Load Reduction Leadership: A Cognitive Load Theory-Based Framework Differentiating Performance Patterns in NYC Schools

Abstract

This dissertation applies cognitive load theory to teacher working conditions in New York City. To connect small-scale cognitive processes with perennial organization-level effects, the theoretical components of this paper develop a novel framework. Load reduction leadership (LRL) illuminates how day-to-day school operations impact staff members’ cognition and school-level student performance. LRL extrapolates various cognitive load phenomena to schools’ complexities and time scales. Eight longitudinal case studies were found through New York State summative exam data. Schools were selected based on their abilities to over- and under-perform at improving their students’ proficiency, including schools that changed from under- to over-performance and vice versa. Public documents provided samples of organizational practices during each performance period, which were analyzed using LRL. The ratio of LRL-aligned to -misaligned coding's differentiated between samples taken from periods of over- and under-performance. Three exceptional former New York City principals from different schools were interviewed. Those transcripts provided further insight into the framework’s potential to explain mechanisms linking school leaders’ actions to school-wide performance. These quantitative and qualitative explorations generate recommendations for school improvement practices and future research.