scholarly journals Promoting Second-year Engineering Students’ Epistemic Beliefs and Real-world Problem-solving Abilities through Case-Based E-Learning Resources

2020 ◽  
Author(s):  
Ikseon Choi ◽  
Yi-Chun Hong ◽  
David Gattie ◽  
Nadia Kellam ◽  
Melissa Gay ◽  
...  
Keyword(s):  
Problem Solving ◽  
Real World ◽  
Engineering Students ◽  
Epistemic Beliefs ◽  
Learning Resources ◽  
Real World Problem ◽  
E Learning ◽  
Second Year ◽  
Case Based

Systems theories

2018 ◽  
Author(s):  
Marc J. Stern
Keyword(s):  
Social Networks ◽  
Problem Solving ◽  
Natural Resources ◽  
Real World ◽  
Common Pool Resources ◽  
Ecological Systems ◽  
Effective Governance ◽  
Social Ecological Systems ◽  
Social Ecological ◽  
Real World Problem

This chapter covers systems theories relevant to understanding and working to enhance the resilience of social-ecological systems. Social-ecological systems contain natural resources, users of those resources, and the interactions between each. The theories in the chapter share lessons about how to build effective governance structures for common pool resources, how to facilitate the spread of worthwhile ideas across social networks, and how to promote collaboration for greater collective impacts than any one organization alone could achieve. Each theory is summarized succinctly and followed by guidance on how to apply it to real world problem solving.

scholarly journals Preparing Biomedical Engineers For Real World Problem Solving

2020 ◽  
Author(s):  
David Kelso ◽  
John D. Enderle ◽  
Kristina Ropella
Keyword(s):  
Problem Solving ◽  
Real World ◽  
Real World Problem

The Model Eliciting Activity (MEA) Construct: Moving Engineering Education Research Into the Classroom

2008 ◽  
Author(s):  
Larry J. Shuman ◽  
Mary Besterfield-Sacre ◽  
Renee Clark ◽  
Tuba Pinar Yildirim
Keyword(s):  
Problem Solving ◽  
Student Performance ◽  
Engineering Students ◽  
Undergraduate Curriculum ◽  
Conceptual System ◽  
Learning Material ◽  
Professional Skills ◽  
Real World Problem ◽  
Upper Level ◽  
Problem Solvers

A growing set of “professional skills” including problem solving, teamwork, and communications are becoming increasingly important in differentiating U.S. engineering graduates from their international counterparts. A consensus of engineering educators and professionals now believes that mastery of these professional skills is needed for our graduates to excel in a highly competitive global environment. A decade ago ABET realized this and included these skills among the eleven outcomes needed to best prepare professionals for the 21st century engineering world. This has left engineering educators with a challenge: how can students learn to master these skills? We address this challenge by focusing on models and modeling as an integrating approach for learning particular professional skills, including problem solving, within the undergraduate curriculum. To do this, we are extending a proven methodology — model-eliciting activities (MEAs) — creating in essence model integrating activities (MIAs). MEAs originated in the mathematics education community as a research tool. In an MEA teams of students address an open-ended, real-world problem. A typical MEA elicits a mathematical or conceptual system as part of its procedural requirements. To resolve an MEA, students may need to make new connections, combinations, manipulations or predictions. We are extending this construct to a format in which the student team must also integrate prior knowledge and concepts in order to solve the problem at hand. In doing this, we are also forcing students to confront and repair certain misconceptions acquired at earlier stages of their education. A distinctive MEA feature is an emphasis on testing, revising, refining and formally documenting solutions, all skills that future practitioners should master. Student performance on MEAs is typically assessed using a rubric to measure the quality of solution. In addition, a reflection tool completed by students following an MEA exercise assists them in better assessing and critiquing their progress as modelers and problem solvers. As part of the first phase a large, MEA research study funded by the National Science Foundation and involving six institutions, we are investigating the strategies students use to solve unstructured problems by better understanding the extent that our MEA/MIA construct can be used as a learning intervention. To do this, we are developing learning material suitable for upper-level engineering students, requiring them to integrate concepts they’ve learned in foundation courses while teasing out misconceptions. We provide an overview of the project and our results to date.

The Effects of Elaboration in Creativity Tests as it Pertains to Overall Scores and How it Might Prevent a Person From Thinking of Creative Ideas During the Early Stages of Brainstorming and Idea Generation

2015 ◽  
Author(s):  
Caitlin Dippo ◽  
Barry Kudrowitz
Keyword(s):  
Problem Solving ◽  
Negative Correlation ◽  
Real World ◽  
Idea Generation ◽  
Occurrence Rate ◽  
The Novel ◽  
Strong Negative Correlation ◽  
Relative Occurrence ◽  
Real World Problem ◽  
Creative Solutions

Previous studies have found that the first few ideas we think of for a given prompt are likely to be less original than the later ideas. In this study, 460 participants were given the Alternative Uses Test (AUT) where they were asked to list alternative uses for a paperclip, creating a database of 235 unique answers, each having a relative occurrence rate in that pool. It was found that later responses were significantly more novel than early responses and on average the originality of responses exponentially increased with quantity. A closer look at this data reveals that a person is likely to have a lower overall originality score if he or she has more elaborate responses. 89 of these participants were also given the Abbreviated Torrance Test For Adults (ATTA) and the data from both tests was used to study relationships between elaboration, fluency, and originality. The data from the AUT reveals a strong negative correlation between an individual’s average number of words per response and his or her average originality score. It is hypothesized that people who spend more time writing multiple-word responses have less time to generate many different ideas thus hindering their ability to reach the novel ideas. Similarly, the ATTA reveals that after two extraneous details, elaboration on a drawing will negatively impact fluency and originality scores. This is not to say that elaborate ideas cannot be original, but rather that in time-limited situations, elaboration may hinder the production of original ideas. In applying this to real world problem solving and idea generation, it is suggested that people may prevent themselves from finding creative solutions if too much time is spent on discussing the first few suggested ideas from a brainstorming session. It is suggested that a more effective brainstorming session will delay discussion until a significant number of ideas are generated.

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