An Approach to Automatically generating Riddles aiding Concept
  Attainment
Niharika Sri Parasa Chaitali Diwan Srinath Srinivasa
One of the primary challenges in online learning environments, is to retain
learner engagement. Several different instructional strategies are proposed
both in online and offline environments to enhance learner engagement. The
Concept Attainment Model is one such instructional strategy that focuses on
learners acquiring a deeper understanding of a concept rather than just its
dictionary definition. This is done by searching and listing the properties
used to distinguish examples from non-examples of various concepts. Our work
attempts to apply the Concept Attainment Model to build conceptual riddles, to
deploy over online learning environments. The approach involves creating
factual triples from learning resources, classifying them based on their
uniqueness to a concept into `Topic Markers' and `Common', followed by
generating riddles based on the Concept Attainment Model's format and capturing
all possible solutions to those riddles. The results obtained from the human
evaluation of riddles prove encouraging.