Examining pedagogical interventions in e-learning activities of mathematics through analysis of fine-grained students' behaviors

Abstract

This study examines the effects of pedagogical interventions on fine-grained students’ behaviors during e-learning activities of mathematics by using tablet computers and personal computers for supporting teaching and learning. To measure and evaluate finegrained students’ behaviors, there is a need to derive generalized methods to identify students’ behaviors in the representation of the learning traits of engagement, emotion, and motivation. Through performing data analytics on experimental results to measure the status of the learning traits, the effects of specific pedagogical intervention can, therefore, be reviewed. The design principles developed during the three iterations of research activities are generalized as the guiding framework for examining fine-grained students’ behaviors. The guiding framework is presented as a 4-step feedback process that includes designing the selected pedagogical intervention, identifying possible learning metrics for the pedagogical intervention, formulating possible models for the learning traits, and detecting the effects of the pedagogical intervention through data analytics on experimental results. The outputs of this study contribute to the foundation work of examining fine-grained students’ behaviors based on students’ participation and reviewing the effectiveness of pedagogical interventions. The journey of this design-based research also offers design references for researchers and teachers who aspire to build e-learning platforms that can measure students’ behaviors. This study, however, shows the need to continue the research efforts by deriving theoretical models of each learning trait and factoring the interrelationships among different learning traits into the measurement of students’ behaviors.