The Learning Impacts of a Concept Map based Classroom Response System

Concept map is a powerful tool to achieve meaningful learning. In order to improve the capabilities of traditional classroom response systems to foster students’ higher-order thinking, in this study we propose an innovative Concept Map based Classroom Response System characterized by interactivity, diagnosticity and enjoyment, and empirically evaluate its effectiveness on improving students' cognitive and affective levels in learning. This research entails important pedagogical implications and demonstrates the appropriateness of applying the system into higher education.

[1]  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 .

[2]  Izak Benbasat,et al.  Investigating the Influence of the Functional Mechanisms of Online Product Presentations , 2007 .

[3]  John Hulland,et al.  Use of partial least squares (PLS) in strategic management research: a review of four recent studies , 1999 .

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

[5]  Jill A. Marshall,et al.  Classroom Response Systems: A Review of the Literature , 2006 .

[6]  Jeffrey D. Karpicke,et al.  Retrieval Practice Produces More Learning than Elaborative Studying with Concept Mapping , 2011, Science.

[7]  James A. Senn,et al.  Challenges and strategies for research in systems development , 1992 .

[8]  Melissa Davidson,et al.  The Taxonomy of Learning , 2008, International anesthesiology clinics.

[9]  M. Gilly,et al.  Shopping Online for Freedom, Control, and Fun , 2001 .

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

[11]  David L. Darmofal,et al.  Using concept maps and concept questions to enhance conceptual understanding , 2002, 32nd Annual Frontiers in Education.

[12]  Robert R. Hoffman,et al.  Applied Concept Mapping: Capturing, Analyzing, and Organizing Knowledge , 2011 .

[13]  Rolph E. Anderson,et al.  Multivariate Data Analysis: Text and Readings , 1979 .

[14]  Scott B. MacKenzie,et al.  Common method biases in behavioral research: a critical review of the literature and recommended remedies. , 2003, The Journal of applied psychology.

[15]  Ron Chi-Wai Kwok,et al.  Can a lean medium enhance large-group communication? Examining the impact of interactive mobile learning , 2010 .

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

[17]  Ron Chi-Wai Kwok,et al.  Can a lean medium enhance large-group communication? Examining the impact of interactive mobile learning , 2010, J. Assoc. Inf. Sci. Technol..

[18]  Izak Benbasat,et al.  A study of demographic embodiments of product recommendation agents in electronic commerce , 2010, Int. J. Hum. Comput. Stud..

[19]  William Haseman,et al.  User attitude as a mediator of learning performance improvement in an interactive multimedia environment: an empirical investigation of the degree of interactivity and learning styles , 2001, Int. J. Hum. Comput. Stud..

[20]  Jeff Cain,et al.  An audience response system strategy to improve student motivation, attention, and feedback. , 2009, American journal of pharmaceutical education.

[21]  J. Nunnally.  Psychometric Theory (2nd ed), New York: McGraw-Hill. , 1978 .

[22]  C. Fornell.  A Second generation of multivariate analysis : classification of methods and implications for marketing research , 1985 .