Connections between Empirical and Structural Reasoning in Technology-Aided Generalization Activities

Mathematical generalization can take on different forms and be built upon different types of reasoning. Having utilized data from a series of task-based interviews, this study examined connections between empirical and structural reasoning as preservice mathematics teachers solved problems designed to engage them in constructing and generalizing mathematical ideas aided by digital tools. The study revealed closer connections between naive empiricism and result pattern generalization, between naive empiricism and recognizing a structure in thought, between reasoning by generic example and process pattern generalization, and between reasoning by generic example and reasoning in terms of general structures. Results from this study imply that the ability to generalize based on perception and numerical pattern does not necessarily lead learners to generalize based on mathematical structure.

[1]  L. Radford Iconicity and contraction: a semiotic investigation of forms of algebraic generalizations of patterns in different contexts , 2008 .

[2]  R. Mouhayar Trends of progression of student level of reasoning and generalization in numerical and figural reasoning approaches in pattern generalization , 2018 .

[3]  Ornella Robutti,et al.  Technology and the Role of Proof: The Case of Dynamic Geometry , 2012 .

[4]  Max Stephens,et al.  Appreciating mathematical structure for all , 2009 .

[5]  G. Harel,et al.  The General, the Abstract, and the Generic in Advanced Mathematics , 1991 .

[6]  W. Dörfler,et al.  Forms and Means of Generalization in Mathematics , 1991 .

[7]  A. Graham,et al.  Developing Thinking in Algebra , 2005 .

[8]  Murad Jurdak,et al.  Variation of student numerical and figural reasoning approaches by pattern generalization type, strategy use and grade level , 2016 .

[9]  Dietmar Küchemann,et al.  From empirical to structural reasoning in mathematics : Tracking changes over time , 2009 .

[10]  L. Radford Gestures, Speech, and the Sprouting of Signs: A Semiotic-Cultural Approach to Students' Types of Generalization , 2003 .

[11]  Dietmar Küchemann Using patterns generically to see structure , 2010 .

[12]  M. Mitchelmore,et al.  Awareness of pattern and structure in early mathematical development , 2009 .

[13]  Ana Kuzle,et al.  Delving into the Nature of Problem Solving Processes in a Dynamic Geometry Environment: Different Technological Effects on Cognitive Processing , 2017, Technol. Knowl. Learn..

[14]  Xiangquan Yao,et al.  Middle school students’ generalizations about properties of geometric transformations in a dynamic geometry environment , 2019, The Journal of Mathematical Behavior.

[15]  Casey Hawthorne,et al.  Looking For and Using Structural Reasoning , 2019 .

[16]  Ryan C. Smith,et al.  The Nature of Arguments Provided by College Geometry Students with Access to Technology while Solving Problems. , 2010 .

[17]  Michal Yerushalmy Generalization in Geometry , 2013 .

[18]  Michel Gagnon,et al.  Issues and Challenges in Instrumental Proof , 2019, Proof Technology in Mathematics Research and Teaching.

[19]  Olga Kosheleva,et al.  Mathematical knowledge and practices resulting from access to digital technologies , 2009 .

[20]  Keith Weber,et al.  On the sophistication of naïve empirical reasoning: factors influencing mathematicians' persuasion ratings of empirical arguments , 2013 .

[22]  Marios Pittalis,et al.  Proofs through Exploration in Dynamic Geometry Environments , 2004 .

[23]  Barbara J. Dougherty,et al.  Developing Essential Understanding of Algebraic Thinking for Teaching Mathematics in Grades 3-5 , 2011 .

[24]  Keith Jones,et al.  Task Design Principles for Heuristic Refutation in Dynamic Geometry Environments , 2019 .

[25]  Nicolas Balacheff,et al.  Establishing links between conceptions, argumentation and proof through the ck¢-enriched Toulmin model , 2016 .

[26]  Anna Baccaglini-Frank,et al.  Generating Conjectures in Dynamic Geometry: The Maintaining Dragging Model , 2010, Int. J. Comput. Math. Learn..

[27]  Anna Baccaglini-Frank,et al.  Dragging, instrumented abduction and evidence, in processes of conjecture generation in a dynamic geometry environment , 2019, ZDM.

[28]  Barbara Mayer Thinking Mathematically 2nd Edition , 2016 .

[29]  Xiangquan Yao Characterizing Learners’ Growth of Geometric Understanding in Dynamic Geometry Environments: a Perspective of the Pirie–Kieren Theory , 2020, Digital Experiences in Mathematics Education.

[30]  R. Lachmy,et al.  The interplay of empirical and deductive reasoning in proving “if” and “only if” statements in a Dynamic Geometry environment , 2014 .

[31]  F. Arzarello,et al.  A cognitive analysis of dragging practises in Cabri environments , 2002 .