Evaluating a student’s academic progress entirely on a preset, stagnant set of guidelines and within a rigid timeline is fast becoming a thing of the past in American education. Flexibility, natural progression, and personalization are all major components in the framework for learning that has been developed by education researchers and practitioners in recent years.
One educational approach that’s grown out of this trend involves the “competency-based” model or system. Competency-based systems allow students to learn at their own pace in the setting and style that best suits their individual learning process and needs. Examples of strategies that can be used in competency-based systems are project-based and community-based learning, online/blended learning, credit recovery, and dual enrollment.
Benefits of competency-based systems include enhanced flexibility in the way that credits are awarded as well as more personalized learning opportunities for students. This type of learning typically leads to better student engagement because the content is relevant to each student and customized to their individual needs. Research has also shown that student achievement usually improves in competency-based systems as customized pacing tends to lead to better outcomes.
Competency-based systems have also proven effective in creating multiple pathways to graduation, a model which has proven effective in reducing dropout rates. By using technology more constructively, applying teachers’ skills and interests to greater effect, and maximizing learning opportunities outside of school hours and walls, competency-based systems increase the efficiency and productivity of students’ learning.
In 2009, Westminster Public Schools (WPS) in Colorado began to transition to a competency-based education system. Since making this switch, WPS has organized courses of study according to performance levels instead of traditional grade levels. As part of its College and Career Readiness Research Alliance, REL Central at Marzano Research assisted WPS in evaluating the efficiency of the new system after it had been in place for a decade.
A key indicator in REL Central at Marzano Research’s evaluation platform was measuring the length of time it had taken WPS students to advance through their respective performance levels, as was examining how well teachers’ ratings of students’ competency (learning target scores) aligned with external assessments of the students’ academic achievement. We used data from the WPS learning management system in the evaluation, focusing on the length of time it took elementary and middle school students to complete math and literacy performance levels 3–8 during the timeline of a traditional academic year.
The correlation between WPS students’ learning target scores and their scores on Colorado’s standardized achievement test were also a focus of the assessment. To provide a more complete picture of students’ academic progress, their learning target scores were aggregated by REL Central at Marzano research in order to create an overall performance-level competency score. These performance-level competency scores were then used to predict students’ scores and proficiency levels on the Transitional Colorado Assessment Program.
Findings from the study showed that a majority of students completed their math and literacy courses in about one academic year. Whereas most of the students who were in a math or literacy performance level below their traditional grade level also completed their course of study in a similar time frame, a larger percentage of these students (43–47%) finished their level in three or fewer quarters. Students in a performance level at their traditional grade level, meanwhile, were in the 17–22% range.
These results suggest that the WPS competency-based system provides students who are behind academically with an opportunity to complete performance levels in less time than in a traditional education system. Students’ performance-level competency scores also corresponded well with their Transitional Colorado Assessment Program scores. Math performance-level competency scores accurately predicted math proficiency levels on the state achievement test for 40% of students, and literacy performance-level competency scores accurately predicted reading proficiency levels on the test for 59% of students.
Not all results from the study were positive, however. For example, the study found that performance-level competency scores of students in a performance level below their traditional grade level were more likely to predict that their state achievement test proficiency level would be higher than it actually was. In contrast, for students above their grade level, performance-level competency scores were more likely to predict that their state achievement test proficiency level would be lower than it actually was.
As competency-based systems grow in popularity throughout the United States, it’s important to monitor their efficiency and regularly assess their success. To learn more about competency-based education or other forms of personalized learning, feel free to get in touch with us HERE.