Task Design in Mathematics Education. Proceedings of
ICMI Study 22
Claire Margolinas
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Task Design in Mathematics Education
Proceedings of ICMI Study 22
Claire Margolinas (editor)
Janet Ainley
Janete Bolite Frant
Michiel Doorman
Carolyn Kieran
Allen Leung
Minoru Ohtani
Peter Sullivan
Denisse Thompson
Anne Watson
Yudong Yang
Oxford, UK, July 2013
2
INTRODUCTION 7
Anne Watson,Minoru Ohtani, Janet Ainley, Janete Bolite Frant, Michiel Doorman, Carolyn Kieran, Allen Leung, Claire Margolinas, Peter Sullivan, Denisse Thompson, Yudong Yang
THEME A - TOOLS AND REPRESENTATIONS 15
Allen Leung, Janete Bolite Frant
Using crises, feedback and fading for online task design 17 Christian Bokhove
A Holistic Approach for Designing Tasks that Capture and Enhance Mathematical
Understanding of a Particular Topic: The Case of the Interplay between Examples and Proof 25 Orly Buchbinder, Orit Zaslavsky
Rotational symmetry: semiotic potential of a transparency toolkit 35 Yip-Cheung CHAN, Allen LEUNG
Designing tasks within a multi-representational technological environment:
An emerging rubric. 45
Alison Clark-Wilson, Jaiwant Timotheus
Digital design: RME principles for designing online tasks 53 Paul Drijvers, Peter Boon, Michiel Doorman, Christian Bokhove, Sietske Tacoma
Designing tasks for a more inclusive school mathematics 61 Lulu Healy, Solange Hassan Ahmad Ali Fernandes, Janete Bolite Frant
Using computers in classroom mathematical tasks: revisiting theory
to develop recommendations for the design of tasks 69 Marie Joubert
The interaction between task design and technology design
in creating tasks with Cabri Elem 79
Kate Mackrell, Michela Maschietto, Sophie Soury-Lavergne
Designing Tasks to Foster Operative Apprehension for Visualization and Reasoning
in Dynamic Geometry Environment 89
Anthony C. M. OR
Dynamic representations for algebraic objects available in AlNuSet:
how develop meanings of the notions involved in the equation solution. 99 E. Robotti
Designing Tasks for Use With Digital Technology 109
Michael O. J. Thomas, Catherine Lin Designing mathematical modelling tasks
in a technology rich secondary school context 119
Vince Geiger, Trevor Redmond
Optimizing through geometric reasoning supported by 3-D models:
Visual representations of change 129
Walter Whiteley, Ami Mamolo
Instrumental value and semiotic value of ostensives and task design 141 Floriane Wozniak
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Emergent tasks—spontaneous design supporting in-depth learning 153 Angelika Bikner-Ahsbahs, Thomas Janßen
Mathematical Investigations: The Impact of Students’ Enacted Activity
on Design, Development, Evaluation and Implementation 163 James Calleja
Writing the Student into the Task: Agency and Voice 173 David Clarke, Carmel Mesiti
Making distinctions in task design and student activity 183 Alf Coles, Laurinda Brown
Applying the Phenomenographic Approach to Students’ Conceptions of Tasks 193 Kimberly Gardner
On what epistemological thinking brings (or does not bring) to the analysis
of tasks in terms of potentialities for mathematical learning 203 Pierre Job, Maggy Schneider
Designing Covariation Tasks to Support Students’ Reasoning
about Quantities involved in Rate of Change 211
Heather L. Johnson
Designing tasks that enhance mathematics learning through creative reasoning 221 Johan Lithner, Bert Jonsson, Carina Granberg, Yvonne Liljekvist, Mathias Norqvist, Jan
Olsson
Shortcomings in the milieu for algebraic generalisation arising
from task design and vagueness in mathematical discourse 231 Heidi Strømskag Måsøval
Order of tasks in sequences of early algebra 241
Pedro Palhares, Leonel Vieira, Joaquim Gimenez
A Task Design for Conjecturing in Primary Classroom Contexts 249 Pi-Jen Lin, Wen-Huan Tsai
Using Student Solutions to Design Follow-up Tasks to Model-Eliciting Activities 259 Peter Radonich, Caroline Yoon
Tasks to Promote Holistic Flexible Reasoning about Simple Additive Structures 269 Annie Savard, Elena Polotskaia, Viktor Freiman, Claudine Gervais
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THEME C - DESIGN AND USE OF TEXT-BASED RESOURCES 279
Denisse Thompson, Anne Watson
Designing Tasks for Engaging Students in Active Knowledge Organization 283 Bärbel Barzel, Timo Leuders, Susanne Prediger, Stephan Hußmann
Developing Young Students' Geometric Insight Based on
Multiple Informal Classifications as a Central Principle in the Task Design 293 Marita Barabash, Raisa Guberman
How Do Students Learn Mathematical Proof?
