Computational assessment of long-term memory structures from SDA-M related to action sequences

Strenge B, Vogel L, Schack T (2019)
PLoS ONE 14(2): e0212414.

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Zeitschriftenaufsatz | Veröffentlicht | Englisch
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Assistance systems should be able to adapt to individual task-related skills and knowledge. Structural-dimensional analysis of mental representations (SDA-M) is an established method for retrieving human memory structures related to specific activities. For this purpose, SDA-M involves a semi-automatized survey of users (the “split procedure”), which yields data about users’ associations between action representations in long-term memory. Up to now this data about associations has commonly been clustered and visualized by SDA-M software in the form of dendrograms that can be used by human experts as a tool to (manually) assess users’ individual expertise and identify potential issues with respect to predefined action sequences. This article presents new algorithmic approaches for automatizing the process of assessing task-related memory structures based on SDA-M data to predict probable errors in action sequences. This automation enables direct integration into technical systems, e.g. user-adaptive assistance systems. An evaluation study has compared the automatized computational assessments to predictions made by human scholars based on visualizations of SDA-M data. The different algorithms’ outputs matched human experts’ manual assessments in 84% to 86% of the test cases.
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PLoS ONE
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14
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2
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e0212414
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Article Processing Charge funded by the Deutsche Forschungsgemeinschaft and the Open Access Publication Fund of Bielefeld University.
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Strenge B, Vogel L, Schack T. Computational assessment of long-term memory structures from SDA-M related to action sequences. PLoS ONE. 2019;14(2):e0212414.
Strenge, B., Vogel, L., & Schack, T. (2019). Computational assessment of long-term memory structures from SDA-M related to action sequences. PLoS ONE, 14(2), e0212414. doi:10.1371/journal.pone.0212414
Strenge, B., Vogel, L., and Schack, T. (2019). Computational assessment of long-term memory structures from SDA-M related to action sequences. PLoS ONE 14, e0212414.
Strenge, B., Vogel, L., & Schack, T., 2019. Computational assessment of long-term memory structures from SDA-M related to action sequences. PLoS ONE, 14(2), p e0212414.
B. Strenge, L. Vogel, and T. Schack, “Computational assessment of long-term memory structures from SDA-M related to action sequences”, PLoS ONE, vol. 14, 2019, pp. e0212414.
Strenge, B., Vogel, L., Schack, T.: Computational assessment of long-term memory structures from SDA-M related to action sequences. PLoS ONE. 14, e0212414 (2019).
Strenge, Benjamin, Vogel, Ludwig, and Schack, Thomas. “Computational assessment of long-term memory structures from SDA-M related to action sequences”. PLoS ONE 14.2 (2019): e0212414.
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2019-02-27T09:51:39Z

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Data for Strenge et al. 2018 PLOS ONE article
Strenge B (2018)
Bielefeld University.

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