Beyond Attainment: Examining Student Growth

Damian Betebenner

As a first year college student enrolling in an advanced Spanish course, I found myself sitting in class with students from diverse backgrounds. Many students, like myself, had barely visited a country with Spanish as its native language. Others in the class had actually lived in Spanish speaking countries and spoke—at least to my ear—fluent Spanish. This situation presented a challenge to the teacher in terms of grading. Students were entering the class with vastly different fluency levels in Spanish. Judging people at the end of the course on their Spanish fluency without taking account of their starting place wouldn’t be fair to those entering the class at the lower end of the fluency spectrum. The teacher’s solution was simple: Instead of judging us based solely on our attained fluency at the end of the course, she would judge us based upon our growth.

The situation in this class is in many respects a microcosm of efforts being undertaken in education nationally over the last decade. As part of the “big data” movement where efficient data collection and management is being leveraged to glean insights previously invisible across almost every sector, including education, we are now “connecting the dots” and looking not just at how students perform at the end of a class, but also how much they’ve grown—taking account of where they started. Unique student identifiers together with modern data management systems allow teachers, principals, administrators and policy makers to follow the child and understand not only their level of mastery at a point-in-time but also the progress they have made along the way.

The transition, however, has not been instantaneous. Education is replete with nomenclature which describes the point-in-time measures of student level of mastery of a topic. In US public schools, for example, the term proficiency has described the manner in which level of mastery has been characterized in reading and mathematics based upon performance on state standardized assessments. More recently, career ready and college ready are terms widely in use. These and similar terms are characterizations of a student’s performance that don’t take account of where the student began. The benefits of going beyond simple point-in-time views of student performance are profound. Taking account of where a student starts allows practitioners to tailor instruction to the student and where they are at. Simultaneously, by monitoring their progress, mid-course adjustments can be implemented based upon the real-time needs of the student.
students perform at the end of a class, but also how much they’ve grown—taking account of where they started. Unique student identifiers together with modern data management systems allow teachers, principals, administrators and policy makers to follow the child and understand not only their level of mastery at a point-in-time but also the progress they have made along the way.

If one thinks of education as a journey, educational leaders are concerned, even obsessed, about whether students reach their destinations. How does one go beyond level of mastery to characterize a student’s educational journey? The answer is to look at student growth in conjunction with student level of mastery. As the formula distance = rate x time implies, the distance a student travels in the education journey is a function of where they start (initial level) and the rate they travel along the way (i.e., growth). Examining student growth is simply a view of level of mastery over time—a level of mastery timeline for each student, monitoring their academic progress as they move through the education system.

This picture is a student level of mastery timeline that communicates the progress of a public school student. The main features of the figure, however, are relevant to monitoring progress of a student in any subject and in any educational context. In the picture, the grey-scale background indicates the criterion-referenced level of mastery levels in reading against which student level of mastery is judged (Unsatisfactory, Part Proficient, Proficient, and Advanced), and the white dots show the level of level of mastery of the student in the indicated grade and year. For example, in grade 3/2009-2010, the student’s level of mastery was judged Unsatisfactory. In grade 4/2010-2011, the student’s mastery was judged as Part Proficient followed by Part Proficient level of mastery in grade 5/2011-2012 and Proficient level of mastery in grade 6/2012-2013. Relative to the level of mastery levels, the student’s progress between grades 3 and 6 can be characterized as “catching-up.”

Note that regardless of content area, a criterion-referenced examination of level of mastery over time can be constructed. Whether for physical education or social studies, one need only have level of mastery standards and tests anchored to those content areas to produce the figure. What the figure provides in addition to criterion-referenced level of mastery over time is a norm-referenced interpretation of that progress, indicated by the arrows and fan. Because so many students take the same assessments in the public schools, it is possible to calculate growth norms indicating the relative growth of students in addition to their standard based/criterion-referenced growth. For the student in the picture, their growth in level of mastery is exemplary in a norm-referenced sense with student growth percentiles of 69, 85, and 74 in 2009-2010, 2010-2011, and 2011-2012, respectively.

Progress monitoring encompasses two complementary views of time-based level of mastery: a retrospective view and a prospective view. The retrospective view in the picture above shows a student demonstrating exemplary growth and catching up from what was considered unsatisfactory to proficiency in reading. The student has experienced three consecutive years of solid progress, taking them from what would generally be considered at-risk status to a student thriving in the subject. Retrospective views of a student’s level of mastery allows parents, teachers and even students to identify strengths and weaknesses and ideally leverage any information gleaned to maximize progress going forward.

By contrast, a prospective view of student level of mastery looks to the future and lays out what the next steps on the student’s education journey might look like. If the goal for all students is to put forward and accomplish ambitious yet reasonable goals, the fan in the figure above highlights the range of possible outcomes based upon the data of students just completing that year. The upper end of the fan indicates the upper range of achievement observed by previous students across the academic year while the lower end of the fan indicates the lower range of achievement.

To establish growth norms, states utilize data on vast numbers of students. In contexts without the thousands of students necessary to create growth norms, it is a bigger challenge to know whether the growth demonstrated by a student is impoverished or exemplary. For example, a student might go from Unsatisfactory to Part Proficient in a year in one content area. But is that fantastic progress or typical among students? A parent might believe that their student is making progress (which they are relative to the standards). But if the parent were informed that it is typical for students to progress from unsatisfactory to proficient in a year, then the progress the student made doesn’t look as exemplary. Norms help us to anchor what ambitious yet reasonable progress is. But without data to establish such norms, educators are left to apply their expert judgment (likely based upon their many experiences) on what “exemplary” looks like.

One benefit of individual level student growth data is that it enables those interested to aggregate the data and look for patterns. Do some curricula support greater levels of student growth than others? Are there schools where students grow faster than others? If so, why? Student growth provides another lens through which to understand student performance, with the hope that corrections can be made early enough to maximize the chances for a student to reach their level-of-mastery goals.

Examinations of student growth are often considered confusing because of the complicated calculations that take place to create the results. The analyses utilize regression techniques and all the data available to model expected levels of growth of students. Monitoring students’ progress throughout their educational journey is not as complicated as the calculations might suggest. Often the most difficult parts are the record keeping required to keep track of students as they pass from grade to grade in the education system (changing teachers and schools) and the creation of grade-level performance standards against which to monitor student progress. Once those features are in place, one has all the necessary components to chart student progress along their education journey.

 

Damian Betebenner is senior associate at the Center for Assessment. [email protected]

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HaYidion Taking Measure Fall 2015
Taking Measure
Fall 2015