skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.


Title: Leveraging Prediction and Reflection in a Computational Setting to Enrich Undergraduate Students’ Combinatorial Thinking
In this paper, I discuss undergraduate students’ engagement in basic Python programming while solving combinatorial problems. Students solved tasks that were designed to involve programming, and they were encouraged to engage in activities of prediction and reflection. I provide data from two paired teaching experiments, and I outline how the task design and instructional interventions particularly supported students’ combinatorial reasoning. I argue that emergent computational representations and the prompts for prediction and reflection were especially useful in supporting students’ reasoning about fundamental combinatorial ideas. I argue that this particular mathematical example informs broader notions of disciplinary reflexivity and representational heterogeneity, providing insight into computational thinking practices in the domain of mathematics. Ultimately, I aim to explore the nature of computing and enumeration, shedding light on why the two disciplines are particularly well-suited to support each other. I conclude with implications and avenues for future research.  more » « less
Award ID(s):
1650943
PAR ID:
10336909
Author(s) / Creator(s):
Editor(s):
Enyedy, Noel
Date Published:
Journal Name:
Cognition and Instruction
ISSN:
0737-0008
Page Range / eLocation ID:
1 to 43
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. null (Ed.)
    EcoMOD uses a design-based research approach to develop and study an elementary curriculum that combines an immersive virtual environment with interactive computer programming interface to support computational modeling, ecosystem science understanding, and causal reasoning. Here we report on changes in students’ perspectives on modeling before and after use of the fifteen day interactive, technology-based curriculum in a 3rd and 4th grade classroom. Pre-post interviews were conducted with ten students, and preliminary results suggest that students demonstrated an increased awareness that models are designed for a purpose, and the purposes students described aligned more closely with scientifically relevant activities like prediction, investigation and explanation. Students also increased in their level of sophistication related to ecosystem science understanding and causal reasoning. 
    more » « less
  2. de Vries, E. (Ed.)
    This study investigates how the design of hybrid mathematics and computational activities influences the ways in which students leverage ideas from both disciplinary topics. We examine two design cycles of a computer programming summer camp for middle school students which foreground computational thinking and then mathematics alongside computational thinking respectively. We review the rationale for each design iteration, the trends we saw in students’ engagement, and the implications for students’ reasoning. Findings of this study demonstrate the importance of thinking critically about the boundary objects that are included in design that support students to make bridges between multiple disciplinary practices. 
    more » « less
  3. Abstract BackgroundThis study posits that scaffolded team-based computational modeling and simulation projects can support model-based learning that can result in evidence of representational competence and regulatory skills. The study involved 116 students from a second-year thermodynamics undergraduate course organized into 24 teams, who worked on three two-week-long team-based computational modeling and simulation projects and reflected upon their experience. ResultsResults characterized different levels of engagement with computational model-based learning in the form of problem formulation and model planning, implementation and use of the computational model, evaluation, and interpretation of the outputs of the model, as well as reflection on the process. Results report on students’ levels of representational competence as related to the computational model, meaning-making of the underlying code of the computational model, graphical representations generated by the model, and explanations and interpretations of the output representations. Results also described regulatory skills as challenges and strategies related to programming skills, challenges and strategies related to meaning-making skills for understanding and connecting the science to the code and the results, and challenges and strategies related to process management mainly focused on project management skills. ConclusionCharacterizing dimensions of computational model-based reasoning provides insights that showcase students’ learning, benefits, and challenges when engaging in team-based computational modeling and simulation projects. This study also contributes to evidence-based scaffolding strategies that can support undergraduate students' engagement in the context of computational modeling and simulation. 
    more » « less
  4. Computational thinking can be deemed as thinking in algorithmic way, with which one can transpose given problems into computer algorithms. Since computational thinking requires abstract reasoning, it should not depend on particular programming languages. Unfortunately, introductory programming courses (CS1) often give students false impression that their goals are to teach a particular programming language. This study shares the design of new pedagogy for CS1 that removes dependency on a particular language and promotes computational thinking by teaching multiple programming languages simultaneously. Specifically, chosen programming languages range from low-level to high-level to expose students to different levels of abstraction from the details of computer architecture. Initial student survey responses from both trial and control groups show that there are significant improvements for the trial groups. 
    more » « less
  5. Sacristán, A.I; Cortés-Zavala, J.C.; Ruiz-Arias, P.M. (Ed.)
    In this paper we present an integrated design approach for bridging content between science, technology, engineering, math, and computational thinking (STEM+C). We present data from a design experiment to show examples of the kinds of integrated reasoning that students exhibited while engaging with our design. We argue that covariational reasoning can provide strong scaffolding in making integrated connections between the STEM+C content areas. 
    more » « less