The Future in Higher
Education:
Trends to come in the very near
future
By Prof. Jonathan Acuña-Solano, M. Ed.
School of English
Faculty of Social Sciences
Universidad Latina de Costa Rica
Wednesday, March 23, 2016
Post 237
“Life is not linear but organic” (Robinson, 2010), and so is education. Learning
is then a process in which pupils create their own knowledge coming from very
different angles, viewpoints, and perspectives. That is, technology nowadays is
auspicious of all these new trends in autonomous, flipped learning students are
facing and encountering every step of their education process. Instead of
profligate technologies or intentions to use Internet-mediated “learning,” as
stated by Prof. Sebastian Thrun, we teaching professional ought to look for
ways to “democratize” learning (VOA Voice of
America, 2012) in various formats to involve as many of our students as
possible in the new trends that are common for them, more than they are for us
individuals who were born before this digitalized way of education (Robinson, 2010) learners are experiencing in
their day-to-day lives.
Mobile computing, or simply apps, supported by
Galaxy, Android, and iPhone, is one of the most important trends in digital learning.
“Mobile apps are particularly useful for learning as they enable people to
learn and experience new concepts wherever they are, often across multiple
devices” (NMC Horizon Project, 2013).
Take the case of the students who need to take the GRE test and are looking for
ways to practice, enhance, or learn new lexical items to be graded on the
vocabulary, written part of this test; what can they do? Kaplan or Magoosh have
created apps to help learners work on their word-base to face this part of the
GRE test.
Mobile computing, based on the NMC Horizon Project (2013), has a time-to-adpotion
span of one year or less. As stated above, and avoiding a harangue of incomprehensible
facts about apps, we can have a glimpse of how these mobile computing products
are contributing to higher education. The array of apps is so vast that
learners can practice from algebra to phonetics, from vectors to literature,
and so on. And as “new research from
the University of Maryland has found […] mobile Apps - and even text messages -
enhanced learning and produced a richer learning experience for college
students” (UMD Research Shows Mobile Apps Help
Students Learn, 2010), can we faculty members imagine the potential
these apps have in our fields of work and teaching? And how about going beyond
the acrimony some pre-digital ear teaching professionals profess towards
technology-mediated learning and assessment, and getting the right training to
create our own apps ourselves to have summative evaluations (quizzes, tests,
etc.) or terminology review and its corresponding practice? Mobile computing is
fertile ground but though its adoption is not that much, we faculty members need
to get the training to move upwards in the latter of education technology.
As a language professor working with
literature and phonemics in higher education, I often struggle to stop the
areas in which learners are having trouble and cannot provide them with
immediate feedback for their academic improvement. If I could get to use and
apply learning
analytics, students will be blessed with meaningful and
instantaneous feedback. As stated by West (2012),
“many of the typical pedagogies provide little immediate feedback to students,
require teachers to spend hours grading routine assignments, aren’t very
proactive about showing students how to improve comprehension, and fail to take
advantage of digital resources that can improve the learning process.” Those “typical
pedagogies” West (2012) mentions are present in our day-to-day teaching/assessment
practices and we cannot get back to our pupils with meaningful feedback for
their improvement. And in spite of the fact that learning analytics is still
taking its very first steps, all these data produced by learners can help us
plan courses, lessons, learning activities, etc. to help them improve
individually. We will see how it evolves in the next two to three years, which
is its time-for-adpotion horizon timeframe (NMC Horizon Project, 2013).
“Data-driven
approaches make it possible to study learning in real-time and offer systematic
feedback to students and teachers” (West, 2012). With an approach like this, neither
learners nor teachers do have to wait for datat to be analyzed to supply individualized
feedback that can help students their learning practices. As stated by Siemens (2013),
“Learning analyticsis is the measurement, collection, analysis and reporting of
data about learners and their contexts, for purposes of understanding and
optimizing learning and the environments in which it occurs.” If we had access
to these “measurement, collection, analyis and reporting of data” from any form
of student learning activity, we could be able to work with pupils in higher
education to really develop their skills and competencies needed for their working
field. By spotting any single area where students need to coached, then the
teacher can intervine to give a helping hand if the system cannot provide
learners with individualized coaching.
“Known in industrial circles as rapid prototyping,
3D printing refers to technologies that construct physical objects from
three-dimensional (3D) digital content” (NMC
Horizon Project, 2013). 3D Printing in education contexts can be the
next boom in learning. Though this is not my area of expertise, nor my cup of
tea, this type of new technology can be a real hit in product design,
engineering, and so on, where students can create prototypes that can be then
physically represented (printed) for further analysis and improvement. Though
its time-to-adoption horizon is four to five years (NMC Horizon Project, 2013), its potential in higher education is
simply out of question.
From the Getting Smart webpage (Parker, 2012), it can be seen the many
possible uses for 3D printing in educational fields. Parker (2012) singles out
several uses for 3D printing, among them she states its use in biology, auto
industry, geography, drafting in architecture, graphic design, history, and artifacts
in anthropology. In today’s higher education, all these areas benefit from this
kind of printing. 3D printing can give learners tactile experiences they could
not have had before when they had only pictures of books instead of the
manipulation of a replica of the object of study. We are indeed in the verge of
encountering a gamut of uses for this piece of technology that time will help
us discover and utilize in higher education.
If we are just passive spectators during the abandonment of broken models of education systems, as Robinson (2010) refers to them, and we do not dare to challenge what we educators have taken for granted since our student college days, learners will mutiny on us demanding for more meaninful ways of getting an education and of develping the skills and competencies needed by them for their current and future jobs. We cannot simply state that these innovations in education systems around the world are just barging in on my comfort teaching zone, and we cannot be blinded by the old dogmas in education that cannot cope with the advancements in technology we all are facing in the 21st Century.
References
NMC
Horizon Project. (2013). NMC Horizon Project Short List 2013 Higher
Education Edition.
Parker,
N. (2012, November 14). 7 Educational Uses for 3D Printing. Retrieved
from
GettingSmart.Com:
http://gettingsmart.com/2012/11/7-educational-uses-for-3d-printing/
Robinson,
K. (2010). Bring on the Learning Revolution. Retrieved from
http://www.tedx.com/talks/sir_ken_robinson_bring_on_the_revolution
Siemens,
G. (2013, January 9). The Structure and Logic of the Learning Analytics
Field. Retrieved from SlideShare.Com:
http://www.slideshare.net/gsiemens/columbia-tc?ref=http://www.learninganalytics.net/
UMD
Research Shows Mobile Apps Help Students Learn. (2010, March 23). Retrieved from Merrill College of
Journalism, University of Mariland:
https://www.flickr.com/photos/umdnews/7881316248
VOA
Voice of America. (2012, March 21). Getting a Free Education, in Huge Online
Classes. Retrieved from SlideShare.Com: http://www.slideshare.net/jonacuso/se-edmassiveopenonlinecourses
West,
D. (2012, September 12). Big Data for Education: Data Mining, Data
Analytics, and Web Dashboards. Retrieved from Bookings:
http://www.brookings.edu/research/papers/2012/09/04-education-technology-west
Wednesday, March 23, 2016
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