Mapping the Academic Genome

Technology is enabling the rise of precision academics in higher education, writes Myk Garn, who describes the game-changing potential of mapping and coding the academic genome.

August 27, 2018
 
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Mapping of the human genome is exponentially increasing evidence-based innovation in health care. Through precision medicine, medical treatments are personalized and tailored to the individual characteristics of each patient. Mapping and coding the knowledge, skills, attitudes and behaviors, our “academic genome,” and the emergent field of precision academics it will engender, will be equally catalytic for postsecondary education.

This premise of precision is resonating and growing in postsecondary education. For example, instructional thinkers at the University of Michigan and National University advance the most explicit descriptions of precision academics -- using learning telemetry and analytics to tailor instruction to the characteristics, needs, paths and paces of individual learners.

Competencies are the essential, elemental statements of the knowledge, skills, attitudes and behaviors students are expected to learn and demonstrate throughout, and to culminate, their educational journey through postsecondary education. Mapping its academic genome transforms an institution from reliance on the anecdotal, individual implicit objectives of course- and lesson-level teaching to the explicit -- collaborative, digitally linked, aligned and evidence-based learning objectives and outcomes of a digital academic enterprise.

The transformation of postsecondary education from its long and much beloved history of manual, place-based, faculty-paced, master-crafted model of institutional teaching to one of networked, open, student-driven, digital, dynamic and individual learning is underway. Academia has spent years mapping our curricula, measuring college learning and drafting and reporting student learning outcomes. To paraphrase William Gibson, the academic genome is already being mapped, it’s just not evenly distributed -- or sufficiently connected -- yet.

The benefits of this mapping are numerous. They include assignments, assessments and outcomes explicitly aligned to course and program outcomes, to careers, providing more robust and informative documentation for quality assurance, more dynamic student records and better ways to publish those records for different uses and stakeholders.

In their book Degrees That Matter, Natasha Jankowski and David Marshall describe a “learning systems paradigm” that builds on the work of hundreds of postsecondary institutions using the Degree Qualifications Profile, Tuning and the VALUE Rubrics of the Association of American Colleges & Universities to map what is their local academic genome. This work makes possible the specification and coding of digital, machine readable cyberobjectives and cybercompetencies, which are finely grained, unambiguous, actionable statements of instructional intent. The resulting continuous telemetry of real-time, digital data enables evidence-based analytics and adaptivity developments which are increasing the power and efficacy of learning systems.

Maybe you think that is great … maybe you don’t. But it is happening -- all around us.

Public K-12 systems in many states, including Georgia, are coding and connecting their learning standards together. The 50-State Digital K-12 Academic Standards Registry (announced by IMS Global Learning Consortium) enables coding, sharing and linking standards across every state in the registry. Richard Woods, Georgia’s school superintendent, said, “We see this not just as the adoption of a technical standard, but as a mechanism to help us realize one of our strategic initiatives -- the move toward personalized learning for every Georgia student.”

The Competency Model Clearinghouse, developed by the Employment and Training Administration in collaboration with other federal agencies and work-force development experts, documents the skills and competencies required in emerging and economically vital industries.

The Occupational Information Network (O*NET), developed under the sponsorship of the U.S. Department of Labor’s Employment and Training Administration, has digital descriptors for almost 1,000 occupations covering the entire U.S. economy. Every year, O*NET is used by millions to find the training and jobs they need, and by employers to find skilled workers.

The T3 Innovation Network under development by the U.S. Chamber of Commerce Foundation is building the talent development pipeline and marketplace of the future and using digital Web 3.0 technologies to better align learner, education and work-force data to improve the talent marketplace.

To connect with these digital talent development pipelines, postsecondary education must also become more digital. And there is progress. The Credential Connection is a collaboration of more than 120 postsecondary and work-force organizations. It is curating a highly diverse and fragmented credentialing system into one that evidences educational quality, increased access and better alignment with employers, education and certification/licensure agencies.

Digital Drives Analytics -- Analytics Drive Performance

The future of postsecondary instruction (and learning … and institutions) will be more and more digital. If you have not heard of Georgia State University and predictive analytics, you are missing the awakening of academia to the use of data that significantly informs and improves the performance success and attainment by students. By using data on past performance to predict future problems, GSU has been able to develop, time and deliver effective intervention strategies that have increased degree awards by over 67 percent in six years. The influence on other University System of Georgia institutions is significant. No one shows up at a budget meeting without performance data now. If institutions can make this kind of improvement with static, legacy data, just imagine what they could do with real-time data telemetry from students -- as they are learning.

The emergent field of learning analytics is bringing just this kind of evidence-based telemetry analysis and practices to lesson and course-level design and deployment. Faculty are crossing the chasm from handcrafted to technology-enabled instruction. Want a glimpse of what that might look like? Watch this video. That’s what got (and keeps) me going down this road.

A visual, playful learner seeing the ability to explore and manipulate a digital curriculum, and thus digital courses, is totally captured in the 1:41 it takes Professor Euan Lindsay at Charles Sturt University in Australia to explain how their engineering curriculum can be personalized to the individual student. Imagine being able to take this to the lesson level, with learners and faculty as active co-conspirators in the game of learning. This is what the digital mapping and coding of a curriculum is all about.

Imagine further taking this granular data into a comprehensive learner record. The ability to learn once and render many ways will change expectations and drive the radical transformations George Mehaffy envisions in “Reimaging the First Year of College.”

What Do We Need to Do?

Watching this transformation in other sectors, we can clearly see technology will drive change faster and with greater disruption than we can currently imagine. For generations the currency of academia has been the credit hour. The cybercurrency of the educational future will not be credit hours. It will be cybercompetencies. And there are several things we can do to prepare.

Continuing to map the academic genome is the first step. Mapping our current, handcrafted syllabi transforms them into actionable cyberobjectives, competencies and connects them to the digital ecosystem of learning, credentials and careers.

Build from local curriculum maps to national frameworks using open, shared platforms to collect, aggregate and crosswalk frameworks and their components into resources that inform, and power new instructional and institutional designs rather than maintain the existing limitations on them.

Take the next step by coding the academic genome. Mapping is not the endgame. By coding learning objectives, competencies and outcomes into fine-grained, unambiguous, machine readable/actionable, digital elements we will open and operationalize new continuous telemetry learning models. Good coding, like building good assignments and assessments -- like good teaching -- is hard, but necessary and rewarding work.

Establish an open-source competency ecosystem. We need competencies to be open, shareable and connectable within and among both third-party and open-source platforms. Everyone will benefit from resources connected under common technical constructs. This "edusystem" of competencies will be a resource for faculty building courses, aligning learning to industry competencies and communicating out student proficiencies to transcripts and employers.

Embrace the next paradigm: precision academics. A digital academic genome doesn’t just change the possibilities -- it changes the game. All of the preceding work prepares us to move from episodic dives into programmatic design and redesign to the truly transformative leap into an evidence-based, ongoing engagement in a dynamic curriculum that is continually informed and refreshed.

Digital will drive innovation in postsecondary instruction for the foreseeable future. Technology is fusing with the expertise of faculty in ways that engage, enable and extend the best abilities of each. How much it will transform has yet to be seen.

Bio

Myk Garn is assistant vice chancellor for new learning models at the University System of Georgia.

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