Interplay of cognition and affect in undergraduate math students’ careers: insights from recursive partitioning
Chiara Andrà and Guido Magnano
Data collected in entrance tests for undergraduate curricula in mathematics at the University of Turin are analysed using the recursive partition method, to obtain classification trees for different ”response variables” describing academic achievement or drop-out. The input factors include both math abilities and several affective and motivational factors, the latter having being assessed using internationally validated questionnaires. We argue that classification trees can provide unexpected insight into the interplay of such factors for academic success or failure, specifically for math students.
Chiara Andrà is Lecturer at the University of Torino. She teaches Mathematics Education at the Department of Philosophy and Education in Torino, and Statistics at the Department of Mathematics. Her research interests regard early probabilistic thinking, undergraduate students’ difficulties about mathematics and its learning, and semiotics. Her research is framed within the paradigm of the embodied cognition.
Guido Magnano is associate professor of Mathematical Physics at the University of Torino. Since 2001 he has supervised the design and the administration of student entrance tests at his university, and participated to various research projects, both at regional and at national level, aimed at measuring mathematical ability and other relevant dimensions in students’ transition from high school to undergraduate studies. A significant part of his recent research activity is devoted to Item response theory, in connection with item validation and reliability issues in multiple-choice testing.