Computational psychometrics can be effectively used in support of collaborative educational assessments in the following ways:
1. Item Analysis: analyze the performance of individual items in a test. This analysis can help identify items that are too easy or too difficult and need to be revised.
2. Adaptive Testing: create adaptive tests that adjust the difficulty level of questions based on the performance of the student. This helps to provide a more accurate assessment of the student's abilities.
3. Data Analysis: analyze large amounts of data collected from multiple sources. This analysis can help identify patterns and trends in student performance, which can be used to improve the assessment process.
4. Feedback: provide feedback to students based on their performance. This feedback can be personalized and can help students identify areas where they need to improve.
5. Collaboration: facilitate collaboration between educators and assessment experts.