Themes: The time has come to introduce ITS technology into commercial educational technology. Investment in new eLearning products that feature learning analytics and some form of adaptivity has soared at all levels of education. Meanwhile, established companies such as Carnegie Learning, Knewton, Stottler-Henke, Acuitus, Alelo, Intelligent Automation, ASSISTments, ALEKS, and Reasoning Mind are offering commercial products branded as “intelligent.” The market is ready for intelligent tools for teachers and learners, yet the road from pilot studies that demonstrate efficacy to successful products and meaningful advances in teaching and learning is long and littered with casualties. Can anything be done to expedite the movement of ITS ideas and technology out of the lab and into sustainable products, services, or open source projects with significant market adoption?
There are, of course, multiple reasons that research projects fail to make the leap from the lab to the marketplace, including lack of business experience and lack of interest in commercialization. But even with favorable conditions in place, there is an almost universal shortcoming of the intelligent systems built by researchers that has prevented widespread dissemination and marketplace success: the systems built by researchers are not designed to operate as part of the educational technology software ecosystem. In the past, this simply meant interoperating with learning management systems, registrar, and Human Resources systems. Now it means becoming part of a suite of educational technologies that is complex, rapidly growing, and driven by new standardization efforts.
This tutorial will help participants understand and address the requirements for interaction and data interoperability that define the modern elearning ecosystem.
Content Covered: This tutorial is organized into six segments.
(1) The changing shape of the eLearning ecosystem: Deep and broad structural changes are taking place in elearning – economically, technologically, and pedagogically. These include the introduction of massively online courses, the disassembly of learning management systems, new business models, portability of student records, data-driven learning tools, and an emerging consumer market for self-directed education and training. This tutorial will begin with a survey of the educational technology marketplace from multiple perspectives: those of a student, a business person, a customer, and a software developer. This portion of the tutorial will look at what is “wired,” “tired” and “mired” and will engage participants in thinking about factors such as business models, value propositions, and integration with widespread consumer technologies that affect the ability to commercialize products.
(2) New Product Categories and Architectures: As teachers and students embrace the web and mobile technology, established product categories are being challenged by a variety of new types of learning products, including immersive learning environments, multiplayer games, massive online courses, dashboard apps for teachers, content aggregation services, eBooks, and personal learning assistants for students. These products are generating massive amounts of data about student abilities, history, preferences, comprehension and points of confusion. These data are being stored in new products such as Learning Record Stores and Student Data Lockers, opening up new possibilities for educational data mining and ITS. At the same time, the institutional approach to creating a learning environment is changing to one in which learning systems share data and are aggregated rather than managed centrally. This tutorial will cover these fundamental shifts and engage in a small group exercise in which participants will be asked to propose an ITS in response to an RFP for an aggregated learning environment. The goal is to identify the requirements that an ITS must meet.
(3) Interoperability standards: In an LMS-centric environment, stand-alone interventions may be suitable as teaching tools and for formative assessment, but interventions must report results and outcomes to be considered credit-worthy. As learning analytics and educational data mining become more important, data must be collected and reported by all interventions, regardless of their use or role in a learning experience, course or curriculum. This is the first level of data interoperability. The second level of interoperability for an ITS involves sharing internal models, e.g. domain models and learner models. This enables data gathered by one ITS to be used for adaptation by a second ITS, or by a student’s personal learning assistant or a teacher’s dashboard app. Both levels of interoperability are the subject of multiple standardization efforts that promise to influence and guide how ITS are built. This tutorial will include a “short crash course on standards” that introduces participants to interoperability standards that are used to share data among cooperating learning technologies.
This segment will focus on the data and information shared and not on the technical details of how the data is represented or transmitted. (References to the technical details will be supplied.) Participants will see demonstrations of software that applies the standards and will engage in exercises that construct pairs of hypothetical learning and teaching tools that share data using standards in an essential way. This segment will conclude with a discussion of how data sharing impacts commercial viability and can be used to enhance the marketability and value of educational technologies.
(4) Marketplace Models: There are several models for dissemination of ITS. Some have been developed from the get-go as commercial systems. Others have been transitioned from funded research to a for-profit model. Still others have been disseminated as freely available tools. This segment will examine these models in light of the requirements identified earlier in the tutorial.
(5) Getting to Good Enough: Compromise is inherent in any effort to achieve market adoption and sustainability; the “perfect,” becomes the enemy of the “good.” We will look at a sampling of ITS in a critical but non-judgmental way to identify what compromises have been made in functionality, features, and effectiveness in the interests of commercialization. We will then go through the group exercise of modifying a hypothetical ITS (described in detail on a “handout”) to make it marketable.[Av1]
(6) Wrap-up: We will end with a summary of marketplace issues and pointers to additional resources.
Intended Audience: This tutorial is intended for (a) ITS researchers and developers who are interested in commercialization of their work; (b) a general audience interested in the larger ecosystem of learning technology into which ITS fit; and (c) current ITS product developers who are looking for insights or who would like to share their experience in the marketplace. There is no maximum size limit for the tutorial.
Background Required: Participants should have the general level of knowledge about ITS, elearning, and educational technology that can be assumed of the typical ITS conference attendee. A technical background in software is not required.
Evidence of Interest: We have not solicited attendees. However, the topics to be covered align with multiple current efforts and programs that hope to promote the commercialization of research in advanced elearning systems: NSF’s Innovation Corps, Professor Beverly Woolf’s Presidential Innovation Fellowship, SRI’s Cyberlearning Partnering for Impact project, ONR’s Grand STEM Challenge, and DARPA’s Education Dominance. The massive investment in and broad public awareness of new products like the Khan Academy, Coursera, and edX are evidence that the time is right for ITS technology to have a major impact on the way we teach and learn.
Format: As described above, the format will combine presentations, discussions, demos and with small group exercises centered around detailed, pre-packaged descriptions of hypothetical ITS products. The tutorial will be structured to be interactive and hands-on but will not require participants to work with real products or software.
Outcomes: Participants will leave with a broad understanding of commercial elearning product trends and with the way modern elearning solutions are assembled. Armed with this knowledge, they will be able to re-architect their research projects in anticipation of the commercialization process.