Page 63 - Campus Technology, October/November 2019
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CT: So is the interest in more of a scien- tific, “learning engineering” approach coming from the instructional design community? Wagner: Today’s rising interest in learning engineering is not necessarily coming from learning professions themselves. Some of the biggest growth in interest is coming from professionals working in hard sciences — including computer science and data science, to name two important examples. These are all environments where interest in using emerging new media such as augmented and virtual reality is high, and comfort in dealing with large experiments is significant. Perhaps even more important, there is willingness to engage in large-scale research that is pushing data analysis and evaluation comfort levels past where traditional providers of ID prod- ucts and services are willing to go. Big data research methods, coming from computer science and data science, are starting to chal- lenge education researchers to reconsider their entire approach toward social science research modeling. CT: It sounds like the professionals cover- ing instructional design and the learning sciences are dealing with a complex set of issues that could impact technology adoption and application. Wagner: Welcome to the flexible, frustrating ambiguity of the field of instructional design, sometimes called instructional systems design, sometimes called learning design — which is now also featuring branches of learn- ing experience design — with instructional and education technology, and on rare occa- sion, with human performance technology thrown in for good measure. CT: Of course there are no quick fixes, but is there something relatively simple that could be done to move traditional ID more toward the learning sciences? Wagner: Well, it could be that one of the fruit- ful avenues for exploration is for instructional designers to revisit the literature and practic- es of learning sciences, and to reclaim them for the practice of ID. There is a rich body of ID literature that is available to be shared with those coming from the learning sciences. CT: Circling back to data, what is impor- tant to do in higher education to use our data well? Wagner: As data makes its way into our deci- sion-making paradigms, and as we have tech- nology platforms available in workplaces and on campuses to link learners with assets and experiences, we need to consider what it takes to ensure that those platforms link learners to the learning experiences that they desire to achieve their goals and for enter- prises to realize a return on investment. 63 

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