Four eleven-year olds focus their attention on a game board. One girl rolls a set of dice. The boy across from her scribbles something on a sheet of paper, grins, and then exclaims,“The frequency of 7 is the highest, so far!” What? Since when do eleven-year olds discuss frequency while playing a game with such enthusiasm?
This is a regular occurrence at Quest to Learn, a public middle school in New York City’s District Two. Their students engage in game-like learning on a daily basis. Whether they’re playing board games, creating digital simulations or working to solve large complex challenges, students are building knowledge, skills and understandings – all aligned to state and national standards, and also with standards developed at the school level. One question frequently asked about the Quest school model concerns assessment: how do Quest teachers know whether their students have learned intended knowledge and skills during game play? One answer to this question is embedded assessment.
Embedded assessment is any assessment given to students during their learning process. This kind of assessment gives both both teachers and students data in real time, which can be used to gauge and further support learning. These assessments are also so well integrated into the flow of learning, that oftentimes students do not even notice they are being assessed. Embedded assessments are different from typical assessments, such as quizzes, tests, and reports, because typical assessments focus mainly on what students know, whereas embedded assessments allow for teachers to gauge what students know and how students use the knowledge in action. Let’s see how it works by looking at an example from a board game designed for a probability unit at Quest to Learn and focused on frequency and the impact of frequency on outcomes. The game is called Caterpillar.
To play the game, students roll a pair of dice and use the resulting sum to construct a caterpillar on a numbered game board. Students also tally how many times a sum appears after each dice roll. The goal of the game is to build the longest caterpillar. At the end of the game, students create frequency graphs based on their dice roll results to visually identify the most frequently rolled sum. Then another round of play results from the outcomes of these graphs.
During game play, the teacher circulates around the room and monitors student learning. The first embedded assessment of Caterpillar occurs when students create frequency graphs. After students finish their graphs, the teacher asks students to “mod” or change the game to improve the effectiveness of Caterpillar in teaching frequency. To create a more successful game, students must have a solid knowledge of frequency and must use that knowledge in creative ways. Therefore, the game “mods” designed by the students become a second embedded assessment.
In both cases, students see the assessments as fun and doable challenges, and, for the teacher, they represent strong tools to determine, in the moment, whether students have reached the learning goals for frequency. We find this approach of embedded assessments to be a powerful tool that benefits both students and teachers at Quest to Learn.