Abstract
Adaptive instructional systems support learner and teacher to deter-mine which learning material would be best at a specific time to reach the learner’s goals. The learner’s current state, personality traits, and learning history are important data for a system and a teacher to support the learning process. For a beneficial use of an adaptive instructional system, the effectiveness, efficiency, and the satisfaction of the user must be tracked and evaluated to optimize the learning outcome. The human factors analysis platform AMbER uses objective and subjective measures to evaluate the user state, the efficiency, and effectiveness of the learning process. The modular architecture of the assessment platform AMbER leads to highly flexible dashboards, that can be adapted to the specific requirements of the use case. Assessing adaptive instructional systems is one of many possible scenarios to make use of AMbER. An adaptive instructional system scenario is used as an example, to showcase the benefits of the assessment platform.
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Witte, T.E.F., Gfesser, T., Schwarz, J. (2023). AMbER - Adaptive Instructional Systems as a Use Case for the Holistic Assessment Platform. In: Zaphiris, P., et al. HCI International 2023 – Late Breaking Papers. HCII 2023. Lecture Notes in Computer Science, vol 14060. Springer, Cham. https://doi.org/10.1007/978-3-031-48060-7_26
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