The potential of learning from erroneous models: comparing three types of model instruction

Wijnen, Frances M.; Mulder, Yvonne G.; Alessi, Stephen M.; Bollen, Lars

doi:10.1002/sdr.1546

Cited by 8 publications

(3 citation statements)

References 48 publications

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“…found that participants described personalized care as a critical factor that shaped their positive prenatal care experiences (36). Finally, the model could be adapted to become a teaching tool for health professionals that care for patients experiencing diabetes or impaired glucose tolerance (37).…”

Section: Discussionmentioning

confidence: 99%

Modeling Insulin and Glucose Dynamics and Metabolic Adaptions During Pregnancy under Two Testing Conditions: Oral Glucose Tolerance Test and Hyperinsulinemic-Euglycemic Clamp

Calancie,

Jalali,

Akhavan

et al. 2024

Preprint

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Background Maternal metabolism has important short- and long-term implications for mothers and their infants. Elevated levels of circulating maternal glucose and insulin are associated with large for gestational age infants and increased neonatal adiposity, both of which can have negative health effects. Assessing maternal glucose and insulin dynamics during pregnancy is important for identifying women in need of intervention and has the potential for informing personalized prenatal care. Methods We developed a novel system dynamics simulation model that estimates plasma insulin and glucose levels in early (12–16 weeks) and late (34–36 weeks) pregnancy under two clinical testing conditions: a 3-hour 75g fasted oral glucose tolerance test, and 3-hr fasted hyperinsulinemic-euglycemic clamp conditions. Results Model output closely resembled research data collected from 28 racially and ethnically diverse participants at both time points (e.g., OGTT glucose R2 in early pregnancy: 0.97, OGTT insulin R2 in early pregnancy: 0.98). The late pregnancy model includes five known metabolic adaptations that occur over the course of gestation, which contribute to the development of maternal insulin resistance. This physiologic insulin resistance in pregnancy facilitates nutrient availability to support fetal growth as gestation progresses. Conclusion This study is an initial step toward developing a personalized tool for monitoring maternal glucose dynamics to improve prenatal care, especially for pregnancies complicated by obesity and/or GDM. The novel simulation model shows how a combination of metabolic adaptations during pregnancy can explain the observed development of insulin resistance the occurs between early to late pregnancy. We included key delays in insulin action, an innovative approach to model glucose intake during an OGTT, and used several testing conditions to inform and validate the model. The model output aligned with plasma insulin and glucose in early and late pregnancy among participants (N = 28) under measured OGTT and simulated hyperinsulinemic-euglycemic clamp conditions.

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Section: Discussionmentioning

confidence: 99%

Modeling Insulin and Glucose Dynamics and Metabolic Adaptions During Pregnancy under Two Testing Conditions: Oral Glucose Tolerance Test and Hyperinsulinemic-Euglycemic Clamp

Calancie,

Jalali,

Akhavan

et al. 2024

Preprint

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show abstract

“…Various strategies support this idea of model progression. These include strategies such as learners exploring a full working model [prior exploration ], receiving support in the form of a partial model which outlined the basic structure of a system [partially worked-out models (Mulder et al 2016)], and learners working with a model which contained errors [learning from erroneous models (Wijnen et al 2015)].…”

Section: Model Progression Of Activitiesmentioning

confidence: 99%

VeriSIM: A model-based learning pedagogy for fostering software design evaluation skills in computer science undergraduates

Prasad

Iyer

2022

RPTEL

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Evaluating a software design is an important practice of expert software designers. They spend significant time evaluating their solution, by developing an integrated mental model of the software design and the requirements. However, sufficient emphasis has not been given on teaching and learning of evaluation practices in software design courses, and hence, graduating students find it difficult to critically analyse an existing design and improve upon it. In this paper, we describe a model-based learning pedagogy for teaching–learning of software design evaluation. Model-based learning has been extensively used in science education and entails helping students construct, refine, revise, evaluate, and validate scientific models. We argue that modelling practices in software design evaluation are analogous to these practices. We adapted the model-based learning paradigm and operationalised it into a technology-enhanced learning environment (TELE) for fostering software design evaluation skills in computer science undergraduates. We conducted a research study with 22 undergraduate students to explore how the TELE and its features help students effectively evaluate a given software design. Students attempted a pre-test and post-test which asked them to identify defects in the design. We used the content analysis method to identify categories of defects from student responses in the pre-test and post-test. We also analysed student interaction logs and conducted focus group interviews to identify how features in the TELE contributed towards student learning. Findings from the study showed that students’ understanding of evaluation improved, from merely adding new functionalities and requirements, to a process which involved identifying alternate scenarios in the design which violate the given requirements. Students perceived that pedagogical features of the TELE were useful in helping them effectively evaluate software designs. Findings from the study provide evidence for the model-based learning paradigm as an appropriate pedagogy for software design and also opens the space for researchers to investigate model-based learning in other aspects of software design, such as designs of different types and varying complexities.

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“…Wijnen et al . () have conducted experiments concerning learning from erroneous models. Particular attention has been devoted to the so‐called stock‐and‐flow error, i.e.…”

Section: Introductionmentioning

confidence: 99%

A competence development framework for learning and teaching system dynamics

Schaffernicht

Groesser

2016

Syst. Dyn. Rev.

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Current teaching and learning of system dynamics are based on materials derived from the expertise of masters. However, there is little explicit reference to neither the stages which beginners go through to become proficient nor what is learned at each of these stages. We argue that this hinders cumulative research and development in teaching and learning strategies. We engaged 15 acknowledged masters in the field to take part in a three-round Delphi study to develop an operational representation of the competence development stages and what is learned at each stage. The resulting system dynamics competence framework consists of a qualified, expertevaluated, empirically based set of seven skills and 265 learning outcomes. The skills provide a common orientation, in the language of current educational research, to facilitate research, course design and certification efforts to ensure quality standards. To conclude, this paper provides avenues for future work.

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The potential of learning from erroneous models: comparing three types of model instruction

Cited by 8 publications

References 48 publications

Modeling Insulin and Glucose Dynamics and Metabolic Adaptions During Pregnancy under Two Testing Conditions: Oral Glucose Tolerance Test and Hyperinsulinemic-Euglycemic Clamp

Modeling Insulin and Glucose Dynamics and Metabolic Adaptions During Pregnancy under Two Testing Conditions: Oral Glucose Tolerance Test and Hyperinsulinemic-Euglycemic Clamp

VeriSIM: A model-based learning pedagogy for fostering software design evaluation skills in computer science undergraduates

A competence development framework for learning and teaching system dynamics

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