Toward next-generation, intelligent tutors: Adding natural handwriting input

IEEE Multimedia

Volumn 15, Issue 3, 2008, Pages 64-68

  Anthony, Lisa ^a   Yang, Jie ^a   Koedinger, Kenneth R ^a  

^a CARNEGIE MELLON UNIVERSITY   (United States)

Author keywords

Accuracy; Algebra; Educational institutions; Equations; Handwriting recognition; Multimedia communication; Training

Indexed keywords

ALGEBRA; COMPUTER AIDED INSTRUCTION; LEARNING SYSTEMS;

ACCURACY; EDUCATIONAL INSTITUTIONS; EQUATIONS; HANDWRITING RECOGNITION; INTELLIGENT TUTORING SYSTEMS; MULTIMEDIA COMMUNICATION; STUDENTS LEARNING; TRAINING;

INTELLIGENT SYSTEMS;

EID: 52649168356     PISSN: 1070986X     EISSN: None     Source Type: Journal    
DOI: 10.1109/MMUL.2008.73     Document Type: Article

References (16)

1. C. Wood, "Education," PC Magazine, 2002; http:// www.pcmag.com/article2/0,4149,15154,00.asp.
2. A.T. Corbett, "Cognitive Computer Tutors: Solving the Two-Sigma Problem," Proc. User Modeling, A. Kobsa et al., eds., LNCS 2109, Springer, 2001, pp. 137-147.
3. R.E. Mayer, Multimedia Learning, Cambridge Univ. Press, 2001.
4. Nat'l Center for Education Statistics, Int'l Outcomes of Learning in Mathematics Literacy and Problem Solving, 2005; http://nces.ed.gov/ pubs2005/2005003.pdf.
5. L. Anthony, J. Yang, and K.R. Koedinger, "Evaluation of Multimodal Input for Entering Mathematical Equations on the Computer," Proc. Conf. Human Factors in Computing Systems (CHI), ACM Press, 2005, pp. 1184-1187.
6. L. Anthony, J. Yang, and K.R. Koedinger, "Benefits of Handwritten Input for Students Learning Algebra Equation Solving," Proc. Artificial Intelligence in Education, IOS Press, 2007, pp. 521-523.
7. J. Sweller, "Cognitive Load During Problem Solving: Effects on Learning," Cognitive Science, vol. 12, no. 2, 1988, pp. 257-285.
8. K.R. Koedinger and V. Aleven, "Exploring the Assistance Dilemma in Experiments with Cognitive Tutors," Educational Psychology Rev, vol. 19, no. 3, 2007, pp. 239-264.
9. B.Y. White and J.R. Frederiksen, "Inquiry, Modeling, and Metacognition: Making Science Accessible to all Students," Cognition and Instruction, vol. 16, no. 1, 1998, pp. 3-118.
10. J.R. Anderson et al., "Cognitive Tutors: Lessons Learned," J. Learning Sciences, vol. 4, no. 2, 1995, pp. 167-207.
11. S. Smithies, K. Novins, and J. Arvo, "Equation Entry and Editing via Handwriting and Gesture Recognition," Behaviour & Information Technology, vol. 20, no. 1, 2001, pp. 53-67.
12. E. Tapia and R. Rojas, "Recognition of On-Line Handwritten Mathematical Expressions Using a Minimum Spanning Tree Construction and Symbol Dominance," Graphics Recognition: Recent Advances & Perspectives, J. Lladós and Y.-B. Kwon, eds., LNCS 3088, Springer, 2004, pp. 329-340.
13. R. Zanibbi, D. Blostein, and J.R. Cordy, "Recognizing Mathematical Expressions Using Tree Transformation," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 24, no. 11, 2002, pp. 1455-1467.
14. V.I. Levenshtein, "Binary Codes Capable of Correcting Deletions, Insertions, and Reversals," Soviet Physics Doklady, vol. 10, no. 8, 1966, pp. 707-710.
15. L. Anthony, J. Yang, and K.R. Koedinger, "Adapting Handwriting Recognition for Applications in Algebra Learning," Proc ACM Workshop Educational Multimedia and Multimedia Education, ACM Press, 2007, pp. 47-56.
16. S. Oviatt, "Taming Recognition Errors with a Multimodal Interface," Comm. ACM, vol. 43, no. 9, 2000, pp. 45-51.