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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This contribution presents three lesson activities for lower secondary education that were developed to teach system thinking in concert with subject matter. The pedagogical approach is described, leading to a practical design philosophy for lesson activities using qualitative representations. These representations allow for capturing basic qualitative notions, such as the entities that constitute the system, their changeable features referred to as quantities, and cause-effect relations that propagate changes between these quantities.
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The methodology of biomimicry design thinking is based on and builds upon the overarching patterns that all life abides by. “Cultivating cooperative relationships” within an ecosystem is one such pattern we as humans can learn from to nurture our own mutualistic and symbiotic relationships. While form and process translations from biology to design have proven accessible by students learning biomimicry, the realm of translating biological functions in a systematic approach has proven to be more difficult. This study examines how higher education students can approach the gap that many companies in transition are struggling with today; that of thinking within the closed loops of their own ecosystem, to do good without damaging the system itself. Design students should be able to assess and advise on product design choices within such systems after graduation. We know when tackling a design challenge, teams have difficulties sifting through the mass of information they encounter, and many obstacles are encountered by students and their professional clients when trying to implement systems thinking into their design process. While biomimicry offers guidelines and methodology, there is insufficient research on complex, systems-level problem solving that systems thinking biomimicry requires. This study looks at factors found in course exercises, through student surveys and interviews that helped (novice) professionals initiate systems thinking methods as part of their strategy. The steps found in this research show characteristics from student responses and matching educational steps which enabled them to develop their own approach to challenges in a systems thinking manner. Experiences from the 2022 cohort of the semester “Design with Nature” within the Industrial Design Engineering program at The Hague University of Applied Sciences in the Netherlands have shown that the mixing and matching of connected biological design strategies to understand integrating functions and relationships within a human system is a promising first step. Stevens LL, Whitehead C, Singhal A. Cultivating Cooperative Relationships: Identifying Learning Gaps When Teaching Students Systems Thinking Biomimicry. Biomimetics. 2022; 7(4):184. https://doi.org/10.3390/biomimetics7040184
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The potential for Artificial Intelligence is widely proclaimed. Yet, in everyday educational settings the use of this technology is limited. Particularly, if we consider smart systems that actually interact with learners in a knowledgeable way and as such support the learning process. It illustrates the fact that teaching professionally is a complex challenge that is beyond the capabilities of current autonomous robots. On the other hand, dedicated forms of Artificial Intelligence can be very good at certain things. For example, computers are excellent chess players and automated route planners easily outperform humans. To deploy this potential, experts argue for a hybrid approach in which humans and smart systems collaboratively accomplish goals. How to realize this for education? What does it entail in practice? In this contribution, we investigate the idea of a hybrid approach in secondary education. As a case-study, we focus on learners acquiring systems thinking skills and our recently for this purpose developed pedagogical approach. Particularly, we discuss the kind of Artificial Intelligence that is needed in this situation, as well as which tasks the software can perform well and which tasks are better, or necessarily, left with the teacher.
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We developed a lesson where students construct a qualitative representation to learn how clock genes are regulated. Qualitative representations provide a non-numerical description of system behavior, focusing on causal relation-ships and system states. They align with human reasoning about system dy-namics and serve as valuable learning tools for understanding both domain-specific systems and developing broader systems thinking skills.The lesson, designed for upper secondary and higher education, is imple-mented in the DynaLearn software at Level 4, where students can model feedback loops. Students construct the representation step by step, guided by a structured workbook and built-in support functions within the software. At each step, they run simulations to examine system behavior and reflect on the results through workbook questions. To ensure scientific accuracy, the representation and workbook were evaluated by domain experts.The lesson begins with modeling how increasing BMAL:CLOCK activity enhances the transcription of PER and CRY genes through binding to the E-box. Next, students explore how mRNA production and degradation—two opposing processes—regulate mRNA levels. This is followed by modeling translation at the ribosomes, where PER and CRY proteins are synthesized and subsequently degraded, again illustrating competing regulatory process-es. Students then model how PER and CRY proteins form a complex that translocates to the nucleus, inhibiting CLOCK:BMAL binding and establish-ing a negative feedback loop. Finally, they extend their understanding by ex-ploring how CLOCK:BMAL also regulates the AVP gene, linking clock genes to broader physiological processes.
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Clinical decision support systems (CDSSs) have gained prominence in health care, aiding professionals in decision-making and improving patient outcomes. While physicians often use CDSSs for diagnosis and treatment optimization, nurses rely on these systems for tasks such as patient monitoring, prioritization, and care planning. In nursing practice, CDSSs can assist with timely detection of clinical deterioration, support infection control, and streamline care documentation. Despite their potential, the adoption and use of CDSSs by nurses face diverse challenges. Barriers such as alarm fatigue, limited usability, lack of integration with workflows, and insufficient training continue to undermine effective implementation. In contrast to the relatively extensive body of research on CDSS use by physicians, studies focusing on nurses remain limited, leaving a gap in understanding the unique facilitators and barriers they encounter. This study aimed to explore the facilitators and barriers influencing the adoption and use of CDSSs by nurses in hospitals, using an extended Fit Between Individuals, Tasks, and Technology (FITT) framework.
