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

arXiv 2405.15561 ↗First posted 24 May 2024cs.HC cs.AIcited by 2

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Abstract (arXiv)

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.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 3 of its 68 references that are in the map. First posted on arXiv 24 May 2024.

Builds on

3 of 68 references.

References · 3

  1. 2023Llama 2: Open Foundation and Fine-Tuned Chat Modelscited by 13,028
  2. 2023PaLM 2 Technical Reportcited by 1,162
  3. 2022GPT-3-driven pedagogical agents for training children's curious question-asking skillscited by 29

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 1; 2026: 1.

2 papers.