Human-centred learning analytics: Four challenges in realising the potential

Roberto Martínez-Maldonado
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Abstract

The notion of Human-Centred Learning Analytics (HCLA) is gaining traction as educators and learning analytics (LA) researchers recognise the need to align analytics and artificial intelligence (AI) technologies with specific educational contexts. This has led an increasing number of researchers to adopt approaches, such as co-design and participatory design, to include educators and students as active participants in the LA design process. However, some experts contend that HCLA must go beyond stakeholder participation by also focusing on the safety, reliability, and trustworthiness of the analytics, and balancing human control and algorithmic automation. While the adoption of human-centred design (HCD) approaches promises considerable benefits, implementing these practices in data-intensive educational systems may not be straightforward. This paper emphasises the critical need to address specific ethical, technical, and methodological challenges tied to educational and data contexts, in order to effectively apply HCD in the creation of LA systems. We delve into four key challenges in this context: i) ensuring representative participation; ii) considering expertise and lived experiences in LA design; iii) balancing stakeholder input with technological innovation; and iv) navigating power dynamics and decision-making processes. LIFT Learning: Engage further with the author and the challenges faced when adopting human-centered approaches in learning analytics at the companion LIFT Learning site. The author will be hosting a live webinar on Tuesday 12 September 2023 at 6-7pm AEST (8-9am UTC). Visit the LIFT Learning site at https://apps.lift.c3l.ai/learning/course/coursev1:LEARNINGLETTERS+0106+2023 to sign up for your free ticket to this event. If you are unable to attend the webinar live, then the recording will be made available on this same site shortly afterwards.
以人为本的学习分析:实现潜力的四大挑战
随着教育工作者和学习分析(LA)研究人员认识到需要将分析和人工智能(AI)技术与特定的教育环境相结合,以人为中心的学习分析(HCLA)的概念正在获得关注。这使得越来越多的研究人员采用共同设计和参与式设计等方法,将教育工作者和学生作为洛杉矶设计过程的积极参与者。然而,一些专家认为,HCLA必须超越利益相关者的参与,还必须关注分析的安全性、可靠性和可信度,并平衡人工控制和算法自动化。虽然采用以人为本的设计(HCD)方法有望带来相当大的好处,但在数据密集型教育系统中实施这些做法可能并不简单。本文强调了解决与教育和数据背景相关的特定伦理、技术和方法挑战的关键需求,以便在LA系统的创建中有效地应用HCD。在此背景下,我们深入研究了四个关键挑战:i)确保代表参与;ii)考虑洛杉矶设计的专业知识和生活经验;Iii)平衡利益相关者投入与技术创新;第四,引导权力动态和决策过程。LIFT学习:与作者进一步接触,并在LIFT学习网站上采用以人为中心的学习分析方法时所面临的挑战。作者将于2023年9月12日星期二美国东部时间晚上6-7点(UTC时间上午8-9点)主持现场网络研讨会。访问LIFT学习网站https://apps.lift.c3l.ai/learning/course/coursev1:LEARNINGLETTERS+0106+2023,注册获得免费入场券。如果您无法现场参加网络研讨会,那么录音将在不久之后在同一网站上提供。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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