A Comparison of Geometry Designs in German and Taiwanese Textbooks 303 Yu-Ping Chang, Fou-Lai Lin, Kristina Reiss
Designing the Practical Worksheet for Problem Solving Tasks 313 Jaguthsing Dindyal, Eng Guan Tay, Khiok Seng Quek, Yew Hoong Leong, Tin Lam Toh, Pee Choon Toh, Foo Him Ho
Textbooks’ Design and Digital Resources 325
Ghislaine Gueudet, Birgit Pepin, Luc Trouche
Pedagogical Content Analysis of Mathematics as a Framework for Task Design 337 Eric W. Hart
Task Modification and Knowledge Utilization by Korean Prospective
Mathematics Teachers 347
Kyeong-Hwa Lee, Eun-Jung Lee, Min-Sun Park
The Lemon Squash Task 357
Anna L. V. Lundberg, Cecilia Kilhamn
Designing Interdisciplinary Tasks in an International Design Community 367 Katja Maass, Fco. Javier Garcia, Nicholas Mousoulides, Geoff Wake
Enabling Education for Values with Mathematics Teaching 377 Nitsa Movshovitz-Hadar, Yael Edri
Designing Interdisciplinary Curriculum for College Algebra 389 Susan Staats, Jason Johnson
Assessments Accompanying Published Curriculum Materials: Issues
for Curriculum Designers, Researchers, and Classroom Teachers 401 Denisse R. Thompson, Patricia D. Hunsader, Barbara Zorin
Different features of task design associated with goals and pedagogies
in Chinese and Portuguese textbooks: The case of addition and subtraction 409 Sun Xuhua, Teresa B. Neto, LoudesE. Ordóñez
5 Carolyn Kieran, Michiel Doorman, Minoru Ohtani Task design within the Anthropological Theory of the Didactics:
Study and Research Courses for pre-school 421
Fco. Javier García García, Luisa Ruiz-Higueras
Task design for systemic improvement: principles and frameworks 431 Hugh Burkhardt, Malcolm Swan
Task design in a school-based professional development programme 441 Liping Ding, Keith Jones, Birgit Pepin
Hybrid Tasks: Promoting Statistical Thinking and Critical Thinking
through the Same Mathematical Activities 451
Einav Aizikovitsh-Udi, David Clarke, Sebastian Kuntze Effects of variations in task design using different representations
of mathematical objects on learning: A case of a sorting task 461 Boris Koichu, Orit Zaslavsky, Lea Dolev
Principles of task design to foster proofs and refutations in mathematical learning:
Proof problem with diagram 471
Kotaro Komatsu, Yosuke Tsujiyama The “Language and argumentation” project:
researchers and teachers collaborating in task design 481 Francesca Morselli
Designing and using exploratory tasks 491
João Pedro da Ponte, Joana Mata-Pereira, Ana Cláudia Henriques, Marisa Quaresma Developing Theory for Design of Mathematical Task Sequences:
Conceptual Learning as Abstraction 501
Martin Simon
An Instructional Design Collaborative in One Middle School 509 Michelle Stephan, Didem Akyuz
Mind the gap – Task design principles to achieve conceptual change
in rational number understanding 519
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THEME E - FEATURES OF TASK DESIGN INFORMING TEACHERS’ DECISIONS
ABOUT GOALS AND PEDAGOGIES 529
Peter Sullivan, Yudong Yang
Teachers and researchers collaborating to develop teaching
through problem solving in primary mathematics 531
Mike Askew, Lisa Canty
Conflicts in designing tasks at collaborative groups 541 Jonei Cerqueira Barbosa, Andreia Maria Pereira de Oliveira
A dialogue between cultures about task design for primary school 549 Maria G. Bartolini Bussi, Xuhua Sun, Alessandro Ramploud 549
Scaffolding Tasks for the Professional Development of
Mathematics Teachers of English Language Learners 559
Haiwen Chu
An experience of teacher education on task design in Colombia 569 GEMAD
Designing Professional Tasks for Didactical Analysis as a research process 579 Joaquin Giménez, Vicenç Font, Yuly Marsela Vanegas
Designing Rich Numeracy Tasks 589
Merrilyn Goos, Vince Geiger, Shelley Dole
Task design: Supporting teachers to independently create rich tasks 599 Libby Knott, Jo Olson, Anne Adams, Rob Ely
The same task? - different learning possibilities 609
Angelika Kullberg, Ulla Runesson, Pernilla Mårtensson
On doing the same problem – first lessons and relentless consistency 617 Laurinda Brown, Alf Coles
Reflections of Nigerian teachers on a learning experience designed to develop pupils' multiplicative
reasoning 627
Kathryn I. Omoregie
Designed to facilitate learning: Simple problems that run deep 633 Irit Peled, Anat Suzan
Engaging teachers in the web of considerations underlying the design of tasks
that foster the need for new mathematical concepts or tools: The case of calculus 641 Gila Ron, Orit Zaslavsky, Iris Zodik
7
Introduction
Anne Watson
University of Oxford, UK
Minoru Ohtani
Kanazawa University, Japan
Janet Ainley
School of Education, University of Leicester, UK
Janete Bolite Frant
LOVEME Lab, UNIBAN, Brazil
Michiel Doorman
Utrecht University, Netherlands
Carolyn Kieran
Université du Québec à Montréal, Canada
Allen Leung
Hong Kong Baptist University, Hong Kong
Claire Margolinas
Laboratoire ACTé, Université Blaise Pascal, France
Peter Sullivan
Monash University, Australia
Denisse Thompson
University of South Florida, USA
Yudong Yang
Shanghai Academy of Educational Sciences, China
The study aims to produce a state-of-the-art summary of relevant research and to go beyond that summary to develop new insights and new areas of knowledge and study about task design. In particular, we aim to develop more explicit understanding of the difficulties involved in designing and implementing tasks, and of the interfaces between the teaching, researching, and designing roles – recognising that these might be undertaken by the same person, or by completely separate teams.
Background
In her plenary address to the International Group for Psychology of Mathematics Education (PME) Sierpinska (2003) identified task design and use as a core issue in research reports and in mathematics education research more generally. She commented that research reports rarely give sufficient detail about tasks for them to be used by someone else in the same way. Few studies justify task choice or identify what features of a task are essential and what features are irrelevant to the study. In some studies using intervention/treatment
Introduction
8
comparisons to investigate cognitive development, the intervention tasks are often vague, as if the reader can infer what the learning environment was like from a few brief indications. A similar view had been expressed by Schoenfeld (1980). Yet we learn from applications of variation theory to learning study (e.g., Runesson, 2005), from studies of learning from worked examples (e.g., Renkl, 2005), and from the Adaptive Control of Thought model (ACT-R) (e.g., Anderson & Schunn, 2000) that seemingly minor differences in tasks can have significant effects on learning.
At the same time Burkhardt has drawn attention to the importance of design, with the founding of an international society and a journal, Educational Designer
(www.educationaldesigner.org). (Schoenfeld, 2009) makes a plea for more communication between designers and researchers, making the point, among others, that many designers are not articulate about their design principles, and may not be informed by research. In 2008, the International Congress on Mathematics Education (ICME) hosted a topic study group (TSG),
Research and development in task design and analysis, which provided a forum for that kind
of interaction (http://tsg.icme11.org/tsg/show/35). Designers had to be explicit about their principles and demonstrate how they used them. Participants were given the opportunity to experience various tasks, and compare and critique design principles. Drawing from a wide international field, an overview of the papers makes it apparent that:
(1) it is necessary to have theories about learners’ intellectual engagement to have successful design; and
(2) most design principles included the use of several representations, several kinds of sensory engagement, and several question types.
