Designing adaptive learning environments for continuing education: Stakeholders’ perspectives on indicators and interventions

IF 4.9 Q1 PSYCHOLOGY, EXPERIMENTAL Computers in human behavior reports Pub Date : 2024-12-01 DOI:10.1016/j.chbr.2024.100525
Yvonne M. Fromm , Dirk Ifenthaler
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Abstract

Adaptive learning environments (ALE) provide great potential for personalizing and supporting learning processes in continuing education (CE). However, valid frameworks for designing ALE for CE have been missing so far. For example, user-centered and empirically-based guidelines for selecting indicators (i.e., information about learners and their contexts that should be collected and analyzed by ALE) and interventions for personalizing and supporting learning processes have not been established yet. Therefore, this paper aims to develop a framework of indicators and interventions for ALE for CE by investigating the perspectives of different stakeholders (i.e., learners, CE specialists, and educational technology specialists). We first conducted an interview study (N = 37) to identify indicators for ALE for CE. Subsequently, we conducted focus group interviews (N = 19) and an online survey (N = 72) to specify and evaluate possible interventions. Several indicators related to internal (e.g., prior knowledge) and external (e.g., time available for learning) conditions of learning as well as corresponding interventions (e.g., adaptation of the general difficulty level and thematic focus, recommendation of timely suitable learning resources) were identified. We developed a framework classifying interventions based on indicators and adaptivity type and providing evaluations of learners’ willingness to use these interventions, perceived learning support, and implementation effort. This framework can be used by researchers, system designers, as well as CE and educational technology specialists to design and implement user-centered and trustworthy ALE for CE.
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为继续教育设计适应性学习环境:利益相关者对指标和干预措施的看法
适应性学习环境(ALE)为继续教育(CE)的个性化和支持性学习过程提供了巨大的潜力。然而,到目前为止,还没有为CE设计ALE的有效框架。例如,尚未建立以用户为中心和以经验为基础的选择指标准则(即由ALE收集和分析的关于学习者及其背景的信息)以及个性化和支持学习过程的干预措施。因此,本文旨在通过调查不同利益相关者(即学习者、CE专家和教育技术专家)的观点,为CE的ALE制定一个指标和干预措施框架。我们首先进行了一项访谈研究(N = 37),以确定ALE对CE的指标。随后,我们进行了焦点小组访谈(N = 19)和在线调查(N = 72),以指定和评估可能的干预措施。确定了与学习的内部(例如,先验知识)和外部(例如,可用于学习的时间)条件以及相应的干预措施(例如,对一般难度水平和主题重点的适应,及时推荐合适的学习资源)相关的几个指标。我们开发了一个框架,根据指标和适应性类型对干预措施进行分类,并对学习者使用这些干预措施的意愿、感知到的学习支持和实施努力进行评估。研究人员、系统设计师以及CE和教育技术专家可以使用该框架为CE设计和实现以用户为中心且值得信赖的ALE。
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