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Horizon Report: Knowledge Obsolescence, Artificial Intelligence, and Rethinking the Educator Role

Skiba, Diane J.

doi: 10.1097/01.NEP.0000000000000154
DEPARTMENTS: Emerging Technologies Center
Free

The author declares no conflict of interest.

The New Medium Consortium Horizon Report 2017 is a mixture of old, continuing, and a few new concepts (Adams Becker et al., 2017). Each year I summarize the results of this report, which identifies trends, challenges, and emerging technologies on the horizon. (The method used to determine these factors is outlined in the report.)

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TRENDS

As in the past, the report presents short-term, mid-term, and long-term trends. The short-term trends highlighted for 2017 are blended and collaborative learning. Blended learning has been a consistent trend since 2012. As online learning has become more accepted in the academy (Skiba, 2017a), research to identify best practices in online and face-to-face learning has spearheaded the offering of blended learning opportunities. With the availability of more dynamic learning management platforms, universities are able to offer flexibility, ease of access, and various multimedia technologies to complement the occasional face-to-face meetings. Adams Becker et al. (2017, p. 9) note that the “current focus of this trend has shifted to understanding how applications of digital modes of teaching are impacting students.”

Collaborative learning, mentioned in 2012, has now resurfaced and focuses on four principles: “placing the learner at the center, emphasizing interaction, working in groups, and developing solutions to real challenges” (Adams Becker et al., 2017, p. 9). The term has been around for a long time as many in the online arena have formed communities of practice. What has changed is the technology. We now have cloud-based services and shared workspace tools that facilitate the ability of groups and teams to work together, anytime and anywhere.

A mid-term trend, mentioned since 2013, is the measurement of learning and the use of assessment tools to document academic readiness, learning progress, and educational outcomes. What is different now is the availability of data mining and visualization tools. One continuing difficulty is how to measure the soft skills that employers value, such as collaboration and creativity. The other mid-term trend, mentioned since 2015, is the redesign of learning spaces with more digital tools to promote active learning and engagement in classroom settings.

The two long-term trends are both familiar. The goal of deeper learning (project based, challenge based, or inquiry based), first mentioned in 2012, is “mastery of content that engages students in critical thinking, problem-solving, collaboration, and self-directed learning” (Adams Becker et al., 2017, p. 9). In nursing, deeper learning could be intertwined with the interprofessional team goals outlined in your curriculum.

The second long-term trend is advancing cultures of innovation, mentioned since 2015. As many faculty know, it is difficult to foster an environment of innovation. As noted by Adams Becker et al. (2017, p. 10), a recent Chronicle of Higher Education study (http://chroniclegreatcolleges.com/blog/indicators-cultureinnovation/) identified five overarching themes to foster innovation: “the need for open communication, collaboration within departments, job security when challenging the status quo, shared responsibility, and top-down support.” I remember when we first transitioned courses to an online format in 1998. As associate dean, I wrote letters extolling the leadership and creativity of those early faculty who were fearful of getting terrible course evaluations because they were challenging the status quo.

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CHALLENGES

Two solvable challenges have been on the list since 2015: improving digital literacy and integrating formal and informal learning. We need to push our institutions to have general requirements about digital literacy and provide educational materials to prepare all students and faculty. In nursing education, we need to build on this foundation and expand our teaching from merely judging the validity and veracity of web pages to encompass the social media tools and mobile applications used by our patients.

The integration of informal and formal learning should lead students to develop a commitment to lifelong learning. Institutions in many countries have begun to develop strategies for recognition of prior learning. Information about Australia’s recognition program is online (www.mq.edu.au/study/admissions/recognition-of-priorlearning), as is information about Trinity College’s program (www.tcd.ie/teaching-learning/assets/pdf/RPL%20Policy%20Final.pdf).

California State University offers the Channel Islands Digital Badges project (http://nursingdigitalbadges.jaimeahannans.com/). A student must complete QSEN learning modules and various activities to earn a digital badge. For example, the Caregiver Empathy digital badge requires completion of the QSEN module, submission of a reflective discussion paper, and nomination by a peer or faculty member highlighting an event where the student demonstrated caregiver empathy.

