This article presents a new score generation algorithm to compute the accuracy of student concept maps in comparison to teacher maps. The algorithm follows a compare and remove method to remove the extra vertices and wrong edges of student concept map with respect to teacher map. A group of 230 students were taken to generate student maps on a pretaught chapter for finding multivariate regression coefficients for different independent factors incorporated in the study. It was found that there exists a positive correlation between the score obtained by the students and the degree of knowledge acquired by him while constructing concept maps.
KinchinI.HayD. (2000).
How a qualitative approach to concept map analysis can be used to aid learning by illustrating patterns of conceptual development.Educational Research,
42(1), 43–57. doi:10.1080/001318800363908
4.
MayerR. (1981).
The psychology of how novices learn computer programming.ACM Computing Surveys,
13(1), 121–141. doi:10.1145/356835.356841
5.
McClureJ.SonakB.SuenH. (1999).
Concept map assessment of classroom learning: Reliability, validity, and logistical practicality.Journal of Research in Science Teaching,
36(4), 475–492. doi:10.1002/(SICI)1098-2736(199904)36:4<475::AID-TEA5>3.0.CO;2-O
6.
NovakJ. (2005).
Results and implications of a 12-year longitudinal study of science concept learning.Research in Science Education,
35, 23–40. doi:10.1007/s11165-004-3431-4
7.
NovakJ.GowinD. (1984). Learning how to learn.
New York, NY:
Cambridge University Press.
8.
WestD.ParkJ.PomeroyJ., &SandovalK. (2002).
Concept mapping assessment in medical education: A comparison of two scoring systems.Medical Education,
36, 820–826. doi:10.1046/j.1365-2923.2002.01292.x
