Scaffolding Complex Learning: The Mechanisms of Structuring and Problematizing Student Work

There has been much interest in using software tools to scaffold learners in complex tasks, that is, to provide supports that enable students to deal with more complex content and skill demands than they could otherwise handle. Many different approaches to scaffolding techniques have been presented in a broad range of software tools. I argue that two complementary mechanisms can explain how a diversity of scaffolding approaches in software act to support learners. Software tools can help structure the learning task, guiding learners through key components and supporting their planning and performance. In addition, tools can shape students' performance and understanding of the task in terms of key disciplinary content and strategies and thus problematize this important content. Although making the task more difficult in the short term, by forcing learners to engage with this complexity, such scaffolded tools make this work more productive opportunities for learning. I present arguments for these mechanisms in terms of the obstacles learners face, and I present several brief examples to illustrate their use in design guidelines. Finally, I examine how the mechanisms of structuring and problematizing are sometimes complementary and sometimes in tension in design, discuss design tradeoffs in developing scaffolded investigation tools for learners, and consider the reliance of scaffolding on a classroom system of supports.

[1]  W. Sandoval,et al.  Explanation-Driven Inquiry: Integrating Conceptual and Epistemic Scaffolds for Scientific Inquiry , 2004 .

[2]  Joseph Krajcik,et al.  The design of guided learner-adaptable scaffolding in interactive learning environments , 1996, CHI.

[3]  Donald A. Norman,et al.  User Centered System Design: New Perspectives on Human-Computer Interaction , 1988 .

[4]  L. S. Vygotskiĭ,et al.  Mind in society : the development of higher psychological processes , 1978 .

[5]  Paul J. Feltovich,et al.  Categorization and Representation of Physics Problems by Experts and Novices , 1981, Cogn. Sci..

[6]  John R. Anderson,et al.  Cognitive Tutors: Lessons Learned , 1995 .

[7]  Leona Schauble,et al.  Causal Models and Experimentation Strategies in Scientific Reasoning , 1991 .

[8]  D. C. Merrill,et al.  Tutoring: Guided Learning by Doing , 1995 .

[9]  Ronald W. Marx,et al.  “Maestro, what is ‘quality’?”: Language, literacy, and discourse in project-based science , 2001 .

[10]  T. P. Carpenter,et al.  Problem Solving as a Basis for Reform in Curriculum and Instruction: The Case of Mathematics , 1996 .

[11]  William A. Sandoval,et al.  Conceptual and Epistemic Aspects of Students' Scientific Explanations , 2003 .

[12]  Mark Guzdial,et al.  Software-Realized Scaffolding to Facilitate Programming for Science Learning , 1994, Interact. Learn. Environ..

[13]  Ben Tun-Bin Loh Using articulation and inscription as catalysts for reflection: Design principles for reflective inquiry , 2003 .

[14]  K. Crowley,et al.  Designing for Science: Implications from Everyday, Classroom, and Professional Settings. , 2001 .

[15]  Bruce L Sherin,et al.  How Students Understand Physics Equations , 2001 .

[16]  Matthew W. Lewis,et al.  Self-Explonations: How Students Study and Use Examples in Learning to Solve Problems , 1989, Cogn. Sci..

[17]  Ganesh S. Oak Information Visualization Introduction , 2022 .

[18]  B. Rogoff Apprenticeship in Thinking: Cognitive Development in Social Context , 1990 .

[19]  D. Klahr,et al.  Heuristics for Scientific Experimentation: A Developmental Study , 1993, Cognitive Psychology.

[20]  William A. Sandoval Inquire to explain: structuring inquiry around explanation construction in a technology-supported bi , 1998 .

[21]  David H. Jonassen,et al.  Handbook of Research for educational Communications and Technology , 1997 .

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

[23]  James D. Hollan,et al.  Chapter 2 – Information Visualization , 1997 .

[24]  Allan Collins,et al.  Cognitive Apprenticeship and Instructional Technology , 1988 .

