Adaptivity and Interface Design: A Human-Computer Interaction Study in E-Learning Applications
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Computer based teaching-learning or e-learning provides more flexible methods of interactions with learning contents compared to the traditional classroom set-up. It motivates learners towards self learning and evaluation in an open virtual environment. However, usefulness of e-learning depends upon learner beliefs and the degree of adjustments or adaptations shown by him in his learning behavior. The learning goal and the learning interface have a decisive role in influencing learner adaptations. Various researchers have addressed issues in learner adaptations to the (a) cognitive levels of learning goals and the (b) interaction environment. However they have been addressed separately. Also an efficient methodology of quantifying learner adaptations and learner ability of familiarizing with learning interfaces was lacking. Both these shortcomings have been addressed in this thesis by providing a methodology of measuring adaptations. In this thesis an adaptation score that quantifies adaptations and an adaptivity score that quantifies ability of adapting have been proposed. The thesis attempts to explain the combined impact of learning task complexity and user interface design on learner adaptations in beliefs, interactions and performance which was not done before. Quantitative data of e-learning interactions involving basic three cognitive levels of learning complexity viz. knowledge, comprehension and application and two types of navigation designs viz. hierarchical horizontal menu and non-hierarchical split menu was analyzed. The empirical data suggest the fact that learning task complexity (cognitive level) affects adaptations in interactions between similar tasks (task adaptation) on same interface. Since these task adaptations did not vary across user interfaces, they were found to be task-dependant. As a result, the cognitive load of learning could be judged by the task adaptation score and utilized to adapt pedagogic strategy or learning content. Results of our study reveal that belief in self e-learning skills (self efficacy) affected adaptations in learning behavior and learning performance. On the other hand, adaptivity to navigation design of user interface was found to be interface-dependant and, interestingly, also influenced learning performance. The beliefs were found to mediate the adaptivity scores. Based on the results of the experiments, the thesis provides recommendations on utilization of these metrics in personalization of e-learning on the bases of the adaptations. The study reveals research on the phenomenon of interactions between human and computer using a multidisciplinary view of Human Computer Interaction (HCI) combining computer science, behavioral science and education.
Supervisor: Pradeep Yammiyavar
COMPUTER SCIENCE AND ENGINEERING