Ray Anne E, Greene Kathryn, Pristavec Teja, Hecht Michael L, Miller-Day Michelle A, Banerjee Smita C
University of Kentucky.
Rutgers University.
Educ Technol Res Dev. 2020 Dec;68(6):3143-3163. doi: 10.1007/s11423-020-09813-1. Epub 2020 Aug 12.
Engagement is central to the effectiveness of online health messages and the related educational programs that aim to deliver these messages to the intended audience (Li, Won, Yang et al. 2019: Lin, Hung, Kinshuk et al. 2019). Drawing from health communication and social learning theories, the Theory of Active Involvement (TAI) (Greene, 2013) posits that an online prevention program's impact depends on how engaged participants are. In practice, measuring engagement in this context has relied primarily on self-report measures (e.g., Hamutoglu, Gemikonakli, Duman et al. 2019). However, the emergence and growth of online learning platforms to deliver health-specific information offers other options for assessing engagement. This includes program analytics that capture interaction with content and facilitate examination of patterns via multiple indicators such as responses to interactive questions and time spent in the program (Herodotou, Rienties, Boroowa, et al. 2019; Li, Wong, Yang et al. 2019; van Leeuwen, 2019). However, little is known about the relationships between these different indicators of engagement as it applies to health curricula. This study uses self-report, observational, and program analytic data collected on a small ( = 38) sample using REAL media, an online substance use prevention program, to examine relationships among various indicators of engagement. Findings suggest a cluster of indicators across the three modalities that provide a useful way of measuring engagement. A cluster centered around complexity suggests a separate factor to be considered when designing engaging interventions.
参与度对于在线健康信息以及旨在将这些信息传递给目标受众的相关教育项目的有效性至关重要(Li、Won、Yang等人,2019年;Lin、Hung、Kinshuk等人,2019年)。基于健康传播和社会学习理论,积极参与理论(TAI)(Greene,2013年)认为,在线预防项目的影响取决于参与者的参与程度。在实践中,在这种情况下衡量参与度主要依赖自我报告措施(例如,Hamutoglu、Gemikonakli、Duman等人,2019年)。然而,提供特定健康信息的在线学习平台的出现和发展为评估参与度提供了其他选择。这包括项目分析,它可以捕捉与内容的互动,并通过多个指标(如对互动问题的回答和在项目中花费的时间)促进对模式的检查(Herodotou、Rienties、Boroowa等人,2019年;Li、Wong、Yang等人,2019年;van Leeuwen,2019年)。然而,对于这些不同的参与度指标之间的关系,在应用于健康课程方面知之甚少。本研究使用通过一个在线预防药物使用项目REAL media收集的自我报告、观察和项目分析数据,该数据来自一个小样本(n = 38),以检验各种参与度指标之间的关系。研究结果表明,在这三种模式中有一组指标提供了一种衡量参与度的有用方法。围绕复杂性形成的一组指标表明,在设计引人入胜的干预措施时需要考虑一个单独的因素。