人工智能的学习与发展:系统的文献综述

IF 2.3 Q3 MANAGEMENT
Parag K. Bhatt, Ashutosh Muduli
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引用次数: 4

摘要

目的探讨人工智能(AI)在学习与发展(L&D)功能中的应用。虽然有一些研究报告了人工智能和人员管理流程,但主要缺乏系统和结构化的研究,以评估人工智能与L&D的整合,重点关注范围、采用和影响因素。本研究旨在通过分析、设计、开发、实施和评估方法,探索与学习与开发相关的人工智能创新、人工智能在学习与开发过程中的作用、采用人工智能的优势以及导致基于人工智能的有效学习的因素。设计/方法/方法本研究采用了系统的文献综述方法,通过确定所涉及的广泛主题,批判性地分析、综合和绘制现有研究。审查方法包括确定时间范围、数据库选择、文章选择和文章分类。使用Emerald、Sage、Francis和Taylor等数据库,选取1996年至2022年间发表的81篇研究文章进行分析。研究结果表明,自然语言处理、人工神经网络、交互式语音响应、文本到语音、语音到文本、技术增强学习和机器人等人工智能创新可以提高L&D流程效率。我们可以通过促进学习模块的衔接,通过人脸识别和语音识别系统识别学习者,完成课程作业等来实现这一目标。此外,研究结果还表明,人工智能可以用于评估学习能力、测试学习者的记忆、跟踪学习进度、衡量学习效果、帮助学习者识别错误并建议纠正。最后,L&D专业人员可以使用AI来促进更快,更准确,更便宜的学习过程,适合大量的学习对象,灵活,高效,方便,对学习者来说更便宜。在缺乏人工智能在L&D功能方面的系统研究的情况下,本研究的结果可能为研究人员和从业者提供有用的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Artificial intelligence in learning and development: a systematic literature review
Purpose The presented research explored artificial intelligence (AI) application in the learning and development (L&D) function. Although a few studies reported AI and the people management processes, a systematic and structured study that evaluates the integration of AI with L&D focusing on scope, adoption and affecting factors is mainly absent. This study aims to explore L&D-related AI innovations, AI’s role in L&D processes, advantages of AI adoption and factors leading to effective AI-based learning following the analyse, design, develop, implement and evaluate approach. Design/methodology/approach The presented research has adopted a systematic literature review method to critically analyse, synthesise and map the extant research by identifying the broad themes involved. The review approach includes determining a time horizon, database selection, article selection and article classification. Databases from Emerald, Sage, Francis and Taylor, etc. were used, and the 81 research articles published between 1996 and 2022 were identified for analysis. Findings The result shows that AI innovations such as natural language processing, artificial neural networks, interactive voice response and text to speech, speech to text, technology-enhanced learning and robots can improve L&D process efficiency. One can achieve this by facilitating the articulation of learning module, identifying learners through face recognition and speech recognition systems, completing course work, etc. Further, the result also shows that AI can be adopted in evaluating learning aptitude, testing learners’ memory, tracking learning progress, measuring learning effectiveness, helping learners identify mistakes and suggesting corrections. Finally, L&D professionals can use AI to facilitate a quicker, more accurate and cheaper learning process, suitable for a large learning audience at a time, flexible, efficient, convenient and less expensive for learners. Originality/value In the absence of any systematic research on AI in L&D function, the result of this study may provide useful insights to researchers and practitioners.
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来源期刊
CiteScore
5.10
自引率
13.60%
发文量
53
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