Yi Shang
- 1.J. R. Anderson, A. T. Corbett, K. Koedinger, and R. Pelletier. Cognitive tutors: lessons learning. The Journal of the Learning Sciences, 4(2):167-207, 1995.]]Google Scholar
Cross Ref
- 2.T. A. Angelo. The campus as learning community: Seven promising shifts and seven powerful levers. AAHE Bulletin, 49(9):3-6, 1997.]]Google Scholar
- 3.L. Barnett, J. Kent, J. Casp, and D. Green. Design and implementationof an interactive tutorial framework. SIGCSE Bulletin, 30(1):87-91, March 1998.]] Google ScholarDigital Library
- 4.M. Bauer. A Dempster-Shafer approach to modeling agent references for plan recognition. User Modeling and User-Adapted Interaction, 5:317-348, 1996.]]Google ScholarCross Ref
- 5.J. E. Beck and B. P. Woolf. Using a learning agent with a student model. In B. P. Goettl, H. M. Halff, C. L. Redfield, and V. J. Shute, editors, Intelligence Tutoring System (Proc. 4th Int'l Conf. ITS'98), pages 6-15. Springer, 1998.]] Google ScholarDigital Library
- 6.C. Bonwell. Building a supportive climate for active learning. The National Teaching and Learning Forum, 6(1):4-7, 1996.]]Google Scholar
- 7.C. Buron, M. Grinder, and R. Ross. Tying it all together: Creating self-contained, animated, interactive, web-based resources for computer science education. SIGCSE Bulletin, 31(1):7-11, March 1999.]] Google ScholarDigital Library
- 8.C. A. Carver, R. A. Howard, and W. D. Lane. Enhancing student learning through hypermedia courseware and incorporation of student learning styles. IEEE Trans. on Education, 42(1):33-38, February 1999.]]Google ScholarDigital Library
- 9.C. Chou. Developing hypertext-based learning courseware for computer networks: The macro and micro stages. IEEE Trans. on Education, 42(1):39-44, February 1999.]]Google ScholarDigital Library
- 10.K. P. Cross. Why learning communities? why now? About Campus, 3(3):4-11, 1998.]]Google ScholarCross Ref
- 11.A. Davidovic and E. Trichina. Open learning environment and instruction system (OLEIS). SIGCSE Bulletin, 30(3):69-72, September 1998.]] Google ScholarDigital Library
- 12.V. F. Hartman. Teaching and learning style preferences: Transitions through technology. VCCA Journal, 9(2):18-20, 1995.]]Google Scholar
- 13.F. Hattori, T. Ohguro, M. Yokoo, S. Matsubara, and S. Yoshida. Socialware: Multiagent systems for supporting network communities. Communications of the ACM, 42(3):55-61, March 1999.]] Google ScholarDigital Library
- 14.L. W. Hawkes, S. J. Derry, and E. A. Rundensteiner. Individualized tutoring using an intelligent fuzzy temporal relational database. Int'l Journal of Man-Machine Studies, 33:409-429, 1990.]] Google ScholarDigital Library
- 15.E. Freeman S. Hupfer and K. Arnold. JavaSpaces Principles, Patterns, and Practice. Addison-Wesley, 1999.]] Google ScholarDigital Library
- 16.JATLite. http://java.stanford.edu/java agent/html.]]Google Scholar
- 17.N. R. Jennings and M. J. Wooldridge. Agent technology: Foundations, applications, and Markets. Springer, Berlin, 1998.]] Google ScholarDigital Library
- 18.H.A. Latchman, C. Salzmann, D. Giblet, and H. Bouzekri. Information technology enhanced learning in distance and conventional education. IEEE Trans. on Education, 42(4):247-254, November 1999.]]Google ScholarDigital Library
- 19.D. McArthur, C. Stasz, J. Hotta, O. Peter, and C. Burdorf. Skill-oriented task sequencing in an intelligent tutor for basic algebra. Instructional Science, 17(4):281-307, 1988.]]Google ScholarCross Ref
- 20.W. R. Murray. A practical approach to Bayesian student modeling. In B. P. Goettl, H. M. Halff, C. L. Redfield, and V. J. Shute, editors, Intelligence Tutoring System (Proc. 4th Int'l Conf. ITS'98), pages 424-433. Springer, 1998.]] Google ScholarDigital Library
- 21.V. A. Petrushin and K. M. Sinista. Using probabilistic reasoning techniques for learner modeling. In World Conf. on AI in Education, pages 418-425, Edinburgh, 1993.]]Google Scholar
- 22.L. G. Richards. Promoting active learning with cases and instructional modules. Journal of Engineering Education, 84(4):375-381, 1995.]]Google ScholarCross Ref
- 23.L. Rubin and C. Hebert. Model for active learning: Collaborative peer teaching. College Teaching, 46(1):26-30, 1998.]]Google ScholarCross Ref
- 24.Y. Shang, C. Sapp, and H. Shi. An intelligent web representative. Information, 3(2):253-262, 2000.]]Google Scholar
- 25.Y. Shang and H. Shi. A web-based multi-agent system for interpreting medical images. World Wide Web, 2(4):209-218, 1999.]] Google ScholarDigital Library
- 26.H. Shi, Y. Shang, A. Joshi, and M. Jurczyk. Laboratory-oriented teaching in web and distributed computing. In Proc. 2000 ASEE Annual Conference & Exposition, St. Louis, June 2000.]]Google Scholar
- 27.M. K. Stern and B. P. Woolf. Curriculum sequencing in a Web-based tutor. In B. P. Goettl, H. M. Halff, C. L. Redfield, and V. J. Shute, editors, Intelligence Tutoring System (Proc. 4th Int'l Conf. ITS'98), pages 584-593. Springer, 1998.]] Google ScholarDigital Library
- 28.V. Tinto. Universities as learning organizations. About Campus, 1(6):2-4, 1997.]]Google ScholarCross Ref
- 29.M. Villano. Probabilistic students models: Bayesian belief networks and knowledge space theory. In Intelligence Tutoring System (Proc. 2nd Int'l Conf. ITS'92), pages 491-498. Springer, 1992.]] Google ScholarDigital Library
- 30.G. Weber. Individual selection of examples in an intelligent learning environment. Journal of Artificial Intelligence in Education, 7(1):3-31, 1996.]] Google ScholarDigital Library
- 31.G. Weiss, editor. Multiagent Systems: A Modern Approach to Distributed Artificial Intelligence. The MIT Press, Cambridge, MA, 1999.]] Google ScholarDigital Library
- 32.xml.com. XML.COM online, 2001. http://www.xml.com.]]Google Scholar
Index Terms
- An intelligent distributed environment for active learning
Recommendations
An intelligent distributed environment for active learning
Active learning is an effective learning approach. In this article we present an intelligent agent-assisted environment for active learning to better support the student-centered, selfpaced, and highly interactive learning approach. The environment uses ...
Motivational active learning: engaging university students in computer science education
ITiCSE '14: Proceedings of the 2014 conference on Innovation & technology in computer science educationAttracting and engaging computer science students to enhance their mathematical and algorithmic thinking skills are challenging tasks. In winter 2013 we introduced a new teaching format for a course, which combines theory in computer science with hands-...
Students' perceptions of clickers as an instructional tool to promote active learning
The purpose of this study was to evaluate students' perceptions of clickers as an instructional tool to promote active learning in a Physical Geography undergraduate class. A convenience sample of 24 undergraduate students registered in a physical ...
Comments