Data science as we define it 'captures structure or unstructured data' often through a scientific method; whether it is qualitative (opinions or perspectives) or quantitative (numerical values that reflect points in or over time). Currently, education is affected or influenced by data science in a few major ways. In a brief, here are a few examples.
Technology- A LMS system can track, monitor and report large amounts of user data for instructional analysis and feedback.
Marketing- Quantitative or qualitative data is used as evidence to persuade people either for the purpose of education sales or recruitment for participation of education initiatives that affect student academic outcomes.
Trend Insights- Different types of data are often used to determine strategic planning for small or large projects that help with hiring new educational staff, faculty or reform efforts in the area of diversity and inclusion.
Adaptive Technology- Data science has been a huge help to companies like DreamBox, that rely on data to assist with modifying lesson plans (adaptive technology) based on a student's learning progress. For example, as a student moves through an adaptive software lesson plan, the lesson plan will not advance to new problems unless the student demonstrates competency in the initial problems presented to them.
Hope this helps!
Kim recommends the following next steps:
- Take a free online course by Edx.org in the area of data science in order to learn more it. This will help you infer new ways of thinking about how education and data science continue to blend with technological advances.