Abstraction Through Multiple Representations in an Integrated Computational Thinking Environment

We present reflections based on qualitative analysis of data from the CHEM+C Project which promotes computational thinking (CT) in classrooms through integration with science classes. The curriculum utilizes multiple representations, requiring students to work with physical phenomena, chemical equations, digital simulations, and modifiable code-based representations. Much CT focus on abstraction naturally emphasizes (1) extraction of a set of features from an object or process, and (2) finding commonality between objects and processes. But Rosen encourages us to think about abstraction as also including the production of new concepts or actions. Integrating CT into science offers the possibility of enhancing this aspect of abstraction. Changing the representational affordances available to the students allows them to take their CT thinking beyond learning-to-abstract towards learning-through-abstraction. This perspective moves computation from an internally focused exercise into the expression of valued ideas in a computational medium.

[1]  HambruschSusanne,et al.  A multidisciplinary approach towards computational thinking for science majors , 2009 .

[2]  Michael S. Horn,et al.  Defining Computational Thinking for Mathematics and Science Classrooms , 2016 .

[3]  R. Kozma.  The material features of multiple representations and their cognitive and social affordances for science understanding , 2003 .

[4]  Jill Denner,et al.  Children learning computer science concepts via Alice game-programming , 2012, SIGCSE '12.

[5]  Lori L. Pollock,et al.  Infusing Computational Thinking Across Disciplines: Reflections & Lessons Learned , 2019, SIGCSE.

[6]  Michael S. Horn,et al.  Bringing Computational Thinking Into High School Mathematics and Science Classrooms , 2016, ICLS.

[7]  Shuchi Grover,et al.  Computational Thinking in K–12 , 2013 .

[8]  Shaaron Ainsworth,et al.  The Educational Value of Multiple-representations when Learning Complex Scientific Concepts , 2008 .

[9]  Nicholas Lytle,et al.  PRADA: A Practical Model for Integrating Computational Thinking in K-12 Education , 2019, SIGCSE.

[10]  Haluk Özmen,et al.  Some Student Misconceptions in Chemistry: A Literature Review of Chemical Bonding , 2004 .

[11]  Tamar Fuhrmann,et al.  Using the Bifocal Modeling Framework to Resolve “Discrepant Events” Between Physical Experiments and Virtual Models in Biology , 2016, Journal of Science Education and Technology.

[12]  Jeannette M. Wing.  Computational thinking and thinking about computing , 2008, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[13]  Peter Musaeus,et al.  Computational Thinking in the Danish High School: Learning Coding, Modeling, and Content Knowledge with NetLogo , 2019, SIGCSE.

[14]  Dor Abrahamson,et al.  NetLogo: Where We Are, Where We're Going , 2005 .

[15]  Susanne E. Hambrusch,et al.  A multidisciplinary approach towards computational thinking for science majors , 2009, SIGCSE '09.

[16]  A. Truman Schwartz,et al.  Contextualized Chemistry Education: The American experience , 2006 .

[17]  Mark Guzdial,et al.  A media computation course for non-majors , 2003, ITiCSE '03.

[18]  C. Atman,et al.  How people learn. , 1985, Hospital topics.

[19]  Seymour Papert,et al.  Mindstorms: Children, Computers, and Powerful Ideas , 1981 .

[20]  U. Netlogo Wilensky,et al.  Center for Connected Learning and Computer-Based Modeling , 1999 .

[21]  Janet L. Kolodner,et al.  Problem-Based Learning Meets Case-Based Reasoning in the Middle-School Science Classroom: Putting Learning by Design(tm) Into Practice , 2003 .

[22]  Baker Franke,et al.  Infusing computational thinking into the middle- and high-school curriculum , 2012, ITiCSE '12.

[23]  Michael S. Horn,et al.  Computational Thinking in Constructionist Video Games , 2016, Int. J. Game Based Learn..

[24]  R. Kozma,et al.  The Roles of Representations and Tools in the Chemistry Laboratory and Their Implications for Chemistry Learning , 2000 .

[25]  Johnny Saldaña,et al.  The Coding Manual for Qualitative Researchers , 2009 .

[26]  L. Schauble,et al.  Cultivating Model-Based Reasoning in Science Education , 2005 .

[27]  Mitchel Resnick,et al.  Adventures in Modeling: Exploring Complex, Dynamic Systems with StarLogo , 2001 .

[28]  David C. Webb,et al.  Recognizing computational thinking patterns , 2011, SIGCSE.

[29]  Austin Cory Bart,et al.  Design and Preliminary Results From a Computational Thinking Course , 2015, ITiCSE.

[30]  Ton de Jong,et al.  The effects of representational format on learning combinatorics from an interactive computer simulation , 2009 .

[31]  Gautam Biswas,et al.  Investigating Student Generated Computational Models of Science , 2014, ICLS.

[32]  Celia Hoyles,et al.  Developing new notations for a learnable mathematics in the computational era , 2002 .

[33]  Carol K. K. Chan,et al.  Conceptual change and epistemic growth through reflective assessment in computer-supported knowledge building , 2010, ICLS.

[34]  Susanne E. Hambrusch,et al.  Introducing computational thinking in education courses , 2011, SIGCSE.

[35]  Joyce Malyn-Smith,et al.  Computational thinking for youth in practice , 2011, INROADS.

[36]  Ann L. Brown,et al.  How people learn: Brain, mind, experience, and school. , 1999 .

[37]  Yasmin B. Kafai,et al.  The writers' workshop for youth programmers: digital storytelling with scratch in middle school classrooms , 2012, SIGCSE '12.

[38]  Jeannette M. Wing.  An introduction to computer science for non-majors using principles of computation , 2007, SIGCSE.

[39]  Elliot Soloway,et al.  Learning to program = learning to construct mechanisms and explanations , 1986, CACM.

[40]  Alex H. Johnstone,et al.  Multiple Representations in Chemical Education , 2009 .

[41]  Michael D. Ernst,et al.  A Data Programming CS1 Course , 2015, SIGCSE.

[42]  David C. Webb,et al.  Scalable game design and the development of a checklist for getting computational thinking into public schools , 2010, SIGCSE.

[43]  Andrea A. diSessa,et al.  Changing Minds: Computers, Learning, and Literacy , 2000 .

[44]  Ngss Lead States.  Next generation science standards : for states, by states , 2013 .

[45]  Cari F. Herrmann-Abell,et al.  Using Distractor-Driven Standards-Based Multiple-Choice Assessments and Rasch Modeling to Investigate Hierarchies of Chemistry Misconceptions and Detect Structural Problems with Individual Items. , 2011 .