Assessment Based on Linkage patterns in Concept Maps

Concept maps have been adopted extensively in teaching and assessment. Assess ment schemes, including the closeness index and the N-G method, have also been widely applied to evaluate the quality of students' concept maps. Teachers must make great efforts to evaluate students' concept maps, because present concept map assessment schemes do not reveal ways to help them improve such maps. Additionally, teachers cannot easily provide constructive suggestions to students to improve their learning, particularly when concept maps incorporate many concept; and links. This work presents linkage algorithms that can he used to discover the patterns (such as confused concepts, substitute concepts, and hidden wrong concepts) in concept maps to support assessment. Teachers can use the discovered patterns not onty to become aware of the conceptions of students, but also to improve students' conceptions efficiently.

[1]  Michael J. A. Berry,et al.  Data mining techniques - for marketing, sales, and customer support , 1997, Wiley computer publishing.

[2]  Terence R. Keen,et al.  Personal Construct Psychology and Education , 1981 .

[3]  Peder J. Johnson,et al.  Assessing Structural Knowledge. , 1991 .

[4]  Ellis Horowitz,et al.  Fundamentals of data structures in C , 1976 .

[5]  Chen‐Chung Liu *,et al.  Peer assessment through web‐based knowledge acquisition: tools to support conceptual awareness , 2005 .

[6]  Gwo-Dong Chen,et al.  Discovering Decision Knowledge from Web Log Portfolio for Managing Classroom Processes by Applying Decision Tree and Data Cube Technology , 2000 .

[7]  G. Kelly The Psychology of Personal Constructs , 2020 .

[8]  P Eric,et al.  Concept Mapping: a Graphical System for Understanding the Relationship Between Concepts , 1997 .

[9]  Hugh Munby,et al.  Concept mapping and misconceptions: a study of high-school students' understandings of acids and bases , 1991 .

[10]  Gwo-Dong Chen,et al.  Student modeling for performance assessment using Bayesian network on web portfolios , 2001 .

[11]  C A Nelson,et al.  Learning to Learn , 2017, Encyclopedia of Machine Learning and Data Mining.

[12]  Joseph D. Novak,et al.  Assessing science understanding , 2005 .

[13]  Lynne Anderson-Inman,et al.  Computer-Based Concept Mapping: Active Studying for Active Learners. , 1993 .

[14]  Nick Hammond,et al.  Computer-based tools to support learning from hypertext: concept mapping tools and beyond , 1994 .

[15]  P. Reimann,et al.  Turning examples into cases: Acquiring knowledge structures for analogical problem solving , 1996 .

[16]  J. Mintzes,et al.  The concept map as a research tool: Exploring conceptual change in biology , 1990 .

[17]  Yao-Ting Sung,et al.  Learning through computer-based concept mapping with scaffolding aid , 2001, J. Comput. Assist. Learn..

[18]  Katia Passerini,et al.  A developmental model for distance learning using the Internet , 2000 .

[19]  Chun-Chieh Huang,et al.  The evaluation and influence of interaction in network supported collaborative concept mapping , 2000, Comput. Educ..

[20]  Petra Perner,et al.  Data Mining - Concepts and Techniques , 2002, Künstliche Intell..

[21]  R. Shavelson,et al.  Problems and Issues in the Use of Concept Maps in Science Assessment. , 1996 .

[22]  Brian R. Gaines,et al.  Concept maps as hypermedia components , 1995, Int. J. Hum. Comput. Stud..

[23]  J. Novak Concept maps and Vee diagrams: two metacognitive tools to facilitate meaningful learning , 1990 .