NMC Horizon Project Technology Outlook: Where Our Learners Are Going

June 24, 2013

With the release of their first Technology Outlook: Community, Technical, and Junior Colleges (2013-2018), our colleagues at the New Media Consortium (NMC) have provided the fourth of a four-part comprehensive overview of how the learners headed for our workplace learning and performance (staff training) programs are using technology in their own learning endeavors. (The other three parts of that overview are the 2013 K-12 report, with a brief overview video; the Technology Outlook for STEM + Education 2012-2017; and the Horizon Project 2013 Higher Education report with its own video overview.)

NMC--Tech_Outlook_Community_CollegesAlthough the flagship Higher Education report remains one of NMC’s key publications each year (as I documented in four interrelated blog posts earlier this year after serving on the report advisory board), the K-12, STEM + Education, and Community/Technical/Junior Colleges editions help us see how technology continues to be an important element of the learning experience for everyone, from our younger (K-12) learners through those involved in colleges and universities. And if that weren’t enough for those of us working with graduates of our formal academic system, NMC also has facilitated annual future of education conferences over the past couple of years to produce lists of metatrends and essential challenges in teaching-training learning to guide us in our own efforts to keep up with what our learners and colleagues involved in facilitating learning are experiencing.

As is the practice with other NMC reports, the Community, Technical, and Junior Colleges report focuses on highlight lists of technologies that are likely to have significant impacts within short (one-year), medium (two- to three-year), and longer (four- to five-year) horizons. Top trends impacting technology decisions within the venues are explored within the report; significant challenges facing learners and learning facilitators within those venues are also summarized and highlighted.

But most interesting in terms of bridging the venues covered by those four (K-12, STEM + Education, community/technical/junior colleges, and higher education) complementary reports is a section in the new report comparing final topics across various NMC projects.

Community_College_Research_Center_LogoWhat we see from that summary on the first few pages of the new report is that innovations including flipped classrooms, the use of mobile apps in learning, augmented reality, games and gamification, and wearable technology are finding their way into learning at all levels—just as they are in our own workplace learning and performance endeavors. We also see that attention-grabbing innovations including massive open online courses (MOOCs) are changing the way we view our approach to online education, but they are entering our learning landscape at differing rates. (Higher education seems far better positioned to effectively incorporate MOOCs into our learning landscape than do community colleges, where a recent first-rate study—“Adaptability to Online Learning: Differences Across Types of Students and Academic Subject Areas,” published through the Community College Research Center, Teachers College, at Columbia University—documented the difficulties that community-college students face in learning how to learn in online environments.)

And this is where the new report makes a firm connection to what we are doing and facing in workplace learning and performance: “The workforce demands skills from college graduates that are more often acquired from informal learning experiences than in universities,” the report writers note (p. 2). This provides new challenges for teacher-trainer-learners in community, technical, and junior college settings, they continue: “As technology becomes more capable of processing information and providing analysis, community college efforts will focus on teaching students to make use of critical thinking, creativity, and other soft skills.”

The learning circle becomes complete when we acknowledge that our own training-teaching-learning roles are rapidly changing in ways many of us still have not completely understood or accepted; just as our colleagues in academia are having to come to terms with facilitating learning as much as attempting to control it, we are going to have to argue—with our employers, our colleagues, and our clients—that one-size-fits-all learning was never a great model under any circumstances; that learning offerings that remain focused on learners passing exams and achieving certification/recertification really don’t serve anyone very well; and that creating communities of learning where technology facilities rather than drives learning ultimately produces learning that meets learner and business goals in magnificent ways.

Reading, thinking about, and acting upon the contents of any single NMC report certainly places each of us—and our learners—in a great position: we walk away from these reports with our own crash courses in what is happening in our ever-expanding and wonderfully challenging learning landscapes. Reading, comparing, and acting upon the content of the various reports helps us viscerally understand what we need to know so we can help our learners more effectively shine in a world where learning never stops—to the benefit of all involved.


