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Personalized assessments are of increasing interest because of their potential to lead to more equitable decisions about the examinees. However, one obstacle to the widespread use of personalized assessments is the lack of a measurement toolkit that can be used to analyze data from these assessments. This article takes one step toward building such a toolkit by proposing a validation framework for personalized assessments. The framework is built on the threats‐to‐validity approach. We demonstrate applications of the suggested framework using the AP 3D Art and Design Portfolio examination and a more restrictive culturally relevant assessment as examples. 

Caring assessments is an assessment design framework that considers the learner as a whole and can be used to design assessment opportunities that learners find engaging and appropriate for demonstrating what they know and can do. This framework considers learners’ cognitive, meta-cognitive, intra-and inter-personal skills, aspects of the learning context, and cultural and linguistic backgrounds as ways to adapt assessments. Extending previous work on intelligent tutoring systems that “care” from the field of artificial intelligence in education (AIEd), this framework can inform research and development of personalized and socioculturally responsive assessments that support students’ needs. In this article, we (a) describe the caring assessment framework and its unique contributions to the field, (b) summarize current and emerging research on caring assessments related to students’ emotions, individual differences, and cultural contexts, and (c) discuss challenges and opportunities for future research on caring assessments in the service of developing and implementing personalized and socioculturally responsive interactive digital assessments.