There are a few trending issues that are contributing to the growing need of personalization in education. These issues include significant increases in school enrollment, technology outpacing skills development, and increased digitization. As a result, these issues mean that our current educational system fails to adequately prepare students for employment. In fact, many of the jobs that students are preparing for do not yet exist. Meanwhile, people will continue to struggle to keep pace with a rapidly evolving world.
Clearly, we need to transform our methods of teaching students.
The good news is that there is a solution to the education dilemma. By borrowing an approach from the healthcare sector of precision-based solutions, we can start to close the skills gap. The trending issues mentioned previously pave the way for educators to apply a precision model approach to their delivery system. Precision treatment models are largely applied to medicine by diagnosing a patient and tailoring a customizable treatment plan that uses evidence-based outcomes. Applying similar principles to education can make all the difference. The new methodology could be named Precision Based Education. While the comparisons have not previously been defined, it’s clear that educators are instinctively applying this model of precision to improve student outcomes.
Marketplace skills are quickly evolving and schools are having trouble keeping pace. A Forbes article reports that 15 years from now, 65 percent of graduates will go into jobs that don’t yet exist. The Brookings Institute references these same deficiencies every time technology evolves while noting schools’ ability to keep pace only during times of social pain. This means schools are more reactive versus proactive in their evolution. Yet, schools need to be proactive to train their students for a constantly changing economy.
The Department of Education released a report entitled Enhancing Teaching and Learning Through Educational Data Mining and Learning Analytics. In the report, they make a strong case to educators to pay attention to the emerging field of adaptive learning analytics and its potential application in the classroom.
Education data scientists are beginning to closely monitor the vast amounts of data produced. One example is the Alt-School in San Francisco, which uses data to customize student-paced learning and the KIPP schools, which are developing data warehousing systems to collect, manage and analyze data to improve student results and increase graduation rates.
Across the globe, schools in Australia are also finding data useful to inform their decision making and instruction.
As the healthcare sector is using vast swaths of available data to their advantage, it would be a mistake for educators to bypass this opportunity. The gains could massively reduce the dropout rate and increase accurate identification of teacher talent. Teachers would be better able to predict student learning behavior, fill the ongoing skills gap, and uncover optimal learning methods. By providing early intervention and personalized learning, teachers could create a much stronger educational ecosystem.
If applied effectively, this approach is dynamic, agile, predictive, and proactive. Utilizing data about student learning will allow administrators, teachers, parents, and students the ability to look around the corner when new skills and jobs emerge in the marketplace. This foresight makes teaching and student learning highly proactive.
Education can take a lesson from the emerging and important field of preventive medicine. The goal is to use data proactively to provide a precision-based education delivery system. As technology inevitably shifts, data about student learning provides the opportunity to find hidden patterns for future skills development. Thus, we can create a more agile, targeted approach to better serve students for jobs of the future, whether or not the jobs currently exist.