Framework to support personalized learning in complex systems

Abstract

Purpose Numerous studies document that students struggle to comprehend complex dynamic systems (CDS). The purpose of this paper is to describe a design framework applied to the creation of a personalized and adaptive online interactive learning environment (OILE) to support students in their study of CDS. Design/methodology/approach A holistic instructional design is applied in five steps to create the OILE. The OILE has the following characteristics: first, it presents a complex, dynamic problem that learners should address in its entirety. It then allows learners to progress through a sequence of learning tasks from easy to complex. Second, after completion of each learning task, the OILE provides learners with supportive information based on their individual performance. The support fades away as learners gain expertise. Third, the OILE tracks and collects information on learners’ progress and generates learning analytics. The OILE was tested on 57 system dynamics students. Findings This paper provides evidence that supports the theoretical design framework from the literature. It also provides a sample from students’ progress logs to demonstrate how the OILE practically facilitated students’ cognitive development. In addition, it provides empirical evidence regarding students’ attitudes toward the OILE that was obtained from administering two questionnaires. Originality/value In light of supportive evidence from the literature, students’ progress in the cognitive domain, and confirmative response in the affective domain, the use of personalized and adaptive OILE to support learning about CDS is considered promising.

Supporting Student System Modelling Practice Through Curriculum and Technology Design

“…These include identifying the components of the system and the relationships between them, iteratively developing the structure of the models by adding detail as needed, comparing simulated with real behaviour, and iteratively testing and validating the model. Students face many challenges in thinking about complex dynamic systems (Stratford et al, 1998;Tadesse & Davidsen, 2020), and there has long been hope within the SD community for new tools to introduce these challenging ideas to an audience not as constrained by age and ability (Gould-Kreutzer, 1993).…”

COVID-19 and Financial Sustainability of Academic Institutions

“…The framework developed in this article can be turned into a system-dynamics based interactive learning environment, SDILE, which is a tool for improving decision making in dynamic tasks [58]. It can also be part of a personalized and adaptive online interactive learning environment, OILE, [59] used during an institutional planning process. By interacting with such learning environments, individuals can improve structural knowledge, decision heuristics, and decision time leading to better strategies [59,60].…”

“…It can also be part of a personalized and adaptive online interactive learning environment, OILE, [59] used during an institutional planning process. By interacting with such learning environments, individuals can improve structural knowledge, decision heuristics, and decision time leading to better strategies [59,60]. To improve their efficacy, such decision support systems can be combined with prior exploration [61] and debriefing [62][63][64].…”

Will colleges survive the storm of declining enrollments? A computational model

“…The computational model can also provide value as part of an interactive learning environment that can help with dynamic decision making [ 70 ]. System-based learning and planning environments can improve performance and decision-making on several scales including decision heuristics, structural knowledge, decision time and decision strategy [ 71 , 72 ], especially when combined with prior exploration [ 73 ] and debriefing [ 74 – 77 ].…”