Advances in Artificial Intelligence (AI) and sensors are significantly impacting multiple areas, including education and workplaces. Following the PRISMA methodology, this review explores the current status of using AI to support the training and assessment of professionals. We examined 83 research papers, analyzing: (1) the targeted professionals, (2) the skills assessed, (3) the AI algorithms utilized, (4) the data and devices employed, (5) data fusion techniques utilized, (6) the architecture of the proposed platforms, (7) the management of ethics and privacy, and (8) validations of the proposals. The review highlights a trend in evaluating healthcare professionals (especially surgeons) motivated by the critical role of hands-on training in these professionals. Besides, the review reveals that data fusion techniques and certain technologies, like transfer learning and explainable AI, are not widely utilized despite their huge potential. Finally, the review underscores that most proposals remain within the research domain, lacking the integration and maturity needed for sustained use in real-world environments. Therefore, most of the proposals are not currently available to support the training of professionals. The insights of this review can guide researchers aiming to improve the training of professionals and, consequently, their education.

中文翻译：

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人工智能支持专业人员的培训和评估：系统文献综述


人工智能 （AI） 和传感器的进步正在对多个领域产生重大影响，包括教育和工作场所。遵循 PRISMA 方法，本综述探讨了使用 AI 支持专业人员培训和评估的现状。我们检查了 83 篇研究论文，分析了：（1） 目标专业人员，（2） 评估的技能，（3） 使用的 AI 算法，（4） 采用的数据和设备，（5） 使用的数据融合技术，（6） 拟议平台的架构，（7） 道德和隐私管理，以及 （8） 提案的验证。本综述强调了评估医疗保健专业人员（尤其是外科医生）的趋势，其动机是实践培训在这些专业人员中的关键作用。此外，审查显示，数据融合技术和某些技术，如迁移学习和可解释的人工智能，尽管具有巨大的潜力，但并未得到广泛利用。最后，该审查强调，大多数提案仍处于研究领域内，缺乏在实际环境中持续使用所需的集成和成熟度。因此，大多数提案目前无法支持专业人员的培训。本综述的见解可以指导旨在改善专业人员培训的研究人员，从而改善他们的教育。