The time of Big Data has touched base in higher education as IT gets to be progressively implanted in the courses of action that include "attending a university, for example,course enlistment, classroom guideline, and understudy administrations. Information about student journeys, successes, and failures can be caught to enhance both individual and aggregate across all of higher education when given back to students in valuable ways.
Here is an interesting video about the possible applications of big data and analytics in higher education:
Here is an interesting video about the possible applications of big data and analytics in higher education:
Importance of Big Data in Higher Education:
Why is big data important to higher education?
It permits institutions to use Facebook as a marketing platform on the grounds that Facebook advertisers are willing to pay for targeted advertisements based on user behaviour
It enables alumni and career services offices to utilize the potential of LinkedIn’s enormous career and employment data repositories to network and enable connections for job seekers
It allows your conference hashtags to trend on Twitter. The trends and responses to the tags can be later analyzed and measured to derived valuable insights.
For example:
For example:
Big data through predictive modeling enables us to crack the problems with student recruitment , retention and job placements before they can start
Analytical data from sources such as Google Analytics for websites, provides huge potential to make strategic decision about how to enhance websites and retain visitors on the websites over time
How can Big Data Help Higher Education:
Feedback: Learning data can be informative from a feedback and context perspective. Some students may often regularly underperform in a topic but have not idea why he is not doing well. It gets intriguing when the learner can look at himself, as well as all other individuals who have had similar experiences. This may enable him to gain insights and explanation on what is going wrong so that he is not frustrated and can use the knowledge to rectify mistakes and improve his chances to succeed.
Motivation:If big data is implemented comprehensively, individuals will be convinced to invest in putting data into the process as they will be able to see the impact of how it works.
Personalization: Big data will help in changing the way course and learning plans are designed by enabling developers to customize and fit the courses according the the individual needs of the learners. This will allow learners to raise the standards and have a more efficient learning environment.
Efficiency: Big Data can improve efficiency by saving us hours upon hours of time and effort with regard to the matter of understanding our objectives and the methods we have to accomplish them. Let's assume somebody needs to take work B, having done work A for a year. Big data would demonstrate, above all else, the number of individuals who did work A and who then landed in B. Of the individuals who landed position B, what qualities or skill sets did they have? It likewise would demonstrate which learning projects were best, and what the timing was for when they decided to change to work B.
Tracking: Big data can enable institutions to comprehend the real patterns of students all the more successfully by permitting them to track a learner’s involvement in a course. By examining the digital footprints or ‘breadcrumbs’ learners leave behind, institutions can track the learners trajectory throughout the learning experience.
Understanding the learning process: By monitoring big Data, we can see which parts of a task or exam were excessively simple and which parts were difficult to the point that a learner got stuck. Different parts of the flow that can now be tracked and investigated includes, pages returned to frequently, sections prescribed to peers, favored learning styles, and the time of day when learning works best.
Challenges of Big Data for Higher Education
What are the challenges that stop higher education institutions from utilizing the true potential of big data?
Data quality: The biggest problem is the lack of good data. The data should be well-structured and there should be clear policies defining the data structure and how it should be used.
Infrastructure: The systems should be able to work with big data. This includes software systems that can generate user-friendly actionable reports, tools to extract data from multiple data sources and a reliable database.
Dearth of resources: One must know what to do with the data in order to take some action. This requires resources who are proficient at interpreting data and cleaning up existing data sources.
Awareness: Decision makers should know why big data is worth having in the organization. They should know of the potential of big data. Management and leadership should be aware of the best sources of information on the topic.
Although there are challenges facing the higher education domain, we believe that with time and financial resources these can be overcome to utilize big data to its fullest.
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