Rise of Technology-Mediated Learning Systems Research Paper

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[. . .] Nonetheless even though access to funding is one inspiration, it is not the single reason for the heightened awareness in corporate-academic businesses. There are some universities that put the emphasis on particular areas of applied research, for instance, while others give out instruction that is tailored to the exclusive necessities of specific career paths, providing corporate partner's admission to exceedingly trained, "job-ready" applicants. SonomaState University's Mr. Scalise makes the point: "Campuses that are small usually are not able to compete with bigger universities when it comes to information technology accounts, so they have to discover other ways to distinguish ourselves, through niche contributions.

Even though university participants look at technology as having a big positive influence on their campuses, they are also able to acknowledge a lot of challenges. However, the largest of these more than likely is cost, a factor that is near to 60% of university respondents refer to as their utmost concern (Warner, 2014). Established organizational cultures could be another problem, as academic faculty members that are used to old-style modes of instruction could be reluctant to change. In reality, beyond one-third of those polled say that tenancy and promotional supplies will need to be re-weighted to consist of technology-based teaching standards.

Then there is the question of information technology's arrangement with global leadership and policy establishing. These days, moderately few university CIOs appear to have a some good ideas when it comes to strategy. Of those questioned, only one-quarter state that their CIOs are tangled in matters that are strategic. Given IT's expanding footprint on campus, in the near future, this will be expected to change in regards to increasing revenue in higher learning. Research show that over the next four years, 63% of members presume that the CIO part will be increased to the university's important choice-making team. For instance, when Queens College in New York finished its "Five Presidential Goals" in concerns of increasing revenue in higher learning agenda a few years ago, it looked technology as one of the serious components in moving the college onward. Out of that advantage, Naveed Husain was selected the College's initial CIO.

"Our leader and executive committee recognized that technology was important to making an advanced learning environment and giving Queens a real market benefit," says Mr. Husain (Clark, 2009).

Within the classroom, technology could be seen as a disruptive tools in ways not planned. Survey contributors along with those questioned make the note that general multi-tasking among smart-phone, laptop, and other technologies in the classroom regularly keep students distracted. Even in extremely disciplined organizations like the U.S. Military Academy at West Point, this can be true (Fain, 2013). Lieutenant Colonel Greg Conti, administrator of West Point's Information Technology Operations Center, makes the point by saying "it is difficult to sit someone in front of the World Wide Web and expect them not to use it (Phillips, 2007). He goes on to make the point that Faculty, teachers and supervisors, have to recognize that if we're going to utilize technology in the classroom, there have to be additional methods to keep content expressive, even if it comes down to the humble assignment of demanding computer monitors down all through the instructional era and back up throughout the hands-on share of class."

Massive Open Online Course (MOOC)

The MOOC have been a big help when it comes to increasing revenue in higher learning. MOOCs and other online education spaces are able to generate large amounts of data in regards to learning styles, student behavior, and connections with course material, teachers, and other students (Carlson, 2011). Research shows that MOOCs also gives out data in regards to time that has been spent on certain assignments and engagement on the whole with the MOOC setting. The advantage is that it can be known when students are online and offline, and even find out the length of time that they are on it. Ostensibly, examination of this data is able can show that there is a great deal in regards to learning. This option has individuals broadcasting Big Data as one of the next big thing.

The research shows that big data services are something that is already all around us. Amazon and Google are organizations that are collecting and analyzing huge quantities of data on their customers and users. Government agencies utilize big data and analytics to recognize patterns of behavior. On the whole, government and business expect Big Data to assistance in driving decision-making with data and analysis instead of experience and intuition.

With the arrival of online learning, higher education is now ensuing the lead of government organizations and for-profit businesses by plunging its toe in the big-statistics waters. Sometime, in 2011, Ganesan (Ravi) Ravishanker, Chief Information Officer at Wellesley College, printed "Doing Academic Analytics Right: Intellectual Answers to Artless Questions," Ravishanker makes the point that "data-driven decision-making is ever more essential." (George, 2013) Then he goes on to mention that establishments will do well to inspire systemic communication with data intelligences as part of the procedure of guaranteeing a return on their asset, and that applying data analytics to official learning environments is an prospect missed on a lot of campuses. With regard to learning management systems and the volumes of interpretable information they represent, Ravishanker inspires campus leaders to question "faculty and student access designs, how numerous artifacts are related with a course, how are students and faculty even utilizing the entire system." (Carlson, 2011)

With that being said, MOOCs -- and even "old-style" local classroom learning organizations -- harvest massive quantities of data that can be analyzed with these implements, in the hopes of refining learning outcomes. However, online learning systems, accumulations of data, and the ease of use of analytics could be joining to refurbish the teaching-and-learning electrical system. That latent is driving new merchants to go after higher education. A short assessment of some developing players and their products highpoints the possibility of this emerging academic support business.

Adaptive Learning

Adaptive learning plays a key role in increasing revenue in higher learning. This has happened because online learning and MOOCs, analytics, and big data, have re-animated a long-standing instructive resourcefulness -- technology-mediated teaching (Lim, 2005). Adaptive learning, constructing on big data and learning analytics, is the up-to-date duplication. Modern adaptive learning consist of the application of data-driven analytics in order to aid faculty in forming the delivery of course materials so as to adapt to individual aptitudes.

These tools have been a plus when it comes to increasing revenue in higher learning because they offer personalized learning, arbitrated by technology. For instance, Peter Stokes, executive director of postsecondary innovation in the College of Professional Studies at Northeastern University, believes higher revenue because he describes adaptive learning as "an setting where technology and brain science work together with big data to cut out modified trails through curriculums for individual learners and free up teachers to dedicate their dynamisms in more productive and accessible ways." (George, 2013)

History even shows that there is a long history of teaching machines -- computers mechanical, and multimedia, -- going all the way back to an 1809 patent for an educational application for the instruction of reading. Research shows that by 1936, there were closely seven hundred patents for teaching strategies (Carlson, 2011). The history of these strategies can be outlined from the original patented machineries of the nineteenth century through the teaching/testing strategies of Sidney Pressey during the 1920s to the more classy teaching machineries of Harvard psychologist B.F. Skinner in the 1950s (Clark, 2009).

In order to make sure that increasing revenue in higher learning is going strong, strategies have to take place. For example, the foundation's strategy is to capitalize in "market change drivers" that consist of exemplary putting into practice of adaptive learning courses collective with research and examination of learning outcomes so as to quicken the acceptance of adaptive learning in higher education (Phillips, 2007). The Foundation likewise has fashioned a loose alliance of leaders from a dozen colleges and two relations to share information about developing and implementing adaptive learning in order to increase revenue. These universities and this alliance could turn out to be a rich laboratory for partnerships between technology vendors and campuses in the near future.

Conclusion

It is clear that increasing revenue in higher learning is key, especially with the new innovations that are rising up in technology. In the future, institutions will need to decide their capacity to manage the associations of these new technology, especially since most colleges are embracing them. Even though there are some barriers, it seems as though that the rise of technology-mediated Learning Systems.

References

Carlson, V. & . (2011). Technology-enhanced learning/distance education: Market survey of occupational health and safety professionals. AIHAJ, 349-355.

Clark, R.E. (2009). Translating research into new instructional technologies for higher education: The active ingredient process. Journal of Computing in Higher Education, 23(9), 4-18.

Clegg, S.T. (2011). Not just for men:… [END OF PREVIEW]

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