Premium
Item difficulty in the evaluation of computer‐based instruction: An example from neuroanatomy
Author(s) -
Chariker Julia H.,
Naaz Farah,
Pani John R.
Publication year - 2012
Publication title -
anatomical sciences education
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.126
H-Index - 51
eISSN - 1935-9780
pISSN - 1935-9772
DOI - 10.1002/ase.1260
Subject(s) - generalization , computer science , computer assisted instruction , set (abstract data type) , neuroanatomy , margin (machine learning) , affect (linguistics) , mathematics education , cognitive psychology , psychology , artificial intelligence , machine learning , multimedia , mathematical analysis , mathematics , communication , psychiatry , programming language
This article reports large item effects in a study of computer‐based learning of neuroanatomy. Outcome measures of the efficiency of learning, transfer of learning, and generalization of knowledge diverged by a wide margin across test items, with certain sets of items emerging as particularly difficult to master. In addition, the outcomes of comparisons between instructional methods changed with the difficulty of the items to be learned. More challenging items better differentiated between instructional methods. This set of results is important for two reasons. First, it suggests that instruction may be more efficient if sets of consistently difficult items are the targets of instructional methods particularly suited to them. Second, there is wide variation in the published literature regarding the outcomes of empirical evaluations of computer‐based instruction. As a consequence, many questions arise as to the factors that may affect such evaluations. The present article demonstrates that the level of challenge in the material that is presented to learners is an important factor to consider in the evaluation of a computer‐based instructional system. Anat Sci Educ. © 2011 American Association of Anatomists.