The TSG increased its membership during the conference, indicating that a serious, organised look at task design was of growing interest. A further TSG is due to take place at ICME 12 in July 2012 in Seoul, Korea. Working groups on task design using digital technologies, and design of digital learning environments, proliferate, but we are not aware of a similar level of activity in other environments.
Mathematics educators have focused to a great extent on the social cultures of classrooms and designed learning environments, on patterns of argumentation, on emotional aspects of engagement, and on measures of learning. A distinct mathematical contribution can be made in understanding whether and how doing tasks, of whatever kind, enables conceptual learning. For example, Lagrange (2002) suggests that applying routine techniques can achieve results, and also provide the basis for conceptual understanding and new theorising; (Watson & Mason, 2006) have shown how a set of procedural exercises, seen as one object, can provide raw material for conceptualisation; Realistic Mathematics Education (RME) from the Netherlands and Mathematics in Context materials (from the United States) show how carefully designed situational sequences can turn a learners’ attention to abstract similarities.
Our statement that task design is core to effective teaching is well-illustrated by the success of theoretically-based long term design-research projects resulting in publications such as those from Shell Centre (Swan, 1985), Realistic Mathematics Education (de Lange, 1996) and Connected Mathematics (Lappan & Phillips, 2009). In these, design and research over time have combined to develop materials and approaches that have appealed to teachers. In addition, research related to the QUASAR project (Quantitative Understanding: Amplifying Student Achievement and Reasoning) found that the cognitive demand of designed tasks was often reduced during implementation (Henningsen & Stein, 1997). A research forum at PME in Mexico (Tzur, Sullivan, & Zaslavsky, 2008) offered cogent explanations for the inevitability and even desirability of teachers’ alteration of the cognitive demand of tasks. Further, Choppin (2011) suggests how adaptation differs among teachers. Thus, a possible area of investigation is how published tasks are appropriated by teachers for complex purposes. In variation theory, a distinction is made between the intended, enacted,
9
and lived objects of learning. The Documentational Approach of Didactics (Gueudet & Trouche, 2009, 2011) also refers to the practitioner perspective in terms of the resources on which teachers draw. Didactic engineering was the topic of the 15th summer school in mathematics didactics in 2009 (Margolinas, Abboud-Blanchard, Bueno-Ravel, Douek, Fluckiger, Gibel, Vandebrouck, & Wozniak, 2011). The discussion focused not only on various principles of task design (see the contributions of Bessot, Chevallard, Boero, and Schneider) but also on the problem of the influence of task design on the development of actual mathematics teaching (see contributions of Perrin-Glorian, René de Cotret and Robert). The tasks in these references are all complex, multi-stage tasks which address complex purposes, such as those usefully summarised in Kilpatrick, Swafford, & Findell (2011), namely the development of conceptual understanding; procedural fluency; strategic competence; adaptive reasoning; and productive disposition.
We would like to encourage an interest in tasks that have more limited but valid intentions, such as tasks that have a change in conceptual understanding as an aim, or tasks that focus only on fluency and accuracy. Research can investigate how students perceive and conceptualise from the examples they are given, or on which they work. Most mathematics learners world-wide learn procedures and possibly concepts through ‘practice’, regardless of the de-emphasis on procedures held by reform enthusiasts. Thus, the design of sequences of near-similar tasks deserves attention. For reasons of global reality and equity, the study conference shall also focus on textbook design partly because textbooks are often informed by tradition or by an examination syllabus rather than through research and development (Valverde, Bianchi, Wolfe, Schmidt, & Houang, 2002), but also because in some countries textbooks are the major force for change. Textbooks are not the only medium in which sequences of tasks, designed to afford progressive understanding or shifts to other levels of perception, can be presented, and we expect that study conference participants will look also at the design of online task banks.
Work from Sullivan indicates the need to educate new teachers in the use of complex tasks (Sullivan, 1999) and it is inevitable that teacher education will cross several of our suggested areas. A volume of the Handbook of Mathematics Teacher Education was devoted to the tasks and processes of teacher education (Tirosh & Wood, 2009). A particular relationship between teacher education and task design is the design of tasks for teacher education purposes. Mathematics teacher education, as a subfield of mathematics education, has paid significant recent attention to the nature, role and use of tasks with a triple special issue of the Journal of Mathematics Teacher Education (volume 10, 4-6) edited by Mason, Watson and Zaslavsky, and a book edited by Zaslavsky & Sullivan (2011)
The meaning of ‘task’
The word ‘task’ is used in different ways. In activity theory (Leont'ev, 1975) task means an operation undertaken within certain constraints and conditions (that is in a determinate situation, see Brousseau (1997)). Some writers (Christiansen & Walter, 1986; Mason & Johnston-Wilder, 2006) express ‘task’ as being what students are asked to do. Then ‘activity’ means the subsequent mathematical (and other) motives that emerge from interaction between student, teacher, resources, environment, and so on around the task. By contrast, in some professional traditions, ‘activity’ means a situation set up by the teacher in which a student has to engage in a certain way. Other traditions (e.g.Chevallard, 1999) distinguish between tasks, techniques, technology and theories, as a way to acknowledge the various aspects of a praxeology. We are also aware that ‘task’ sometimes denotes designed materials or environments which are intended to promote complex mathematical activity (e.g. Becker & Shimada, 1997), sometimes called ‘rich tasks’. In this study, we use ‘task’ to mean a wider range of ‘things to do’ than this, and include repetitive exercises, constructing objects,
Introduction
10
exemplifying definitions, solving single-stage and multi-stage problems, deciding between two possibilities, or carrying out an experiment or investigation. Indeed, a task is anything that a teacher uses to demonstrate mathematics, to pursue interactively with students, or to ask students to do something. Task can also be anything that students decide to do for themselves in a particular situation. Tasks, therefore, are the mediating tools for teaching and learning mathematics and the central issues are how tasks relate to learning, and how tasks are used pedagogically.
Task design
The design and use of tasks for pedagogic purposes is at the core of mathematics education (Artigue & Perrin-Glorian, 1991). Tasks generate activity which affords opportunity to encounter mathematical concepts, ideas, strategies, and also to use and develop mathematical thinking and modes of enquiry. Teaching includes the selection, modification, design, sequencing, installation, observation and evaluation of tasks. This work is often undertaken by using a textbook and/or other resources designed by outsiders.
