The Effect of Informing Agency in Self-Directed Online Learning Environments

Benjamin Xie, Greg L. Nelson, Harshitha Akkaraju, William Kwok, Amy J. Ko
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引用次数: 7

Abstract

Choices learners make when navigating a self-directed online learning tool can impact the effectiveness of the experience. But these tools often do not afford learners the agency or the information to make decisions beneficial to their learning. We evaluated the effect of varying levels of information and agency in a self-directed environment designed to teach programming. We investigated three design alternatives: informed high-agency, informed low-agency, and less informed high-agency. To investigate the effect of these alternatives on learning, we conducted a study with 79 novice programmers. Our results indicated that increased agency and information may have translated to more motivation, but not improved learning. Qualitative results suggest this was due to the burden that agency and information placed on decision-making. We interpret our results in relation to informing the design of self-directed online tools for learner agency.
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自主在线学习环境中通知代理的作用
学习者在使用自主在线学习工具时所做的选择会影响学习体验的有效性。但是这些工具通常不能为学习者提供做出有利于他们学习的决定的代理或信息。我们评估了在设计用于编程教学的自我导向环境中不同程度的信息和代理的效果。我们调查了三种设计方案:知情的高代理、知情的低代理和不太知情的高代理。为了调查这些选择对学习的影响,我们对79名新手程序员进行了一项研究。我们的研究结果表明,增加的代理和信息可能转化为更多的动机,但不是提高学习。定性结果表明,这是由于机构和信息对决策造成了负担。我们解释了我们的研究结果,为学习者代理的自主在线工具的设计提供了信息。
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Trust, Sustainability and [email protected] L@S'22: Ninth ACM Conference on Learning @ Scale, New York City, NY, USA, June 1 - 3, 2022 L@S'21: Eighth ACM Conference on Learning @ Scale, Virtual Event, Germany, June 22-25, 2021 Leveraging Book Indexes for Automatic Extraction of Concepts in MOOCs Evaluating Bayesian Knowledge Tracing for Estimating Learner Proficiency and Guiding Learner Behavior
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