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We have developed a pedagogical approach wherein learners acquire systems thinking skills and content knowledge by constructing qualitative representations. In this paper, we focus on how learners learn about the biological mechanisms of calcium regulation by constructing such a representation, how they interact with the software, and the effect on learning outcomes. The software contains various functionalities to support learners, and a workbook guides them through the process. Cluster analysis of learners’ use of the software categorizes them into three styles, which we have labelled: exploratory, comprehensive, and efficient. Learning outcomes are evaluated through pre- and post-tests and show overall improvement on systems thinking skills and content knowledge. No significant differences in outcome are observed between the interaction styles of learners. This implies that constructing qualitative representations effectively increases learners’ systems thinking skills and understanding of calcium regulation, regardless of their interaction style.
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Background: A paradigm shift in health care from illness to wellbeing requires new assessment technologies and intervention strategies. Self-monitoring tools based on the Experience Sampling Method (ESM) might provide a solution. They enable patients to monitor both vulnerability and resilience in daily life. Although ESM solutions are extensively used in research, a translation from science into daily clinical practice is needed. Objective: To investigate the redesign process of an existing platform for ESM data collection for detailed functional analysis and disease management used by psychological assistants to the general practitioner (PAGPs) in family medicine. Methods: The experience-sampling platform was reconceptualized according to the design thinking framework in three phases. PAGPs were closely involved in co-creation sessions. In the ‘understand’ phase, knowledge about end-users’ characteristics and current eHealth use was collected (nominal group technique – 2 sessions with N = 15). In the ‘explore’ phase, the key needs concerning the platform content and functionalities were evaluated and prioritized (empathy mapping – 1 session with N = 5, moderated user testing – 1 session with N = 4). In the ‘materialize’ phase, the adjusted version of the platform was tested in daily clinical practice (4 months with N = 4). The whole process was extensively logged, analyzed using content analysis, and discussed with an interprofessional project group. Results: In the ‘understand’ phase, PAGPs emphasized the variability in symptoms reported by patients. Therefore, moment-to-moment assessment of mood and behavior in a daily life context could be valuable. In the ‘explore’ phase, (motivational) functionalities, technological performance and instructions turned out to be important user requirements and could be improved. In the ‘materialize’ phase, PAGPs encountered barriers to implement the experience-sampling platform. They were insufficiently facilitated by the regional primary care group and general practitioners. Conclusion: The redesign process in co-creation yielded meaningful insights into the needs, desires and daily routines in family medicine. Severe barriers were encountered related to the use and uptake of the experience-sampling platform in settings where health care professionals lack the time, knowledge and skills. Future research should focus on the applicability of this platform in family medicine and incorporate patient experiences.
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Having learners (K7–10) acquire system thinking skills is challenging. Together with teachers we deploy qualitative representations of complex systems to enable this learning process. Teachers select their own topics for their leaners to work on which makes that lessons vary in content depending on the teacher’s preference. Within this setting we face the challenge of adequately coaching learners while they create their knowledge models. For this, we use norm-model based feedback, ignoring learner specific information. Here we report the working and effectiveness of this approach.
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Background: Peer review is at the heart of the scientific process. With the advent of digitisation, journals started to offer electronic articles or publishing online only. A new philosophy regarding the peer review process found its way into academia: the open peer review. Open peer review as practiced by BioMed Central (BMC) is a type of peer review where the names of authors and reviewers are disclosed and reviewer comments are published alongside the article. A number of articles have been published to assess peer reviews using quantitative research. However, no studies exist that used qualitative methods to analyse the content of reviewers’ comments. Methods: A focused mapping review and synthesis (FMRS) was undertaken of manuscripts reporting qualitative research submitted to BMC open access journals from 1 January – 31 March 2018. Free-text reviewer comments were extracted from peer review reports using a 77-item classification system organised according to three key dimensions that represented common themes and sub-themes. A two stage analysis process was employed. First, frequency counts were undertaken that allowed revealing patterns across themes/sub-themes. Second, thematic analysis was conducted on selected themes of the narrative portion of reviewer reports. Results: A total of 107 manuscripts submitted to nine open-access journals were included in the FMRS. The frequency analysis revealed that among the 30 most frequently employed themes “writing criteria” (dimension II) is the top ranking theme, followed by comments in relation to the “methods” (dimension I). Besides that, some results suggest an underlying quantitative mindset of reviewers. Results are compared and contrasted in relation to established reporting guidelines for qualitative research to inform reviewers and authors of frequent feedback offered to enhance the quality of manuscripts. Conclusions: This FMRS has highlighted some important issues that hold lessons for authors, reviewers and editors. We suggest modifying the current reporting guidelines by including a further item called “Degree of data transformation” to prompt authors and reviewers to make a judgment about the appropriateness of the degree of data transformation in relation to the chosen analysis method. Besides, we suggest that completion of a reporting checklist on submission becomes a requirement.
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