Comparing the effects of representational tools in collaborative and individual inquiry learning

Constructing a representation in which students express their domain understanding can help them improve their knowledge. Many different representational formats can be used to express one’s domain understanding (e.g., concept maps, textual summaries, mathematical equations). The format can direct students’ attention to specific aspects of the subject matter. For example, creating a concept map can emphasize domain concepts and forming equations can stress arithmetical aspects. The focus of the current study was to examine the role of tools for constructing domain representations in collaborative inquiry learning. The study was driven by three questions. First, what are the effects of collaborative inquiry learning with representational tools on learning outcomes? Second, does format have differential effects on domain understanding? And third, does format have differential effects on students’ inclination to construct a representation? A pre-test post-test design was applied with 61 dyads in a (face-to-face) collaborative learning setting and 95 students in an individual setting. The participants worked on a learning task in a simulation-based learning environment equipped with a representational tool. The format of the tool was either conceptual or arithmetical or textual. Our results show that collaborative learners outperform individuals, in particular with regard to intuitive knowledge and situational knowledge. In the case of individuals a positive relation was observed between constructing a representation and learning outcomes, in particular situational knowledge. In general, the effects of format could not be linked directly to learning outcomes, but marked differences were found regarding students’ inclination to use or not use specific formats.

[1]  P. V. Meter,et al.  The Promise and Practice of Learner-Generated Drawing: Literature Review and Synthesis , 2005 .

[2]  Michael J. Baker,et al.  How do argumentation diagrams compare when student pairs use them as a means for debate or as a tool for representing debate? , 2007, Int. J. Comput. Support. Collab. Learn..

[3]  Ton de Jong,et al.  Discovery simulations and the assessment of intuitive knowledge , 2001, J. Comput. Assist. Learn..

[4]  Henny van der Meijden,et al.  Face-to-face versus computer-mediated communication in a primary school setting , 2005, Comput. Hum. Behav..

[5]  Daniel D. Suthers,et al.  Comparing the roles of representations in face-to-face and online computer supported collaborative learning , 2003, Comput. Educ..

[6]  Geraldine Clarebout,et al.  The relationships between learner variables, tool-usage behaviour and performance , 2009, Comput. Hum. Behav..

[7]  Adrianus W. Lazonder,et al.  The guided discovery principle in multimedia learning. , 2005 .

[8]  Herbert A. Simon,et al.  Why a Diagram is (Sometimes) Worth Ten Thousand Words , 1987 .

[9]  Joseph D. Novak,et al.  Meaningful learning: The essential factor for conceptual change in limited or inappropriate propositional hierarchies leading to empowerment of learners , 2002 .

[10]  R. Slavin.  Cooperative Learning: Theory, Research and Practice , 1990 .

[11]  Jianwei Zhang,et al.  Triple scheme of learning support design for scientific discovery learning based on computer simulation: experimental research , 2004, J. Comput. Assist. Learn..

[12]  Katharina Scheiter,et al.  Learning with hypermedia: The influence of representational formats and different levels of learner control on performance and learning behavior , 2009, Comput. Hum. Behav..

[13]  Mitchell J. Nathan,et al.  A theory of algebra-word-problem comprehension and its implications for the design of learning environments. , 1992 .

[14]  Toon Calders,et al.  Proceedings of the International Workshop on Applying Data Mining in e-Learning (ADML-2007, Sissi, Crete, Greece, September 18, 2007) , 2008 .

[15]  Shaaron Ainsworth,et al.  The effects of self‐explaining when learning with text or diagrams , 2003 .

[16]  C. Boxtel,et al.  Collaborative learning tasks and the elaboration of conceptual knowledge. , 2000 .

[17]  K. Koedinger,et al.  Designing Knowledge Scaffolds to Support Mathematical Problem Solving , 2005 .

[18]  Joan Garfield,et al.  Difficulties in Learning Basic Concepts in Probability and Statistics: Implications for Research. , 1988 .

[19]  Heinz Mandl,et al.  Supporting learning using external representations , 2008, Comput. Educ..

[20]  Helge I. Strømsø,et al.  Content and processes in problem-based learning: a comparison of computer-mediated and face-to-face communication , 2007, J. Comput. Assist. Learn..

[21]  Valerie Anderson,et al.  Producing Written Summaries: Task Demands, Cognitive Operations, and Implications for Instruction , 1986 .

