Author: Mohamed Askar, Southern Utah University, USA
Published: December 1, 2019
Citation: Askar, M. (2019). Faculty Target-Based Engagement Assessment Statistical Model for Enhancing Performance and Education Quality. IAFOR Journal of Education, 7(2). https://doi.org/10.22492/ije.7.2.02
There is a worldwide interest in developing quantitative faculty members’ activity evaluation models. However, implementing a fair and reliable model is challenging. Without capable and high-quality faculty members, no education improvement effort subsequently can succeed. Based on the gap analysis of the literature, lack of a quantitative faculty member assessment model might affect teaching and scholarly performance and lead to undesirable effects. Therefore, most of the existing metrics assessment models do not capture the full range of activities that support and transmit knowledge to students.
The main objective of the current research is to develop a practical, comprehensive and flexible statistical Target-Based Engagement assessment model of faculty members that considers both the specific faculty needs and the academic unit management concerns. A mathematical relationship between one or more random and additional non-random variables was used to develop the model. Descriptive and inferential statistical methods were applied in the data analysis. The Target-Based Engagement model has seven interconnected aspects and three subsequent modules. It is a robust statistical framework for automatic faculty assessment.
The results of this model are beneficial for faculty assessment in addition to having well-aligned key performance indicators inside the different levels of the institution. The model helps in supporting different strategic decision-making of the institution and is considered as a long-term improvement method in the academic profession. Creating a vision for future faculty assessment statistical models will improve the faculty performance and enhance the performance of all higher education stakeholders.
target-based engagement, statistical model, quality of engineering education, self-assessment, faculty member assessment