Using learning sciences to solve real-world education challenges

Learning science is the collective term for a broad range of scientific approaches that seek to measure how people gain knowledge and, therefore, evaluate how effectively information is taught.¹ Understood to be a combination of disciplines ranging from behavioral economics to cognitive neuroscience, all focused on the study of learning, the discipline is often referred to as the learning sciences.

Learning sciences master’s graduates find their way into a variety of fields, including corporate training and artificial intelligence (AI) research. For example, a better understanding of how we learn contributes to a better understanding of how AI can be used constructively in the classroom, generating clear guidelines for teachers to apply in their everyday practice.²

In education, learning sciences help in the development of more effective teaching methods and real-world learning solutions. They generate evidence-backed principles and techniques that can be applied to solve a range of challenges.

This post looks at some of the issues in education that the learning sciences can help address—from achievement gaps to challenges with student engagement and motivation—and the solutions that emerge from a learning sciences approach to problem-solving.

Understanding the learning sciences

The International Society of the Learning Sciences describes its mission as “the research of learning in all its forms.”³ Focused on understanding learning, the field is necessarily interdisciplinary. Whether it’s a concept emerging from the study of neuroscience or economics, if it applies to learning, it is of interest to learning scientists.

As a relatively new field, learning sciences is, in a sense, still developing as a field of study. Nonetheless, most sources agree that the formal study of learning sciences emerged in the 1990s, heralded by the first International Conference of the Learning Sciences and the debut of the Journal of the Learning Sciences.⁴

Historians of the field, such as Stanford University’s Dr Victor Lee, note that the learning sciences date back to the 1980s and a divergence in the field of cognitive science. In short, some cognitive and computer scientists were interested in developing models of human thought that could be applied to machines—the genesis of AI research. Others sought to apply that research to real-world issues in training and education, which is how learning sciences was born.⁴

Common real-world education challenges

Learning scientists are at the forefront of education innovation careers and research, investigating some of the more persistent challenges in the field, including:

• Achievement gaps and equity issues: An achievement gap is any disparity in educational outcomes or performance between groups of students.⁵ Often, these relate to equity issues—for example, there is a persistent achievement gap between students from high-income and low-income families.⁶ The U.S. faces an achievement gap in math and science education compared to other countries⁷
• Student engagement and motivation: Even adequately defining engagement can be a thorny issue for learning scientists,⁸ but most agree that engaged, attentive, motivated students learn better⁹
• Adapting to diverse learning needs: The concept of “differentiation in education” describes the notion that education can tailor instruction and assessment to the needs of various learners, thereby collectively improving student engagement and achievement¹⁰
• Technology integration in classrooms: You’ll find some of the most visible applications of learning sciences in edtech, where developers are often looking for evidence-based approaches to inform their concepts and validate their products¹¹

How learning sciences provide solutions

The solutions provided by learning sciences are always predicated on a commitment to empirical, evidence-based research. It is from the learning sciences that we have an increasing proliferation of evidence-based instructional strategies—teaching methods based on proven outcomes rather than intuition.

One example is learning analytics. By gathering and analyzing data on learning and outcomes, learning scientists can develop models that allow instructors to measure the effectiveness of teaching approaches and modify them to achieve better results. In time, this gives rise to personalized and adaptive learning models informed by data and revised to meet measurable goals.

Finally, understanding how and why we learn helps inform the design of new digital learning environments.¹² Developing effective online programs and teaching tools, fueling the multi-billion-dollar e-learning market, is one of the foremost modern-day practical uses of learning sciences.¹³

Benefits of a learning sciences approach

Learning sciences in education is focused on improving student outcomes and teacher effectiveness with solutions that can be implemented at scale across education systems.

The Maryland Education Code, for example, includes the provision that a system of professional development for teachers must include: “Advanced training on the science of learning specific to individual disciplines.”¹⁴ As noted by Learning Forward, a Professional Learning Association, this effectively directs Maryland instructors to align their teaching practice with the latest research findings on how learning works. The practical outcome is the use of techniques such as concept maps to assess students’ understanding of what has been covered before moving on to new material in class.¹⁵

Launch your career in the learning sciences with an online master’s from SMU

The learning sciences function as a crucible for innovation in education. Real-world challenges are examined empirically, with a focus on developing solutions backed by evidence and data. Degrees such as the online Master of Science in the Learning Sciences from SMU’s Simmons School of Education & Human Development offer a thorough grounding in the principles and practice of learning analytics and learning technology design.

At SMU, a well-rounded learning sciences curriculum includes modules in research methods and data modeling, as well as a capstone project in which you apply your skills and knowledge to a real-world education problem. Courses in learning analytics and data modeling prepare educators, policymakers and researchers to advance careers in learning sciences at the intersection of technology and education theory.

For more information about SMU’s learning sciences master’s program, explore our online resources, such as admissions and tuition information. When you’re ready to discuss advancing your career with a learning sciences degree, schedule an appointment with one of our admissions outreach advisors to talk about what SMU can do for you.