Systematically reviewing the potential of concept mapping technologies to promote self-regulated learning in primary and secondary science education

Abstract We systematically searched five databases to assess the potential of concept mapping-based technologies to promote self-regulated learning in science education. Our search uncovered 17 relevant studies that investigated seven different types of learning technologies. We performed a narrative analysis assessing how each technology affects self-regulated learning through cognitive, metacognitive, and motivation strategies, according to Schraw et al. (2006)'s model. We suggest concept mapping technologies may affect self-regulated learning through enhancing these strategies to varying degrees. Computer software was particularly useful for developing cognitive strategies through ease of use. Teaching agents were particularly useful for developing metacognitive strategies by coupling visualisation of knowledge patterns with performance monitoring, aided by a teaching metaphor. Finally, mobile devices and teaching agents were most effective in enhancing motivation. Effects on knowledge gains remain unclear due to small sample sizes.

[1]  Yao-Ting Sung,et al.  A New Assessment for Computer-based Concept Mapping , 2005, J. Educ. Technol. Soc..

[2]  Charlotte Dignath,et al.  How can primary school students learn self-regulated learning strategies most effectively? A meta-analysis on self-regulation training programmes , 2008 .

[3]  Frank M. Pajares,et al.  Self-Efficacy Beliefs in Academic Settings , 1996 .

[4]  Shu-Sheng Liaw,et al.  Perceived satisfaction, perceived usefulness and interactive learning environments as predictors to self-regulation in e-learning environments , 2013, Comput. Educ..

[5]  J. Novak.  Concept mapping: A useful tool for science education , 1990 .

[6]  B. Rittle-Johnson,et al.  Does comparing solution methods facilitate conceptual and procedural knowledge? An experimental study on learning to solve equations. , 2007 .

[7]  Lauren Cifuentes,et al.  Using Computers to Individually-generate vs. Collaboratively-generate Concept Maps , 2007, J. Educ. Technol. Soc..

[8]  Ceren Tekkaya,et al.  Modeling the Relations Among Students' Epistemological Beliefs, Motivation, Learning Approach, and Achievement , 2009 .

[9]  Mun Y. Yi,et al.  Predicting the use of web-based information systems: self-efficacy, enjoyment, learning goal orientation, and the technology acceptance model , 2003, Int. J. Hum. Comput. Stud..

[10]  Richard E. Clark,et al.  Why Minimal Guidance During Instruction Does Not Work: An Analysis of the Failure of Constructivist, Discovery, Problem-Based, Experiential, and Inquiry-Based Teaching , 2006 .

[11]  Katrin Rakoczy,et al.  Promotion of self-regulated learning in classrooms: investigating frequency, quality, and consequences for student performance , 2010 .

[12]  Gwo-Jen Hwang,et al.  Effects of Touch Technology-based Concept Mapping on Students' Learning Attitudes and Perceptions , 2013, J. Educ. Technol. Soc..

[13]  Beate Sodian,et al.  Examining implicit metacognition in 3.5-year-old children: an eye-tracking and pupillometric study , 2013, Front. Psychol..

[14]  Claudia Olaciregui,et al.  The effects of a concept map-based information display in an electronic portfolio system on information processing and retention in a fifth-grade science class covering the Earth's atmosphere , 2008, Br. J. Educ. Technol..

[15]  Amy L. Baylor,et al.  Permutations of Control: Cognitive Considerations for Agent-Based Learning Environments , 2001 .

[16]  Peggy A. Ertmer,et al.  Teacher beliefs and technology integration practices: A critical relationship , 2012, Comput. Educ..

[17]  K. Scheiter,et al.  Learner Control in Hypermedia Environments , 2007 .

[18]  Chee-Kit Looi,et al.  Use of Agent Prompts to Support Reflective Interaction in a Learning-by-Teaching Environment , 2008, Intelligent Tutoring Systems.

[19]  B. Zimmerman.  Self-Regulated Learning and Academic Achievement: An Overview , 1990 .

[20]  Daniel L. Schwartz,et al.  Preparing students for future learning with Teachable Agents , 2010 .

[21]  Blanche W. O'Bannon,et al.  Teacher perceptions of using mobile phones in the classroom: Age matters! , 2014, Comput. Educ..

[22]  Pei-Luen Patrick Rau,et al.  Using mobile communication technology in high school education: Motivation, pressure, and learning performance , 2008, Comput. Educ..

[23]  L. Bigozzi,et al.  The role of individual writing in fostering scientific conceptualization , 2011 .

[24]  Gwo-Jen Hwang,et al.  An Evaluation of the Learning Effectiveness of Concept Map- Based Science Book Reading via Mobile Devices , 2013, J. Educ. Technol. Soc..

