Data-Driven Teaching Opens New Pathways for Learning

Data mining in today’s classrooms is helping teachers provide individualized instruction for all types of learners.

“Every truth has two sides; it is as well to look at both, before we commit ourselves to either.” — Aesop

How many times have you heard that some districts are making data-driven decisions or using research-based practices to announce a new initiative or request funding for the latest silver bullet in education?

Because of misconceptions about data or a lack of understanding about how it can be used to make strategic and well-planned decisions, many are unwilling to denounce data.

On the other hand, ever since Edward Snowden exposed spying on Americans by the National Security Agency, the rhetoric on the use of data has struck fear into the minds of parents nationwide. According to InformationWeek editor David Carr, many privacy advocates fear that “education data gathered together in a big national pool could be misused, or hacked or leaked in some inappropriate way.”

As in all areas of life — from politics to religion to education — there’s danger when something is not used for its intended purpose. However, it would be ignorant and irresponsible to dismiss the use of data in education without fully understanding the potential upside when it’s used appropriately.

Let’s explore the many ways that educational data can improve teaching and learning if we overcome our fears about its potential for misuse.

Data in Education: Then and Now

To best exemplify effective uses of data collection and analytics, here are two hypothetical situations.

Imagine a 10-year-old student qualified for reading intervention and additional progress monitoring. This student gets pulled from class and works in a small-group setting with others who are reading below their grade level. The students are asked to read short stories and work with a teacher, who gives each member of the group a workbook with written tests every other week. The assessments measure vocabulary and reading comprehension. Every few days, the teacher grades and returns the workbooks.

The results show that the student did well on vocabulary but needs to work on reading comprehension. In this scenario the teacher must spend hours grading routine assignments and finding appropriate content based on the individual needs of each student in the group. It is a model of learning typically used in the past or in schools that have yet to implement technology at the classroom level.

Today, students often learn to read on some type of Internet-connected device, working independently and without being pulled out of class. They take quizzes on these devices, which collect data on reading rate, comprehension, vocabulary and other factors. Furthermore, students receive instant feedback about the correct answers. They can track their progress with visual data that is easy to understand, and software makes timely suggestions for further growth.

If the computer concludes that a task is too difficult, it will adapt the content of the learning activity to the student’s level and provide resources that can explain concepts that the individual found too challenging. This affords teachers more time to collaborate with their colleagues and focus on creating student-centric learning activities. This type of education is being adopted by an increasing number of schools around the world.

Improvements Made Through Data Mining

Darrell M. West, director of the Center for Technology Innovation at Brookings Institution, wrote a 2012 report, Big Data for Education, about the potential for improved research, evaluation and accountability through data mining, data analytics and web dashboards. Rather than fear Big Data based on misconceptions, West says we should leverage technology to do more assessments for learning (better known as formative assessment) rather than testing of learning (summative assessment). He notes that recent advances in data collection also make it possible to mine learning information for insights into student performance and learning approaches.

According to West's report, teachers can analyze learning in far more nuanced ways with data analytics.

"Online tools enable evaluation of a much wider range of student actions, such as how long they devote to readings, where they get electronic resources, and how quickly they master key concepts," he writes.

Administrators and teachers alike have been craving access to information like this for years in order to provide students with the best possible learning opportunities according to their individual needs.

Unfortunately, recent times called for traditional methods that make proactive decisions about teaching difficult and prohibit educators from using electronic resources. Is the operation of the technology in practice adequately described in the case study? Are concrete examples provided? Do they illustrate the way the technology's underlying theory of learning translates into practice?

A Matter of Time

As we progress through the digital age of education, technological advances will bring many improvements to teaching and learning. The potential for better research, evaluation and accountability through data mining and analytics is very exciting. It will prove crucial in providing the kind of education that students need to be successful in an increasingly global and digital society.

However, it’s going to take time for the public to better understand how technology is being used to collect data and to feel confident about the privacy and security of their children’s personal information. I, for one, am optimistic about the possibility of student-centric, adaptive learning digital environments and the use of data to educate students based on their path, pace and interests.

[title]Connect IT: Bridging the Gap Between Education and Technology

This article is part of the Connect IT: Bridging the Gap Between Education and Technology series. Please join the discussion on Twitter by using the #ConnectIT hashtag.

4774344sean/Thinkstock
Nov 26 2014

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