Generative Learning Objects Instantiated with Random Numbers Based Expressions

Ciprian Bogdan Chirila, Horia Ciocârlie, Lăcrămioara Stoicu-Tivadar


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.


e-learning, learning objects, generative learning objects, meta-programming, compiling techniques, function composition

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