The extent and detail of design varies widely among those who work on task design. For some (e.g., Shell Centre) design includes full necessary materials, task sequences and advice about effective choices, and detailed pedagogic advice about ways of working, verbal interventions, likely misconceptions and possibly extensions. For others (Ainley, Bills, & Wilson, 2004, 2005) there may be provision of a question, or a microworld, or some physical material, with no written object to describe ‘the complete task’, but rather a series of things that the teacher might say, perhaps supported by some written prompts. During the resulting activity, learners may ask questions or make comments to which the teacher needs to respond, and part of the design is trying to anticipate these and have a general picture of the shape of responses which would complement the task design. Another form of design is to refine a question or problem-situation until it is most likely to promote intriguing mathematical reactions (e.g., (ATM, various dates)). Sullivan, Zevenbergen, & Mousley (2006) have identified a need to design whole lesson sequences around certain types of tasks. All of these approaches have implications for implementation, with some relying on teachers’ existing skills, some providing advice to extend teachers’ skills, and others dependent on teachers maintaining or adapting the original task intentions (see, e.g., Kieran, Tanguay, & Solares, 2011).
Tasks also arise spontaneously in educational contexts, with teachers and/or learners raising questions or providing prompts for action by drawing on a repertoire of past experience. We are interested in how these are underpinned with implicit design principles.
Task sequences
This discussion of tasks may lead readers to assume that we are focused only on tasks as single events, but it is important to address also the question of sequences of tasks. There are different aspects embedded in the design of sequences and, while this is an obvious consideration when designing textbooks, it also stretches across the whole field of task design.
To achieve the goal of teaching a whole conceptual field (e.g., rational numbers), we have to describe the different aspects of this knowledge and the way the aspects are linked (for interesting examples see Brousseau, Brousseau, & Warfield, 2004a, 2004b, 2007, 2008, 2009). In Brousseau’s Theory of Didactic Situations (Brousseau, 1997), particular situations (or single tasks) are generated from more general situations. The earlier tasks in a sequence should provide experiences that scaffold the student in the solution of later tasks, allowing them to engage in more sophisticated mathematics than would otherwise have been the case. In some published sequences, the earlier tasks might be technical components to be used and
11
combined later; in others, the earlier tasks might provide images or experiences which enable later tasks to be undertaken with situational understanding.
To understand how tasks are linked in order to support teaching, it is important to understand the nature of the transformation of knowledge from implicit knowledge-in-action (see Vergnaud, 1982) to knowledge which is formulated, formalized, memorized, related to cultural knowledge, and so on.
However, there are different ways to create sequences of tasks, some of them are more commonly known by teachers themselves. One of these types of task sequences is that in which the problem formulation remains constant but the numbers used increase the complexity of the task, say moving from small positive integers (for which answers might be easy to guess) to other ranges of numbers for which a method might be needed. Another type of sequence is one in which the problem is progressively made more complex by the addition of steps or variables, such as in a network task where additional nodes are added. A third type of sequence may be one where the concept itself becomes more complex, such as in a sequence of finding areas or progressively more complex shapes from rectangles, to composite shapes, to irregular shapes. These different types of sequences, and their relation to the teaching unit as a whole, are often the focus of lesson study cycles, such as those reported in for example Corey, Peterson, Lewis, & Bukarau (2010); Huang & Bao (2006) Yoshida, (1999).
The importance of sequencing is explicit in Realistic Mathematics Education. In that tradition, a task sequence starts with situated problems (Gravemeijer, 1999), like dividing large numbers of people into smaller groups (quotative division problems) to evoke informal strategies and representations, and continues by changing the focus to formalizing and generalizing solution procedures, i.e. in this case a general algorithm that can be used for various division problems. In this type of task sequence the idea of 'guidance with didactical models' from informal to formal is important as an alternative strategy for the increasing mathematical complexity of problems students encounter (Van den Heuvel-Panhuizen, 2003). The situated problems are often already rather complex and can be solved before you know 'the' mathematical solution procedure, and therefore can be good starting points for problematizing a concept.
Design communities and methods
Of course, teachers also design tasks explicitly and deliberately. Whereas some authors think it desirable that designing and teaching are separate acts carried out by separate groups of people (e.g. Wittman, 1995), the experience of the authors of this discussion document indicates that the communities involved in task design are naturally overlapping and diverse. Design can involve designers, professional mathematicians, teacher educators, teachers, researchers, learners, authors, publishers and manufacturers, or combinations of these, and individuals acting in several of these roles. In the study, we wish to illuminate the diverse communities and methods that lead to the development and use of tasks. In all methods, the central consideration is the interaction between teachers and learners through the designed artefacts and/or the design process. A major focus in the study will therefore be on learning how design impacts on learners and learning, rather than research which focuses solely on the design process. For example, research which identifies implicit design principles would be of interest if connections are made between these principles and the impact on learning; research about identities of different players in the design process would be of interest if it contrasted ‘teacher-as-task-designer’ and ‘teacher-as-task-user’.
Introduction
12 References
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Sierpinska, A. (2003). Research in Mathematics Education: Through a Keyhole. In E. Simmt & B. Davis (Eds.),
Proceedings of the Annual Meeting of Canadian Mathematics Education Study Group: Acadia
University.
Sullivan, P. (1999). Seeking a rationale for particular classroom tasks and activities. In J. M. Truran & K. N. Truran (Eds.), Making the difference. Proceedings of the 21st Conference of the Mathematics
Educational Research Group of Australasia (pp. 15-29). Adelaide: MERGA.
Sullivan, P., Zevenbergen, R., & Mousley, J. (2006). Teacher actions to maximise mathematics learning opportunities in heterogeneous classrooms. International Journal in Science and Mathematics
Teaching, 4, 117-143.
Tirosh, D., & Wood, T. (Eds.). (2009). The International Handbook of Mathematics Teacher Education (Vol. 2). Rotterdam: Sense publishers.
Tzur, R., Sullivan, P., & Zaslavsky, O. (2008). Examining Teachers’ Use of (Non-Routine) Mathematical Tasks in Classrooms from three Complementary Perspectives: Teacher, Teacher Educator, Researcher. In O. Figueras & A. Sepúlveda (Eds.), Proceedings of the Joint Meeting of the 32nd Conference of the
International Group for the Psychology of Mathematics Education, and the 30th North American Chapter (Vol. 1, pp. 133-137). México: PME.