[22]  Jiajie Zhang,et al.  The Nature of External Representations in Problem Solving , 1997, Cogn. Sci..

[23]  Meekyoung Kim,et al.  Do students benefit equally from interactive computer simulations regardless of prior knowledge levels? , 2009, Comput. Educ..

[24]  John Sweller,et al.  Cognitive technology: Some procedures for facilitating learning and problem solving in mathematics and science. , 1989 .

[25]  James J. Kaput,et al.  Creating Cybernetic and Psychological Ramps from the Concrete to the Abstract: Examples from Multiplicative Structures , 1997 .

[26]  Jianwei Zhang,et al.  Supporting scientific discovery learning in a simulation environment , 2003, J. Comput. Assist. Learn..

[27]  Geraldine Clarebout,et al.  The complexity of tool use in computer-based learning environments , 2009 .

[28]  Y. Lou,et al.  Small Group and Individual Learning with Technology: A Meta-Analysis , 2001 .

[29]  Yun-Ke Chang,et al.  Collaborative learning in wikis , 2011, Educ. Inf..

[30]  Pieter Wouters,et al.  Learner Performance in Multimedia Learning Arrangements: An Analysis Across Instructional Approaches , 2009 .

[31]  Graham Alfred Jones,et al.  Exploring Probability in School: Challenges for Teaching and Learning , 2005 .

[32]  J. Novak.  Concept maps and Vee diagrams: two metacognitive tools to facilitate meaningful learning , 1990 .

[33]  R. Mayer.  Rote Versus Meaningful Learning , 2002 .

[34]  Nadira Saab,et al.  Supporting Communication in a Collaborative Discovery Learning Environment: the Effect of Instruction , 2007 .

[35]  Richard Catrambone,et al.  Aiding Transfer in Statistics: Examining the Use of Conceptually Oriented Equations and Elaborations during Subgoal Learning. , 2003 .

[36]  Ton de Jong,et al.  The influence of learner-generated domain representations on learning combinatorics and probability theory , 2010, Comput. Hum. Behav..

[37]  Joseph Krajcik,et al.  A Scaffolding Design Framework for Software to Support Science Inquiry , 2004, The Journal of the Learning Sciences.

[38]  Geraldine Clarebout,et al.  Benefits of inserting support devices in electronic learning environments , 2009, Comput. Hum. Behav..

[39]  Daniel D. Suthers,et al.  An Experimental Study of the Effects of Representational Guidance on Collaborative Learning Processes , 2003 .

[40]  Ton de Jong,et al.  Facilitating collaborative inquiry learning with shared concept maps and propositions tables , 2006 .

[41]  U. Wilensky.  Paradox, programming, and learning probability: A case study in a connected mathematics framework , 1995 .

[42]  D. Suthers,et al.  “Mapping to know”: The effects of representational guidance and reflective assessment on scientific inquiry , 2002 .

[43]  Ton de Jong,et al.  Co-Lab: research and development of an online learning environment for collaborative scientific discovery learning , 2005, Comput. Hum. Behav..

[44]  Anthonius J.M. de Jong,et al.  Types and qualities of knowledge , 1993 .

[45]  A. Renkl,et al.  Instructional Aids to Support a Conceptual Understanding of Multiple Representations. , 2009 .

[46]  Daniel D. Suthers,et al.  Empirical Studies of the Value of Conceptually Explicit Notations in Collaborative Learning , 2008 .

[47]  Jeroen Janssen,et al.  Visualization of agreement and discussion processes during computer-supported collaborative learning , 2007, Comput. Hum. Behav..

[48]  Ton de Jong,et al.  Technological Advances in Inquiry Learning , 2006 .

[49]  Elwin R. Savelsbergh,et al.  The Relation between Students’ Epistemological Understanding of Computer Models and their Cognitive Processing on a Modelling Task , 2009 .

[50]  Jan Elen,et al.  The use of support devices in electronic learning environments , 2009, Comput. Hum. Behav..

[51]  J. Hiebert.  Conceptual and procedural knowledge : the case of mathematics , 1987 .

[52]  Daniel D. Suthers,et al.  Beyond threaded discussion: Representational guidance in asynchronous collaborative learning environments , 2008, Comput. Educ..

[53]  R. Cox.  Representation construction, externalised cognition and individual differences , 1999 .

[54]  Carole Greenes.  Mathematics Learning and Knowing: A Cognitive Process , 1995 .

