Why It Is Important For Students To Get Into Data Literacy At An Early Stage

Is data literacy important in children? The answer is yes because data is now a part of everyday life. It has almost become a responsibility of the average citizen to have some level of data literacy and understanding. Interestingly, this research paper argues that young learners have the ability to work with complex data sets if they are supported in the right way and if the tasks are grounded in real-life context.

Data Science has risen in popularity of late and there has been a rapid increase of accessible sources of data and the tools to work with it for students interested in this buzzing field. For example, increasingly Google Forms are used for the survey to collect data, and Google Charts, enable allows users to visualise results. In the face of this rapidly rising interest, many universities have quickly added programs to the growing demand for trained data scientists.  

Here Are The Top Tools Which Can Be Used To Foster Data Literacy:

Data Collection tools: From Google Survey to tools like Mentimeter, Socrative, and Poll Everywhere, there are a number of tools which allow students to collect responses for surveys or reports and develop visualisations that represent information graphically.

Visualisations: There is a slew of easy-to-use infographic tools such as Infogram and Piktochart which can be used for projects or storytelling. These tools make creating a compelling infographic straightforward through a combination of intuitive features and online tutorials.

Data Analysis Projects: For those looking to delve into data analysis projects, Databasic.io’s suite of tools offers web-based ways of exploring and understanding data, complete with activity guides designed for use with teens. Best of all, there is an increasing amount of open data available from local groups and government agencies that can offer relatable and interesting datasets for teens to analyse.

One of the pioneering influencers of the data science field Kirk Borne emphasises the value of teaching data in the classroom. He noted that he is not advocating the teaching of hard-core data science to school students, but techniques such as data mining and other data science applications can come in handy in teaching subjects. The prominent influencer also advocated a reading list compiled in 2015. You can access it here.

Borne noted in a blog that data literacy can play a pivotal role in training the next-generation workforce/data analysts to be skilled in data analysis. “Today, data literacy has become fundamental to every job and should be imparted at the earliest levels of learning, and it should continue through all years of education. Education research has shown the value of using data in the classroom to teach any subject — so, I am not advocating the teaching of hard-core data science to children, but using data techniques for various subjects,” he wrote in a blog.

Top Free Resources For Students:

Interestingly, these free resources do not require high-level Math and will only deepen the conceptual understanding of the subject. Also, knowledge of these topics is very valuable, and the books shed a light on data science techniques and how they should be applied.

1. The Basics of Data Literacy: Helping Your Students (and You!) Make Sense of Data
2. Databases for Inquiry-Based Learning About Influenza
3. Using a Classroom Response System for Real-Time Data Display and Analysis in Introductory Biology Labs
4. The Virtual Vee Map: A Template for Internet Inquiry

Conclusion

Borne also emphasised in another paper that there will be an exponential need for non-specialists with data literacy skills as productive members of the 21st-century workforce. That is why integrating data literacy will be crucial since this will become a foundational skill for lifelong learning in a world increasingly dominated by data.

Specialists must learn and apply new data science research techniques in order to advance our understanding of the Universe, he wrote in the paper. Given how data analysis and science make up the fastest growing jobs out there — education and information literacy in the early stages will become pivotal to understanding what’s going on in the industry and building a solid, informed talent pipeline.