Systems thinking is a complex skill for learners in secondary education. We argue that qualitative representations can be valuable tools to actively engage in learning this skill. However, the effectiveness of these tools is currently hampered by complexity and the lack of instructional embedding. In this contribution, we present our developments on scaffolds for learning, instructional formats, and automated support in order to unleash the potential of qualitative representations for secondary education.
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We developed an application which allows learners to construct qualitative representations of dynamic systems to aid them in learning subject content knowledge and system thinking skills simultaneously. Within this application, we implemented a lightweight support function which automatically generates help from a norm-representation to aid learners as they construct these qualitative representations. This support can be expected to improve learning. Using this function it is not necessary to define in advance possible errors that learners may make and the subsequent feedback. Also, no data from (previous) learners is required. Such a lightweight support function is ideal for situations where lessons are designed for a wide variety of topics for small groups of learners. Here, we report on the use and impact of this support function in two lessons: Star Formation and Neolithic Age. A total of 63 ninth-grade learners from secondary school participated. The study used a pretest/intervention/post-test design with two conditions (no support vs. support) for both lessons. Learners with access to the support create better representations, learn more subject content knowledge, and improve their system thinking skills. Learners use the support throughout the lessons, more often than they would use support from the teacher. We also found no evidence for misuse, i.e., 'gaming the system', of the support function.
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In this paper, we discuss the pedagogical approach of two lessons that are aimed at learning domain knowledge and systems thinking simultaneously using qualitative representations. Next to understanding basic cause-effect relationships, these lessons focus on the notion that systems can move through different states of behavior. An additional focus concerns system boundaries and distinguishing between what is part-of and not part-of a system.
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