Online assessment of students’ reasoning when solving example-eliciting tasks: using conjunction and disjunction to increase the power of examples

We argue that examples can do more than serve the purpose of illustrating the truth of an existential statement or disconfirming the truth of a universal statement. Our argument is relevant to the use of technology in classroom assessment. A central challenge of computer-assisted assessment is to develop ways of collecting rich and complex data that can nevertheless be analyzed automatically. We report here on a study concerning a dedicated design pattern of a special kind of task for assessing student’s reasoning when establishing the validity of geometry statements that go beyond a single case, concerning the similarity of triangles. In each task students are given three relations that exist either in every triangle or in special types. Their task is to verify, by creating an example, claims that argue for logically compounded claims built out of the given relations. 50 students, aged 15–16, were asked to verify or disprove claims. Their submissions were automatically characterized along categories based on the correctness of the claims they chose and the examples they used to support the claims. We focus on characterizing the properties of the conjunction/disjunction design for automatically assessing conceptions related to examples generated by the learner with interactive diagrams. Our analysis shows that our automated scoring environment, which supports interactive example-eliciting-tasks, and the design principles of conjunction and disjunction of geometric relations, enable one to assess students’ exploration of the logic of universal claims, characterize successful and partial answers, and differentiate between students according to their work.

[1]  Nicolas Balacheff,et al.  The instrumental deconstruction as a link between drawing and geometrical figure , 2019 .

[2]  Celia Hoyles,et al.  Software Tools for Geometrical Problem Solving: Potentials and Pitfalls , 2002, Int. J. Comput. Math. Learn..

[3]  I. Lakatos PROOFS AND REFUTATIONS (I)*† , 1963, The British Journal for the Philosophy of Science.

[4]  Orit Zaslavsky,et al.  Strengths and inconsistencies in students’ understanding of the roles of examples in proving , 2019, The Journal of Mathematical Behavior.

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

[6]  Dov Zazkis,et al.  Prospective Teachers’ Conceptions of Proof Comprehension: Revisiting a Proof of the Pythagorean Theorem , 2016 .

[7]  L. Schauble,et al.  Design Experiments in Educational Research , 2003 .

[8]  Andreas J. Stylianides,et al.  Mathematics for teaching: A form of applied mathematics , 2010 .

[9]  Michael De Villiers,et al.  Proof and Proving in Mathematics Education , 2012 .

[10]  O. Zaslavsky,et al.  Example-Generation as Indicator and Catalyst of Mathematical and Pedagogical Understandings , 2014 .

[11]  O. Zaslavsky,et al.  A FRAMEWORK FOR UNDERSTANDING THE STATUS OF EXAMPLES IN ESTABLISHING THE VALIDITY OF MATHEMATICAL STATEMENTS , 2009 .

[12]  G. Stylianides AN ANALYTIC FRAMEWORK OF REASONING-AND-PROVING , 2008 .

[13]  F. Arzarello,et al.  Experimental approaches to theoretical thinking in the mathematics classroom: artefacts and proofs , 2012 .

[14]  Chris Sangwin,et al.  Micro-level automatic assessment supported by digital technologies , 2009 .

[15]  I. Lakatos,et al.  Proofs and Refutations: Frontmatter , 1976 .

[16]  D. Chazan High school geometry students' justification for their views of empirical evidence and mathematical proof , 1993 .

[17]  John Mason,et al.  Mathematics as a Constructive Activity: Learners Generating Examples , 2005 .

[18]  Ron Hoz The effects of rigidity on school geometry learning , 1981 .

[19]  Michal Yerushalmy,et al.  How Might the Use of Technology in Formative Assessment Support Changes in Mathematics Teaching , 2016 .

[20]  Roza Leikin,et al.  Forms of Proof and Proving , 2012 .

[21]  Michal Yerushalmy,et al.  Design of tasks for online assessment that supports understanding of students’ conceptions , 2017 .

[22]  M. Mills A framework for example usage in proof presentations , 2014 .

[23]  Ferdinando Arzarello,et al.  Approaching Proof in the Classroom Through the Logic of Inquiry , 2019, ICME-13 Monographs.

[24]  Alison Clark-Wilson,et al.  Emergent pedagogies and the changing role of the teacher in the TI-Nspire Navigator-networked mathematics classroom , 2010 .

[25]  Ayl Leung,et al.  Developing learning and assessment tasks in a dynamic geometry environment , 2006 .

[26]  Carolyn Kieran,et al.  A conceptual model of mathematical reasoning for school mathematics , 2017 .

[27]  Keith Jones Providing a Foundation for Deductive Reasoning: Students' Interpretations when Using Dynamic Geometry Software and Their Evolving Mathematical Explanations , 2000 .

[28]  Robert J. Mislevy,et al.  Assessing Model-Based Reasoning using Evidence- Centered Design: A Suite of Research-Based Design Patterns , 2017 .

[29]  Annalisa Cusi,et al.  Task design fostering construction of limit confirming examples as means of argumentation , 2019 .

[30]  Daniel Chazan Similarity: Exploring the Understanding of a Geometric Concept. Technical Report 88-15. , 1988 .

[31]  Keith Weber,et al.  An assessment model for proof comprehension in undergraduate mathematics , 2012 .

[32]  John R. Anderson Cognitive Psychology and Its Implications , 1980 .

[33]  A. Watson,et al.  The structuring of personal example spaces , 2011 .

[34]  Gila Ron,et al.  What Can You Infer from This Example? Applications of Online, Rich-Media Tasks for Enhancing Pre-service Teachers’ Knowledge of the Roles of Examples in Proving , 2017 .