Valverde, G. A., Bianchi, L. J., Wolfe, R. G., Schmidt, W. H., & Houang, R. T. (2002). According to the Book.
Using TIMSS to investigate the translation of policy into practice through the world of textbooks.
Dordrecht: Kluwer Academic Publishers.
Van den Heuvel-Panhuizen, M. (2003). The didactical use of models in realistic mathematics education: an example from a longitudinal trajectory on percentage. Educational Studies in Mathematics, 54, 9-35. Vergnaud, G. (1982). Cognitive and developmental psychology and research in mathematics education: some
theoretical and methodological issues. For the Learning of Mathematics, 3(2), 31-41.
Watson, A., & Mason, J. (2006). Seeing an Exercise as a Single Mathematical Object: Using Variation to Structure Sense-Making. Mathematical Thinking and Learning, 8(2), 91-111.
Wittman, E. (1995). Mathematics Education as a 'Design Science'. Educational Studies in Mathematics, 29(4), 355-374.
Yoshida, M. (1999). Lesson study: A case study of a Japanese approach to improving instruction through
school-based teacher development. Doctoral dissertation, The University of Chicago, Chicago, IL.
Zaslavsky, O., & Sullivan, P. (Eds.). (2011). Constructing Knowledge for Teaching Secondary Mathematics
Introduction
15
Theme A
Tools and Representations
Allen Leung
Hong Kong Baptist University, Hong Kong
Janete Bolite Frant
LOVEME Lab, UNIBAN, Brazil
In the mathematics classroom, concrete tools (for example, compasses and ruler, unit blocks, interactive ICT platforms) are usually used as resources to enhance the teaching-learning activity (see for example, Bartolini Bussi & Maschietto, 2008; Maschietto & Trouche, 2010; Radford, 2011). In this context, tools are broadly interpreted as physical or virtual artefacts that have potential to mediate between mathematical experience and mathematical understanding. This theme concerns designing teaching-learning tasks that involve the use of tools in the mathematics classroom and consequently how, under such design, tools can represent mathematical knowledge. A task here is a teacher designed purposeful ‘thing to do’ using tools for students in order to activate an interactive tool-based environment where teacher, students and resources mutually enhance each other in producing mathematical experiences. On a meta-level, it is about possible tool-driven relationships within the design, teaching and learning triad. In this connection, this type of task design rests heavily on the complex relationship between artefacts and mathematical knowledge.
There are a few theoretical grounds on which to build and expand this discussion. Instrumental genesis explicates how the usage of a tool can be turned into a cognitive instrumentation process for knowledge acquisition. A Vygotskian approach examines how an artefact can be turned into a psychological tool in the context of social and cultural interaction developed through the zone of proximal development and internalization processes. Semiotic mediation can be used as an integrated approach to explore the mathematics classroom under which a tool takes on multiple pedagogical functions (Bartolini Bussi & Mariotti, 2008). Embodiment theory proposes that there are strong relationships among sensory activities and cultural artefacts in the appropriation of mathematical practices, and in particular, their application to inclusive mathematics education (Healy & Fernandes, 2011). The guided re-invention principle of RME (Realistic Mathematics Education) practiced by the Freudenthal school can be used to direct the design of tool-based mathematical tasks. These theoretical orientations, and/or others, may serve to facilitate discussion on tool-based task design and representation in the mathematics classroom.
An important question to address in this theme is: How to design tasks that can bring about situated discourses (hence representations) for the mathematical knowledge mediated by tools in the mathematics classroom and how these discourses relate to mathematics knowledge? This in turn comprises several additional questions.
Possible questions about tools and representation:
•What mathematics epistemological considerations are taken into account when designing tasks using tools?
Theme A - Introduction
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•How do we create a tool environment for the mathematics classroom to support the design of teaching and learning tasks for specific mathematic topics?
•How do different types of tools afford different mathematical activities/tasks, different representations and/or discourses, and different interactions between representations?
•How do different task designs using tools impact on students’ learning and understanding of mathematics?
•How do we design mathematical tasks that can transform an artefact into a pedagogical instrument?
•Are there models (theoretical or pragmatic) of tool-based task design for the teaching and learning of mathematics?
References
Bartolini Bussi, M., & Maschietto, M. (2008). Machines as tools in teacher education. In D. Tirosh & T. Wood (Eds.), Tools and Processes in Mathematics Education. Rotterdam: Sense Publishers.
Bartolini Bussi, M. G., & Mariotti, M. A. (2008). Semiotic mediation in the mathematics classroom. Artifacts and signs after a Vygotskian perspective. In L. English, M. Bartolini Bussi, G. A. Jones, R. A. Lesh & B. Sriraman (Eds.), Handbook of International Research in Mathematics Education (pp. 746-783). New York and London: Routledge.
Healy, L., & Fernandes, S. H. A. A. (2011). The role of gestures in the mathematical practices of those who do not see with their eyes. Educational Studies in Mathematics, 77, 157-174.
Maschietto, M., & Trouche, L. (2010). Mathematics learning and tools from theoretical, historical and practical points of view: the productive notion of mathematics laboratories. ZDM - The International Journal on
Mathematics Education, 42, 33-47.
Radford, L. (2011). On the Cognitive, Epistemic, and Ontological Roles of Artifacts. In G. Gueudet, B. Pepin & L. Trouche (Eds.), From Text to 'Lived' Resources Mathematics Curriculum Materials and Teacher
17
Using crises, feedback and fading for online task design
Christian Bokhove
University of Southampton, United Kingdom
A recent discussion involves the elaboration on possible design principles for sequences of tasks. This paper builds on three principles, as described by Bokhove and Drijvers (2012b). A model with ingredients of crises, feedback and fading of sequences with near-similar tasks can be used to address both procedural fluency and conceptual understanding in an online environment. Apart from theoretical underpinnings, this is demonstrated by analysing a case example from a study conducted in nine schools in the Netherlands. Together with quantitative results of the underlying study, it shows that the model described, could be a fruitful addition to the task design repertoire.
