We live in a digital world, surrounded by young natural data scientists.
They are virtually unprecedented in their ability to handle new information.
Their ability to mine information from the Internet allows them to present a wealth of knowledge and innovative ideas.
This is the new Data-Native Generation of students.
Big Data Learning Democracy
The new generation of learners don’t always fit into the traditional school system, which remains rooted in late 19th and early 20th group instruction and a standard exercise model. This teaching model can be a deterrent in choosing STEM subjects even when students possess a strong interest, for example, in biology or chemistry.
Data Science/Big Data Education permits new learners to take initiative and attain ownership of their education. It democratizes the learning process, allowing students to take their own path in the acquisition of knowledge through whatever learning style they see fit.
Data-native Generation Education
A change in the pedagogical paradigm: one which recognizes the fact that school teachers and university professors do not have a monopoly on knowledge, and are instead facilitators of the process of inquiry and education.
The roles of teachers and professors are changing. There is a greater need for a responsive learning environment with an emphasis on project management rather than classical lecturing. The best educators already act as integrators of leading learning platforms. Faculties should therefore consider the introduction of project management education as a new training course for teachers, and possibly even a qualification essential for educators in information technology and STEM.
The phenomenon of student-driven education, which involves social networks and forums where students crowd-source complex scientific problems, speaks volumes about the learning styles espoused by the new generation of data-native students. The question is, can educators meet them halfway?
STEM Fellowship aims to develop natural data analysis talents, providing the new generation of students with opportunities and competitions in Data Science Education.
We emphasize four key skills:
- Computational Thinking – ability to translate aggregates of data into abstract concepts and conduct data-based reasoning
- Design Mindset – ability to create solutions in contexts where only part of the requirements are known
- Cognitive Load Management – ability to discriminate and filter the information needed to produce successful solutions
- Social Intelligence – ability to participate in the collaborative construction of solutions
The Big Data Challenge for High School Students is our flagship event, providing high school students with an ideal opportunity to develop all four of these skills in a team-based research project.