Prior knowledge activation: how different concept mapping tasks lead to substantial differences in cognitive processes, learning outcomes, and perceived self-efficacy

Two experiments investigated the effects of characteristic features of concept mapping used for prior knowledge activation. Characteristic demands of concept mapping include connecting lines representing the relationships between concepts and labeling these lines, specifying the type of the semantic relationships. In the first experiment, employing a within-subjects design, 20 psychology students completed a label-provided-lines economics mapping task and then a create-and-label-lines meteorology mapping task or vice versa. The analysis of 40 think-aloud protocols indicated more elaboration processes for the label-provided-lines task than for the create-and-label-lines task. On the other hand, the protocols indicated more model-construction and organization processes in the create-and-label-lines task. The second experiment used the same variation but focused on learning outcomes and perceived self-efficacy as dependent measures. Forty-two psychology students were randomly assigned to either a label-provided-lines mapping task or a create-and-label-lines mapping task. Subsequently, both groups completed a learning phase in a hypertext environment and a posttest. Results showed substantial differences in learning outcomes and perceived self-efficacy in favor of the label-provided-lines prior knowledge activation task. The findings are congruent with coherence effects found in text-comprehension research and support the position that concept mapping should not be seen as a unitary method but be differentiated according to the specific tasks to be completed.

[1]  Richard E. Mayer,et al.  The Teaching of Learning Strategies. , 1983 .

[2]  R. Shavelson,et al.  Problems and Issues in the Use of Concept Maps in Science Assessment. , 1996 .

[3]  M. Hannafin,et al.  Cognitive strategies and learning from the world wide web , 1997 .

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

[5]  Joseph D. Novak,et al.  Learning How to Learn , 1984 .

[6]  W. Schneider,et al.  Domain-Specific Knowledge and Memory Performance: A Comparison of High- and Low-Aptitude Children , 1989 .

[7]  W. Kintsch.  The role of knowledge in discourse comprehension: a construction-integration model. , 1988, Psychological review.

[8]  Margaret G. McKeown,et al.  The Contribution of Prior Knowledge and Coherent Text to Comprehension , 1992 .

[9]  Roger Azevedo,et al.  Does adaptive scaffolding facilitate students ability to regulate their learning with hypermedia? q , 2004 .

[10]  David N. Rapp,et al.  Integrating Memory-Based and Constructionist Processes in Accounts of Reading Comprehension , 2005 .

[11]  R. Mayer,et al.  Multimedia learning: Are we asking the right questions? , 1997 .

[12]  Friedrich W. Hesse,et al.  The Use of Hypertext for Learning , 1999 .

[13]  Danielle S. McNamara,et al.  Learning from texts: Effects of prior knowledge and text coherence , 1996 .

[14]  Walter Kintsch,et al.  Readability and recall of short prose passages: A theoretical analysis. , 1980 .

[15]  Jean-François Rouet,et al.  Effects of content representation and readers' prior knowledge on the comprehension of hypertext , 2003, Int. J. Hum. Comput. Stud..

[16]  J. Novak,et al.  Educational Psychology: A Cognitive View , 1969 .

[17]  A. Bandura.  GUIDE FOR CONSTRUCTING SELF-EFFICACY SCALES , 2006 .

[18]  Amy M. Shapiro,et al.  The Relevance of Hierarchies to Learning Biology From Hypertext , 1999 .

[19]  Walter Kintsch,et al.  Toward a model of text comprehension and production. , 1978 .

[20]  Franz Emanuel Weinert,et al.  The neglected role of individual differences in theoretical models of cognitive development , 1998 .

[21]  T. Trabasso,et al.  Constructing inferences during narrative text comprehension. , 1994 .

[22]  Matthias Nückles,et al.  Supporting Concept Mapping for Learning from Text , 2006, ICLS.

[23]  David H. Jonassen,et al.  Hypertext Principles for text and Courseware Design , 1986 .

