LAUSR

Middle school is an important phase in the academic trajectory, which plays a major role in the path to successful post-secondary outcomes such as going to college. Despite this, research on factors leading to college-going choices do not yet utilize the extensive fine-grained data now becoming available on middle school learning and engagement. This paper uses interaction-based data-mined assessments of student behavior, academic emotions and knowledge from a middle school online learning environment, and evaluates their relationships with different outcomes in high school and college. The data-mined measures of student behavior, emotions, and knowledge are used in three analyses: (1) to develop a prediction model of college attendance; (2) to evaluate their relationships to intermediate outcomes on the path to college attendance such as math and science course-taking during high school; (3) to develop an overall path model between the educational experiences students have during middle school, their high school experiences, and their eventual college attendance. This gives a richer picture of the cognitive and non-cognitive mechanisms that students experience throughout varied phases in their years in school, and how they may be related to one another. Such understanding may provide educators with information about students’ trajectories within the college pipeline.