Effects of prior knowledge on learning from different compositions of representations in a mobile learning environment

Two experiments examined the effects of prior knowledge on learning from different compositions of multiple representations in a mobile learning environment on plant leaf morphology for primary school students. Experiment 1 compared the learning effects of a mobile learning environment presenting text and photos of plants on a tablet PC, either in combination with or without real plants in the physical environment. Results indicated that there were no interactions between prior knowledge and experimental condition. Students who learned with tablet PCs only outperformed students who additionally learned with real plants on a comprehension and an application test. In addition, high prior knowledge students outperformed low prior knowledge students on both tests. To investigate whether these effects were caused by the specific characteristics of the combination of photos of real plants and real plants, Experiment 2 compared the differential effects of prior knowledge on learning with the combination of texts, photos and real plants to a combination in which the photos were replaced by schematic hand drawings. Results indicated that both low and high prior knowledge students, who learned with the combination of texts, schematic hand drawings and real plants performed better on a comprehension and an application test. High prior knowledge students performed better on both tests. It is concluded that the number and type of representations used is critical for the effectiveness of mobile learning environments.

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

[2]  Robert Heinich,et al.  Instructional Media and Technologies for Learning , 1996 .

[3]  Marcello Gallucci,et al.  A conceptual and empirical examination of justifications for dichotomization. , 2009, Psychological methods.

[4]  Günter Daniel Rey,et al.  The expertise reversal effect: cognitive load and motivational explanations. , 2011, Journal of experimental psychology. Applied.

[5]  Yuh-Shyan Chen,et al.  A mobile learning system for scaffolding bird watching learning , 2003, J. Comput. Assist. Learn..

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

[7]  T. Gog,et al.  Development of an instrument for measuring different types of cognitive load , 2013, Behavior Research Methods.

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

[9]  Slava Kalyuga,et al.  The Expertise Reversal Effect , 2003 .

[10]  D. Geary.  Evolutionary educational psychology. , 2012 .

[11]  John Sweller,et al.  Cognitive Load Theory , 2020, Encyclopedia of Education and Information Technologies.

[12]  F. Paas,et al.  Attention guidance in learning from a complex animation: Seeing is understanding? , 2010 .

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

[14]  S. Kay.  On the Nature of Expertise. , 1992 .

[15]  F. Paas,et al.  Towards a Framework for Attention Cueing in Instructional Animations: Guidelines for Research and Design , 2009 .

[16]  Jie-Chi Yang,et al.  Affordances of mobile technologies for experiential learning: the interplay of technology and pedagogical practices , 2007, J. Comput. Assist. Learn..

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

[18]  Tzu-Chien Liu,et al.  Split-attention and redundancy effects on mobile learning in physical environments , 2012, Comput. Educ..

[19]  Francis M. Dwyer,et al.  A guide for improving visualized instruction , 1972 .

[20]  Michelene T. H. Chi,et al.  Expertise in Problem Solving. , 1981 .

[21]  Yi-Chun Lin,et al.  Implementing clickers to assist learning in science lectures: The Clicker-Assisted Conceptual Change model , 2011 .

[22]  Slava Kalyuga.  Expertise Reversal Effect and Its Implications for Learner-Tailored Instruction , 2007 .

[23]  Lloyd G. Humphreys,et al.  Research on individual differences requires correlational analysis, not ANOVA , 1978 .

[24]  E. Wiebe,et al.  The influence of prior knowledge on viewing and interpreting graphics with macroscopic and molecular representations , 2008 .

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

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

[27]  J. Sweller,et al.  Cognitive load effects in a primary-school geometry task , 1993 .

[28]  Richard E. Mayer,et al.  Multimedia Learning , 2001, Visible Learning Guide to Student Achievement.

[29]  M. Chi,et al.  The Nature of Expertise , 1988 .

[30]  John Sweller.  CHAPTER 8 The Split-Attention Principle in Multimedia Learning , 2010 .

[31]  F. Paas,et al.  Instructional control of cognitive load in the training of complex cognitive tasks , 1994 .

[32]  L. Humphreys,et al.  Pseudo-Orthogonal and Other Analysis of Variance Designs Involving Individual-Differences Variables. , 1974 .

[33]  Tzu-Chien Liu,et al.  Effects of cues and real objects on learning in a mobile device supported environment , 2013, Br. J. Educ. Technol..

[34]  Slava Kalyuga,et al.  Incorporating Learner Experience into the Design of Multimedia Instruction. , 2000 .

[35]  David C. Geary,et al.  An Evolutionarily Informed Education Science , 2008 .

[36]  S. Maxwell,et al.  Dichotomization, Partial Correlation, and Conditional Independence , 1996 .

[37]  Tzu-Chien Liu,et al.  The Effects of Mobile Natural-science Learning Based on the 5E Learning Cycle: A Case Study , 2009, J. Educ. Technol. Soc..

[38]  John Sweller,et al.  The Cambridge Handbook of Multimedia Learning: The Split-Attention Principle in Multimedia Learning , 2005 .

[39]  H. Mandl,et al.  Learning from Worked-Out Examples: The Effects of Example Variability and Elicited Self-Explanations , 1998, Contemporary educational psychology.

[40]  Richard Mayer,et al.  Multimedia Learning , 2001, Visible Learning Guide to Student Achievement.

[41]  F. Paas,et al.  An Evolutionary Upgrade of Cognitive Load Theory: Using the Human Motor System and Collaboration to Support the Learning of Complex Cognitive Tasks , 2012 .

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

[43]  R. Mayer,et al.  Multimedia Learning: Frontmatter , 2001 .

[44]  Tzu-Chien Liu,et al.  The design and implementation of a meaningful learning-based evaluation method for ubiquitous learning , 2011, Comput. Educ..

[45]  Paul Chandler,et al.  Some Conditions under Which Integrated Computer-Based Training Software Can Facilitate Learning , 1996 .

[46]  Gwo-Jen Hwang,et al.  A concept map approach to developing collaborative Mindtools for context-aware ubiquitous learning , 2011, Br. J. Educ. Technol..

[47]  Joel R. Levin,et al.  Educating the evolved mind : conceptual foundations for an evolutionary educational psychology , 2007 .

[48]  Tzu-Chien Liu,et al.  What comes with technological convenience? Exploring the behaviors and performances of learning with computer-mediated dictionaries , 2011, Comput. Hum. Behav..

[49]  Yao-Ting Sung,et al.  Designing an electronic guidebook for learning engagement in a museum of history , 2010, Comput. Hum. Behav..

[50]  Wolfgang Schnotz,et al.  Interactive and Non-Interactive Pictures in Multimedia Learning Environments: Effects on Learning Outcomes and Learning Efficiency , 2009 .

[51]  Tzu-Chien Liu,et al.  Teaching in a Wireless Learning Environment: A Case Study , 2007, J. Educ. Technol. Soc..

[52]  Cheryl I. Johnson,et al.  Revising the Redundancy Principle in Multimedia Learning. , 2008 .