[55]  Ton de Jong,et al.  Scientific Discovery Learning with Computer Simulations of Conceptual Domains , 1998 .

[56]  Richard Mayer,et al.  Multimedia Learning , 2001, Visible Learning Guide to Student Achievement.

[57]  T. Jong,et al.  Measuring intuitive knowledge in science: The development of the what-if test , 1996 .

[58]  James E. Tarr,et al.  How Can Teachers Build Notions of Conditional Probability and Independence , 2005 .

[59]  Olusola O. Adesope,et al.  Learning With Concept and Knowledge Maps: A Meta-Analysis , 2006 .

[60]  Lloyd P. Rieber,et al.  Discovery learning, representation, and explanation within a computer-based simulation: finding the right mix , 2004 .

[61]  J. Hiebert,et al.  Conceptual and Procedural Knowledge in Mathematics: An Introductory Analysis , 1986 .

[62]  Elwin R. Savelsbergh,et al.  The effect of external representation on constructing computer models of complex phenomena , 2003 .

[63]  Peter C.-H. Cheng,et al.  Unlocking conceptual learning in mathematics and science with effective representational systems , 1999, Comput. Educ..

[64]  Michael J. Hannafin,et al.  Scaffolding in technology-enhanced learning environments , 2007, Interact. Learn. Environ..

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

[66]  Paul W. Foos,et al.  The effect of variations in text summarization opportunities on test performance , 1995 .

[67]  David N. Perkins,et al.  Software Goes to School: Teaching for Understanding with New Technologies. , 1997 .

[68]  Ton de Jong,et al.  Regulative support for collaborative scientific inquiry learning , 2006, J. Comput. Assist. Learn..

[69]  B. Rittle-Johnson,et al.  Developing Conceptual Understanding and Procedural Skill in Mathematics: An Iterative Process. , 2001 .

[70]  R. Mayer.  Should there be a three-strikes rule against pure discovery learning? The case for guided methods of instruction. , 2004, The American psychologist.

[71]  David Niemi,et al.  Assessing Conceptual Understanding in Mathematics: Representations, Problem Solutions, Justifications, and Explanations , 1996 .

[72]  R. Ploetzner,et al.  Collaborative Inquiry Learning: Models, tools, and challenges , 2010 .

[73]  Brian J. Reiser,et al.  Scaffolding Complex Learning: The Mechanisms of Structuring and Problematizing Student Work , 2004, The Journal of the Learning Sciences.

[74]  Uday S. Murthy,et al.  Divergent and Convergent Idea Generation in Teams: A Comparison of Computer-Mediated and Face-to-Face Communication , 2004 .

[75]  Stellan Ohlsson,et al.  An Information Processing Analysis of the Function of Conceptual Understanding in the Learning of Arithmetic Procedures. , 1988 .

[76]  Janine Swaak,et al.  Self-directed learning in simulation-based discovery environments , 1998, J. Comput. Assist. Learn..

[77]  Wouter R. van Joolingen,et al.  Students' reasoning during modeling in an inquiry learning environment , 2005, Comput. Hum. Behav..

[78]  Randy L. Bell,et al.  The use of a computer simulation to promote conceptual change: A quasi-experimental study , 2010, Comput. Educ..

[79]  Lynn S. Fuchs,et al.  Enhancing mathematical problem solving among third-grade students with schema-based instruction , 2004 .

[80]  Geraldine Clarebout,et al.  Tool use in computer-based learning environments: towards a research framework , 2006, Comput. Hum. Behav..

[81]  A. Lesgold,et al.  Software support for students engaging in scientific activity and scientific controversy , 1994 .

[82]  Gellof Kanselaar,et al.  Effects of representational guidance on domain specific reasoning in CSCL , 2005, Comput. Hum. Behav..

[83]  Daniel D. Suthers,et al.  Technology affordances for intersubjective meaning making: A research agenda for CSCL , 2006, Int. J. Comput. Support. Collab. Learn..

[84]  Ton de Jong,et al.  Sharing and Confronting Propositions in Collaborative Inquiry Learning , 2009 .

[85]  Peggy Noel Van Meter,et al.  Learner-generated drawing as a strategy for learning from content area text , 2006 .

[86]  Anjo Anjewierden,et al.  Towards educational data mining: Using data mining methods for automated chat analysis to understand and support inquiry learning processes , 2007 .