Students’ Understanding of Computational Problem-Solving Tasks

Alejandra J. Magana; Aidsa I. Santiago-Román; Nayda G. Santiago; Cesar A Aceros; Brandeis H Marshall; Eric T. Matson

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Conference: 2011 ASEE Annual Conference & Exposition
Location: Vancouver, BC
Publication Date: June 26, 2011
Start Date: June 26, 2011
End Date: June 29, 2011
ISSN: 2153-5965
Conference Session: Innovations in Computing Education
Tagged Division: Computing & Information Technology
Page Count: 15
Page Numbers: 22.1347.1 - 22.1347.15
DOI: 10.18260/1-2--18745
Permanent URL: https://strategy.asee.org/18745
Download Count: 383

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Paper Authors

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Alejandra J. Magana Purdue University, West Lafayette orcid.org/0000-0001-6117-7502

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Alejandra J. Magana is a Visiting Assistant Professor in the Department of Computer and Information Technology and the School of Engineering Education, at Purdue University. Alejandra's research interest are focused on identifying how computational tools and methods can support the understanding of complex phenomena for scientific discovery and for inquiry learning.

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Aidsa I. Santiago-Román University of Puerto Rico, Mayaguez

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Aidsa I. Santiago Román is an Assistant Professor in the Department of Engineering Science and Materials and the Director of the Strategic Engineering Education Development (SEED) Office at the University of Puerto Rico, Mayaguez (UPRM). Dr. Santiago earned a B.A. (1996) and M.S. (2000) in Industrial Engineering from UPRM, and Ph.D. (2009) in Engineering Education from Purdue University. Her primary research interest is investigating students’ understanding of difficult concepts in engineering science with underrepresented populations. She also teaches introductory engineering courses such as Problem Solving and Computer Programming, Statics, and Mechanics.

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Nayda G. Santiago University of Puerto Rico, Mayaguez

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Nayda G. Santiago received the B.S.E.E. degree from University of Puerto Rico, Mayaguez Campus, in 1989, the M.Eng.E.E. degree from Cornell University in 1990, and the Ph.D. degree in Electrical Engineering from Michigan State University in 2003. Since 2003, she has been a faculty member of the University of Puerto Rico, Mayaguez at the Electrical and Computer Engineering Department where she holds a position as Associate Professor. Nayda has been recipient of the 2008 Outstanding Professor of Electrical and Computer Engineering Award, 2008 Distinguished Computer Engineer Award of the Puerto Rico Society of Professional Engineers and Land Surveyors, the 2008 HENAAC (Hispanic Engineer National Achievement Awards Conference) Education Award, and the 2009 Distinguished Alumni Award of the University of Puerto Rico, Mayaguez Campus. She is a member of the IEEE and the ACM.

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Abstract

Students’ Understanding of Computational Problem-Solving TasksComputational thinking embodies multiple reasoning processes or ways of thinking thattranscend time and disciplines. As a result, computational thinking represents an attitude andskill-set that is changing the way we think by providing an extension to our cognitive faculties.These changes are impacting science, technology, and society “on ways new discoveries will bemade, innovation will occur, and cultures will evolve” (Wing, 2009). Because computationalthinking constitutes a powerful and pervasive tool to solve problems, researchers have pointedout that there is the need to start teaching computational thinking early and often; howeverseveral challenges have been identified. Questions such as: “What are the effective ways oflearning computational thinking? What are the effective ways of teaching computationalthinking? What are the elemental concepts of computational thinking? And how should theseconcepts be integrated into the curriculum? Are some of the questions that need to be dealtwith.In this phenomenographical study we explore how five to ten technology and engineeringstudents approach solving computational problems. The specific research question for thisstudy is how students understand and respond to a computational problem–solving task? Thisstudy is guided under the premise that people’s ways of experiencing phenomena result fromthe unique interaction of their understanding of the phenomena and the situation in which theymust apply that understanding. Therefore, to pursue this investigation we designedassessments consisting of problem-solving tasks where students will: a) identify what theproblem is about and b) what would be the appropriate way to tackle the problem in terms of theoutcomes of their learning activities. The data analysis will be conducted followingphenomenographical research methods where similarities and differences between students’understandings of a problem and their different approaches for tackling it will be discovered. Ourultimate goal is that by identifying, comparing, and contrasting students’ understandings andstrategies to approach problems, more effective instructional approaches will be identified.

Citation
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Magana, A. J., & Santiago-Román, A. I., & Santiago, N. G., & Aceros, C. A., & Marshall, B. H., & Matson, E. T. (2011, June), Students’ Understanding of Computational Problem-Solving Tasks Paper presented at 2011 ASEE Annual Conference & Exposition, Vancouver, BC. 10.18260/1-2--18745

TY - CPAPER
AB - Students’ Understanding of Computational Problem-Solving TasksComputational thinking embodies multiple reasoning processes or ways of thinking thattranscend time and disciplines. As a result, computational thinking represents an attitude andskill-set that is changing the way we think by providing an extension to our cognitive faculties.These changes are impacting science, technology, and society “on ways new discoveries will bemade, innovation will occur, and cultures will evolve” (Wing, 2009). Because computationalthinking constitutes a powerful and pervasive tool to solve problems, researchers have pointedout that there is the need to start teaching computational thinking early and often; howeverseveral challenges have been identified. Questions such as: “What are the effective ways oflearning computational thinking? What are the effective ways of teaching computationalthinking? What are the elemental concepts of computational thinking? And how should theseconcepts be integrated into the curriculum? Are some of the questions that need to be dealtwith.In this phenomenographical study we explore how five to ten technology and engineeringstudents approach solving computational problems. The specific research question for thisstudy is how students understand and respond to a computational problem–solving task? Thisstudy is guided under the premise that people’s ways of experiencing phenomena result fromthe unique interaction of their understanding of the phenomena and the situation in which theymust apply that understanding. Therefore, to pursue this investigation we designedassessments consisting of problem-solving tasks where students will: a) identify what theproblem is about and b) what would be the appropriate way to tackle the problem in terms of theoutcomes of their learning activities. The data analysis will be conducted followingphenomenographical research methods where similarities and differences between students’understandings of a problem and their different approaches for tackling it will be discovered. Ourultimate goal is that by identifying, comparing, and contrasting students’ understandings andstrategies to approach problems, more effective instructional approaches will be identified.
AU - Alejandra J. Magana
AU - Aidsa I. Santiago-Román
AU - Nayda G. Santiago
AU - Cesar A Aceros
AU - Brandeis H Marshall
AU - Eric T. Matson
CY - Vancouver, BC
DA - 2011/06/26
PB - ASEE Conferences
TI - Students’ Understanding of Computational Problem-Solving Tasks
UR - https://strategy.asee.org/18745
DO - 10.18260/1-2--18745
ER -