Determinant Factors of Teaching Performance in COVID-19 Context

COVID-19 pandemic still impact higher education system, stakeholders and environment all around the world.
Students, teachers, academic institutions and education decision makers were shocked by an atypical new context they promptly
put in face, asking drastic change in behavior and procedures at individual, familial and institutional levels. Full lockdown and
closing campuses enforced students and teachers staying and sticking home, fronting unusual domestic for work atmosphere and unacquainted online learning and teaching technologies. Consequent back to classroom framework also imposes new sanitary and social distancing conditions leading to new teaching and learning habits that affected in many ways the performance of teaching. The aim of this paper is to apprehend all the challenges that may arise in similar critical situations to make convenient decisions helping to avoid the education system shutdown or to benefit from the previous experience to adapt future behaviors and perform tools and practices. For such purpose, the present paper reviews all the determinant factors of the teaching performance in both alternative online and classroom modes of dispensing courses in the COVID-19 Lebanese context, using Partial Least Squares Structural Equation Modeling approach (PLS-SEM). It appears that all manifest variables corresponding to latent variables have a reflective measurement model. After the convergence of the algorithm of Partial Lest Square (PLS), the structural path significance test of both inner and outer model is verified by a bootstrap procedure with 1000 subsamples.