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Short online cross-disciplinary mini-course of themed modeling assignments for building systems thinking

Design · All designs
Evidence · 2 claims (2 for) · 1 study (1 design), q2 · 0 of 1 report an effect size · 2 claims rest on one study

Description

This pattern is a short, cross-disciplinary online learning sequence in which learners complete a small set of themed assignments and produce conceptual models. In the article, participants "performed four food-related learning assignments and created conceptual models in Object-Process Methodology", and their "responses to online assignments were analyzed along with their perceptions, captured via a reflection questionnaire". The pattern combines domain content (food), modeling practice, and reflective self-report, and is designed so that systems thinking basics can be developed in less than one semester.

Design Implications

Context

Requirements

  • Assignments must be cross-disciplinary and require creating conceptual models in a shared modeling language.

Constraints

  • Evidence reported is for engineering students and engineering and science teachers in an online format; scope beyond these populations is not established in the supplied text.

Target Learners

  • engineering students
  • engineering and science teachers

Learning Goals

  • systems thinking
  • conceptual modeling skills

Claims

Examples

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Key Sources

  • Peretz, R., Tal, M., Akiri, E., Dori, D., & Dori, Y. J. (2023). Fostering engineering and science students' and teachers' systems thinking and conceptual modeling skills. Instructional Science, 51, 509–543. https://doi.org/10.1007/s11251-023-09625-9
Page metadata
Field Value
type design
id cross-disciplinary-online-modeling-assignment-sequence
title Short online cross-disciplinary mini-course of themed modeling assignments for building systems thinking
description This pattern is a short, cross-disciplinary online learning sequence in which learners complete a small set of themed assignments and produce conceptual models.
status review
generated by process:settle-candidates on 2026-10-18
trust unverified — no one has confirmed this page's content
sources 1 — peretz-2023

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