Emotion as Identity Work in Children's Data Modeling Practices: A Response to Lanouette

ABSTRACT In this response to Lanouette as part of the special issue Centering Affect and Emotion Toward Justice and Dignity in Science Education , this commentary highlights key themes in relation to welcoming affect and emotion into elementary science classrooms to support learners’ data modeling practices. These themes include: (1) the idea that social interactions in classrooms are emotional encounters that can be framed along a continuum, and that no emotions are off‐limits or out‐of‐bounds in these settings (i.e., competition can be just as important to learning science as collaboration); (2) the pedagogical implications of relational work from an arts‐based perspective and thoughtfulness required as the designer/teacher/researcher working toward supporting learners’ dignity in science classrooms; and (3) embedding reflection as a process that is part of the emotional work in making sense of learning experiences. I put the manuscript into conversation with examples from research that positions the arts as a mediating process for supporting sense making around emotion and affect across disciplines. I end with a discussion of emotion as a design imperative for supporting learners’ identities within data modeling practices in elementary science classrooms.