Exploring digital competence’s impact on faculty well-being through SEM-SVM analysis

This research aims to explore the impact of digital teaching competence on faculty career well-being, teacher self-efficacy, and the moderating role of pedagogical content knowledge within the context of colleges in Pakistan. A quantitative approach was adopted, involving 266 faculty members from various academic programs in colleges across Pakistan. Data were collected through an online survey using validated scales adapted from prior research. The study used partial least squares structural equation modeling (PLS-SEM) to analyze the relationships between constructs. Support vector machine (SVM) analysis was conducted using JASP software to enhance predictive accuracy and identify the importance of key features in the dataset. The results confirm that digital teaching competence significantly impacts faculty career well-being and teacher self-efficacy. Teacher self-efficacy mediated the relationship between digital teaching competence and faculty career well-being, providing deeper insights into this linkage. Furthermore, pedagogical content knowledge moderated the effect of digital teaching competence on faculty career well-being, emphasizing its critical role. The inclusion of SVM analysis revealed the significance of variables such as psychological factors and AI exposure in influencing predictive performance, further validating the robustness of the findings. This study contributes to the existing literature by demonstrating the critical role of digital teaching competencies in enhancing faculty members’ well-being and effectiveness. It underscores the need for targeted professional development programs that integrate technology and pedagogy, ultimately fostering a more supportive educational environment for faculty and improving overall teaching quality.