Affective learning is a major focus of the national K-12 physical education (PE) content standards (National Association for Sport and Physical Education [NASPE, 2004]). Understanding how students might fit into different affective learning subgroups would help extend affective learning theory in PE and suggest possible intervention strategies for teachers wanting to increase students' affective learning. The present study used cluster analysis (CA) and latent profile analysis (LPA) to develop a two-level affective learning-based typology of high school students in compulsory PE from an instructional communication perspective. The optimal classification system had ten clusters and four latent profiles. A comparison of students' class and cluster memberships showed that the two classification procedures yielded convergent results, thus suggesting distinct affective learning profiles. Students' demographic and biographical characteristics, including gender, race, body mass index, organized sport participation, and free time physical activity, were helpful in further characterizing each profile.