Adaptability to Online Education: Replacing Failure with Success

March 8, 2013

Those of us engaged in and stimulated by #etmooc (an online Educational Technology & Media course) and other training-teaching-earning endeavors already have plenty of evidence that the best online learning offerings can produce results at least as good as what comes out of the best face-to-face learning. Our participation in that massive open online course (MOOC), in fact, is providing us with visceral proof that online engaging can be engaging, rewarding, and capable of producing tangible results if the right elements are in place and if we are properly prepared.

etmoocNow, thanks to researchers Di Xu and Shanna Smith Jaggars, we have a thoughtful and thought-provoking research-based study showing what can hinder success among certain groups of online learners.

Focusing on failure rates of online learners drawn from a very large sample (40,000 community and technical college learners throughout Washington state, tracked over a five-year period), Xu and Jaggars have produced a paper that includes insights useful to any of us involved in training-teaching learning. “Adaptability to Online Learning: Differences Across Types of Students and Academic Subject Areas” (published through the Community College Research Center, Teachers College, at Columbia University), opens with a well-balanced introduction that cites previous research papers comparing face-to-face and online learning; provides observations about why some students may do better than others in online learning environments, e.g., “those with more extensive exposure to technology or those who have been taught skills in terms of time-management and self-directed learning…may adapt more readily to online learning than others” (p. 1); and includes the suggestion that “insufficient time management and self-directed learning skills” could contribute to the online learning failures examined in their paper (p. 4). Reading that section alone gives us a wonderfully concise overview of the challenges we and our learners face, and it serves as a great example of the sort of resources coming out of the open movement—the subject of our latest #etmooc module.

As we move more deeply into Xu and Jaggars’ 32-page paper, we learn more about the writers’ meticulous methodology; the subjects of their study and the types of courses they were attempting to complete; and the possibility that “older students’ superior adaptability to online learning lends them a slight advantage in online courses in comparison with their younger counterparts” (pp. 17-18). They go far beyond the usual basic levels of evaluation and ponder the possibility that peers’ behavior can have positive or negative effects on the learning process: “These descriptive comparisons suggest that a given student is exposed to higher performing peers in some subject areas and lower performing peers in others and that this could affect his or her own adaptability to online courses in each subject area” (p. 21).

Community_College_Research_Center_LogoIn reaching the conclusion that those who struggle with face-to-face learning are even more likely to struggle with and fail at online learning, Xu and Jaggars lead us to an interesting set of conclusions and recommendations that include “screening, scaffolding, early warning, and wholesale [course] improvement” (p. 25).  Acknowledging the difficulties inherent within each of their four suggestions, they leave us with proposals to define online learning “as a privilege rather than a right” and delay learners’ entry into online learning “until they demonstrate that they are likely to adapt well to the online context”; to incorporate “the teaching of online learning skills into online courses…”; to build “early warning systems into online courses in order to identify and intervene with students who are having difficulty adapting”; and “focus on improving the quality of all online courses…to ensure that their learning outcomes are equal to those of face-to face courses” (pp. 25-26).

None of this is revolutionary, nor is it beyond our reach. Preparing learners for new learning experiences before we toss them into the deep end of the learning pool simply makes good sense. Offering them help in developing their online learning skills is something that many of us already routinely do for online learners, and there are plenty of online examples at the community-college level alone for anyone who has not yet traveled this particular learning path. Building early warning systems into the process goes hand-in-hand with the increasing levels of attention we are giving to learning analytics and learning analytics tools; even at a rudimentary level, I’ve been able to increase retention rates in online courses by noting who is falling behind on assignments and sending individual notes to check in occasionally with those learners—the result is that the learners invariably note, in their course evaluations, that they had no idea online learning could be so personal and engaging. And the suggestion that we look for ways to further improve the quality of courses to make them more responsive to learners’ needs is a conclusion that hardly needs response; the wicked problem we face in meeting that challenge is to obtain the resources needed so we—and our learners—will be successful rather than being part of another report on why learners fail.

N.B.: This is the eighteenth in a series of posts responding to the assignments and explorations fostered through #etmooc.


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