Personalising knowledge assessments to remove compensation and thereby improve preparation for safe practice – developing content adaptive progress testing

An increasing number of data across many higher education programmes indicate that the traditional
construction of knowledge assessments allows students to pass all exams even if they lack knowledge in
certain areas of the curriculum. This may be particularly problematic for healthcare programmes such as
medicine, where students can graduate without achieving sufficient competency in certain subjects.
Summative and formative knowledge assessments may indicate areas of weakness, but there is no
guarantee that students will address them. Therefore, compensation of content both within and across
assessments can potentially lead to graduating students with insufficient knowledge. To address this
issue and remove any compensation it is now possible to use personalised knowledge assessments in
the form of adaptive progress testing to improve graduate students’ knowledge and increase their safety
to practice. Computerized adaptive assessments utilise algorithms to select items depending on the
candidate’s previous answers. Such assessments can select questions according to their difficulty or
content of the blueprint. Adaptive testing by difficulty aims to give a more reliable measure of each
individual student’s performance, while adaptive testing by content aims to ensure successful
performance in all required content by all students. Here we present an overview of computerised
adaptive progress testing and discuss the rationale and practicality of this approach to assessment.

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