[25]  J. Roschelle Learning by Collaborating: Convergent Conceptual Change , 1992 .

[26]  Annemarie S. Palincsar,et al.  The Case of Carla: Dilemmas of Helping All Students to Understand Science , 2002 .

[27]  Identifiers Australia,et al.  Annual Meeting of the National Association of Research in Science Teaching , 1999 .

[28]  R. A. Engle,et al.  Guiding Principles for Fostering Productive Disciplinary Engagement: Explaining an Emergent Argument in a Community of Learners Classroom , 2002 .

[29]  Elizabeth A. Davis,et al.  Scaffolding students' knowledge integration: prompts for reflection in KIE , 2000 .

[30]  Jill H. Larkin,et al.  Cognition in Scientific and Everyday Domains: Comparison and Learning Implications. , 1991 .

[31]  Emily H. van Zee,et al.  Reflective discourse: developing shared understandings in a physics classroom , 1997 .

[32]  J. Osborne,et al.  Establishing the norms of scientific argumentation in classrooms , 2000 .

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

[34]  D. Perkins,et al.  Partners in Cognition: Extending Human Intelligence with Intelligent Technologies , 1991 .

[35]  J. Bruner,et al.  The role of tutoring in problem solving. , 1976, Journal of child psychology and psychiatry, and allied disciplines.

[36]  Brian J. Reiser,et al.  Complementary roles of software-based scaffolding and teacher-student interactions in inquiry learning , 1997, CSCL.

[37]  Mark Guzdial,et al.  Learner-centered design: the challenge for HCI in the 21st century , 1994, INTR.

[38]  R. Duschl,et al.  "Doing the Lesson" or "Doing Science": Argument in High School Genetics , 2000 .

[39]  J. Lemke Talking Science: Language, Learning, and Values , 1990 .

[40]  Elaine B. Coleman,et al.  Using Explanatory Knowledge During Collaborative Problem Solving in Science , 1998 .

[41]  Daniel C. Edelson Learning-for-use : A framework for the design of technology-supported inquiry activities , 2001 .

[42]  William Damon,et al.  Problem solving with equals: Peer collaboration as a context for learning mathematics and spatial concepts. , 1989 .

[43]  Howard Greisdorf,et al.  Exploring Science: The Cognition and Development of Discovery Processes , 2003, J. Documentation.

[44]  J. Kelly Science for All Americans (A Project 2061 Report on Literacy Goals in Science, Mathematics, and Technology) American Association for the Advancement of Science , 1990 .

[45]  D. Kuhn Science as argument : Implications for teaching and learning scientific thinking , 1993 .

[46]  J. Frederiksen,et al.  Inquiry, Modeling, and Metacognition: Making Science Accessible to All Students , 1998 .

[47]  B. Reiser Developing reflective inquiry practices: A case study of software, the teacher and students: Implications from everyday, classroom, and professional settings , 2001 .

[48]  Brian K. Smith,et al.  National Geographic unplugged: classroom-centered design of interactive nature films , 1998, CHI.

[49]  Susan E. Newman,et al.  Cognitive Apprenticeship: Teaching the Craft of Reading, Writing, and Mathematics. Technical Report No. 403. , 1987 .

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

[51]  M. Pressley,et al.  Discourse Patterns and Collaborative Scientific Reasoning in Peer and Teacher-Guided Discussions , 1999 .

[52]  Iris Tabak,et al.  BGuILE: Stragtegic and conceptual scaffolds for scientific inquiry in biology classrooms , 2001 .

[53]  Liam J. Bannon,et al.  Beyond the Interface: Encountering Artifacts in Use , 1989 .

[54]  Marlene Scardamalia,et al.  Computer Support for Knowledge-Building Communities , 1994 .

[55]  Roy D. Pea,et al.  Distributed Multimedia Learning Environments: Why and How? , 1992, Interact. Learn. Environ..