[24]  Eduardo Vidal-Abarca,et al.  Two procedures to improve instructional text: Effects on memory and learning. , 2000 .

[25]  Yao-Ting Sung,et al.  Learning through computer‐based concept mapping with scaffolding aid , 2001 .

[26]  D. McNamara.  Reading both high-coherence and low-coherence texts: effects of text sequence and prior knowledge. , 2001, Canadian journal of experimental psychology = Revue canadienne de psychologie experimentale.

[27]  Katharina Scheiter,et al.  Resource-adaptive Selection of Strategies in Learning from Worked-Out Examples , 2000 .

[28]  A. Dillon,et al.  Hypermedia as an Educational Technology: A Review of the Quantitative Research Literature on Learner Comprehension, Control, and Style , 1998 .

[29]  Alexander Renkl,et al.  Are high-coherent concept maps better for prior knowledge activation? Differential effects of concept mapping tasks on high school vs. university students , 2008, J. Comput. Assist. Learn..

[30]  Angela M. O'Donnell,et al.  Knowledge Maps as Scaffolds for Cognitive Processing , 2002 .

[31]  Amy M. Shapiro,et al.  LEARNING FROM HYPERTEXT: RESEARCH ISSUES AND FINDINGS , 2004 .

[32]  Dan Bowman,et al.  The differential effects of prior knowledge on learning: A study of two consecutive courses in earth sciences , 2001 .

[33]  Jacob Cohen.  Statistical Power Analysis for the Behavioral Sciences , 1969, The SAGE Encyclopedia of Research Design.

[34]  Shaaron Ainsworth,et al.  The impact of text coherence on learning by self-explanation , 2007 .

[35]  Jill H. Larkin,et al.  Learning From Electronic Texts: Effects of Interactive Overviews for Information Access , 1995 .

[36]  A. Bandura.  Self-Efficacy: The Exercise of Control , 1997, Journal of Cognitive Psychotherapy.

[37]  R. Shavelson,et al.  On the Validity of Cognitive Interpretations of Scores From Alternative Concept-Mapping Techniques , 2001 .

[38]  A. Bandura.  Social learning theory , 1977 .

[39]  B. K. Britton,et al.  Using Kintsch's computational model to improve instructional text: Effects of repairing inference calls on recall and cognitive structures. , 1991 .

[40]  Andrew Dillon,et al.  HyperText and Cognition , 1996 .

[41]  Walter Kintsch,et al.  An Overview of Top-Down and Bottom-Up Effects in Comprehension: The CI Perspective , 2005 .

[42]  Eduardo Vidal-Abarca,et al.  Some good texts are always better: text revision to foster inferences of readers with high and low prior background knowledge , 2005 .

[43]  D. Rubin,et al.  Contrasts and Effect Sizes in Behavioral Research , 1999 .

[44]  Danielle S. McNamara,et al.  Reversing the Reverse Cohesion Effect: Good Texts Can Be Better for Strategic, High-Knowledge Readers , 2007 .

[45]  R. Azevedo,et al.  The Role of Self-Regulated Learning in Fostering Students' Conceptual Understanding of Complex Systems with Hypermedia , 2004 .

[46]  R. Azevedo,et al.  Does training on self-regulated learning facilitate students' learning with hypermedia? , 2004 .

[47]  Esen Uzuntiryaki,et al.  Effect of conceptual change approach accompanied with concept mapping on understanding of solution concepts , 2005 .

[48]  Roger Azevedo,et al.  The Role of Self-Regulated Learning in Fostering Students' Understanding of Complex Systems with Hypermedia. , 2003 .

[49]  Katharina Scheiter,et al.  Goal Configurations and Processing Strategies as Moderators Between Instructional Design and Cognitive Load: Evidence From Hypertext-Based Instruction , 2003 .

[50]  W. Kintsch,et al.  Are Good Texts Always Better? Interactions of Text Coherence, Background Knowledge, and Levels of Understanding in Learning From Text , 1996 .