Posted in Blog on 9 December 2015
The field of analytics is steadily gaining prominence in the world of higher education. Analytics can have a significant positive impact if it is seen as a tool which can help institutions carve out solutions for their most specific and problem-defining questions across all functional areas.
With huge volume of data available well over the tipping point, analytics is an effective tool to optimize areas like time to degree, recruitment, student relationship management, learning outcomes, productivity enhancement, teacher effectiveness, and so on.
Here are a few areas where institutions are utilizing analytics in higher education:
Enhancing learning outcomes
Most educational institutions have specific learning-related issues which they feel are not addressed through LMS. Analytics can play a crucial role in such cases and help institutions to understand the root cause and improve the outcomes.
For instance, University of Maryland Easter Shore had issues like slide in SAT scores, retention rates and graduation rates. This prompted larger incoming freshman-level courses leading to an imbalance between lower and upper level course offering. The University used analytics and developed a ‘student success monitoring system’. This helped them limit enrolment, increase SAT scores, and target transfer students which solved their issue.
Improving student retention and success rate
Predictive analytics gives the ability to be more informed, right from student recruitment to alumni management. It can bring down the cost of recruitment, increase retention, enhance educational effectiveness, and student-faculty interactions. It can also help detect early signs of student distractions and dropout probability.
Bowie State University had students from disadvantaged backgrounds which led to high dropout rates. Through predictive analytics the University captured real-time data related to student retention effort and immediately flagged the issues to the students, faculty, advisors, and other concerned staff. This helped them considerably increase student retention rate.
Enhancing student performance
Learning Management Systems (LMS) are common in most universities; however, they often fail to decipher insights that can lead to enhanced student performance. Analytics based on students’ log data from LMS usage and performance can easily give precise information that can help faculty members design courses and assignments to enhance student performance.
Analytics can also be engaged to give effectiveness indexes of online training initiatives, hybrid programs and flipped classroom models to help faculty members and staff, measure and customize programs to increase students’ performance.
Today, big data analytics is used to enhance student performance in various ways. For instance, current performance of the student can be compared with previous test results. This information can be combined with social media data and clusters of students can be formed based on those insights. These optimum work groups can then be guided according to their propensity to learn.
Manage college and brand reputation
Campus interactions are an indicator of students’ involvement; however, with social media emerging as the key platform for students, universities will have to consider it as a resource to know their views which could impact the education process. With advanced analytics, social media data can be analysed to understand trends in student perceptions and enable faculty and staff to take informed decisions or address problems early.
Social media analytics also extensively helps the management in recruiting, branding and analysing its reputation amongst students. Bournemouth University studied the impact of corporate marketing communications and researched search, reach and engagement in higher education conversations relevant to international recruitment and reputation. The university utilized three types of social media analytics tools to understand the conversations on the web. They found that twitter was the top platform that showed different engagement levels in various countries and this insight helped the university in tailoring their marketing strategy accordingly.
Optimizing institutional effectiveness
Most data required for institutional analytics is present with the universities in the form of student details, background information, choice of course, data from enrolment to graduation, use of support services, scores, LMS, etc.
Institutional analytics can help universities to refocus on the nature and kind of data that is conventionally gathered, leading to increase in data fields and data specifics. These additional data sets, in combination with conventional data, enable deployment of insightful analytical engines which can in turn enhance the overall performance of the institution.
Universities can enhance the value of their systems by linking new data sources with existing information systems to give more meaningful and actionable insights on time.
In a report by Noel-Levitz, one of the universities covered in the report mentioned the use of analytics to enable its admission team to assess the likelihood of an applicant getting enrolled based on data including geographic location, ethnicity, source of first contact, anticipated college major, etc. Equipped with this information the university can judge the inquiry’s likelihood of enrolling for their course and also spend its effort and money accordingly.
Teaching and learning effectiveness
Analytics can be used to make the education system more efficient, by mapping teacher performance with student performance. By utilizing analytics, educational institutions can accurately measure performance based on topics, student demographics/ behaviour/ rankings, number of students and many other variables. Time-tables and schedules can also be optimized according to insights on high performing times.
Primarily, analytics needs to be considered as a tool which can deliver clarity where bulk data and speculation currently prevails. With the benefits not only conventional, but experimental and customizable as well, the future of analytics in the higher education sector is quite bright.
Considering the huge volume of data readily available, institutions that are quick to utilize analytics effectively can hope to take the lead in the competitive arena of education.
Tagged in: analytics, Higher education