HCAIMay 24, 2024

When Generative AI Meets Workplace Learning: Creating A Realistic & Motivating Learning Experience With A Generative PCA

arXiv:2405.15561v14 citationsh-index: 15ECIS
Originality Incremental advance
AI Analysis

This addresses the challenge of scalable and engaging training for employees, though it is incremental as it builds on existing PCA and generative AI methods.

The paper tackled the problem of ineffective and costly workplace learning by developing a Generative Pedagogical Conversational Agent (GenPCA) for organizational communication training, which was positively perceived by employees and improved self-determined learning.

Workplace learning is used to train employees systematically, e.g., via e-learning or in 1:1 training. However, this is often deemed ineffective and costly. Whereas pure e-learning lacks the possibility of conversational exercise and personal contact, 1:1 training with human instructors involves a high level of personnel and organizational costs. Hence, pedagogical conversational agents (PCAs), based on generative AI, seem to compensate for the disadvantages of both forms. Following Action Design Research, this paper describes an organizational communication training with a Generative PCA (GenPCA). The evaluation shows promising results: the agent was perceived positively among employees and contributed to an improvement in self-determined learning. However, the integration of such agent comes not without limitations. We conclude with suggestions concerning the didactical methods, which are supported by a GenPCA, and possible improvements of such an agent for workplace learning.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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