving a relevant problem. Of course, there is always a specific product presented during professional learning. However, we can also do a better job of deconstructing apps to their core features and use-cases as opposed to demoing an entire product as if selling the instructor a used car. By relegating instructors to consumers of products, we are putting them in a limiting position, setting them up for failure when a product drops off the market or when a license agreement ends.

Focusing professional learning on how tools and features work in combination with each other has two important effects on the future of plug-and-play:

  • First, it better supports iterative adoption of technologies with a transferrable knowledge domain. We can better help instructors think about the components of a lesson plan or learning unit (on-ground, online, or blended), and the various tools, content, and deliveries that can be used to augment and complement components. By avoiding product-dependence and assisting instructors in thinking about apps as modular components, instructors can re-focus on their own pedagogy and student needs, as opposed to trying to master all the features of a single app without ever understanding how multiple apps work with each other.
  • Second, as vendors see their tools being used in more and more specific ways, they in turn may focus on improving those features as opposed to developing entirely new ones, cutting down on feature creep in apps and feature redundancies across apps, neither of which benefit the plug-and-play experience.

Learning Analytics: From Evaluation To Experience

In much the same way that vendor adoption of developer standards such as LTI would improve interoperability in a plug-and-play ecosystem, a similar standard-driven strategy for learning data could ensure 3rd party apps, the Learning Management System, and Student Information Systems (SIS) all deliver uniformly structured data events to a central location, like a Learner Record Store (LRS). Whether this standard is the aforementioned Caliper Framework or something else, when it comes to 3rd party apps in particular, an agreement with vendors to deliver data back to the institution in a standards-compliant format is crucial to the success of learning analytics in plug-and-play. A full picture of a student’s digital footprint offers a wealth of possibilities for improving instruction and early alert systems.

While a universally adopted metric can have an immediate impact, the words “data” and “analytics” still inspire anxieties and uncertainties among many faculties. These uncertainties usually begin with a lack of transparency and knowledge about how data are being collected and used by both edTech vendors and institutions. Widespread adoption of a standard, along with greater clarity around data usage, is a great first step to alleviating anxieties. However, we still want to empower instructors and students to play a more active role in their own data management. For example, a team at UC Berkeley presented a prototype for an analytics dashboard that would communicate to students the data being collected about them and then provide opt-in/opt-out controls for managing how their data are used and accessed (see “Learning Analytics at Scale” for presentation slides).

Transparency and control can help alleviate anxieties about data security and privacy, but instructors remain rightfully worried about how student analytics and performance data will be used to evaluate and track instructor performance. Will instructor analytics motivate instructors to improve their practice, or coerce them to inflate grades under threat of evaluation? It will be important that the former be the point of emphasis and not the latter, and in a fully matured plug-and-play environment, a look at data generated across apps and tools would not only provide a pathway to transparency, but also improve rapid iteration and refinement of courses. Consistent data brought together from across apps and activities can shift the focus from purely outcomes-based insights about what students learned, to deeper looks into student processes and how they learned. A process-based focus can ease anxieties about the limiting context and reliability of purely outcomes-centric approaches, and provide both students and instructors real-time insight into their learning.

Advancing Instructor Success Ιn Plug-Αnd-Play

Refining our professional learning programs and instructional support for plug-and-play begins by:

  • Addressing the foundation and pedagogical arc of a learning experience.
  • Breaking it down into its constituent parts.
  • Mapping that student experience to the variety of tools, activities, and content available online.

Course builder tools that can make more fine-tuned app recommendations based on an instructor’s experience level, the nature of the learning activity and desired outcome, as well as a tool’s feature compatibility with other apps already in the configuration, could help instructors make more informed decisions about the apps they integrate into their course. In terms of data, we can also continue to think about better ways to communicate information about student learning in more process-oriented terms through visualizations that capture student flow in an environment. Most importantly, by moving instructors away from being consumers of products to critical users and appropriators of digital tools, they will also be able to exercise greater agency as influencers in the edTech marketplace.

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