Vergara, C. E., & Urban-Lurain, M., & Sticklen, J., & Esfahanian, A., & McQuade, H., & League, A., & Bush, C. J., & Cavanaugh, M. (2014, June), Towards Improving Computational Competencies for Undergraduate Engineering Students  Paper presented at 2014 ASEE Annual Conference & Exposition, Indianapolis, Indiana. 10.18260/1-2--23201

\bibitem{asee_peer_23201}
  Vergara, C. E., \& Urban-Lurain, M., \& Sticklen, J., \& Esfahanian, A., \& McQuade, H., \& League, A., \& Bush, C. J., \& Cavanaugh, M. (2014, June), \emph{Towards Improving Computational Competencies for Undergraduate Engineering Students}
  Paper presented at 2014 ASEE Annual Conference \& Exposition, Indianapolis, Indiana.
  10.18260/1-2--23201

Claudia Elena Vergara, Mark Urban-Lurain, Jon Sticklen, Abdol-Hossein Esfahanian, Hannah McQuade, Andrew League, Chris John Bush, and Michael Cavanaugh.  "Towards Improving Computational Competencies for Undergraduate Engineering Students".  2014 ASEE Annual Conference & Exposition, Indianapolis, Indiana, 2014, June.  ASEE Conferences, 2014.  https://peer.asee.org/23201 Internet.  23 Apr, 2024

\bibitem{asee_peer_23201}
  Claudia Elena Vergara, Mark Urban-Lurain, Jon Sticklen, Abdol-Hossein Esfahanian, Hannah McQuade, Andrew League, Chris John Bush, and Michael Cavanaugh.
  "Towards Improving Computational Competencies for Undergraduate Engineering Students".
  \emph{2014 ASEE Annual Conference \& Exposition, Indianapolis, Indiana, 2014, June}.
  ASEE Conferences, 2014.
  https://peer.asee.org/23201 Internet.  23 Apr, 2024

@INPROCEEDINGS{asee_peer_23201
author = "Claudia Elena Vergara, Mark Urban-Lurain, Jon Sticklen, Abdol-Hossein Esfahanian, Hannah McQuade, Andrew League, Chris John Bush, and Michael Cavanaugh"
title = "Towards Improving Computational Competencies for Undergraduate Engineering Students"
booktitle = "2014 ASEE Annual Conference \& Exposition"
year = "2014"
month = "June"
address = "Indianapolis, Indiana"
publisher = "ASEE Conferences"
note = {https://peer.asee.org/23201}
number = {10.18260/1-2--23201}
}

TY  - CPAPER
AB  -      Towards Improving Computational Competencies for Undergraduate                         Engineering Students    The overarching goal for the Collaborative Process to Align Computing Education withEngineering Workforce Needs (CPACE) team is to redesign the role of computing withinengineering programs at  and  to develop computationalcompetencies – informed by industry needs. In CPACE I we: a) identified the computationalcompetencies needed in the engineering workplace; and b) aligned them with Computer Science(CS) concepts to be used in curricular implementation (CPACE Computational Competencies).In CPACE II our goal is to infuse computational problem-solving competencies throughout thecurricula starting with courses in Chemical and Civil Engineering. Our strategy involves usingproblems derived from contemporary industrial engineering practice. We collected studentsurveys at the beginning and end of target courses, and student interviews and focus groups, aswell as sample course work e.g. final project reports and relevant homework assignments. Tocompare students’ self-reported data regarding their computational abilities and their actualperformance in classroom assignments, we developed and continue testing rubrics based on theCPACE computational competencies.    Preliminary survey analyses indicated that students who are engaged in project or classroomactivities that encourage the use of computational skills report statistically significant gains in theuse and application of important computational competencies. Very importantly both Chemicaland Civil engineering students entering their disciplinary courses either at the sophomore orjunior level reported a marked drop in confidence in their ability to use and apply importantcomputational skills (e.g. MATLAB and EXCEL-related). One of the most challenging aspectsduring the implementation phase has been the lack of assessment instruments to measure studentcomputational competencies. Initial analyses of student artifacts using the CPACE computationalcompetencies rubric revealed that to understand the students’ computational thinking processesas they solve engineering problems, we needed to complement the artifact analyses with studentinterviews.    We conducted a total of 15 one –hour semi-structured interviews with students enrolled inthe target courses. Our objectives were to better understand the process by which students solveengineering problems using computational tools, specifically how, when and why computationaltools are employed during the problem solving process. Students described their thought processas they solved the engineering problem using their course projects as a guide for both interviewerand interviewee.    Interview analyses have enabled us to more clearly alignments between the CPACEcomputational competencies [using the rubric] and the student artifacts. Hence we have a betterunderstanding about the ways in which students use computational skills as they solveengineering problems (table 1). A major conclusion of our study is that students have difficultiesmaking connections between different computational tools and skills and fail to integrate theirknowledge in ways that would allow them to extend what they learn in one context to new anddifferent contexts. This points to a limited understanding about underlying computationalprinciples. In this paper we will present the results of the CPACE implementation emphasizingstudents’ impact.                                                                                                     1Table 1. Sample interview data aligned to CPACE computational competencies         Exemplar Computational Competencies                                           Interview QuotesAlgorithmic thinking and programming: students who             “It's such a multicomponent system that to try to do it bydescribe the use/function of particular computational tools    hand would be just tedious … went to Polymath …hit goand as a result demonstrate an understanding (or lack of)      and it'll, it spits out a table and a graph if you want it.”of the tool. How/why a particular tool works the way it        “MATLAB has more built-in functions in terms of math.does; references to programming, coding, debugging,            Also, you know, Python is a powerful language, but itdesign, iteration, parameterization, refinement, and utility   will require me as a programmer to code most of theof particular applications*.                                   functions and math myself, and that just leaves more                                                               room for error”Digital representation of information: examples include        “[…] there's just so many things you need to input, to getreferences to: conversion, copy and pasting, migrating         Aspen to actually work, you know, the number of stages,info, and representing data across fields*.                    the diameter of the column, the feed stage, the reflux                                                               ratio..”Limitations of technology: examples include references to      “So instead of creating an Aspen document first and liketool capabilities/purposes in relation to the problem;         getting our whole process flow in there and then trying toawareness of the assumptions made when simulating a            get it all to work, we figured it's probably just a better'real world' phenomenon; assessing what/when tool can be       idea to, to tackle each individual process first and then tryapplied *.                                                     to like interconnect them in Aspen.”Modeling and abstraction: Examples include references to       “From my basic knowledge, just being able to type in linemethods for representing 'real world' phenomena through        then you’re able to create a line which has a simplecomputer modeling. References to representing a problem        command. [...] you make a rectangle so those simpleas a model (system equations, graphs, simulations) and         commands kind of add –gave me a sense of what I wantedimplementing the model to obtain solution or solve             to try.”problems (debug)*.* Descriptor from the rubric used to inform the interview coding process.                                                                                                                               2
AU  - Claudia Elena Vergara
AU  - Mark Urban-Lurain
AU  - Jon Sticklen
AU  - Abdol-Hossein Esfahanian
AU  - Hannah McQuade
AU  - Andrew League
AU  - Chris John Bush
AU  - Michael Cavanaugh
CY  - Indianapolis, Indiana
DA  - 2014/06/15
PB  - ASEE Conferences
TI  - Towards Improving Computational Competencies for Undergraduate Engineering Students
UR  - https://peer.asee.org/23201
DO  - 10.18260/1-2--23201
ER  -