[25]  Hannie Gijlers,et al.  Using Concept Maps to Facilitate Collaborative Simulation-Based Inquiry Learning , 2013 .

[26]  S. Miller,et al.  Using Evidence‐Based Practices to Build Mathematics Competence Related to Conceptual, Procedural, and Declarative Knowledge , 2007 .

[27]  A. G. Balim.  Use of technology-assisted techniques of mind mapping and concept mapping in science education: a constructivist study , 2013 .

[28]  Gwo-Jen Hwang,et al.  A concept map-embedded educational computer game for improving students' learning performance in natural science courses , 2013, Comput. Educ..

[29]  Pei-Lin Liu,et al.  Effects of a computer-assisted concept mapping learning strategy on EFL college students' English reading comprehension , 2010, Comput. Educ..

[30]  Wilfried Admiraal,et al.  Mobile game-based learning in secondary education: engagement, motivation and learning in a mobile city game , 2009, J. Comput. Assist. Learn..

[31]  Askin Asan,et al.  Concept Mapping in Science Class: A Case Study of Fifth Grade Students , 2007, J. Educ. Technol. Soc..

[32]  T. Jong,et al.  The effects of a concept map-based support tool on simulation-based inquiry learning , 2013 .

[33]  Shueh-Cheng Hu,et al.  Applying Computerized Concept Maps in Guiding Pupils to Reason and Solve Mathematical Problems: The Design Rationale and Effect , 2013 .

[34]  Delia Neuman,et al.  High school students' Information seeking and use for class projects , 2007 .

[35]  Kent J. Crippen,et al.  Promoting Self-Regulation in Science Education: Metacognition as Part of a Broader Perspective on Learning , 2006 .

[36]  Nian-Shing Chen,et al.  Effects of an integrated concept mapping and web-based problem-solving approach on students' learning achievements, perceptions and cognitive loads , 2014, Comput. Educ..

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

[38]  Gwo-Jen Hwang,et al.  An interactive concept map approach to supporting mobile learning activities for natural science courses , 2011, Comput. Educ..

[39]  Alexander Renkl,et al.  Prior knowledge activation: how different concept mapping tasks lead to substantial differences in cognitive processes, learning outcomes, and perceived self-efficacy , 2010 .

[40]  Ute Harms,et al.  Assessing System Thinking Through Different Concept-Mapping Practices , 2012 .

[41]  Ton de Jong,et al.  Regulative support for collaborative scientific inquiry learning , 2006, J. Comput. Assist. Learn..

[42]  Dale H. Schunk,et al.  Goal and Self-Evaluative Influences During Children’s Cognitive Skill Learning , 1996 .

[43]  D. Moher,et al.  Preferred reporting items for systematic reviews and meta-analyses: the PRISMA Statement , 2009, BMJ : British Medical Journal.

[44]  Bryce B. Hudgins,et al.  Teaching Critical Thinking Skills to Fourth and Fifth Graders through Teacher-Led Small-Group Discussions , 1986 .

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

[46]  J. Novak.  The Theory Underlying Concept Maps and How To Construct Them , 2004 .

[47]  A. Bandura.  Perceived Self-Efficacy in Cognitive Development and Functioning , 1993, Educational Psychologist.

[48]  Gary R. Morrison,et al.  Past and Present : Balancing Rigor and Relevance to Impact School Learning , 2010 .

[49]  Lauren Cifuentes,et al.  The comparative effect of individually-constructed vs. collaboratively-constructed computer-based concept maps , 2009, Comput. Educ..

[50]  P. Winne,et al.  Feedback and Self-Regulated Learning: A Theoretical Synthesis , 1995 .

[51]  Ron Ritchhart,et al.  Uncovering students’ thinking about thinking using concept maps , 2009 .

[52]  Yen-Lin Chen,et al.  A Mobile Learning Support System for Ubiquitous Learning Environments , 2013 .

[53]  Alberto J. Cañas,et al.  A TEORIA SUBJACENTE AOS MAPAS CONCEITUAIS E COMO ELABORÁ-LOS E USÁ-LOS * THE THEORY UNDERLYING CONCEPT MAPS AND HOW TO CONSTRUCT AND USE THEM , 2010 .

[54]  Theodore J. Kopcha,et al.  Teachers' perceptions of the barriers to technology integration and practices with technology under situated professional development , 2012, Comput. Educ..

[55]  Maria Puzziferro.  Online Technologies Self-Efficacy and Self-Regulated Learning as Predictors of Final Grade and Satisfaction in College-Level Online Courses , 2008 .

[56]  M. Volman,et al.  Critical Thinking as a Citizenship Competence: Teaching Strategies. , 2004 .

[57]  ThomasKevin,et al.  Teacher perceptions of using mobile phones in the classroom , 2014 .