[56]  John Millar Carroll Interfacing Thought: Cognitive Aspects of Human-Computer Interaction , 2003 .

[57]  M. Lepper,et al.  Motivational techniques of expert human tutors: Lessons for the design of computer-based tutors. , 1993 .

[58]  Stephanie D. Teasley Constructing a Joint Problem Space: The Computer as a Tool for Sharing Knowledge , 1993 .

[59]  Elliot Soloway,et al.  Symphony: a case study in extending learner-centered design through process space analysis , 1999, CHI '99.

[60]  T. Landauer,et al.  Handbook of Human-Computer Interaction , 1997 .

[61]  Leona Schauble,et al.  Students' Understanding of the Objectives and Procedures of Experimentation in the Science Classroom , 1995 .

[62]  D. Kuhn,et al.  The development of scientific thinking skills , 1988 .

[63]  M. Baker,et al.  Computer-Mediated Epistemic Dialogue: Explanation and Argumentation as Vehicles for Understanding Scientific Notions , 2002 .

[64]  L. Vygotsky Mind in Society: The Development of Higher Psychological Processes: Harvard University Press , 1978 .

[65]  E. Davis Prompting Middle School Science Students for Productive Reflection: Generic and Directed Prompts , 2003 .

[66]  James D. Hollan,et al.  Direct Manipulation Interfaces , 1985, Hum. Comput. Interact..

[67]  Annemarie S. Palincsar,et al.  Motivating Project-Based Learning: Sustaining the Doing, Supporting the Learning , 1991 .

[68]  Michael Pressley,et al.  Scaffolding scientific competencies within classroom communities of inquiry. , 1997 .

[69]  Janet L. Kolodner,et al.  Designing to Learn About Complex Systems , 2000 .

[70]  L. Resnick,et al.  Knowing, Learning, and Instruction , 2018 .

[71]  Ann S. Rosebery,et al.  Appropriating Scientific Discourse: Findings from Language Minority Classrooms. , 1992 .

[72]  Marcia C. Linn,et al.  Designing the Knowledge Integration Environment , 2000 .

[73]  Donald A. Norman,et al.  Things That Make Us Smart: Defending Human Attributes In The Age Of The Machine , 1993 .

[74]  Eleni A. Kyza,et al.  Reflective inquiry: enabling group self-regulation in inquiry-based science using the progress portfolio tool , 2002, CSCL.

[75]  Marcia C. Linn,et al.  Internet Environments for Science Education , 2004 .

[76]  Cynthia Passmore,et al.  A modeling approach to teaching evolutionary biology in high schools , 2002 .

[77]  Roy D. Pea,et al.  Addressing the Challenges of Inquiry-Based Learning Through Technology and Curriculum Design , 1999 .

[78]  John M. Carroll,et al.  Designing Interaction: Psychology at the Human-Computer Interface , 1991 .

[79]  Jennifer A. Fredricks,et al.  Inquiry in Project-Based Science Classrooms: Initial Attempts by Middle School Students , 1998 .

[80]  Brian K. Smith,et al.  Combining General and Domain-Specific Strategic Support for Biological Inquiry , 1996, Intelligent Tutoring Systems.

[81]  Ann L. Brown,et al.  Guided discovery in a community of learners. , 1994 .

[82]  Martha Stone Wiske,et al.  Teaching for understanding : linking research with practice , 1998 .

[83]  M. Linn,et al.  Scientific arguments as learning artifacts: designing for learning from the web with KIE , 2000 .

[84]  Donald A. Norman,et al.  Cognitive artifacts , 1991 .

[85]  David Klahr,et al.  Dual Space Search During Scientific Reasoning , 1988, Cogn. Sci..

[86]  James D. Hollan,et al.  Distributed cognition: toward a new foundation for human-computer interaction research , 2000, TCHI.

[87]  Susan M. Williams,et al.  Putting Case-Based Instruction Into Context: Examples From Legal and Medical Education , 1992 .