Learning from abstract and contextualized representations: The effect of verbal guidance

An experiment examined the effects of providing explicit verbal guidance to learners in integrating information with abstract or contextualized representations during computer-based learning of engineering. Verbal guidance supported learners in identifying correspondences and making mental connections among multiple textual and diagrammatic representations. Results from a 2 (abstract (A) or contextualized (C) representation)x2 (no guidance or guidance) design showed that without guidance, abstract representations led to better transfer than contextualized representations. Moreover, learners in the contextualized representation group benefitted from the guidance, while the abstract representation group did not benefit from guidance. These findings suggest that abstract representations promote the development of deep, transferrable knowledge and that verbal guidance denoting correspondences among representations can facilitate learning when less effective representational formats are utilized.

[1]  P. Shah,et al.  Review of Graph Comprehension Research: Implications for Instruction , 2002 .

[2]  Paul Chandler,et al.  Levels of Expertise and Instructional Design , 1998, Hum. Factors.

[3]  Marian Petre,et al.  Learning to Read Graphics: Some Evidence that 'Seeing' an Information Display is an Acquired Skill , 1993, J. Vis. Lang. Comput..

[4]  Martin Reisslein,et al.  Optimizing Worked‐Example Instruction in Electrical Engineering: The Role of Fading and Feedback during Problem‐Solving Practice , 2009 .

[5]  L. Verschaffel,et al.  Abstract or concrete examples in learning mathematics? A replication and elaboration of Kaminski, Sloutsky, and Heckler’s study , 2011 .

[6]  Robert L. Goldstone,et al.  The transfer of abstract principles governing complex adaptive systems , 2003, Cognitive Psychology.

[7]  Richard E. Mayer,et al.  The Cambridge Handbook of Multimedia Learning: Cognitive Theory of Multimedia Learning , 2005 .

[8]  R. Mayer,et al.  A Split-Attention Effect in Multimedia Learning: Evidence for Dual Processing Systems in Working Memory , 1998 .

[9]  Gary J. Anglin,et al.  On Empirically Validating Functions of Pictures in Prose , 1987 .

[10]  M. Lipsey,et al.  The efficacy of psychological, educational, and behavioral treatment. Confirmation from meta-analysis. , 1993, American Psychologist.

[11]  D. Uttal,et al.  Spatial Thinking and STEM Education. When, Why, and How? , 2012 .

[12]  Vladimir M Sloutsky,et al.  The Advantage of Abstract Examples in Learning Math , 2008, Science.

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

[14]  Thomas Andre,et al.  The effective use of an interactive software program to reduce students' misconceptions about batteries , 2004 .

[15]  Wolfgang Schnotz,et al.  Commentary: Towards an Integrated View of Learning from Text and Visual Displays , 2002 .

[16]  Francis M. Dwyer,et al.  The Effects of Prior Knowledge, Presentation Mode, and Visual Realism on Student Achievement. , 1984 .

[17]  Mary Hegarty,et al.  Effects of knowledge and display design on comprehension of complex graphics , 2010 .

[18]  R. Mayer,et al.  Cognitive constraints on multimedia learning: When presenting more material results in less understanding. , 2001 .

[19]  Kathryn Ley,et al.  National Convention of the Association for Educational Communications and Technology , 2012 .

[20]  J. Sweller,et al.  The Use of Worked Examples as a Substitute for Problem Solving in Learning Algebra , 1985 .

[21]  Slava Kalyuga,et al.  Managing split-attention and redundancy in multimedia instruction , 1999 .

[22]  A. Collins,et al.  Situated Cognition and the Culture of Learning , 1989 .

[23]  Kent J. Crippen,et al.  Teaching with External Representations: The Case of a Common Energy-Level Diagram in Chemistry , 2010 .

[24]  J. Kray,et al.  How useful is executive control training? Age differences in near and far transfer of task-switching training. , 2009, Developmental science.

[25]  Martin Reisslein,et al.  Technological Literacy Learning With Cumulative and Stepwise Integration of Equations Into Electrical Circuit Diagrams , 2012, IEEE Transactions on Education.

[26]  W. Schnotz.  Integrated Model of Text and Picture Comprehension , 2021, The Cambridge Handbook of Multimedia Learning.

[27]  Mitchell J. Nathan,et al.  The Real Story Behind Story Problems: Effects of Representations on Quantitative Reasoning , 2004 .

[28]  J. Levin.  On functions of pictures in prose , 1979 .

[29]  Robert L. Goldstone,et al.  The Transfer of Scientific Principles Using Concrete and Idealized Simulations , 2005, Journal of the Learning Sciences.

[30]  Jürgen Baumert,et al.  Teachers' Beliefs, Instructional Behaviors, and Students' Engagement in Learning from Texts with Instructional Pictures. , 2011 .

[31]  Shaaron Ainsworth,et al.  The functions of multiple representations , 1999, Comput. Educ..

[32]  R. Mayer,et al.  Animations need narrations : an experimental test of a dual-coding hypothesis , 1991 .

[33]  Martin Reisslein,et al.  Teaching with Concrete and Abstract Visual Representations: Effects on Students' Problem Solving, Problem Representations, and Learning Perceptions. , 2011 .

