Fostering complex learning-task performance through scripting student use of computer supported representational tools

This study investigated whether scripting student use of computer supported representational tools fostered students' collaborative performance of a complex business-economics problem. Scripting the problem-solving process sequenced and made its phase-related part-task demands explicit, namely (1) determining core concepts, (2) proposing multiple solutions, and (3) coming to a final solution. The representational tools facilitated students in constructing specific representations of the domain (i.e., conceptual, causal, or mathematical) and were each suited for carrying out the part-task demands of a specific phase. Student groups in four experimental conditions had to carry out all part-tasks in a predefined order, but differed in the representational tool(s) they received during their collaborative problem-solving process. In three mismatch conditions, student groups received either a conceptual, causal, or simulation representational tool which supported them in only carrying out one of the three part-tasks. In the match condition, student groups received the three representational tools in the specified order, each matching the part-task demands of a specific problem phase. The results revealed that student groups in the match condition constructed more task-appropriate representations and had more elaborated and meaningful discussions about the domain. As a consequence, those student groups performed better on the complex learning-task. However, similar results were obtained by student groups who only received a representational tool for constructing causal representations for all part-tasks.

[1]  Janet Mannheimer Zydney The effect of multiple scaffolding tools on students' understanding, consideration of different perspectives, and misconceptions of a complex problem , 2010, Comput. Educ..

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

[3]  Andrew T. Stull,et al.  Three Experimental Comparisons of Learner-generated versus Author-provided Graphic Organizers , 2007 .

[4]  Leslie J. Briggs,et al.  Principles of Instructional Design , 1974 .

[5]  Simon Buckingham Shum,et al.  Visualizing Argumentation: Software Tools for Collaborative and Educational Sense-Making , 2012 .

[6]  E. Paice,et al.  Collaborative learning , 2003, Medical education.

[7]  A. E. Veldhuis-Diermanse CSCLearning? Participation, learning activities and knowledge construction in computer-supported collaborative learning in higher education (Summary PhD dissertation) , 2002 .

[8]  Richard F. Schmid,et al.  Supporting the Learning Process with Collaborative Concept Mapping Using Computer-Based Communication Tools and Processes , 2001 .

[9]  Andrei Popescu-Belis,et al.  What are discourse markers ? , 2003 .

[10]  P. Kirschner,et al.  CSCL in higher education?: a framework for designing multiple collaborative environments , 2004 .

[11]  Symeon Retalis,et al.  Using computer supported collaborative learning strategies for helping students acquire self-regulated problem-solving skills in mathematics , 2010, Comput. Educ..

[12]  Pei-Lin Liu,et al.  Effects of a computer-assisted concept mapping learning strategy on EFL college students' English reading comprehension , 2010, Comput. Educ..

[13]  D. Cicchetti,et al.  A Computer Program for Assessing Specific Category Rater Agreement for Qualitative Data , 1978 .

[14]  Nasser Mansour,et al.  Exploring creative thinking in graphically mediated synchronous dialogues , 2010, Comput. Educ..

[15]  David H. Jonassen,et al.  Using Cognitive Tools to Represent Problems , 2003 .

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

[17]  Pierre Dillenbourg,et al.  What we know about CSCL and implementing it in higher education , 2004 .

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

[19]  Michael J. Baker,et al.  Argumentation, Computer Support, and the Educational Context of Confronting Cognitions , 2003 .

[20]  Ruey-Shiang Shaw,et al.  A study of learning performance of e-learning materials design with knowledge maps , 2010, Comput. Educ..

[21]  David H. Jonassen,et al.  Designing effective supports for causal reasoning , 2008 .

[22]  Jan-Willem Strijbos,et al.  Methodological challenges for collaborative learning research , 2007 .

[23]  Hans Spada,et al.  Learning to Relate Qualitative and Quantitative Problem Representations in a Model-Based Setting for Collaborative Problem Solving , 1999 .

[24]  Jeroen Janssen,et al.  Automatic coding of online collaboration protocols , 2006 .

[25]  Judith Good,et al.  Learning to Think and Communicate with Diagrams: 14 Questions to Consider , 2001, Artificial Intelligence Review.

[26]  Gijsbert Erkens,et al.  Coordination processes in computer supported collaborative writing , 2005, Comput. Hum. Behav..

[27]  Benjamin S. Bloom,et al.  A Taxonomy for Learning, Teaching, and Assessing: A Revision of Bloom's Taxonomy of Educational Objectives , 2000 .

[28]  N. Mercer,et al.  Methods for studying the processes of interaction and collaborative activity in computer-based educational activities , 2004 .

[29]  J. Merriënboer,et al.  Selecting learning tasks: Effects of adaptation and shared control on learning efficiency and task involvement☆ , 2008 .

