SWIFT Adaptive Tests
"Gemini's technology made it so easy for us to expand and enhance our
eLearning suite of products - we were able to do it in a matter of hours."
Joe Oswald, Vice President of the Technical Education department at RAND
Worldwide.
A wide range of questions can be easily developed in SWIFT Author and
published to a number of different environments depending on your corporate
requirements. Used by organizations worldwide SWIFT tests and Stellar
assessments provide secure and effective testing features for assessing
competency, skills and for certification purposes.
SWIFT Tests
SWIFT tests can be delivered as stand-alone tests or within a SWIFT
course. They are fixed-length and designed to assess learner competency
based on a desired mastery level. Questions are selected randomly using
a wide range of question types. SWIFT Tests can be set to the number of
times a learner can attempt a test and the length of time they are allowed
to complete a test.
Adaptive Testing
Intelligent Tutoring Systems gather information about a student's progress
by observing them as they interact with the learning environment. Many
systems use exercises, quizzes, and exams as the setting for these observations
since the range of possible inference about the student can be more easily
constrained. Organizations also require that a training system provide
concrete records of progress, we chose formative and summative testing
as our means for observing the student in SWIFT.
One of the problems with traditional exams is that they are of fixed
length; a student must complete a long series of questions in order for
the system to determine how well they know a subject. This characteristic
can cause frustration for both novices and experts, who may know after
a few questions that the subject matter is either bewildering or trivial.
Adaptive testing allows exams to be significantly shorter than traditional
tests, without losing any predictive power about a learner's mastery of
the material. The SWIFT Adaptive Testing algorithm was based on the work
of [Frick & Welch, 1993]. The algorithm uses Bayes' theorem to estimate
the probability that the learner is a master or non-master of the material
after each test question is answered. In SWIFT, novices (non-masters)
and experts (masters) can be determined in as few as five questions.
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