On the horizon: trends, challenges, and educational technologies in higher education.
Let's start with trends that will drive technology planning and decision-making. Trends are reported in terms of their short-, mid-, and long-term impact. Short-term trends will either become "commonplace or fade away in that time" (Johnson et al., 2016, p. 6). Table 1 compares 2016 with 2015 trends.
As you can see, there are some consistencies as well as shifts between 2015 and 2016. For example, the increased use of blended learning remained consistent. I believe this statement identifies a driving force: "Students have expectations that higher education will mirror the information accessibility and immediacy of their connected lives" (Johnson et al., 2016, p. 18). Blending learning draws upon the distinct advantages of both the online and face-to-face worlds. The University of Central Florida has an open resource website (http://blended.online.ucf.edu/) that provides useful tools and information about blended learning. The growth in blended learning has an impact on policy, leadership, and practice.
The second trend, the growing focus on measuring learning, which moved from mid-term to short-term over the last year, is precipitated by the growing amount of data being collected on students. Through various tools, data are being amassed on learning as well as student activities (e.g., use of the library, social networks, shopping on college-based networks). With the growth in learning analytics, these data can be harvested and used to examine student readiness, progression, and remediation.
This trend has renewed interest in the examination of learning and the best methods to measure learning. It has also raised ethical questions. For example, should we have consent from students to use their data for administrative decisions? What are the legal and ethical concerns related to data privacy and security of sensitive student data?
In terms of mid-term trends, the redesign of learning spaces shifted from short term in 2015 to mid term in 2016.1 would suspect that funding for higher education has delayed the redesign of learning spaces to be more student-centric with smart room technologies and flexible spaces for cross-disciplinary interactions. For some standards and guidelines regarding learning spaces, you can use Educause's Learning Space Rating System (www.educause.edu/eli/initiatives/learning-space-rating-system).
The mid-term trend, shifting to deeper learning, represents the growing need to ensure that our graduates have the knowledge and skills needed for the job market. This trend acknowledges the movement away from surface learning (memorization and multiple-choice tests) to deeper learning, "defined as the mastery of content that engages students in critical thinking, problem-solving, collaboration and self-directed learning" (Johnson et al., 2016, p.14). There is a growing emphasis on teaching through project-based, inquiry-based, or challenge-based learning strategies. The Lumina Foundation's Degree Qualification Profile is a good site to broaden your thinking about deeper learning (www.luminafoundation.org/resources/dqp) and the intellectual skills needed by associate, baccalaureate, and master's degree students.
Advancing cultures of innovation remains a long-term trend and reflects the role of the university in fostering innovation, creativity, and entrepreneurial thinking. A new long-term trend Is the reexamination of higher education models. Competing market factors, employer needs, and consumer demands for accessible education are precipitating an examination of new roles and models for higher education. Staley (2015), who presents five, quite provocative models, gets one thinking about the future of the university.
As you can see in Table 2, challenges have stayed consistent from 2015. Blending formal and informal learning and the improvement of digital literacy are still considered solvable challenges. Personalized learning still remains a difficult challenge. Despite the demand, there are a limited number of higher-education Institutions that have fully implemented personalized learning, and there is a great need for faculty buy-in to make this successful.
It is interesting to note that competing models of education moved from a wicked challenge to a now difficult challenge. Both inside and outside the academic environment, there is a persistent challenge to the traditional campus-based model of education. Several new models have been proposed over the years such as MOOCs (massively online open courses), competency-based education programs, nanodegree programs, and coding boot camps. For there to be widespread acceptance, issues of academic quality, funding models, and regulatory standards must be addressed.
Two new wicked challenges appeared this year. The idea behind keeping education relevant raises the following questions: What is the value of a college degree? Do you need a college degree to be gainfully employed? What are the drawbacks of not having a degree?
There is no doubt that the balance of our connected and unconnected lives is an important challenge. Institutions of higher education have the responsibility to help learners understand how to make full use of the Connected Age while also taking time to digest, reflect, and experience the real world and grow as a knowledgeable person. As noted by Johnson et al. (2016, p. 30), "to prevent students from getting lost in the abundant seas of digital tools, universities are tasked with encouraging mindful use while making them aware of their digital footprint and accompanying implications." Faculty also need to examine the balance between their connected and unconnected lives.
Table 3 helps compare 2015 and 2016 technologies. Without a doubt, we are living through the "bring your own device" era (BYOD). Now both faculty and students seem to be participating in BYOD. The flipped classroom has become more commonplace and is used in various disciplines. Learning analytics and adaptive learning have moved to the present and have technologies that will facilitate personalized learning. As noted by Johnson et al. (2016, p. 38), these technologies are "capable of learning how people learn ... they can adapt to each student in real time." A good example comes from the University of Tennessee at Chattanooga (Fagan, 2015), where it was found that failing an English class--not biology or chemistry --hindered progression into the nursing program.
Makerspaces remain a mid-term technology. As I mentioned previously (Skiba, 2015), we need to encourage the development of more MakerSpace opportunities in health care to help with the redesign of nursing care. You should check out the MakerSchools Higher Education Alliance report (Byrne & Davidson, 2015) and see if your school is part of the alliance. Perhaps your school can host a nursing MakerSpace opportunity.