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

[31]  Susanne Narciss,et al.  Promoting self-regulated learning in web-based learning environments , 2007, Comput. Hum. Behav..

[32]  Gijsbert Erkens,et al.  3. COLLABORATIVE LEARNING , 2000 .

[33]  Paul A. Kirschner,et al.  Designing support to facilitate learning in powerful electronic learning environments , 2007, Comput. Hum. Behav..

[34]  N. Ding,et al.  Visualizing the sequential process of knowledge elaboration in computer-supported collaborative problem solving , 2009, Comput. Educ..

[35]  J. J. H. M. Janssen,et al.  Using visualizations to support collaboration and coordination during computer-supported collaborative learning , 2003 .

[36]  Jeroen Janssen,et al.  Automatic coding of dialogue acts in collaboration protocols , 2008, Int. J. Comput. Support. Collab. Learn..

[37]  S. Ainsworth DeFT: A Conceptual Framework for Considering Learning with Multiple Representations. , 2006 .

[38]  Jan-Willem Strijbos,et al.  Content analysis: What are they talking about? , 2006, Comput. Educ..

[39]  Roger Azevedo,et al.  Monitoring, planning, and self-efficacy during learning with hypermedia: The impact of conceptual scaffolds , 2008, Comput. Hum. Behav..

[40]  H. Simon,et al.  Scientific discovery as problem solving , 1981, Synthese.

[41]  Wolfgang Schnotz,et al.  External and internal representations in the acquisition and use of knowledge: visualization effects on mental model construction , 2008 .

[42]  Ulrike Cress,et al.  The need for considering multilevel analysis in CSCL research—An appeal for the use of more advanced statistical methods , 2008, Int. J. Comput. Support. Collab. Learn..

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

[44]  Min Liu,et al.  Cognitive tools, individual differences, and group processing as mediating factors in a hypermedia environment , 2006, Comput. Hum. Behav..

[45]  C. Hmelo‐Silver,et al.  Scaffolding and Achievement in Problem-Based and Inquiry Learning: A Response to Kirschner, Sweller, and Clark (2006) , 2007 .

[46]  P. Dillenbourg,et al.  Three worlds of CSCL: Can we support CSCL? , 2002 .

[47]  Richard E. Clark,et al.  Why Minimal Guidance During Instruction Does Not Work: An Analysis of the Failure of Constructivist, Discovery, Problem-Based, Experiential, and Inquiry-Based Teaching , 2006 .

[48]  Pierre Dillenbourg,et al.  Over-scripting CSCL: The risks of blending collaborative learning with instructional design , 2002 .

[49]  Brigid Barron When Smart Groups Fail , 2003 .

[50]  Jeroen Janssen,et al.  Guiding students' online complex learning-task behavior through representational scripting , 2010, Comput. Hum. Behav..

[51]  Ramon Prudencio S. Toledo Visualizing Argumentation: Software Tools for Collaborative and Educational Sense-Making , 2005, Inf. Vis..

[52]  A. L. Veerman,et al.  Diagram-mediated collaborative learning : diagrams as tools to provoke and support elaboration and argumentation , 2001 .

[53]  Matthew T. McCrudden,et al.  The effect of causal diagrams on text learning , 2007 .

[54]  Ioannis Stamelos,et al.  The effect of scaffolding students' context-generating cognitive activity in technology-enhanced case-based learning , 2008, Comput. Educ..

[55]  Paul A. Kirschner,et al.  Ten Steps to Complex Learning: A Systematic Approach to Four-Component Instructional Design , 2007 .

[56]  Pieter J. Beers,et al.  Coercing shared knowledge in collaborative learning environments , 2006, Comput. Hum. Behav..

[57]  Friedrich W. Hesse,et al.  Manipulable graphics for computer-supported problem solving , 1997, J. Comput. Assist. Learn..

[58]  M. Chi Quantifying Qualitative Analyses of Verbal Data: A Practical Guide , 1997 .

[59]  F. Fischer,et al.  Fostering collaborative knowledge construction with visualization tools , 2002 .

[60]  F. Fischer,et al.  Epistemic and social scripts in computer–supported collaborative learning , 2005 .

[61]  Daniel Bodemer,et al.  External and mental referencing of multiple representations , 2006, Comput. Hum. Behav..

[62]  D. Annis Dyadic Data Analysis , 2007 .

[63]  Manu Kapur Productive Failure , 2006, ICLS.

[64]  Geraldine Clarebout,et al.  Supporting learners: Increasing complexity? , 2007, Comput. Hum. Behav..

[65]  Jean-François Rouet,et al.  Information problem solving instruction: Some cognitive and metacognitive issues , 2008, Comput. Hum. Behav..