iRahul.com :: Adaptive Learning Systems

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

The advantages of using such tools are:

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 disadvantages of using such tools are:

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.

References

[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

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