How Big Data Will Boost Learning and Teaching in Higher Education

The uptake in adaptive learning courseware continues to rise in Higher Education institutions. Instructors and administrators are aware of the benefits of developing personalized and adaptive learning programs, and how teaching and learning experiences can be enhanced. Access to granular data illustrating students’ use of online materials, and their progress, is a key factor for the success of those platforms.
Often, the benefits of data generation, collection and analysis can slip under the radar, as administrators and instructional designers implement adaptive learning technology on campus.
In this article, we look at what Big Data is and how it can be used to enhance your teaching practices and thus, empower your students.

What is Big Data?

Data is gathered in everything we do online. We generate it with each digital footstep, transmitting it wherever we go – online shopping, social media, streaming movies, and downloading music.

In a Higher Education context, Big Data can change the way learners, educators, and administrators communicate. The generation and analysis of Big Data creates a new paradigm – one where stakeholders make keen choices that enhance learner experiences, streamline teaching practices, keep learners safe, and ensure institutions can account for student attrition, satisfaction, and success.

Universities gleam data from surveys, tests, and self-assessments – even from students’ general interaction with online courses. This data isn’t usually personal data like demographics, but progress and behavioral data.

ipad with grading graph

Big Data and Higher Education

Institutions have data pouring in from a variety of areas – online applications, personalized learning courses, classroom activity software for exercises and testing, social media, blogs, and surveys of staff and students.

The sheer volume of data flowing into Higher Education institutions can be overwhelming for faculty. Currently, the sector lacks the technology, infrastructure, mechanisms, and staffing needed to manage and moderate the data to an effective level before data analysis can begin.

This is changing – with the advancement of adaptive learning platforms. We now know that one of the key driving factors behind institutions implementing personalized and adaptive learning approaches is the desire to explore new technology and to stay ahead of the competition who might be more cautious about building courseware into their courses.

Universities can use Big Data in a range of ways to their advantage. Providing personalized feedback to students, monitoring student satisfaction, increasing attainment, and to empower students by offering them ways to reflect on their own learning. As learners’ experiences become increasingly digital – with course material being available in virtual spaces, and the growing use of personal digital devices – the volume of data on learning will grow, giving teachers a better-rounded view of each student.

There is growing recognition that using Big Data and data analytics can vastly improve research output. Earlier this year, the Higher Education Commission in the UK commissioned a report entitled From Bricks to Clicks: The potential of data and analytics in higher education. It assesses what Big Data can actually mean for the higher education sector, institutions, and their learners.

Big Data and Teaching – Collect Data while your Students Learn

Making the link between teaching and data doesn’t always come naturally, however the process of teaching has always been based on gathering specific information on students learning and the information taught to them. By utilizing Big Data in a more concentrated way, teaching becomes more fulfilling for both students and teachers.
The best way to get started is to focus on these key points:

  • Start at the end

What outcome are you aiming for with this project? We’ve talked about how Big Data can aid research, enhance the teaching and learner experiences, and grow attainment levels. Before investing effort and budget into a data project, identify the outcome; develop a strategy and source the data technology needed to achieve your institution’s goals.

  • One step at a time

Identify one key issue in your teaching / students learning / course / class that can be improved by using analytics and build from there. Once this has been achieved, you can move onto the next area and so on.

  • Change the culture

Big Data comes from embracing a culture of digital technologies. Adopting personalized learning and adaptive technologies within your department, faculty, or institution can effectively capture and store the data you need – and can make its analysis straightforward. Develop a network of stakeholders who want to drive forward digital analytic initiatives and the technologies behind them.

Big Data and Personalized and Adaptive Learning Programs

By applying the knowledge that comes from Big Data you will:

  • Eliminate subjective perceptions of learner experiences
  • Find trends in learning and teaching experience – positive and negative – that can improve the quality of learning and teaching throughout your institution
  • Discover previously un-known trends which impact new directions for your institution, keeping you ahead of the competition
  • Generate factual analysis and evidence to back up the need for change implementation with stakeholders and gatekeepers
  • Create a historical record of information to provide analytical answers to future issues and concerns
  • Sort and filter to allow for meaningful conclusions that faculty can investigate as a team

What to look for in Adaptive / Personalized learning courseware?

An effective adaptive learning platform collects and intelligently interprets data on every learner interaction, keeping you updated through real-time reports and teacher dashboards. This will provide a deeper insight into every student, allowing you to direct your teaching strategies where they’re needed most, to ensure a better outcome.
Additionally, adaptive learning platforms learn from this data to personalize the online experience of the content to each student and their needs.

female teacher helping younger student

How does it work?

Processes in adaptive learning platforms are in place to surface learning data, analyze it, and present it in a meaningful way. Instructors are immediately aware of each student and their class as a whole and are able to intervene if necessary. Its automatic personalization of the online experience will help students overcome learning gaps at their own pace. This provides a more empowering learning experience and a more rewarding way of teaching.

Big Data and a rewarding teaching experience

Big Data is about being able to use data-enriched tools that can impact the future of higher education institutions – in terms of course offerings and student attainment. It gives real depth of meaning to student needs and preferences, resulting in the quality of your courses and teaching staff, and the satisfaction levels of your students, to stand way out in front of other universities.