Automated expert modeling for automated student evaluation

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

Volumn 4053 LNCS, Issue , 2006, Pages 1-10

  Abbott, Robert G ^a  

^a SANDIA NATIONAL LABORATORIES   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATION THEORY; EXPERT SYSTEMS; LEARNING SYSTEMS; MATHEMATICAL MODELS; STUDENTS;

AUTOMATED STUDENT EVALUATION; INTELLIGENT TUTORING SYSTEMS (ITS); MANUAL KNOWLEDGE; SYSTEM IMPLEMENTATION;

COMPUTER SIMULATION;

EID: 33746359663     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11774303_1     Document Type: Conference Paper

References (18)

1. Centre, C.A.L.L.: The after action review process, learning more from our training. Army Lessons Learned Centre Dispatches 6(3) (1999)
2. DeGrosky, M.T.: Improving after action review (aar) practice. In: Eighth International Wildland Fire Safety Summit. (2005)
3. Meliza, L.: After action review: Methods and tools, http://www.hqda.army. mil/ari/news/factsheets.shtml, retrieved on Dec 2, 2005 (2004)
4. Jensen, R., Nolan, M., Chen, D.Y.: Automatic causal explanation analysis for combined arms training aar. In: Proceedings of the Industry/Interservice, Training, Simulation and Education Conference (I/ITSEC). (2005)
5. Cohen, P.A., Kulik, J.A., Kulik, C.C.: Educational outcomes of tutoring: A meta-analysis of findings. American Educational Research Journal 10 (1982) 237-248
6. Corbett, A.T.: Cognitive computer tutors: Solving the two-sigma problem. In: UM '01: Proceedings of the 8th International Conference on User Modeling 2001, London, UK, Springer-Verlag (2001) 137-147
7. Burns, H., Capps, C.: Foundations of intelligent tutoring systems: An introduction. In Polson, M.C., Richardson, J.J., eds.: Foundations of Intelligent Tutoring Systems. Lawrence Erlbaum Associates Publishers (1988) 1-18
8. Murray, T.: Authoring intelligent tutoring systems: An analysis of the state of the art. International Journal of Artificial Intelligence in Education 10 (1999) 98-129
9. Welch, G., Foxlin, E.: Motion tracking: no silver bullet, but a respectable arsenal. IEEE Computer Graphics and Applications 22(6) (2002) 24-38
10. Quinlan, J.R.: C4.5: Programs for Machine Learning. Morgan Kaufmann (1992)
11. Srinivasa, N., Ahuja, N.: A topological and temporal correlator network for spatiotemporal pattern learning, recognition and recall. IEEE Transactions on Neural Networks 10(2) (1999) 356-371
12. Hastie, T., Tibshirani, R., Friedman, J.: The Elements of Statistical Learning. Springer (2001)
13. Sutton, R., Barto, A.: 3.5 The Markov Property. In: Reinforcement Learning. MIT Press (1998) 61-65
14. Kornecki, A., Hilburn, T., Diefenbach, T., Towhidnajad, M.: Intelligent tutoring issues for ate training system. IEEE Transactions on Control Systems Technology 1(3) (1993) 204-211
15. Hess, S.M., MacMillan, J., Sefarty, D., Elliot, L.: From cognitive task analysis to simulation: Developing a synthetic team task for awacs weapons directors. Air Force Research Laboratory (1999)
16. Kohavi, R.: A study of cross-validation and bootstrap for accuracy estimation and model selection. In: IJCAI. (1995) 1137-1145
17. Zweig, Campbell: Receiver-operating characteristic (roc) plots: a fundamental evaluation tool in clinical medicine. Clin Chem 39(4) (1993) 561-577
18. Ali, K., Langley, P., Maloof, M., Sage, S., Binford, T.: Improving rooftop detection with interactive visual learning. In: Proceedings of the Image Understanding Workshop, San Francisco, CA, Morgan Kaufmann (1998) 479-492