Paper Authors

Abstract

NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract

Using Computational Tools to Enhance Problem Solving Abstract

Many engineering curriculum around the country are re-evaluating their introductory computer programming requirement. At our university, several departments have introduced new computer-based modeling courses that integrate critical thinking and problem solving with computational thinking and programming as a replacement of the traditional first computer programming course. The skills learned in such freshman level courses are being iterated and expanded on in subsequent courses in these curricula in order to create a ‘computational thinking thread’. One unforeseen consequence of the computer based modeling course was an increase in the student’s problem solving ability. This study explores the role that computing has on student’s problem solving abilities and tries to quantify its impact. Students in several freshman and senior level engineering courses across different disciplines were asked to solve a common problem solving task as well as reflect on the process they used to solve the problem. The student’s solutions were scored using a protocol based on Wolcott’s ‘Steps for better thinking rubric’ The paper will outline the problem used; report on the scoring procedures and methodology; and present the results from the study. The results demonstrated that students who utilized computing generated better solutions and are better problem solvers than those who did not use a computer.

Introduction

This work is part of an ongoing project that stems from assessing the impact of new introductory computer-based modeling courses that were created in two engineering departments at our university. These freshman level courses aim to educate students to model problems relevant to their specific engineering discipline, solve these problems using modeling tools (including a range of software platforms, such as Excel and VBA), and then to analyze the solutions through decision support systems (i.e., to become “power users” not programmers). Emphasis is placed on the analysis of data in order to make more efficient and effective decisions. The courses employ a series of “in-class labs”, integrating the traditional lab and lecture sessions into one, and all in-class activities are done on student-owned laptops [1, 2]. The labs are crafted to capture the student’s attention the entire time owing to the large distraction of having a computer. Many of the homework assignments and case studies come from industrial sponsored data and represent real world situations. Course content as well as teaching methodologies employed and developed have been described in earlier research [1, 2]. Even though this course is offered in two different departments, they follow the same curriculum (i.e., labs, homework, projects, and tests) throughout the semester.

One of the main reasons for creating these new courses was to enhance the students’ ability to think critically, develop algorithmic solutions to problems (flow chart out a basic solution to a problem), and develop general problem solving skills. However, in order to teach these modeling techniques to solve a series of case studies, the faculty had to break up the larger problem into smaller steps (i.e., they applied their experience in solving these problems) to make them solvable in a regular class period by students. A secondary outcome of these labs was that students were seeing how to approach and solve a wide variety of different problems. For

• Citation

• Format
  • APA
  • APA - LaTeX bibitem
  • MLA
  • MLA - LaTeX bibitem
  • Bibtex
  • EndNote - RIS

Raubenheimer, D., & Joines, J., & Craig, A. (2009, June), Using Computational Tools To Enhance Problem Solving Paper presented at 2009 Annual Conference & Exposition, Austin, Texas. 10.18260/1-2--4610