Keywords: task, design, sequence, near-similar, crisis, feedback, fading
Introduction
In recent years more and more attention has been paid to task design. In the call for papers for the 22ndICMI study on task design the reasons for this are clearly described. One problem is that tasks are often only described vaguely. Furthermore, Schoenfeld (2009) advises on having more communication between designers and researchers. In this way educational research and design can be bridged, as the communities involving task design are naturally overlapping and diverse. This paper was triggered by some of the remarks that were made in the call for papers:
The topic of understanding whether and how doing tasks, of whatever kind, enable conceptual learning. The study reported in this paper supports Lagrange (2002) who suggested that applying routine techniques can achieve results, and also provide the basis for conceptual understanding and new theorizing.
To not only address tasks as single events, but also address the question of sequences of tasks.
It is suggested that the design of sequences of near-similar tasks deserves attention. Therefore, the paper makes a point of defining a ‘task’ to mean a wider range of ‘things to do’ than just one task, and include repetitive exercises.
Several types of task sequences are mentioned. “One of these types of task sequences is that in which the problem formulation remains constant but the numbers used increase the complexity of the task, say moving from small positive integers (for which answers might be easy to guess) to other ranges of numbers for which a method might be needed.”. Building on an earlier article (Bokhove & Drijvers, 2012b) an extra type of task sequences is proposed, whereby the complexity of tasks first increases, and then –with the help of feedback- decreases.
In one sense this can be seen as an adaptation of the ‘variation’ Watson and Mason (2006) coined: “From a modelling perspective the term micromodelling’ may be helpful to describe learners’ response to exercises in which dimensions of variation have been carefully
Theme A – C. Bokhove
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controlled, because the aim is to promote generalization of the dimensions being varied in the exercise, and thence to focus on mathematical relationships between dimensions.” (p.104)
Summarizing these points we would want to formulate design principles for: (i) sequences of tasks; (ii) near similar and/or repetitive tasks; and (iii) addressing both conceptual understanding and procedural fluency. This paper synthesizes, elaborates on and illustrates design principles of a study first described by Bokhove and Drijvers (2012a, b). The principles regarding crises, feedback and fading are applied to a sequence of digital tasks. This paper sets out to describe the three principles in an additional cohesive model, and describes one case example of student work. Bearing the aforementioned goals in mind it should be a model that could prove to be fruitful while designing tasks. The model bears elements of both my roles as a designer and researcher when doing my PhD as a teacher at a secondary school in the Netherlands. The study called ‘Algebra met Inzicht’ [Algebra with Insight] was designed in the Digital Mathematical Environment (http://www.fi.uu.nl/dwo/en)1. The intervention consists of a pen-and-paper pre-test, four digital modules, a digital diagnostic test, and a final digital test and, finally, a pen-and-paper post-test. It was deployed in fifteen 12th grade classes from nine Dutch secondary schools (N=324), involving eleven mathematics teachers. The schools were spread across the country and showed a variation in school size and pedagogical and religious backgrounds. The participating classes consisted of pre-university level ‘wiskunde B’ students (comparable to grade 12 in Anglo-Saxon countries). As this article is about design principles, I refer to different articles for more details of the set-up of the study and the actual effects of the digital intervention (Bokhove & Drijvers, 2012a, b).
Figure 1 shows the proposed model for sequences of (near-similar) tasks.
figure 1: proposed model for crises, feedback and fading
I contend that it is okay to use near-similar tasks and repetitive exercises, but suggest that the sequence is interspersed by intentional crises i.e. tasks that are hard or impossible to solve with skills and knowledge that are available. In other words, the ‘load’ of the task is too high. I will not go into the word ‘load’ in detail. There is a vast body of knowledge connected to the term Cognitive Load Theory (Sweller, 1988). There also is, rightly so, criticism (De
1 An English translation of part of the module can be found at http://www.fi.uu.nl/dwo/soton. Log in as guest, and choose ‘Demo for 22nd ICMI study’. Java is needed.
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Jong, 2010). For the purpose of this paper, we will only assume that knowledge that isn’t known potentially will bear a larger load than unknown knowledge. Then, let students overcome crises by providing feedback. To avoid a dependency on feedback for the summative assessments fade the feedback during the course of the sequence of tasks.
A model for sequences of near-similar tasks
I will first elaborate on the three main ingredients of the model: crises, feedback and fading.
With a crisis we refer to a principle that the poet John Keats so eloquently described in the early 19th century ‘failure is the highway to success’. This principle corresponds to similar concepts that have been described during the years. Piaget (1964) used the concept of equilibrium and disequilibrium. Essentially, whenever the child’s experience/interaction with the environment yielded results that confirmed her mental model, she could easily assimilate the experience. When the experience resulted in something new and unexpected, the result was disequilibrium, and a child may experience this as confusion or frustration. Eventually, the child changes his or her cognitive structures to accommodate the new experience and moves back into equilibrium. Piaget studied the individual case, on a societal level Kuhn (1962) referred to a paradigm shift, arguing that scientific advancement is not evolutionary, but rather a “series of peaceful interludes punctuated by intellectually violent revolutions”, and that in those revolutions “one conceptual world view is replaced by another”. Tall (1977) refers to cognitive conflicts: “one of the distinguishing factors in catastrophe theory is the existence of discontinuities, or sudden jumps in behaviour when certain paths are taken.”. In his ‘levels of thinking’ van Hiele (1985) discerns structure and insight. There can be a ‘crisis of thinking’, which has a link to the vygotskian zone of proximal development. The common ground between the two is that there is a need for challenge. More recently, Kapur (2010) uses the term productive failure and cites Clifford (1984): “However, allowing for the concomitant possibility that under certain conditions letting learners persist, struggle, and even fail at tasks that are complex and beyond their skills and abilities may in fact be a productive exercise in failure requiring a paradigm shift”. Kapur explains this by stating that it is reasonable to reinterpret their central findings collectively as an argument for a delay of structure in learning and problem-solving situations, be it in the form of, feedback and explanations, coherence in texts, or direct instruction. The difference with my own work (Bokhove & Drijvers, 2012b) seems to be whether crisis are an inherent part of learning when solving open problems, or actually embedding tasks that could intentionally cause a crisis. It is proposed that intentional crisis tasks are added to sequences of near-similar tasks, for example in the way depicted in table, which illustrates the way in which crisis items are integrated within the digital tool. The general structure of a sequence is: pre-crisis items, crisis item, post-crisis items. But then the question becomes: how can students address this crisis? Can we add another principle which enables students to use assessment for learning. One way would be to make use of formative assessment. Black and Wiliam (1998) define assessment as being ‘formative’ only when feedback from learning activities is actually used to modify teaching to meet the learner’s needs. From this it is clear that feedback plays a pivotal role in the process of formative assessment. Hattie and Timperley (2007) conducted a meta-review of the effectiveness of different types of feedback. The feedback effects of hints and corrective feedback are deemed best. However, in my personal experience as a teacher I have seen there can be an over-reliance on feedback that is provided. Assuming that students finally have to pass an exam themselves, it makes sense to address this over-reliance on feedback. In a follow-up paper Kapur (2011) notes that scaffolding implies help to overcome failure (Pea 2004). It turns out that when dealing with previously stored information in the long term memory, these limits tend to disappear.
