Browsing by Subject "Training and Development"

Now showing 1 - 2 of 2
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    Learning to lead: A quasi-experimental test of the interplay between experience and training
    (2015-07) Jones, Stephen
    Two dominant ways that employees learn leadership skills are formal training and on-the-job experience. Both types of learning are ubiquitous in organizations, but their interplay is rarely considered. In this study, I adopt learning theories from educational and cognitive psychology to explain why experience may help or hinder the effectiveness of leadership training, and I test my hypotheses using a quasi-experiment in a public accounting firm. I also examine the impact of other individual differences--cognitive ability, motivation to lead, learning goal orientation, and pre-training self-efficacy--on training effectiveness. From the perspective of the leader, prior leadership experience significantly improved the effectiveness of leadership training. Leaders who had led more projects and had been exposed to a broader range or leadership situations were those who benefit the most from leadership training. The results support the theory that cognitive constraints impede learning during training for novice leaders and are alleviated when leaders possess more experience. However, the same support was not found from the manager and subordinate perspectives. Regarding individual differences, there was clear evidence for the benefit of a learning goal orientation, mixed evidence for the benefit of motivation to lead, very limited evidence for self-efficacy, and no evidence for cognitive ability. The implications of these findings for theory and practice are discussed.
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    Using a Generative AI Chatbot in Learner-Controlled Training
    (2024-07) Li, Hanwen
    The advancements in generative AI technologies have provided various opportunities to enhance human resource development (HRD) activities. Scholars have discussed the benefits of using AI chatbots, a popular AI application, in training activities. Yet, the current literature still lacks a comprehensive understanding of how AI chatbots can be used in training activities. Drawing from the self-determination theory (SDT) and the technology acceptance model (TAM), this study examines trainees’ AI readiness in terms of attitude toward AI, perceived autonomy support, and knowledge of AI, and its influence on their motivation to use AI in a learner-controlled training session taught by a generative AI chatbot designed and developed using the latest large language model. Their AI readiness and motivation to use AI were measured before the training. Training outcomes were measured after the training in terms of transfer of training and learning achievements. This study employed a within-subject design, with 43 participants completing the experiment. The multiple linear regression analysis shows that knowledge of AI predicts motivation to use AI. Attitude toward AI was measured by perceived usefulness and perceived ease of use. Perceived usefulness significantly predicts motivation to use AI; however, perceived ease of use is insignificant. Perceived autonomy support was also found to be insignificant in predicting motivation to use AI. The analysis shows that motivation to use AI is significant in predicting training transfer but insignificant in predicting learning achievements. This study provides empirical data for the understanding of how the utilization of generative AI chatbots in training activities affects trainees’ intrinsic motivation to interact with the AI and, therefore, influences the training outcome. The findings indicate the need to prepare employees for the AI era and urge future studies to gain a deeper and broader understanding of this phenomenon.