Exploring AI Adoption Post-COVID: Impact On Faculty Wellbeing And Teaching Confidence - Dr. Aqeel Ahmad Khan, Madiha Akram, Gull Naz Khan, Amna Liaquat, Javeria Saleem, Bisma Akhlaq, Aamir Iqbal (Migration Letters, 2024)
The main purpose of this study is to assess the reception of Artificial Intelligence applications in the post-COVID era and their influence on lecturers’ occupational wellbeing as well as teaching self-efficacy, using UTAUT2 model. The paradigm adopted for this research was non-experimental survey design which employed quantitative approach in order to explore the associations between performance expectancy, effort expectancy, social influence, facilitating conditions, price value, habit and dependent variables i.e. occupational wellbeing and teaching self-efficacy. The data was collected through an online questionnaire distributed in Facebook and What Sapp groups resulting [1]to 350 responses (57.1%, male = 200/female = 42.9%). Confirming a significant positive relationship (p < .001) between occupational wellbeing, teaching self-efficacy and UTAUT2 constructs showing that AI acceptance by academicians depends on these factors. In conclusion, this study highlights that the acceptance of Artificial Intelligence applications among lecturers in the post-COVID era significantly influences their occupational wellbeing and teaching self-efficacy, with key UTAUT2 constructs playing a vital role in shaping this acceptance.