Theme A – C. Bokhove
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1.1 Tasks: “Solve the following equation:” Pre-crisis items
In the initial items students are confronted with equations they have experience with. Students may choose their own strategy. Many students choose to expand brackets as that is the strategy that they have used often: work towards the form 0 and use the Quadratic Formula. There is some limited feedback on the task.
1.2 1.3 1.4
1.5
1.6 Crisis item
Students are then confronted with an intentional crisis: if a student uses his/her conventional strategy of expanding the expression. The yellow tick at the bottom of the screen denotes that the equation is algebraically equivalent to the initial one, but that it is not the final answer. This is accompanied by a partial score for an item and some feedback in Dutch: ‘You are rewriting correctly’. Although these students showed good rearranging skills, in the end they were not able to continue, as they did not master the skill to solve a third order equation. There is some limited feedback on the task.
1.7
1.8 Post-crisis items
After the crisis item students are offered help by providing a ‘voorbeeldfilm’, an instructional screencast, and buttons to get hints (‘tip’), the next step in the solution (‘stap’) or a worked solution (‘losop’). These features have in common that they provide feedforward information at the task level and self-regulation.
1.9 1.10 1.11 1.12 1.13
table1: Sequence of items illustrating crises and feedback
As Kirschner et al (2006) argued “any instructional theory that ignores the limits of working memory when dealing with novel information or ignores the disappearance of those limits when dealing with familiar information is unlikely to be effective.“ As a design principle it is therefore proposed that initially a lot of feedback is provided to foster learning, but the amount is decreased towards the end, to facilitate transfer. Using scaffolding this way is based on the concept of fading (Renkl, Atkinson, & Große, 2004). Formative scenarios
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(Bokhove, 2008) are a variation of this concept, starting off with much feedback, and providing a gradually decreasing level of feedback. Figure 2 shows how this principle was implemented in the intervention. At the start feedback is provided for all intermediate steps of a solution. The subsequent part of the intervention concerns self-assessment and diagnostics: the student performs the steps without any feedback and chooses when to check his or her solution by clicking a “check” button. Feedback is then given for the whole of the exercise.
figure 2: Outline of fading feedback in formative scenarios
Finally, students get a final exam with no means to see how they performed. Just as is the case with a paper test, the teacher will be able to check and grade the exam (in this case automatically) and give students feedback on their performance. A student needs to be able to accomplish tasks independently, without the help of a computer. An implicit advantage of implementing feedback in a sequence of tasks is that teachers and designers have to think upfront about possible student responses.
Principles at work: a case example
Let’s look at one student named Paula during the course of this module. The student starts off with a pre-test. Apart from the calculation error on the right hand side of the equation, figure 3 clearly shows that Paula’s strategy here is to expand the expressions, similar to students in earlier phases of the study (Bokhove & Drijvers, 2010).
Theme A – C. Bokhove
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Not surprisingly this strategy fails in the case of this equation. Paula only scores 14 out of 100 for the whole pre-test. With regard to symbol sense, Paula scores a -4 for (for details on the calculation I refer to Bokhove & Drijvers, 2012a). Paula then starts with the sequence of digital tasks. In the first task the student has to get acquainted with the digital environment. The pre-crisis items pose no problem for most students, including Paula. On arriving at the crisis item students roughly exhibit three behaviours, roughly corresponding with the ones already observed in the pre-test: (i) students solve the equation correctly, (ii) students recognize the pattern of the equation but subsequently make mistakes (for example by losing solutions in the process), and (iii) students expand the expressions and get stuck with an equation with a third power. Figure shows that our case student Paula again shows the third type of behaviour. At this moment feedback is still restricted to correct/incorrect. In addition, students are allowed to choose their own strategies, even when they aren’t efficient or would lead to problems. In the post-crisis items, as well as feedback correct/incorrect, Paula is provided with buttons for hints, and a movie clip demonstrating the solution. From the log-files of the online environment it becomes clear that Paula fails at the crisis-item (0 out of 10), but succeeds at the post-crisis item with feedback (10 out of 10). When looking at attempts made, Paula attempts the crisis-item 73 times, and the post-crisis item, being aided by feedback, only 3 times.
Figure 4: Paula’s digital work. Left: crisis item left. Right: post-crisis item
Finally, in the post-test Paula shows a significant increase in the total score (70 out of 100) and symbol sense behaviour (+1, an increase of 5). Even though mistakes are made they were not caused by a lack of symbol sense any more but errors in calculations. Focusing only on similar types of equations it becomes clear that Paula manages to solve these equations correctly. Paula is not a unique case in this school. Overall, students in participating schools improved on their scores and symbol sense behaviour.
Conclusion
Illustrated by the theoretical underpinnings, the overall results in the study, and case example, it is concluded it would be a good idea to study design principles that can be used to design sequences of near-similar tasks in more detail. By combining three principles from an initial study -crises, feedback and fading- in one model for sequences of tasks, three important aspects of this ICMI study are addressed: (i) sequences of tasks; (ii) near similar and/or repetitive tasks; and (iii) addressing both conceptual understanding and procedural fluency. We propose that educators, teachers, designers and researchers alike can adopt these principles when designing and implementing sequences of (near-similar) tasks. It is, however, important to note some points of discussion. The difficulty of every task or sequence of tasks depends on the context. What can be a simple task for one year eight student can prove to be difficult for another student, even when at first sight they seem fairly similar. Also, the way in
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which a crisis is overcome can differ: some students learn from repeating near-similar tasks, others seem to recognize ‘a pattern’ immediately and apply this to new tasks. Given this diversity, it is important to field-test and evaluate sequences of tasks, again combining the power of teaching, researching and designing. I think it would be unfair to indefinitely classify certain tasks as ‘more creative’ and other tasks as ‘less creative’. This, too depends on the background and context of the learner: a wonderful, new and creative task can become a repetitive task the second time around. Looking back on this paper I wonder whether the predicate ‘near-similar’ does not actually apply to all tasks, if a student has seen a task before, even the elaborate, creative ones. It is my wish that we look at the total picture, and integrate all these tasks in one clear picture for the learning student. One way would be to not so much study the nature of solitary tasks but place them in sequences and their corresponding contexts. Hopefully, this paper provides general design principles that can be used, and task design can be taken forward.
