In a global economy, where information travels in nano-seconds, the potential of big data is taking centre stage. Here are some practical tips to manage your big data.
A look at emerging trends in education offer a few pointers, among these:
Step 1 – Clarify the concepts
Your investment in big data involves clarity around the concepts and terminologies. An initial step is to demystify the trends and improve insights using analytics and data mining tools.
In education, big data is being used to improve testing that tracks the strengths and weaknesses for numeracy, reading, writing, spelling, grammar and punctuation, says Dr Judy Smeed from the Queensland University of Technology (QUT) Education Faculty, School of Professional Learning.
This learning is being tracked using the National Assessment Program – Literacy and Numeracy program. Among the benefits, big data can help assess learning and performance where leveraged as a value-add to overall annual performance.
For example, an in-depth tracking and analytics’ system enables teachers to respond and tailor teaching methods. Big data comes into play when tracking programs that’re doing well or those that need more immediate attention. These insights enable curriculum developers to tackle the problems at the outset.
Step 2 – Don’t let data sit idle
The advice is to not leave data sitting idly inside computers or staffs’ desks. This oversight may mean your teaching stays unfocused or unchallenged.
It’s important to teach the teachers about tracking where a school, class or individual may be struggling. Insights into students’ needs enable programs to be more tailored and focused. The demographic data encompasses insights and the ability to track a learner’s overall achievement chart.
One example is the Australian government's My School initiative that tracks performance nationally. An astute investment in big data improves learning outcomes, hiring decisions and enables organisations to deliver more mileage from learning programs.
Step 3 – Leverage social media
In a digital world, the boundaries have blurred between the digital and physical world. Business, government or consumer data comes from many different sources. This includes mobile and smart devices, online channels, sensors, GPS systems or the internet-of-things (IoT).
How do you ensure this data is leveraged to gain an edge, improve learning, manage privacy, or use available analytics tools more efficiently?
To build the deeper relationships, you can tap into the more ambient data found in social media, according to Kate Carruthers, the manager for data governance and business intelligence, at the University of NSW.
She told a recent Amcom higher education roundtable that this data offers a snapshot of the digital environment interactions and offers a complete picture of student profiles or life journey.
The ambient data encompasses a ticker-tape of unstructured dialogue that is relayed across social media channels. The value of this data lies in being able to synthesise the chatter, derive meaning from it, and build profiles using predictive analytics or other data mining tools.
Step 4 – Build adaptive learning
Big data is being leveraged for adaptive learning. This platform tracks participants through lessons, while playing to their strengths. Students’ journey through lessons can be measured, including the time spent on each assignment.
Information is mined from tablets, smart devices or the internet. This includes social media, email or internet communication. The downside is this communication may generate too much or overly-complex data.
Conventional tools or relational database management techniques do not successfully analyse the big data. The advice is to use specialist processing that drills more deeply into the layers of structured or unstructured content.
Step 5 – Manage the digital breadcrumbs
When learners interact with your content, they leave behind “digital breadcrumbs,” according to Sara Briggs from InformED. In a post, Briggs says this trail offers clues around how learning occurs and offers the ability to track the dialogue.
Learning management systems are now a mainstay for education. An exploration of social networks or other media can assess how students interpret, consider or arrive at conclusions around course material.
Step 6 – Tackle privacy concerns
But there are risks and hurdles around big data, among these privacy concerns. For example, online companies offer services including email or storing personal information in the cloud.
This is complemented by online news, Web browsing, scheduling, maps, location tracking, video or sharing photos. Other offerings integrate voice mail, shopping, social networking and whatever else may be of interest to users, at any given time.
In an online or mobile space, an end-user profile is increasingly more personalised. This data is being collected, stored, and cross-referenced across different business or working groups.
A more complete dossier can be built from many different sources, offering a revealing picture of a person. A simple online search can turn up a great deal of information, although the accuracy of this information has come up for scrutiny.
The question, for example, revolves around who gets to see the aggregated data of 1,000 learners, according to Briggs. “Who gets to see a single learner’s data? Levels of privacy, as well as designated access to them, should be carefully considered.”
According to a Columbia University Cousera program, the explosion of global data can be leveraged to improve education and support the basic research for learning. But it’s important to appreciate how and when to use key methods for data analytics.
This learning is around predictive modelling, detecting and understanding behaviour patterns, validating this behaviour, mining relationships, improving visualisation techniques, and refining the knowledge clusters.
Other links tracking big data can be found at related sites including:
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