Automatically Growing Dually Adaptive Online
IRT Testing
System
Authors
Hirose, Hideo; Aizawa, Yu
Source
IEEE International Conference on Teaching, Assessment, and Learning
for Engineering 2014 (TALE 2014), 5C_5,
pp.1-6, December 8-10,
2014, Te Papa Tongarewa National Museum of New Zealand, Wellington,
New Zealand
Abstract
The
item response theory (IRT) is widely used in many fields recently
because it provides us the abilities of examinees and the difficulties
of items simultaneously. Online IRT test systems are often equipped
with the adaptive testing. Such a testing method selects the most
appropriate items to examinees automatically. However, the item
difficulty values remain the same even if the features of the examinees
and the size of the items change. Calibration of the difficulty
values is required in such cases, and the dually adaptive online
IRT testing system works, where gdually adaptiveh means that one
is targeted to the adequate item selection and the other is targeted
to the adjustment of the item difficulty values. Using this, the
database in the system will automatically be growing and be updated.
In this paper, we introduce such a novel system with applications.