ABSTRACT

This reflection considers issues for researchers who study open, flexible, and distance learning (OFDL) systems. In particular, human learning is regarded as an emergent phenomenon occurring in educational complex systems, which may be non-digital or digital in nature. It is suggested the term learning in OFDL, such as learning analytics and machine learning, refers to computational techniques that help identify patterns in large datasets generated in OFDL systems. It is also proposed that OFDL systems are examples of complex systems, and an overview is provided of a set of relevant complexity conceptual principles. Issues are considered about types of learning data in OFDL systems and their lack of suitability for assessing higher-level explanatory and procedural understandings. Finally, an example is provided to illustrate how complexity ideas may be used with LA techniques to study an OFDL research topic. Implications of complexity theorizing for OFDL research are also discussed.

摘要

这种思考为研究开放，灵活和远程学习（OFDL）系统的研究人员考虑了问题。特别地，人类学习被认为是在教育复杂系统中发生的一种新兴现象，其本质上可能是非数字的或数字的。建议学习一词OFDL中的“学习分析和机器学习”等术语是指有助于识别OFDL系统中生成的大型数据集中的模式的计算技术。还提出了OFDL系统是复杂系统的示例，并且提供了一组相关的复杂性概念原理的概述。考虑了有关OFDL系统中学习数据的类型以及它们不适合评估更高级别的解释性和程序性理解的问题。最后，提供了一个示例来说明如何将复杂性思想与洛杉矶技术一起用于研究OFDL研究主题。还讨论了复杂性理论对OFDL研究的意义。