References
Black, P., & Wiliam, D. (1998). Inside the Black Box: Raising Standards Through Classroom Assessment. Phi
Delta Kappan, 80(2), 139–149.
Bokhove, C. (2008, June). Use of ICT in formative scenarios for algebraic skills. Paper presented at the 4th conference of the International Society for Design and Development in Education, Egmond aan Zee, the Netherlands.
Bokhove, C., & Drijvers, P. (2010). Symbol sense behavior in digital activities. For the Learning of
Mathematics, 30(3), 43-49.
Bokhove, C., & Drijvers, P. (2012a). Effects of a digital intervention on the development of algebraic expertise.
Computers & Education, 58(1), 197-208. doi:10.1016/j.compedu.2011.08.010.
Bokhove, C., & Drijvers, P. (2012b). Effects of feedback in an online algebra intervention. Technology,
Knowledge and Learning. Advance online publication. doi:10.1007/s10758-012-9191-8.
Clifford, M. M. (1984). Thoughts on a theory of constructive failure. Educational Psychologist, 19(2), 108–120. Hattie, J., & Timperley, H. (2007). The Power of Feedback. Review of Educational Research, 77(1), 81–112. Jong, T. (2010). Cognitive load theory, educational research, and instructional design: some food for thought.
Instructional Science, 38(2), 105-134. doi:10.1007/s11251-009-9110-0
Kapur, M (2010). Productive failure in mathematical problem solving. Instructional Science, 38,(6), 523-550. Kapur, M. (2011). A further study of productive failure in mathematical problem solving: Unpacking the design
components. Instructional Science, 39,(4), 561-579.
Kirschner, P. A., Sweller, J., & Clark, R. E. (2006). Why minimal guidance during instruction does not work.
Educational Psychologist, 41(2), 75–86.
Kuhn, T. S. (1962). The Structure of Scientific Revolutions. Chicago: University of Chicago Press.
Lagrange, J.-B. (2002). Etudier les mathématiques avec les calculatrices symboliques. Quelle place pour les techniques? In D. Guin & L. Trouche (Eds.), Calculatrices symboliques. Transformer un outil en un
instrument du travail mathématique : un problème didactique (pp. 151-185). Grenoble: La Pensée
Sauvage.
Pea, R. D. (2004). The social and technological dimensions of scaffolding and related theoretical concepts of learning, education, and human activity. Journal of the Learning Sciences, 13(3), 423–451.
Piaget, J. (1964). Development and learning. In R. E. Ripple & V. N. Rockcastle (Eds.), Piaget Rediscovered (pp. 7-20). New York: Cornell University Press.
Renkl, A., Atkinson, R. K., & Große, C. S. (2004). How fading worked solution steps works – a cognitive load perspective. Instructional Science, 32(1/2), 59–82.
Schoenfeld, A. H. (2009). Bridging the cultures of educational research and design. Educational Designer, 1(2). Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12(2), 257–
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Tall, D. (1977). Cognitive Conflict and the Learning of Mathematics. In Proceedings of the First Conference of The International Group for the Psychology of Mathematics Education. Utrecht, Netherlands: PME. Retrieved from http://www.warwick.ac.uk/staff/David.Tall/pdfs/dot1977a-cog-confl-pme.pdf
Van Hiele, P. M. V. (1985). Structure and Insight: A Theory of Mathematics Education. Orlando, FL: Academic Press.
Watson, A., & Mason, J. (2006). Seeing an exercise as a single mathematical object: Using variation to structure sense-making. Mathematical Thinking and Learning, 8(2), 91-111.
Theme A – C. Bokhove
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A Holistic Approach for Designing Tasks that Capture and
Enhance Mathematical Understanding of a Particular Topic: The
Case of the Interplay between Examples and Proof
Orly Buchbinder
The Center for Mathematics Education, UMD & Technion – Israel Institute of Technology
Orit Zaslavsky
New York University & Technion – Israel Institute of Technology
This study2 illustrates an approach to task design that aims at revealing and enhancing students’ understandings of a particular mathematical topic: the roles of examples in proving and refuting mathematical statements. As a preliminary stage we conducted a content analysis that led to the construction of a comprehensive mathematical framework that describes the various aspects of understanding this topic. Based on this framework, we constructed six prototypes of tasks that complement each other in assessing and enhancing students' understanding of the logical connections between examples and statements. In this paper we describe the design principles that guided the construction of the collection of tasks that can be considered a special kind of tool and provide illustrations of how this tool was used.
Keywords: task design, examples, reasoning and proof
Introduction and Background
With the current curricular emphasis on students’ engagement in mathematical investigations and proving, it becomes increasingly important that students develop the understanding of the logical connections between empirical and formal aspects of mathematics. Such understanding manifests itself in understanding of the roles of examples proving and refuting conjectures. Despite the fact that several studies indicate that students encounter difficulties in this area (Fishbein, 1987, Antonini et al., 2011, Bills & Watson, 2008), such connections are not explicitly addressed in the school curriculum and are left to students to develop indirectly mostly on their own. Moreover, there is only scarce work in conceptualizing what constitutes an understanding of the roles of examples in proving (e.g., Zaslavsky & Ron, 1998, Barkai et.al., 2008, Buchbinder & Zaslavsky, 2009, Tabach et. al., 2010). The goal of our study was to develop a tool that could be used both to assess students’ overall understanding of the above topic and to enhance these understandings. Moreover, we were looking for a tool that would help capture the
2 This study was conducted at the Technion – Israel Institute of Technology with support of Israeli Ministry of Education.
