A Function-Based Scoring Method for Evaluating Student Mental Models of Systems

2018 ◽  
Author(s):  
Jacob T. Nelson ◽  
Alexander R. Murphy ◽  
Julie S. Linsey ◽  
Matt R. Bohm ◽  
Robert L. Nagel
Keyword(s):  
Complex Systems ◽  
Mental Models ◽  
Systems Thinking ◽  
Functional Modules ◽  
Functional Modeling ◽  
Scoring Method ◽  
Student Responses ◽  
Holistic Thinking ◽  
Two Systems ◽  
Interactive Simulations

Mental models are loosely-defined constructs people form to reason and make predictions about their surroundings. These models are an important aspect of systems thinking for engineers, a concept that emphasizes holistic thinking when working with complex systems which is increasingly important in multiple engineering disciplines. Methods to evaluate systems thinking and mental models of systems traditionally rely on questionnaires, or detailed interactive simulations of specific processes. This work presents a method based on functional modules for evaluating student responses to an instrument based on Lawson’s bicycle problem, intended to elicit students’ mental models of two systems. Students were given a simple outline of the two systems, a hair dryer and a car radiator, and were prompted to fill and label the components required for the system to fulfil the functionality described. This was done in two sessions, once before learning functional modeling, and once after, to utilize the method of scoring to evaluate any changes in their mental models due to exposure to functional modeling. The scoring method identifies common functional modules between two systems using Module Heuristics, and then identifies students’ recognition of those modules. This allows a direct comparison of the functional similarity between the two systems identified by the students and can capture a wider variety of correct answers than simply counting the components a student provides.

scholarly journals A bridge to systems thinking in engineering design: An examination of students’ ability to identify functions at varying levels of abstraction

2017 ◽  
Vol 31 (4) ◽  
pp. 535-549 ◽  
Author(s):  
Megan Tomko ◽  
Jacob Nelson ◽  
Robert L. Nagel ◽  
Matthew Bohm ◽  
Julie Linsey
Keyword(s):  
Systems Thinking ◽  
Functional Modeling ◽  
Levels Of Abstraction ◽  
Student Responses ◽  
Abstract Function ◽  
Low Level ◽  
Level Function ◽  
High Level ◽  
And Function ◽  
Systems Thinking Approach

AbstractThis paper aims to situate functional abstraction in light of systems thinking. While function does not extensively appear in systems thinking literature, the literature does identify function as part of systems thinking that enables us to recognize and connect that function has a role in building a systems thinking approach for students. A systems thinking approach is valuable for students since it helps them view a system holistically. In this research, we measure how well students are able to abstract function. We asked students to generate functions for two different products and examined how students taught functional modeling and function enumeration compare to students who are only taught function enumeration. The student responses were examined using a rubric that we developed and validated for assessing function. This rubric may be used to classify functions by correctness (correct, partially correct, and incorrect) and categories (high level, interface, low level, and ambiguous). On questions where students were not explicitly asked to write a high-level function or low-level function, and so on, students who were taught functional modeling were able to better demonstrate systems thinking in their responses (low-level and interface functions) than those students who were only taught function enumeration.

scholarly journals A review of the complexity approach to the study human (society)-nature interactions

2010 ◽  
Vol 90 (2) ◽  
pp. 109-137 ◽  
Author(s):  
Dragana Miljanovic
Keyword(s):  
Complex Systems ◽  
Complexity Theory ◽  
Complex Dynamics ◽  
Traditional Approach ◽  
Human Society ◽  
Natural Systems ◽  
Two Systems

Traditional approach to the study of society-nature interactions based on reductionism and linear causality is no longer fully capable of explaining complex dynamics of integrated socio-economic and natural systems. For this reason demands for complexity theory is growing. Understanding interactions between society and nature, human and their environment must come from the examination of how the two systems operate together, and not from examination of those systems themselves in isolation. Since our geographical community is not familiar enough with complexity theory, first part of article is devoted to outlining shift from reductionism to holism and complexity theory. In the second part, features of complex systems as it is human (society)-environment system are discussed. .

