Sense making alone doesn't do it: Fluency matters too! ITS support for robust learning with multiple representations

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 7315 LNCS, Issue , 2012, Pages 174-184

  Rau, Martina A ^a   Aleven, Vincent ^a   Rummel, Nikol ^a,b   Rohrbach, Stacie ^c  

^a Carnegie Mellon University ^*  (United States)

^b RUHR UNIVERSITY BOCHUM   (Germany)

^c CARNEGIE MELLON UNIVERSITY   (United States)

Author keywords

classroom evaluation; connection making; fractions; intelligent tutoring system; Multiple representations

Indexed keywords

CLASSROOM EVALUATION; CONNECTION MAKING; FRACTIONS; INTELLIGENT TUTORING SYSTEM; MULTIPLE REPRESENTATION;

COMPUTER AIDED INSTRUCTION; EDUCATION COMPUTING; EXPERIMENTS;

STUDENTS;

EID: 84862505657     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-30950-2_23     Document Type: Conference Paper

References (21)

1. Suh, J., Moyer, P.S.: Developing Students' Representational Fluency Using Virtual and Physical Algebra Balances. Computers in Mathematics and Science Teaching 26, 155-173 (2007)
2. Ainsworth, S.: DeFT: A conceptual framework for considering learning with multiple representations. Learning and Instruction 16, 183-198 (2006)
3. Rau, M.A., Aleven, V., Rummel, N.: Intelligent tutoring systems with multiple representations and self-explanation prompts support learning of fractions. In: 14th International Conference on Artificial Intelligence, pp. 441-448. IOS Press, Amsterdam (2009)
4. Bodemer, D., et al.: Supporting learning with interactive multimedia through active integration of representations. Instructional Science 33, 73-95 (2005)
5. van der Meij, J., de Jong, T.: Supporting Students' Learning with Multiple Representations in a Dynamic Simulation-Based Learning Environment. Learning and Instruction 16, 199-212 (2006)
6. Rau, M.A., et al.: How to schedule multiple graphical representations? A classroom experiment with an intelligent tutoring system for fractions. In: To appear in the Proceedings of ICLS 2012 (accepted, 2012)
7. Bodemer, D., et al.: The Active Integration of Information during Learning with Dynamic and Interactive Visualisations. Learning and Instruction 14, 325-341 (2004)
8. National Mathematics Advisory Panel: Foundations for Success: Report of the National Mathematics Advisory Board Panel, U.S. Government Printing Office (2008)
9. Charalambous, C.Y., Pitta-Pantazi, D.: Drawing on a Theoretical Model to Study Students' Understandings of Fractions. Educational Studies in Mathematics 64, 293-316 (2007)
10. Siegler, R.S., et al.: Developing effective fractions instruction: A practice guide. In: National Center for Education Evaluation and Regional Assistance. IES, U.S. Department of Education, Washington, DC (2010)
11. Koedinger, K.R., et al.: Knowledge-Learning-Instruction Framework: Bridging the Science-Practice Chasm to Enhance Robust Student Learning. Cognitive Science (in press)
12. Seufert, T., Brünken, R.: Cognitive load and the format of instructional aids for coherence formation. Applied Cognitive Psychology 20, 321-331 (2006)
13. Bodemer, D., Faust, U.: External and mental referencing of multiple representations. Computers in Human Behavior 22, 27-42 (2006)
14. Renkl, A.: The worked-out example principle in multimedia learning. In: Mayer, R. (ed.) Cambridge Handbook of Multimedia Learning, pp. 229-246. Cambridge University Press, Cambridge (2005)
15. Salden, R.J.C.M., Koedinger, K.R., Renkl, A., Aleven, V., McLaren, B.M.: Accounting for beneficial effects of worked examples in tutored problem solving. Educational Psychology Review 22, 379-392 (2010)
16. Berthold, K., Eysink, T., Renkl, A.: Assisting self-explanation prompts are more effective than open prompts when learning with multiple representations. Instructional Science 37, 345-363 (2009)
17. Koedinger, K.R., Corbett, A.: Cognitive Tutors: Technology Bringing Learning Sciences to the Classroom. In: Sawyer, R.K. (ed.) The Cambridge Handbook of the Learning Sciences, pp. 61-77. Cambridge University Press, New York (2006)
18. Koedinger, K.R., Corbett, A.: Cognitive tutors: Technology bringing learning sciences to the classroom. Cambridge University Press, New York (2006)
19. Rittle-Johnson, B., Koedinger, K.R.: Designing Knowledge Scaffolds to Support Mathematical Problem Solving. Cognition and Instruction 23, 313-349 (2005)
20. Aleven, V., et al.: A new paradigm for intelligent tutoring systems: Example-tracing tutors. International Journal of Artificial Intelligence in Education 19, 105-154 (2009)
21. Raudenbush, S.W., Bryk, A.S.: Hierarchical Linear Models: Applications and Data Analysis Methods. Sage Publications, Newbury Park (2002)