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Where is the Learning in Learning Analytics? A Systematic Literature Review on the Operationalization of Learning-Related Constructs in the Evaluation of Learning Analytics Interventions
IEEE Transactions on Learning Technologies ( IF 2.9 ) Pub Date : 2020-06-04 , DOI: 10.1109/tlt.2020.2999970
Justian Knobbout , Esther Van Der Stappen

Learning technologies enable interventions in the learning process aiming to improve learning. Learning analytics provides such interventions based on analysis of learner data, which are believed to have beneficial effects on both learning and the learning environment. Literature reporting on the effects of learning analytics interventions on learning allows us to assess in what way learning analytics improves learning. No standard set of operational definitions for learning affected by learning analytics interventions is available. We performed a systematic literature review of 1932 search hits, which yielded 62 key studies. We analyzed how affected learning was operationalized in these key studies and classified operational definitions into three categories: 1) learning environment ; 2) learning process; and 3) learning outcome . A deepening analysis yielded a refined classification scheme with 11 subcategories. Most of the analyzed studies relate to either learning outcome or learning process . Only nine of the key studies relate to more than one category. Given the complex nature of applying learning analytics interventions in practice, measuring the effects on a wider spectrum of aspects can give more insight into the workings of learning analytics interventions on the different actors, processes, and outcomes involved. Based on the results of our review, we recommend making deliberate decisions on the (multiple) aspects of learning one tries to improve by applying learning analytics. Our refined classification with examples of operational definitions may help both academics and practitioners doing so, as it allows for a more structured, grounded, and comparable positioning of learning analytics benefits.

中文翻译:

学习分析中的学习在哪里?关于学习分析干预评估中与学习相关的结构的操作性的系统文献综述

学习技术使学习过程中的干预措施得以改善。学习分析基于对学习者数据的分析来提供此类干预措施,据认为这对学习和学习环境均具有有益的影响。有关学习分析干预对学习的影响的文献报告使我们能够评估学习分析以何种方式改善学习。没有受学习分析干预影响的用于学习的标准操作定义集。我们对1932个搜索结果进行了系统的文献综述,产生了62项关键研究。我们分析了在这些关键研究中如何对受影响的学习进行操作,并将操作定义分为三类:1)学习环境 ; 2)学习过程; 和3) 学习成果 。深入分析得出了包含11个子类别的精细分类方案。大部分分析的研究都与学习成果 要么 学习过程 。只有九项关键研究涉及多个类别。鉴于在实践中应用学习分析干预措施的复杂性,在更广泛的方面衡量影响可以更加深入地了解学习分析干预措施对不同参与者,流程和结果的影响。根据我们的审查结果,我们建议对学习的(多个)方面做出明智的决定,尝试通过应用学习分析来改善学习。我们使用操作定义示例进行的精细分类可以帮助学术界和从业人员这样做,因为它可以使学习分析的好处更有条理,更基础,更可比。
更新日期:2020-06-04
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