论文标题
Molam：移动多模式学习分析概念框架，以支持学生自我调节的学习
MOLAM: A Mobile Multimodal Learning Analytics Conceptual Framework to Support Student Self-Regulated Learning
论文作者
论文摘要
在线远程学习以学习者为中心，需要学习者的不同技能和能力，以及教学设计，学生支持和资源提供的替代方法。在线学习设置中的学习者自治和自我调节学习（SRL）被认为是预测学生绩效的关键成功因素。 SRL根据Zimmerman的规划，监视，行动和反思的过程包括。通常关注学习者的三个关键特征：（1）使用SRL策略，（2）对学习有效性的自我导向反馈的响应，以及（3）激励过程。 SRL已被确定为与学生成功的直接相关，包括成绩的提高以及相关技能和策略的发展。需要这样的技能和策略才能成为成功的终身学习者。本章介绍了一种移动多模式学习分析方法（MOLAM）。我认为，学生自我调节的学习的发展将从这种方法的采用中受益，并且其使用将允许在在线学习环境中持续测量和提供对学生SRL的时间支持。
Online distance learning is highly learner-centred, requiring different skills and competences from learners, as well as alternative approaches for instructional design, student support, and provision of resources. Learner autonomy and self-regulated learning (SRL) in online learning settings are considered key success factors that predict student performance. SRL comprises processes of planning, monitoring, action and reflection according to Zimmerman. And typically focuses on three key features of learners: (1) use of SRL strategies, (2) responsiveness to self-oriented feedback about learning effectiveness, and (3) motivational processes. SRL has been identified as having a direct correlation with students success, including improvements in grades and the development of relevant skills and strategies. Such skills and strategies are needed to become a successful lifelong learner. This chapter introduces a Mobile Multimodal Learning Analytics approach (MOLAM). I argue that the development of student Self-Regulated Learning would benefit from the adoption of this approach, and that its use would allow continuous measurement and provision of in-time support of student SRL in online learning contexts.