Two new difficult challenges are the achievement gap and achieving digital equity. According to Adams Becker et al. (2017, p. 28), “the achievement gap…reflects a disparity in the enrollment and academic performance between student groups, defined by socioeconomic status, race, ethnicity, or gender.” Rising tuition costs is certainly one major issue, but the question for most institutions is how to use data analytics for personalized learning and to connect students with necessary support systems, such as writing centers and tutors.

Digital equity refers to inadequate access to the Internet, especially broadband access. Although many think this is an issue only in developing countries, Holmes (2016), writing for the Center for Public Integrity, reports that 30 million Americans lack broadband access. It is important to note that access can also refer to making web content accessible to disabled populations. To learn more, you can visit www.w3.org/WAI/intro/accessibility.php.

Two new wicked challenges — those that are complex to even define, much less address — are of particular importance to faculty. The first is managing knowledge obsolescence. It is hard enough in health care to keep pace with the growth of knowledge in one’s own discipline or specialty. As faculty, we are constantly updating courses, trying to stay one step ahead of our students. On top of that, we are expected to manage knowledge related to teaching-learning, educational technologies, and devices that are accelerating at warp speed. In some universities, the emphasis on research and scholarship overrides the recognition of teaching innovations. Pennsylvania State University offers faculty support with a three-pronged approach that encompasses faculty experimentation, programmer and instructional design support, and faculty and administration problem solving. A good example explores smart watches and learning (www.centerdigitaled.com/higher-ed/How-to-Help-Faculty-Explore-Wearable-Technology-for-Learning.html).

The second wicked challenge involves rethinking the roles of educators. Remember the prediction that we, as educators, would move from Sage on the Stage to Guide on the Side? Now, more than ever, this is becoming a reality. Faculty are being asked to incorporate many new teaching strategies that focus on concepts such as learner-centered education and competency-based education, with, of course, all education being supported by use of the latest and greatest educational technologies. As this shift occurs, many schools are beginning to rethink the role of the educator and what faculty models should guide institutions in the future. The TIAA Institute (2016) commissioned a study to examine higher education stakeholders’ views of faculty models. Read the executive summary or full report to learn more.

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ON THE HORIZON

For the category Educational Technology Developments on the Horizon, there are four previously listed technologies and two that emerged recently. Adaptive learning technologies are in the category one year or less. For the marriage between personalized learning and learning analytics, these technologies monitor student learning and adjust the presentation of content based on the learner’s performance, accelerating or remediating as needed. The 2016 Digital Learning Innovation Award was given to an adaptive learning project at Tougaloo College (https://onlinelearningconsortium.org/about/2016-dliaward-recipient-tougaloo-college).

The other technology on the one-year or less horizon, mobile learning, was on the list in 2012 and reemerged. “Mobile devices have become the gateways to personalized working and learning environments that facilitate the exploration of new subjects at each user’s pace” (Adams Becker et al., 2017, p. 40). Learning management tools are being adapted for use on smartphones and tablets as fewer students have desktop computers. We use a video-conferencing program for team meetings, virtual office hours, applicant interviews, and comprehensive exams in our MS program. Most students connect via their tablet or smartphone.

The use of mobile technology is also highlighted in classrooms and large lecture halls as a mechanism to engage students and have them become more interactive. At Purdue University, students use an app, called Hotseat (www.itap.purdue.edu/studio/hotseat/), to ask questions and comment in real time in class. Students can then ask each other questions or add to the comments. Faculty find that the app helps them modify their teaching, engage students, and give voice to those “quiet” students. Here is a good link to how m-learning is helping nurses in African countries maintain their professional licensure (www.nursinglibrary.org/vhl/bitstream/10755/617333/1/Mukami_D_s22990_1.pdf).

On the two- to three-year horizon are two technologies: the Internet of Things (IOT), on the list in 2012, 2015, and 2017, and next-generation learning management system (LMS), a new entry. Asseo, Johnson, Nilsson, Chalapathy, and Costello (2016), industry leaders representing various companies (Salesforce, Google, Extreme Networks, Education Innovation, and Cisco), describe the impact of the Internet of Things on education.

