Mining concept maps to understand university students’ learning

Proceedings of the 5th International Conference on Educational Data Mining, EDM 2012

Volumn , Issue , 2012, Pages

  Yoo, Jin Soung ^a   Cho, Moon Heum ^b  

^a INDIANA UNIVERSITY PURDUE UNIVERSITY FORT WAYNE   (United States)

^b KENT STATE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DATA MINING; EDUCATION COMPUTING;

COLLEGE STUDENTS; COMPLEX STRUCTURE; CONCEPT MAPPING; CONCEPT MINING; DATA MINING METHODS; EDUCATIONAL CONTEXT; UNIVERSITY STUDENTS; VISUAL REPRESENTATIONS;

STUDENTS;

EID: 85084014985     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (24)

1. R. Agarwal and R. Srikant. Fast algorithms for Mining association rules. In Proc. of International Conference on Very Large Databases(VLDB), 1994.
2. A. O. Alves, F. C. Pereira, and A. Cardoso. Automatic reading and learning from text. In Proc. of International Symposium on Artificial Intelligence, 2002.
3. S. Brin, R. Motwani, and C. Silverstein. Beyond market baskets: Generalizing association rules to correlations. In Proc. of ACM SIGMOD International Conference Management of Data, 1997.
4. N.-S. Chen, P. Kinshuk, C.-W. Wei, and H.-J. Chen. Mining e-learning domain concept map from academic articles. Computers & Education, 50:694-698, 2008.
5. R. B. Clariana and R. Koul. A computer-based approach for translating text into concept map-like representations. In Proc. of International Conference on Concep Mapping, 2004.
6. D. Cook and L. Holder. Mining graph data. Wiley Publication, 2007.
7. K. en Chang, Y.-T. Sung, and I.-D. Chen. The effect of concept mapping to enhance text comprehension and summarization. The Journal of Experimental Education, 71(1), 2005.
8. J. Huan, J. Prins, W. Wang, and J. Yang. SPIN: Mining maximal frequent subgraphs from graph databases. In Proc. of ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2004.
9. G. Karypis and M. Kuramochi. Frequent subgraph discovery. In Proc. of International Conference on Data Mining, 2001.
10. I. M. Kinchin. Using concept maps to reveal understanding: A Two-tier analysis. School Science Review, 81:41-46, 2000.
11. J. R. McClure, B. Sonak, and H. K. Suen. Concept map assessment of classroom learning: Reliability, validity, and logistical practicality. The Journal of Research in Science Teaching, 36:475-492, 1999.
12. J. D. Novak and A. J. Canas. The theory underlying concept maps and how to construct and use them. Technical report IHMC Cmap Tools 2006-01 Rev 01-2008.
13. J. D. Novak and D. B. Gowin. Learning how to learn. Cambridge. UK: Cambridge University Press, 1984.
14. W. G. Perry. Forms of intellectual and ethical development in the college years: A scheme. New York:Holt, Rinehart & Winston, 1970.
15. P. R. Pintrich, D. A. Smith, T. Garcia, and W. J. McKeachie. Reliability and predictive validity of the Motivated Strategies for Learning Questionnaire (MSLQ). Educational and Psychological Measurement, 53:801-813, 1993.
16. R. Shen, R. Richardson, and E. Fox. Concept maps as visual interfaces to digial libraries: summarization, collaboration, and automatic generation. In http://vw.indiana.edu/ivira03/shen-et-al.pdf, 2004.
17. P. Tan, M. Steinbach, and V. Kumar. Introduction to Data Mining. Addision Wesley, 2005.
18. E. M. Taricani and R. B. Clariana. A technique for automatically scoring open-ended concept maps . Educational Technology Research & Development, 54:65-82, 2006.
19. A. Valerio and D. Leake. Jump-starting concept map construction with knowledge extracted from documents. In Proc. of International Conference on Concept Mapping, 2006.
20. C. E. Weinstein, A. C. Schulte, and D. R. Palmer. LASSI: Learning and study strategies inventory. H & H Publishing Co., 1987.
21. P. Winne and N. Perry. Measuring self-regulated learning. In M. Boekaerts, P. Pintrich, & M. Zeidner (Eds.) Handbook of self-regulation (532-566) . CA: Academic Press, 2000.
22. X. Yan and J. Han. gSpan: Graph-based substructure pattern mining. In IEEE International Conference on Data Mining, 2001.
23. Y. Yin, J. Vanides, M. A. Ruiz-Primo, C. C. Ayala, and R. J. Shavelson. Comparision of two concept-mapping techniques: implications for scoring, interpretation, and use. Journal of Research in Science Teaching, 2:166-184, 2005.
24. B. Zimmerman. Investigating self-regulation and motivation: Historical background, methodological developments, and future prospects. American Educational Research Journal, 45:166-183, 2008.