ACM SIGCSE publication.
Related Pages (PDFs)
Overview
Adaptive Educational Systems (also Adaptive Learning Systems) aim to precisely tailor
education and training to the needs of educators and learners [NIST]. Adaptive learning
has roots in Artificial Intelligence and Robotics and for online education tools the steps
for adaptive learning are as follows:
Step 1: Diagnostic test for learners
Step 2: Automatic analysis of learner’s performance, identification of deficiencies
and creation of a student model
Step 3: Remedial course presented to learner based on the student model
In presenting such a customized course the goals and key features of such tools are
[Brusilovsky, Weber]:
- Adaptive Presentation: Adapting the content based on the learner’s
goals,
knowledge, experience and other information stored in the student model - Curriculum Sequencing (Instructional Planning Technology): Providing
an
individualized “optimal path” thorough the learning material - Adaptive Navigation Support: Displaying hyperlinks adaptively
to better help
navigation - Intelligent Analysis of student solutions: Providing comprehensive
feedback
about problems/exercises that a student has completed and updating the student
model accordingly - Interactive problem solving support: Provide hints and intelligent
help to students
depending upon their performance - Example based problem solving: This also provides intelligent
help but in the
form of examples from previous materials/questions already covered
- Helps pace the same course appropriately for novice and advanced
students
presenting content they would enjoy - Adaptive navigation helps novices find their way in hyperspace
and prevents
them from getting lost - Courses adapts to student’s background and knowledge enabling
quicker
completion for advanced students - These systems are mostly web based and have a familiar interface
to internet web
sites helping easy use by novices
- The tools are complex to develop and deploy and the technology
is new and
currently under research and development - Course setup requires much effort and preparation by the teaching
staff since
difficulty levels of the materials and questions, course structure and content need
to be rigorously defined - Adaptive Educational Systems are therefore appropriate for online
courses that cater to a
wide student population with varying levels of knowledge. This will provide a course
suitable for all students due its adaptive nature and also justify the additional resources
required to setup the course.
[Bloom 1956] Bloom, B. S., (1956) Taxonomy of Educational Objectives: The Classification of Educational Goals: Handbook I
[Brusilovsky 1996] Brusilovsky, P., (1996) Methods and Techniques of Adaptive Hypermedia, User Modeling and User Adapted Interaction, 1996, v 6, n 2-3, pp 87-129 (Special issue on adaptive hypertext and hypermedia)
[Brusilovsky 2000] Brusilovsky, P., (2000) Course Sequencing for Static Courses and Applying ITS Techniques in Large-Scale Web-Based Education, in Gauthier G, Frasson C, Van Lehn K (eds.), Intelligent Tutoring Systems, Proceedings of the 5th International Conference on Intelligent Tutoring Systems, Lecture Notes in Computer Science, v.1839 pp. 625-634, Springer Verlag, Berlin 2000
[Chickering 1996] Chickering, A. W., Ehrmann, S. C., (1996). Implementing the seven principles: technology as lever, AAHE Bulletin, http://www.tltgroup.org/programs/seven.html
[Conati 2001] Conati, C., VanLehn, K., (2001) Providing Adaptive Support to the Understanding of Instructional Material, IUI, Santa Fe, New Mexico 2001
[Cristea 2002] Cristea A, Aroyo L, (2002) Adaptive authoring of Adaptive Educational Hypermedia, Adaptive Hypermedia and Adaptive Web-Based systems, pp. 122-132 LNCS 2347, Springer Verlag 2002
[De Bra 1998] De Bra, P. and Calvi, L., (1998) AHA! An open Adaptive Hypermedia Architecture, The New Review of Hypermedia and Multimedia, vol. 4, pp. 115-139, Taylor Graham Publishers, 1998.
[Eklund 1998] Eklund, J., Brusilovsky, P., (1998) The Value of Adaptivity in Hypermedia Learning Environments: A Short Review of Empirical Evidence. 2nd Workshop on Adaptive Hypertext and Hypermedia Held in Conjunction with HYPERTEXT '98: The Ninth ACM Conference on Hypertext and Hypermedia, June 20-24, Pittsburgh, PA
[Eklund 2000] Eklund, J., Sinclair, K., (2000) An empirical appraisal of the effectiveness of adaptive interfaces for instructional systems, Educational Technology & Society 3(4), IEEE
[IB] InterBook http://www2.sis.pitt.edu/~peterb/InterBook.html
[Manuel] Freire-Morán, M., Visualization of hypermedia course structures, Departamento de Ingeniería Informática - Universidad Autónoma de Madrid
[ML] MetaLinks http://ddc.hampshire.edu/metalinks/
[NetCoach] http://art.ph-freiburg.de/www/index-e.htm
[NIST] http://www.atp.nist.gov/atp/97wp-lt.htm
[Parker 2002] Parker, B., Hankins, J., (2002) AAHE's seven principles for good practice applied to an online literacy course, Middle Tennessee State University, Consortium for Computing in Small Colleges
[Penn] Writing effective questions to promote learning, Pennsylvania State University, http://tlt.its.psu.edu/suggestions/questionwriting/index.shtml
[Specht 1998] Specht, M., (1998) Empirical evaluation of adaptive annotation in hypermedia. Proceedings of ED-MEDIA & ED-TELECOM98, Vol. 2, Charlottesville, VA: AACE, 1327-1332
[Weber] Weber, G., Adaptive Learning Systems in the World Wide Web, Department of Psychology, University of Education Freiburg, Germany
[Weber 2001] Weber, G., Hans-Christian, K., and Weibelzahl, S., (2001) Developing Adaptive Internet Based Courses with the Authoring System NetCoach. Pedagogical University Freiburg, Germany
[Weibelzahl 2002] Weibelzahl, S., and Weber, G., (2002) Adapting to Prior Knowledge of Learners, Pedagogical University Freiburg, Germany