The next-generation LMS is exciting. I like the idea of a next-generation digital learning ecosystem that represents a mixture of IT systems to enhance learning, support personalized learning, conduct formative assessments, and have interoperability with common tools provided by other vendors. With the growing use of learning analytics and open educational resources, this ecosystem will be more important as we structure competency-based education and adaptive learning strategies. Similar to nurses providing holistic care to a patient, the next-generation LMS ecosystem should provide a holistic picture of learning.

On the four- to five-year horizon, there are natural user interfaces, which first appeared in 2012 and are now resurfacing. With the development of gesture-sensing technology, voice recognition, and haptic technology, the learner can engage in virtual activities using a multitude of natural user interfaces. These are perfect for engaging students who may have disabilities. Natural user interfaces also allow students to feel the experience, such as when nursing students at Hong Kong Polytechnical University use a haptic feedback system to learn how to insert a nasogastric tube (https://www.polyu.edu.hk/cpa/milestones/en/201609/research_innovation/life_sciences/computerised_haptic_system_facilitates_nasogastric/index.html). Another example is HoloMed, a holographic system paired with a gesture-based interface that helps students more accurately visualize the childbirth process (Adams Becker et al., 2017; https://arxiv.org/pdf/1607.05812.pdf).

The newest and most fascinating technology in the four- to five-year window is artificial intelligence. As I mentioned in my last column (Skiba, 2017b), cognitive computing and virtual assistants are already surfacing in the health care arena. IBM’s Watson is being used at Deakin University as a 24/7 online help desk (www.deakin.edu.au/about-deakin/media-releases/articles/ibm-watson-helps-deakin-drive-the-digital-frontier). Imagine that the next-generation LMS will come with virtual assistants that can help tutor students who are struggling with understanding a particular concept or figuring out how to calculate drug dosages for a premature baby. Soon you will call upon Siri, Cortana, and Alexa to help you conduct a literature search to find the best practices for a particular nursing intervention.

I would hope for a virtual writing tutor so students can get guidance when they have an incomplete sentence or a sentence that does not make sense. What will be really exciting is to have tools to mine and analyze the mounds of data we can collect on a learner and use machine learning to create personalized learning pathways and help faculty with student engagement, retention, and the demonstration of learning outcomes. It will be exciting to see what the future holds as artificial intelligence and cognitive computing become more commonplace.

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SUMMARY

The Horizon Report 2017 offers a reinforcement of previous trends, challenges, and technologies. As faculty, we need to embrace some of these technologies and envision how to tackle the challenges before us. I am also excited to see new additions, particularly in the technology realm.

These new technologies offer much to help us provide a holistic learning experience for our students. I am also pleased to see that we are starting to rethink the role of the educator and beginning to explore new faculty models. I look forward to your thoughts and ideas as we venture forth in the new horizon. As always, you can email me at Diane.Skiba@ucdenver.edu.

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REFERENCES

Adams Becker S., Cummins M., Davis A., Freeman A., Hall Giesinger C., & Ananthanarayanan V. (2017). NMC horizon report: 2017 higher education edition. Austin, TX: New Media Consortium. Retrieved from http://cdn.nmc.org/media/2017-nmc-horizon-report-he-EN.pdf
Asseo I., Johnson M., Nilsson B., Chalapathy N., & Costello T. J. (2016, June 27). The Internet of things: Riding the wave in higher education. In Educause Review. Retrieved from http://er.educause.edu/articles/2016/6/the-internet-of-things-riding-the-wave-in-higher-education
Holmes A. (2016, May 12). Rich people have access to high-speed Internet; many poor people don’t. Center for Public Integrity. Retrieved from www.publicintegrity.org/2016/05/12/19659/rich-people-have-access-high-speed-internet-many-poor-people-still-dont
Skiba D. (2017a). Students, technology and teaching: Findings from the ECAR report. Nursing Education Perspectives, 38(1), 51–52. doi:10.1097/01.NEP.0000000000000117
Skiba D. (2017b). Augmented intelligence and nursing. Nursing Education Perspectives, 38(2), 108–109. doi:10.1097/01.NEP.0000000000000124
TIAA Institute. (2016). Rethinking faculty models/roles: An emerging consensus about future directions for the professoriate. Retrieved from https://origin-www.tiaainstitute.org/publication/rethinking-faculty-modelsroles
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