Augmented and virtual realities are a blast from the past; they were mentioned in horizon reports from years ago but faded away. Augmented reality (combination of digital information and real-world spaces) has increased as more people use their GPS-enabled smartphones. The 2016 report contains some relevant health-related learning experiences:
* The University of Maryland opened the Augmentarium for medical and surgery training, a combination of augmented and virtual reality. Students can see through a patient before making an incision (see http://augmentarium.umiacs.umd.edu).
* The nursing school at Boise State University is experimenting with virtual reality to teach catheter insertion, truly the next generation of simulations (see www.centerdigitaled.com/higher-ed/Can-Higher-Education-Innovators-Help-Transform-Teachingand- Leaming.html).
Two new technologies have emerged for the long term: affective computing and robotics. Affective computing, studied particularly at MIT since the 1990s, has been defined as "the ability of humans to program machines to recognize, Interpret, process and simulate the range of emotions" (Johnson et al., 2016, p. 44). We have all experienced some interactions with affective computing through the use of our virtual assistants Siri, Cortana, and Alexa.
In my January/February column (Skiba, 2016b), I wrote about tools used to assess and convey emotions online. Technology and educational thought leaders are becoming more aware of the importance of human-device interaction, as we offer educational opportunities in a connected world. Here are two good examples of the use of affective computing in online education:
* Stanford's YouEDU helps detect confusion In discussion postings and sends an explanatory video clip to students.
* The University of South Florida Is experimenting with assessing patients' health status and providing just-in-time interventions.
As robots become part of the mainstream in various industries, their design and development will have greater importance in higher education. There is also a growing use of humanoids in the consumer market that has Implications for learning and the health care arena. The best example is the humanoid Pepper that was featured at the 2016 Consumer Electronic Show and is being used in Japan in many different capacities (Skiba, 2016a).
IMPLICATIONS FOR NURSING EDUCATION
So what are the key take-aways from this year's Horizon Report?
* The classroom or online lecture will start to disappear as a primary teaching strategy. Trends and technologies are providing active and interactive experiences that foster deep learning.
* In a connected world, affective computing will become more important.
* Augmented and virtual reality will soon become the next generation of simulations ... good bye, Mrs. Chase.
* Learning spaces, both physical and virtual, will dramatically change to accommodate more project-based, challenge-based, or inquiry-based learning.
Given these messages, where are you and your school in terms of looking at the future of nursing education? As always, you can contact me at Diane.Skiba@ucdenver.edu to share your thoughts and ideas for moving nursing education forward.
Diane J. Skiba, PhD, FACMI, ANEF, FAAN
Byrne, D., & Davidson, C. (2015, June). State of making report. MakerSchools Higher Education Alliance. Retrieved from http://make.xsead.omu.edu/week_of_making/report
Fagan, N. (2015, July 7). The power of big data and learning analytics. Retrieved from http://www.edtechmagazine.com/higher/article/2015/07/power-bigdata-and-learning-analytics
Johnson, L, Adams Becker, S., Cummins, M., Estrada, V., Freeman, A., & Hail, C. (2016). NMC horizon report: 2016 higher education edition. Austin, TX: New Media Consortium.
Skiba, D. J. (2015). On the horizon: Implications for nursing education. Nursing Education Perspectives. 36(4), 263-266. doi:10.5480/1536-5026-36.4.263.
Skiba, D. J. (2016a). Consumer electronics show 2016: Implications for nursing education. Nursing Education Perspectives, 37(2), 120-121. doi:10.1097/01 .NEP. 0000480673.43077.85
Skiba, D. J. (2016b). Face with tears of joy is wad of the year: Are emoji a sign of things to come in health care? Nursing Education Perspectives, 37(1), 56-57. doi:10.1097/01 .NEP.0000476112.24899.a1
Staley, D. J. (2015, November 9). The future of the university: Speculative design for innovation in higher education. In Educause Review. Retrieved from http://er. educause.edu/articles/2015/11/the-future-of-the-university-speculativedesign-for-innovation-in-higher-education
Table 1: Trends 2015 and 2016 Short term: Mid term: Long term: 5 or 1-2 years 3-4 years more years 2015 Increasing use of Growing focus on Advancing culture of blended learning measuring learning change and innovation Redesigning Proliferation of Increasing cross- learning spaces open educational institution resources collaboration 2016 Increasing use of Redesigning Advancing culture blended learning learning spaces of innovation designs Growing focus Shift to deeper Rethinking how on measuring learning approaches institutions work learning Table 2: Challenges 2015 and 2016 Solvable Difficult Wicked 2015 Blending formal and Personalized Competing models informal learning learning of education Improving digital Teaching complex Rewards for literacy learning teaching 2016 Blending formal and Personalized Balancing our Informal learning learning connected and unconnected lives Improving digital Competing models Keeping literacy of education education relevant Table 3: Technologies 2015 and 2016 Technologies/Development of Technology Near term: Mid term: Far term: 1 year or less 2-3 years 4-5 years 2015 Bring your own Makerspaces Adaptive learning device (BYOD) technologies Flipped Wearable The internet of classroom technology things (IOT) 2016 Bring your own Makerspaces Affective device (BYOD) computing Learning Augmented and Robotics analytics and virtual reality adaptive learning
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|Title Annotation:||Emerging Technologies Center|
|Author:||Skiba, Diane J.|
|Publication:||Nursing Education Perspectives|
|Date:||May 1, 2016|
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