Investigating Undergraduate Students’ Intention to Engage in Artificial Intelligence Learning - Jacob, Udeme Samuel; Pillay, Jace (Engagement: Jurnal Pengabdian Kepada Masyarakat, 2024)
This study examines how contextual factors and influences shape undergraduate students' attitudes and behaviors regarding artificial intelligence (AI) learning. Globally, AI is becoming increasingly important in education, making it imperative to understand the readiness and intentions of students for AI-enhanced learning. One hundred and ninety-two higher education students in Nigeria were surveyed online about their confidence, attitudes, self-efficacy, and age–the relationships between these factors and students' intentions to learn through AI were analysed using structural equation modelling. A significant direct association was found between confidence, attitudes, self-efficacy, and subjective norms and the intention of students to use AI. Mediation analyses demonstrated that attitudes significantly mediate the relationship between subjective norms and intention. Perceived usefulness is therefore of paramount importance. Despite this, age does not play a significant role in modifying these relationships. A review of the study’s quality criteria, including fit indexes and reliability measures, indicated that the model reasonably fit the data. The study provides valuable insights into the factors influencing undergraduate students' intentions to engage in AI learning