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Enhancing Personalization by Integrating Top-Down and Bottom-Up Approaches to Learner Modeling

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Adaptive Instructional Systems. Adaptation Strategies and Methods (HCII 2021)

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Abstract

Learner models are representations of the learner’s knowledge, skills and other attributes used by Adaptive Instructional Systems (AISs) to personalize their interactions with the learners (e.g., by implementing adaptive feedback, and recommending tasks/activities). Top-down and bottom-up approaches to learner modeling provide various affordances and challenges in terms of the need for interpretable learner models, the amount of data available, the complexity of the model, and the amount of human effort needed to implement and validate learner models. Research shows that hybrid approaches involving both top-down and bottom-up approaches are needed to effectively deal with the challenges of learner modeling in AISs. This paper describes several learner modeling approaches for integrating top-down and bottom-up approaches to gather additional evidence for supporting assessment claims and implementing personalization approaches. We elaborate on several learner modeling issues, including (a) evidence identification and aggregation in assessment systems; (b) making sense of process data aimed at supporting assessment claims related to learner cognition; and (c) approaches for improving interpretability and explainability of student models with some implications for validity and fairness of AISs.

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  1. Educational Testing Service, Princeton, NJ, 08541, USA

    Diego Zapata-Rivera & Burcu Arslan

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  1. Diego Zapata-Rivera
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    Robert A. Sottilare

  2. Fraunhofer FKIE, Wachtberg, Germany

    Jessica Schwarz

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Zapata-Rivera, D., Arslan, B. (2021). Enhancing Personalization by Integrating Top-Down and Bottom-Up Approaches to Learner Modeling. In: Sottilare, R.A., Schwarz, J. (eds) Adaptive Instructional Systems. Adaptation Strategies and Methods. HCII 2021. Lecture Notes in Computer Science(), vol 12793. Springer, Cham. https://doi.org/10.1007/978-3-030-77873-6_17

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