Currently, there is a pending solicitation for data-intensive education research. This solicitation is seeking researchers
who are interested in conducting intensive education research that will complement data sources. Research funding for data-
intensive education is available, and there are many exciting possibilities for how this data can be used. Accessible
descriptions of these data sources and new sources of data that can be used to fuel data analysis are available. New
analytical techniques are being developed that are specifically suited for data-intensive education. Students’ privacy is
always a concern, and it is important to note that appropriate measures are in place to protect their privacy.
There is growing recognition that education is ready to work in data-intensive environments. North Carolina has been a leader
in this area, and has developed a number of successful models for data-intensive education. Carolina School is a first
iteration of this model, which uses data to improve teacher effectiveness. The Phase DBir model is a second iteration of this
model, which uses data to improve student outcomes. Environmental science graduate students in North Carolina are using these
models to research ways to improve environmental science education.
Technology makes data available so that educators can use it to improve student outcomes. Intensive STEM careers require
educators to have expertise in data-intensive technologies, so they can use these technologies to improve student engagement
and learning. Levels of data-intensive education vary, depending on the type of data being used. Academic research often uses
large datasets, so researchers need to have expertise in data analysis.
The article mentions that the education sector needs to be open to new teaching methods and formats in order to be ready to
work in data-intensive environments. In order to be able to work with large datasets, educators need to be trained in data
analysis and have a broad academic background.
According to the article, there are a number of ways that educators can prepare themselves for working in data-intensive
environments. They can take data courses that focus on specific data analysis methods or they can participate in applied
social sciences programs that provide training in how to conduct social science research using data. Students can also
prepare themselves by participating in professional learning experiences that introduce them to data-intensive research
Traditional statistics coursework is a good way to prepare students for working in data-intensive environments. Environmental
science degrees provide students with substantial training in how to use data to understand the environment. Students who
have taken statistics courses may find that they have the basic skills necessary to work in data-intensive environments.
Statistics instructors can play a significant role in helping students to learn how to work in data-intensive environments.
There is moderate disagreement among faculty about whether education is ready to work in data-intensive environments. Results
from a recent survey suggest that a majority of faculty members (57%) do not believe that education is ready to work in data-
intensive environments. This suggests that there is room for improvement in how educators are preparing students for working
in data-intensive environments. Despite the moderate level of disagreement among faculty, some institutions are doing a
better job than others in preparing students for working in data-intensive environments.