On November 14–16, 2016, in Washington DC, United States, as part of the Newton research, Adaptemy presented a virtual paper called “An Evaluation Framework for Adaptive and Intelligent Tutoring Systems” in the E-Learn 2016 World Conference on E-Learning. In this paper, we reviewed the existing framework literature, considered the important parameters and assessment methods that should be included in a comprehensive framework, and proposed an evaluation framework.
Evaluation frameworks for adaptive and intelligent tutoring systems have largely focused on their prediction power or user experience. However, neither subjective or objective method alone is enough to assess all the properties of any given system, including effectiveness, efficiency and accuracy. Most higher education authorities believe that personalised, adaptive learning could make a positive impact on the field of education.
We propose an evaluation framework as well as evaluation recommendations for adaptive and intelligent learning systems. This evaluation framework incorporates objective and subjective measures in terms of learning effectiveness, learning efficiency, system accuracy, satisfaction, ease of use and learner engagement. Furthermore, we provide recommendations for comparison evaluation (with and without the use of adaptive e-learning systems) (Lynch & Ghergulescu, 2016).
Lynch, T., Ghergulescu, I. (2016). An Evaluation Framework for Adaptive and Intelligent Tutoring Systems. Paper presented at the E-Learn 2016 World Conference on E-Learning, Washington, DC, United States.