Constructing an Interpretive Structural Model to Unravel the Interconnected Drivers of Teaching Quality in Higher Education

Lanndon Ocampo, Porferio Almerino Jr., Marilou Martinez, Rogelio Sala Jr., Kent Maningo, Lourdes Garciano, Christine Catyong, Marvin Guinocor, Gerly Alcantara, John de Vera, Veronica Calasang, Randy Mangubat, Larry Peconcillo Jr., Emerson Peteros, Charldy Wenceslao, Rica Villarosa

OAI: oai:igi-global.com:339564 • DOI: 10.4018/IJKSS.339564

Identifying the primary factors of teaching quality remains a pivotal agenda for informed decision making, strategic planning, and resource allocation. This study builds upon ten key factors derived from previous research and recognizes the inherent complexity within their relationships. Emphasizing the necessity for a structured model, this work employs an interpretive structural modelling (ISM) approach and Matrice d'impacts croisés multiplication appliquée á un classment (MICMAC) analysis for constructing a hierarchical model that delineates the interrelationships among the factors influencing teaching quality. The findings indicate the substantial impact of intrinsic factors, particularly teachers' individual and psychological characteristics, on other factors. Additionally, our analysis highlights the critical role of student composition in enhancing overall teaching quality. These insights significantly contribute to the literature by offering valuable guidance to decision makers for maintaining teaching quality within higher education institutions.