scholarly journals FOUNDATIONS OF cHINESE SYSTEMS SCIENCE

2021 ◽  
Author(s):  
Hans Kuijper
Keyword(s):  
Complex Systems ◽  
Systems Thinking ◽  
Systems Science ◽  
Ancient China ◽  
Complex Systems Thinking

The fast developments of (complex) systems thinking cannot be understood without taking the cultural and philosophical context into consideration. In this article, An attempt is made to explain the foundation of thriving CHINESE systems thinking, because China seems to fully undertand the significance and importance of thinking (and engineering) systemically. The conclusion of the paper is two-pronged: (a) the Chinese have been system thinkers (or pattern seekers) from the very beginning of their turbulent history and (B) Western system thinkers, who disagree with each other on many fronts, could, nay should learn something from ancient China, particularly from that amazing, almost forgotten classical book called the Yijing, a book about systems science in a nutshell.

Complex Adaptive Systems Thinking Approach to Enterprise Architecture

2016 ◽  
pp. 339-389
Author(s):  
Marc Rabaey
Keyword(s):  
Complex Systems ◽  
Systems Thinking ◽  
Complex Adaptive Systems ◽  
Adaptive Systems ◽  
Enterprise Architecture ◽  
Time Dynamic ◽  
Complex Adaptive ◽  
Unstable Environment ◽  
Systems Thinking Approach ◽  
High Degree

Complex systems interact with an environment where a high degree of uncertainty exists. To reduce uncertainty, enterprises (should) create intelligence. This chapter shows that intelligence has two purposes: first, to increase and to assess (thus to correct) existing knowledge, and second, to support decision making by reducing uncertainty. The chapter discusses complex adaptive systems. Enterprises are not only complex systems; they are also most of the time dynamic because they have to adapt their goals, means, and structure to survive in the fast evolving (and thus unstable) environment. Crucial for enterprises is to know the context/ecology in which they act and operate. The Cynefin framework makes the organization and/or its parts aware of the possible contexts of the organization and/or its parts: simple, complicated, complex, chaotic, or disordered. It is crucial for the success of implementing and using EA that EA is adapted to function in an environment of perpetual change. To realize this, the chapter proposes and elaborates a new concept of EA, namely Complex Adaptive Systems Thinking – Enterprise Architecture (CAST-EA).

Information-As-System in Information Systems

2010 ◽  
pp. 99-118
Author(s):  
Tuan M. Nguyen ◽  
Huy V. Vo
Keyword(s):  
Information Systems ◽  
Structure Function ◽  
Conceptual Model ◽  
Systems Thinking ◽  
Systems Approach ◽  
Complex Nature ◽  
Holistic Thinking ◽  
Proposed Model ◽  
Nature Of Information

This article investigates the complex nature of information in information systems (IS). Based on the systems thinking framework, this study argues that information in IS is a system in its own right. A conceptual model of information-as-system is built on the systems thinking perspective adopted from Gharajedaghi’s holistic thinking rooted from Ackoff systems approach, which is developed through Peirce’s semiotics with the validity support of Metcalfe and Powell’s perspective of information perception, Mingers and Brocklesby’s schema of situational actions, Toulmin’s theory of argumentation and Ulrich’s theory of systems boundary. The proposed model of information-as-systems is described in terms of triads–on the structure, function, and process, all interdependent–in a context of information-as-system in IS.

E-Government Dynamics

2010 ◽  
pp. 261-276
Author(s):  
Petter Gottschalk ◽  
Hans Solli-Saether
Keyword(s):  
Decision Making ◽  
Complex Systems ◽  
Organizational Performance ◽  
Mental Models ◽  
Complex World ◽  
Dynamic Complexity ◽  
Causal Loop ◽  
Business Dynamics ◽  
Effective Decision ◽  
Effective Decision Making

It was Sterman’s (2000) book entitled “Business Dynamics: Systems Thinking and Modeling for a Complex World” that introduced the term business dynamics. Business dynamics is concerned with learning in and about complex systems. Effective decision-making by growing dynamic complexity requires executives to become systems thinkers – to expand the boundaries of their mental models and develop ways to understand how the structure of complex systems creates behavior. We start this chapter discussing how to overcome barriers to E-Government. Then we present a framework for assessment of E-Government projects. In the context of system dynamics, we discuss causal loop diagramming, modeling and organizational performance.

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