[34]  Richard K. Lowe.  Extracting information from an animation during complex visual learning , 1999 .

[35]  P. Chandler,et al.  Cognitive Load Theory and the Format of Instruction , 1991 .

[36]  Alfred Bork,et al.  Multimedia in Learning , 2001 .

[37]  F. Paas,et al.  Cognitive Architecture and Instructional Design , 1998 .

[38]  M. Malbrán.  The Cambridge Handbook of Multimedia Learning , 2007 .

[39]  J. Sweller.  Element Interactivity and Intrinsic, Extraneous, and Germane Cognitive Load , 2010 .

[40]  Kirsten R. Butcher.  Learning from Text with Diagrams: Promoting Mental Model Development and Inference Generation. , 2006 .

[41]  R. Kozma,et al.  Multimedia and understanding: Expert and novice responses to different representations of chemical phenomena , 1997 .

[42]  Nicole M. McNeil,et al.  Should you show me the money? Concrete objects both hurt and help performance on mathematics problems , 2009 .

[43]  M. Lepper,et al.  Intrinsic motivation and the process of learning: Beneficial effects of contextualization, personalization, and choice. , 1996 .

[44]  Tamara van Gog,et al.  State of the art research into Cognitive Load Theory , 2009, Comput. Hum. Behav..

[45]  R. Mayer,et al.  Cognitive Principles of Multimedia Learning: The Role of Modality and Contiguity , 1999 .

[46]  Tina Seufert.  Supporting Coherence Formation in Learning from Multiple Representations , 2003 .

[47]  Charlotte W. Farr,et al.  Matching Media, Methods, and Objectives in Distance Education. , 1993 .

[48]  John Sweller,et al.  Cognitive Load Theory: New Conceptualizations, Specifications, and Integrated Research Perspectives , 2010 .

[49]  T. Gog,et al.  In the eyes of the beholder: How experts and novices interpret dynamic stimuli , 2010 .

[50]  J. Peeck.  Increasing picture effects in learning from illustrated text , 1993 .

[51]  M. D’Esposito.  Working memory. , 2008, Handbook of clinical neurology.

[52]  R. A. Tarmizi,et al.  Guidance during Mathematical Problem Solving. , 1988 .

[53]  Clara M. Jennings,et al.  Increasing interest and achievement in mathematics through children's literature , 1992 .

[54]  David H. Jonassen,et al.  The Effect of Lesson Structures on Predication and Inference. , 1996 .

[55]  Wolfgang Schnotz,et al.  The Cambridge Handbook of Multimedia Learning: An Integrated Model of Text and Picture Comprehension , 2005 .

[56]  Francis M. Dwyer,et al.  THE EFFECT OF VARYING THE AMOUNT OF REALISTIC DETAIL IN VISUAL ILLUSTRATIONS DESIGNED TO COMPLEMENT PROGRAMMED INSTRUCTION , 1969 .

[57]  Herbert A. Simon,et al.  CaMeRa: A Computational Model of Multiple Representations , 1997, Cogn. Sci..

[58]  Erol Özçelik,et al.  An eye-tracking study of how color coding affects multimedia learning , 2009, Comput. Educ..

[59]  Francis M. Dwyer,et al.  The effectiveness of visual illustrations used to complement programed instruction , 1968 .

[60]  William Winn,et al.  The effect of the spatial arrangement of simple diagrams on the interpretation of english and nonsense sentences , 1993 .

[61]  F. Paas,et al.  Cognitive Load Theory and Instructional Design: Recent Developments , 2003 .

[62]  Susan R. Goldman,et al.  Learning in complex domains: When and why do multiple representations help? , 2003 .

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

[64]  Martin Reisslein,et al.  Representation Guidance with Abstract and Contextualized Representation: Effects on Engineering Learning Performance in Technological Literacy Education , 2012 .

[65]  Martin Reisslein,et al.  Pre‐college Electrical Engineering Instruction: The Impact of Abstract vs. Contextualized Representation and Practice on Learning , 2010 .

[66]  A. Renkl.  The worked-out-example principle in multimedia learning , 2005 .

[67]  R. Mayer,et al.  The Role of Interest in Learning From Scientific Text and Illustrations: On the Distinction Between Emotional Interest and Cognitive Interest , 1997 .

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

[69]  W. Schnotz,et al.  A Reconsideration of Cognitive Load Theory , 2007 .

[70]  Russell N. Carney,et al.  Pictorial Illustrations Still Improve Students' Learning from Text , 2002 .

[71]  Daniel L. Schwartz,et al.  Shuttling Between Depictive Models and Abstract Rules: Induction and Fallback , 1996, Cogn. Sci..

[72]  Richard Lowe,et al.  Animation and learning: selective processing of information in dynamic graphics , 2003 .

[73]  John R. Anderson,et al.  Abstract Planning and Perceptual Chunks: Elements of Expertise in Geometry , 1990, Cogn. Sci..

[74]  R. Mayer,et al.  Aids to computer-based multimedia learning , 2002 .

[75]  Richard E. Mayer,et al.  Cognitive Theory of Multimedia Learning , 2021, The Cambridge Handbook of Multimedia Learning.