Designing Adaptive Learning Environments with Learning Design

12.6 Conclusion

Contemporary learning theory suggests that individual learners differ in the way they learn and that learning must be tailored to the individual learner. Consequently, learning environments must have the flexibility to adapt themselves for the individual learner. This chapter has discussed several different learner-characteristic, driven adaptive learning strategies and how these strategies can be completely implemented within the constraints of the existing LD specification. Adaptive strategies discussed include 1) Synchronous vs. Asynchronous, 2) Rule-Example vs. Example-Rule, and 3) Feedback adaptation. This chapter has also detailed some of the ways in which implementing adaptive strategies entirely within LD can prove insufficient, and suggested one way around these problems.

The LD specification is the first attempt to move existing e-learning interoperability efforts from first-generation products that have traditionally focused primarily on content toward more robust second-generation environments that support richer learning strategies. While LD does not offer all features necessary for implementing extremely complex forms of adaptive learning, it does provide a way to implement many simple adaptive learning strategies. Consequently, this is a positive step toward providing more robust infrastructure for adaptive learning. Thus, it must be viewed as a good first effort that will undoubtedly produce fruit and provide the catalyst for future specifications efforts in this area.