Map Interpretation: Tool for Rapid Learning and Assessment Lens for Cognitive Engagement

  • Arniza GhazaliEmail author
Conference paper


The final-year students electing materials analysis as their course were coached in understanding the concepts of analysis for one semester. Analysis of students’ learning experience shows that systematic development of understanding of the topical contents enabled them to construct the topical maps. Despite students’ inept mapping skill and inability to see the whole course contents as a network of linking topical maps, students who progressively encoded the knowledge by full attendance of lecture sessions were able to rapidly grasp the course’s masterpiece map constructed by the instructor (i-MAC). Given the same time frame as other students, these regular participants also performed extremely well in the final analytical challenge assessing their ability to solve analytical problems, commensurate with the set course learning outcomes. The leap from B to A and even C to A of this group was the outcome of the systematic arrangement of important concept gathered through progressive intellectual development. Upon introducing the topical linkages in i-MAC, grasping of the concept among them was automatic, unlike the extra struggling required of the counterpart. This was assessed from the correctness of their verbal map interpretation (VMI), which is reflective of the final assessment scores. Deliberation on students’ learning identifies the importance of (1) systematic encoding of knowledge, (2) intensified neural activation especially achieved via digestion of i-MAC and the subsequent VMI and (3) instructor’s reflections, needs analysis and carefully designed intervention in the form of i-MAC and feedback to VMI, to engender high-order cognitive engagement. Proving correlation between extent of VMI correctness and performance in the final analytical challenge, verbal i-MAC interpretation, therefore, also serves as a reliable tool for assessing students’ degree of cognitive engagement and their preparedness to function in problem-solving situations.


Learning Cognitive Engagement Mapping 


  1. Banikowski, A. K. (1999). Strategies to Enhance Memory Based on Brain Research Focus on Exceptional Children 0015511X32(2):1–22. Retrieved 17 July 2015 from,
  2. Barke, H. D., Hazari, A., & Yitbarek, S. (2009). Chapter 2 students’ misconceptions and how to overcome them. In H. D. Barke, A. Hazari, & S. Yitbarek (Eds.), Misconceptions in chemistry. doi: 10.1007/978-3-540-70989-3-2. (pp. 21–24), Berlin, Heidelberge: Springer-Verlag.
  3. Bounds, G. (2010). How Handwriting Trains the Brain Forming Letters is Key to Learning, Memory, Ideas, The Wall Street Journal. Retrieved 4 March 2015 from
  4. Cole, M. (1971). Cultural Context of Learning and Thinking: An Exploration in Experimental Anthropology Eric Number ED062465 (p. 298). Retrieved 31 Aug 2015 from,
  5. Cromley, J. (1998). Learning to think, learning to learn: What the science of thinking and learning has to offer adult education. National Institute for Literacy.Google Scholar
  6. Davies, M. (2010). Concept mapping, mind mapping and argument mapping: What are the differences and do they matter? High Education. doi: 10.1007/s10734-010-9387-6.
  7. de Braga, M., Boyd, C., & Abdulnor, S. (2015). Using the principles of SoTL to redesign an advanced evolutionary biology course. Teaching and Learning Inquiry—The ISSOTL Journal, 3(1), 15–29.Google Scholar
  8. Dietrich, A. (2004). The cognitive neuroscience of creativity. Psychonomic Bulletin & Review, 11(6), 1011–1026.CrossRefGoogle Scholar
  9. Fredericks, J. A., & McColskey, W. (2012). The measurement of student engagement: A Comparative analysis of various methods and student self-report. In S. L. Christenson (Ed.), Handbook of research on students engagement (pp. 763–782). New York, NY: Springer.CrossRefGoogle Scholar
  10. Hay, D., Kinchin, I., & Lygo-Baker, S. (2008). Making learning visible: The role of concept mapping in higher education. Studies in Higher Education, 33(3), 295–311.CrossRefGoogle Scholar
  11. Kosslyn, S. M., & Miller, W. (2013). Top brain, bottom brain: Surprising insights into how you think. (ebook pp. Location 90 of 2995). New York: Simon and Schuster Inc.Google Scholar
  12. Kuldas, S., Hashim, S., & Ismail, H. N. (2015). Malaysian adolescent students’ needs for enhancing thinking skills counteracting risk factors and demonstrating academic resillience. International Journal of Adolescence Youth, 20(1), 32–47.CrossRefGoogle Scholar
  13. Marcus, G. (2015). The Computational Brain. In M. Marcus & J. Freeman (Eds.) The future of the brain: Essays by the world’s leading neuroscientist (pp. 205–214). USA: Princeton University Press.Google Scholar
  14. McLeod, S. (2007a). Stages of Memory–Encoding, Storage and Retrieval Simply Psychology. Retrieved July 17 2015 from,
  15. McLeod, S. (2007b). Levels of Processing. Retrieved 17 July 2015 from,
  16. Poole, G., & Chick, N. (2015). Weaving SoTL into our everyday lives. Teaching and Learning Inquiry—The ISSOTL Journal, 3(1), 1.Google Scholar
  17. Rolka, C. & Ramshagen, A. (2015) Showing up is half the battle: Assessing different contextualized learning tools. International Journal Scholarship of Teaching and Learning 9(1), Article 10. Retrieved 8 Sept 2015 from,
  18. Shams, L., & Seitz, A. R. (2008). Benefits of multisensory learning. Trends in Cognitive Sciences, 12(11), 411–417.CrossRefGoogle Scholar
  19. Stigler, J.W. (2012). Struggle for smarts? How Eastern and Western cultures tackle learning. Interview Transcript hosted by Renee Montagne, 12 Nov 2012.Google Scholar
  20. Thompson, F., & Logue, S. (2006). An exploration of common student misconceptions in science. International Education Journal, 7(4), 553.Google Scholar

Copyright information

© Springer Science+Business Media Singapore 2016

Authors and Affiliations

  1. 1.Universiti Sains Malaysia (USM)GelugorMalaysia

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