Generative Learning Objects Instantiated with Random Numbers Based Expressions

Abstract

The development of interactive e-learning content requires special skills like programming  techniques, web integration, graphic design etc. Generally, online educators do not possess such  skills and their e-learning products tend to be static like presentation slides and textbooks. In this  paper we propose a new interactive model of generative learning objects as a compromise between
static, dull materials and dynamic, complex software e-learning materials developed by specialized  teams. We find that random numbers based automatic initialization learning objects increases  content diversity, interactivity thus enabling learners' engagement. The resulted learning object  model is at a limited level of complexity related to special e-learning software, intuitive and capable  of increasing learners' interactivity, engagement and motivation through dynamic content. The  approach was applied successfully on several computer programing disciplines.