Significant effort toward closing the degree attainment gap has focused on creating defined pathways for students, as well as degree-planning and advising programs. For example, the iPASS (Integrated Planning and Advising for Student Success) initiative of the Bill & Melinda Gates Foundation is funding 26 pilot projects in critical functions that impact student success, such as course selection and connecting students to counseling and coaching resources.
The next (and perhaps even more impactful) frontier for colleges and universities working to improve degree attainment will be in curriculum and instruction. Using evidence-based principles of learning design to create more effective online learning experiences, combined with predictive analytics technology that continuously monitors and tracks students’ performance, can significantly improve student achievement. Designing better learning environments based on learning science benefits students who are less prepared for college work, and predictive analytics tools that use student learning data can better connect with student services.
In short, education technology is beginning to align around the linked imperatives of increasing access and degree attainment.
How big is the degree attainment gap?
Last fall, 20.5 million students enrolled in U.S. colleges or universities, according to the National Center for Education Statistics (NCES). Many of these students, however, will not complete a degree. According to projections, roughly 1 out of 3 students who start out for a college degree will finish within six years. The completion rate is much worse for first-generation students, low-income students, and/or students of color. Data from The Education Trust shows that just over half of all Federal Pell Grant recipients complete their degrees.
The completion rate is lowest for students who attend college part time, particularly younger students, says a report from the National Student Clearinghouse Research Center. First-generation, low-income, and minority students face a range of unique challenges. They are often older students who are working and raising families while they attend school. They tend to be less prepared for college-level work than students who have recently graduated from high school. Such students lack basic study skills, manage time poorly, and may not be able to recognize when they are failing a course.
Institutions and instructors must work especially hard to reach these students who may not seem like they want or need help; they are often isolated students, and may lack self-confidence and may not know how to ask for help when they need it.
Related reading: How Does the Degree Attainment Gap Affect Pell Grant Students?
Bloom’s 2 Sigma findings
In 1984, educational psychologist Benjamin Bloom reported that he and his graduate students had zeroed in on a formula for student success: student performance could be improved drastically by combining a mastery learning approach and one-on-one tutoring.
The mastery model meant students were taught using lectures, tests, feedback, and additional practice to ensure that all students mastered learning objectives. If they were then provided with one-on-one coaching, those students’ performances improved by a factor of two standard deviations, or 2 sigma. Ninety percent of the tutored students in Bloom’s study scored at levels achieved by only the highest 20 percent of the control class.
However, despite the potential impact of the results, Bloom’s formula wasn’t scalable. In the 1980s, it wasn’t possible to provide one-on-one tutoring for every student, and Bloom himself concluded that it was “too costly for most societies to bear on a large scale.” He charged researchers with finding a more practical and realistic way to accomplish this one-on-one instruction. Bloom and his students investigated several options — group instruction, study groups, and home instruction — but none of those came close to producing the result of one-on-one tutoring.
Related reading: Using Online Courseware to Create a Personalized Learning Experience
Personalized learning at scale
Recent advances in learning science, technology, and data science have provided the tools and know-how for educators to personalize learning at scale. These “smarter” online learning platforms learn about students as the students learn, capturing and analyzing student behavioral and learning data, and generating a personal learning estimate for every student.
That kind of rich, individualized data is invaluable to instructors, who can use it to develop engaging, personalized interventions with students who need extra help. For example, Erik Moody, an assistant professor of psychology at Marist College in upstate New York, uses adaptive technology to do just that.
Rather than use a textbook, he uses online content on Acrobatiq’s learning platform. His students go online to do their reading and take quizzes, and classes meet twice a week for lectures and exercises. The students in Introduction to Psychology receive feedback from both Acrobatiq and Moody — the formative practice and module-level quizzes give them targeted and timely feedback and, if they require it, additional practice. Moody, who monitors the data collected by the platform on each student as they progress through the online material, provides feedback in class.
Moody is able to intervene as soon as a student begins to get off track in the course. Many students, he says, may not realize their study habits are ineffective. He calls struggling students into coaching sessions, and helps them change their habits.
Using adaptive technology to resolve Bloom’s dilemma
To help all students achieve their best possible outcomes and attain a degree, colleges and universities must find ways to meet students where they are.
Personalized learning platforms that generate real-time information about student performance may be the key to creating an early alert system for large classes. If a learning dashboard shows from early in the semester which students are struggling, instructors are able to intervene in a meaningful, engaging way, such as helping them to correct study habits, better understand course content, or connect with campus resources, such as a tutoring center.
Advances in technology, and the rise of blended learning, may allow instructors to use Bloom’s 2 Sigma method to improve student outcomes. By designing more effective learning experiences that produce meaningful data about how learners are progressing and where students are struggling, educators can answer Bloom’s call to provide personalized learning at scale and begin closing the degree attainment gap.
A.J. O’Connell is a freelance journalist specializing in education reporting and a former college journalism teacher.