Dissecting assessment: A paradigm shift towards technology-enhanced assessments - Said, Mohamed Mohamed Tolba; Aravind, Vasudeva Rao; Ferdinand-James, Debra; Umachandran, Krishnan (2019)
This study proposes a framework for making a paradigm shift from traditional (teacher-centred) to technology-enhanced (student-centred) assessment, using an example of an intelligent tutor. Informed by Situated Learning Theory that addresses students’ needs and concerns in timely learning experiences, the proposed ‘dissecting assessment’ framework has two primary variables: Students’ Expectations and Assessment Deliverable with positive and negative secondary variables such as inbuilt fear to handle failures and exposures and comparison phobia. Employing a case study approach, a purposeful sample of 14 U.S. College students were supported by an intelligent tutoring system in monitoring their learning with prompt corrective feedback in their physics course. This formative assessment prepares students for succeeding on their summative assessments, which is the final outcome of learning with feedback. The analysis of the proposed dissecting assessment framework led to the conclusion that concentrating efforts on the positives in the framework, such as unbiased evaluation, would eventually reduce the negatives, such as comparison phobia.