学习仪表盘个性化设计研究

Research on Personalized Design of Learning Analytics Dashboard

作为"数据驱动教学"的核心,学习仪表盘适用于具有差异的学习者,须解决数据呈现的共性与个性之间的矛盾。研究围绕学习仪表盘的个性化设计展开探索,旨在提供核心指标的基础上,为不同人格偏好学习者呈现个性化的指标。利用"模式识别技术"判定学习者人格特质,基于复制自适应方式建立静态区域与自适应区域,设计了包含"数据指标"以及"前置工具"的自适应呈现内容。设计原型的感知比较验证了设计的合理性;学习行为水平以及成绩的准实验研究表明,学习仪表盘通过恰当的呈现方式放大学习者的感知,从而提升了特定的行为表现;通过推送匹配人格特质的数据指标强化了使用动机,从而助力学习目标的达成。

Learning Analytics Dashboard （LAD）, the core of data-driven instruction, is suitable for learners with different characteristics, and needs to solve the conflict between university and individuality presented by data. This study focuses on the individualized design of LAD and aims to present personalized indicators for learners with different personalities through providing the core indicators. This study uses ＂pattern recognition technology＂ to judge learners＂ personalities, establishes a static region and an adaptive region on based on the replication of the adaptive, and designs adaptive contents including ＂data indicators＂ and ＂front tools＂. The perceptual comparison of the design prototype verifies its rationality. The quasi-experimental study of learning behavior level and exam results show that LAD magnifies learners＂ perceptions through appropriate presentation, and enhances their specific behaviors. By pushing the data matching learners＂ personalities, their motivations are strengthened, which is good for the achievement of learning goals.