Books > Computing & IT > Applications of computing > Artificial intelligence
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Application of Artificial Intelligence to Assessment (Hardcover)
Loot Price: R2,660
Discovery Miles 26 600
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Application of Artificial Intelligence to Assessment (Hardcover)
Series: The MARCES Book Series
Expected to ship within 10 - 15 working days
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Total price: R2,680
Discovery Miles: 26 800
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The general theme of this book is to present the applications of
artificial intelligence (AI) in test development. In particular,
this book includes research and successful examples of using AI
technology in automated item generation, automated test assembly,
automated scoring, and computerized adaptive testing. By utilizing
artificial intelligence, the efficiency of item development, test
form construction, test delivery, and scoring could be dramatically
increased. Chapters on automated item generation offer different
perspectives related to generating a large number of items with
controlled psychometric properties including the latest development
of using machine learning methods. Automated scoring is illustrated
for different types of assessments such as speaking and writing
from both methodological aspects and practical considerations.
Further, automated test assembly is elaborated for the conventional
linear tests from both classical test theory and item response
theory perspectives. Item pool design and assembly for the
linear-on-the-fly tests elaborates more complications in practice
when test security is a big concern. Finally, several chapters
focus on computerized adaptive testing (CAT) at either item or
module levels. CAT is further illustrated as an effective approach
to increasing test-takers' engagement in testing. In summary, the
book includes both theoretical, methodological, and applied
research and practices that serve as the foundation for future
development. These chapters provide illustrations of efforts to
automate the process of test development. While some of these
automation processes have become common practices such as automated
test assembly, automated scoring, and computerized adaptive
testing, some others such as automated item generation calls for
more research and exploration. When new AI methods are emerging and
evolving, it is expected that researchers can expand and improve
the methods for automating different steps in test development to
enhance the automation features and practitioners can adopt quality
automation procedures to improve assessment practices.
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