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Higher Education, Technology and Complexity: Working in the Margins

By Charles Dziuban, Director Research Initiative for Teaching Effectiveness, University of Central Florida

Charles Dziuban, Director Research Initiative for Teaching Effectiveness, University of Central Florida

More than fifty years after the publication of Thomas Kuhn’s classic, “The Structure of Scientific Revolutions” his theory of paradigm shift seems particularly relevant to contemporary higher education. Colleges and universities face many challenges; i.e., rising tuition and ballooning student debt, the widening gap in expectations for degree attainment according to economic status, increasing ambiguity about the value of a college education and the realization that today’s students have an important voice in defining educational excellence. Analysis of the current educational environment confirms that technologies both, informational and instructional, impact higher education in important ways. This is evident from the way universities are organizing learning environments, assessing students’ achievement, determining readiness for the work place and supporting success in gateway courses. Evidence of these changes includes instructional modalities such online, blended, lecture capture, massive open online courses, flipped classrooms and active leaning courses among a growing number of class and program formats. Twenty years ago these terms were revolutionary and others were yet to appear but now they are common place and well-established in the higher education lexicon. Students (and faculty) live in a world of what Moville calls ambient find ability where information is the most readily available resource on the planet and the economies of the G7 countries are primarily driven by information rather goods and services. The potential educational change is so profound that the Economist dedicated and entire issue to these pressures on the learning space terming that piece Creative Destruction.

"Advancing technology is surrounding our educational system and forcing it into configurations scarcely considered a few years ago"

 

In recent years the adaptive learning format (AL) has shown promise as an effective innovation. The process is underpinned by a leaning environment described by John Carroll. He argued that if the amount of time astudent devotes to learning a concept, acquiring knowledge or developing skills is fixed then learning outcomes will be the variable. However, if what students learn is held constant then by definition learning time will become the variable. The idea is well over fifty years old but historically, implementing AL at scale has been too time consuming and cumbersome. Yet modern adaptive learning platforms enable universities to implement programs that give students a large measure of control over their learning space. For example, they can proceed at their own pace finishing a course early or extending the learning time well beyond traditional boundaries such as a semester. Such latitude becomes a distinct advantage for first time in college students as well as those from impoverished communities. The time modification aspect in learning has been demonstrated for other course modalities as well. For instance blended learning can be configured effectively with temporal dimensions. This creates challenges for the traditional organizational structure of universities while it presents many opportunities for innovative practice. The University of Central Florida (UCF) and Colorado Technical Universality (CTU), both early adopters of adaptive instruction, have teamed with their platform provider Realizeit in a cooperative research agreement examining the impact and outcomes of this flexible go at your own pace learning format. Each organization brings particular capabilities to the relationship. UCF is research intensive, CTU is successful at implementing AL at scale and Realizeit is expert in advanced data visualization techniques. Together the three organizations demonstrate that students react positively to the affordances of adaptive learning, that the modality offers promise for real time predictive analytics and that adaptive learning stabilizes the learning environment across disciplines and universities. Because AL reframes teaching and learning, it creates an optimal environment for cooperation among universities and providers. Additional evidence of this growing cooperative trend can be found in the newly formed Empirical Educator Project organized by MindWires (mindwires.com)—a national collaborative among many constituencies creating robust research findings about effective educational practices.

In recent years the adaptive learning format (AL) has shown promise as an effective innovation. The process is underpinned by a leaning environment described by John Carroll. He argued that if the amount of time astudent devotes to learning a concept, acquiring knowledge or developing skills is fixed then learning outcomes will be the variable. However, if what students learn is held constant then by definition learning time will become the variable. The idea is well over fifty years old but historically, implementing AL at scale has been too time consuming and cumbersome. Yet modern adaptive learning platforms enable universities to implement programs that give students a large measure of control over their learning space. For example, they can proceed at their own pace finishing a course early or extending the learning time well beyond traditional boundaries such as a semester. Such latitude becomes a distinct advantage for first time in college students as well as those from impoverished communities. The time modification aspect in learning has been demonstrated for other course modalities as well. For instance blended learning can be configured effectively with temporal dimensions. This creates challenges for the traditional organizational structure of universities while it presents many opportunities for innovative practice. The University of Central Florida (UCF) and Colorado Technical Universality (CTU), both early adopters of adaptive instruction, have teamed with their platform provider Realizeit in a cooperative research agreement examining the impact and outcomes of this flexible go at your own pace learning format. Each organization brings particular capabilities to the relationship. UCF is research intensive, CTU is successful at implementing AL at scale and Realizeit is expert in advanced data visualization techniques. Together the three organizations demonstrate that students react positively to the affordances of adaptive learning, that the modality offers promise for real time predictive analytics and that adaptive learning stabilizes the learning environment across disciplines and universities. Because AL reframes teaching and learning, it creates an optimal environment for cooperation among universities and providers. Additional evidence of this growing cooperative trend can be found in the newly formed Empirical Educator Project organized by MindWires (mindwires.com)—a national collaborative among many constituencies creating robust research findings about effective educational practices.

 

Furthermore, many technologies not specifically targeted to teaching and learning impact higher education. Two obvious candidates are artificial intelligence and quantum computing. There are others as well such as artificially developed fuel, engineered farming, cell mapping, hydrogen powered automobiles, advanced 3D printing and instant language translating ear buds to cite a few examples. Each one or combinations of these technologies should they develop into wide spread application will modify not only what we teach but emerging pedagogy. Advancing technology is surrounding our educational system and forcing it into configurations scarcely considered a few years ago.

However all of this innovation comes with caveats. For instance many educators question the quality of technology mediated learning arguing that it lacks reflectiveness, authenticity and contextual relevance. This has given rise to the culture of identifying the components of quality then using them as the basis of measurement rubrics. Although some progress has been made there are many who contend that measuring quality is not a particularly useful pursuit because is almost entirely observer dependent—an issue that needs resolution

Attempts at using experimental methods to assess the effectiveness of technology mediated learning have not been convincing; for example, studies directed at assessing the learning outcomes from online, blended and face to face courses where each of those modalities has been configured as a treatment effect. Unfortunately those class formats encounter so many confounds form the educational environment that isolating their impact is virtually impossible or at least highly unlikely.

Finally O’Neal calls our attention to the potential harmful impact of algorithms running in the background of our educational and personal lives. She contends that, often, these programs systemize mistakes and bias into the software systems that are opaque and lack any kind of meaningful feedback mechanism. She states, “They define their own reality and use it to justify their results.” Educators need to be vigilant of new technologies that can foster these kinds of negative impacts.

However, despite these concerns, modern instructional technologies are fueling Kuhn’s paradigm shift in higher education, offering more effective learning possibilities across many disciplines for students of all backgrounds. Higher education is changing and in most cases for the better. As we consider the impact of technology, however, my caution is not to overestimate its short term effectiveness and underestimate its long term impact. We are operating within complex systems with the emergent property. They are more than the sum of their individual components where their interactions comprise the most important outcome making cause and effect particularly elusive.

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