Enhancing the Self-Directed Learning of Non-Native English Speaking Employees through an Integration of Peer Support and Digital Applications

Abstract

A combination of globalization and growth of the immigrant population has created a need to foster more inclusive training. Currently, many organizations rely on traditional English-only training and have discriminatory practices which dampen the self-efficacy of non-native English speakers. Digital applications, ChatGPT and Google Translate, and peer support offer cost-effective solutions to foster a sustainable training environment. A quasi-experimental study using four phases including baselining, the intervention of peer training, the intervention of self-directed learning, and evaluation was implemented in a real-world manufacturing environment. A total of 28 non-native English speaking machine operator trainees completed pre-intervention and post-intervention surveys that measured the self-efficacy to engage in self-directed learning. Results from paired samples t-tests indicated statistically significant increases in self-efficacy after the interventions across the entire group as well as all three sampled shifts. The findings indicate that the digital applications and peer support foster improved self-efficacy for non-native English speaking trainees to engage in self-directed learning behaviors. Consequently, this offers leaders of cash strapped organizations a training approach that is practical and affordable while aligning to philosophical trends. It also supports inclusive training of a growing portion of the population which can improve long-term sustainability. Potential limits to the study are in the form of its short-term nature which doesn’t account for the novelty effect, its small sample size, and the survey design does not measure real knowledge growth.