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Personalizing training to acquire and sustain competence through use of a cognitive model

Publication ,  Conference
Jastrzembski, TS; Walsh, M; Krusmark, M; Kardong-Edgren, S; Oermann, M; Dufour, K; Millwater, T; Gluck, KA; Gunzelmann, G; Harris, J; Stefanidis, D
Published in: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
January 1, 2017

One-size-fits-all fixed calendar date approaches to training have proven to be inadequate across an array of domains and contexts, and in the medical field specifically, many studies document that skills deteriorate as early as two months after training (e.g., Madden 2006; Woollard et al. 2006). Given the individual differences learners inherently possess, we posit that it would be much more prudent to personalize training around individual learner needs, so that competency could be both attained and sustained in a tailored and streamlined fashion. We hypothesize that through the application of an innovative new cognitive technology, known as the Predictive Performance Optimizer (PPO), individual trainees may reduce unnecessary time in training while increasing performance effectiveness compared to learners given similar training opportunities at fixed times. PPO functions by capitalizing on the fidelity of objective performance data captured through simulation to prescribe training events/refreshers that help individuals both acquire and sustain competency in specific skills, including CPR, trauma assessment, laparoscopic surgery, and intracranial pressure monitoring. We have amassed increased levels of evidence revealing the ability of PPO to personalize training and prescribe tailored, customized regimens designed to help trainees both acquire and sustain competencies both efficiently and effectively.

Duke Scholars

Published In

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

DOI

EISSN

1611-3349

ISSN

0302-9743

Publication Date

January 1, 2017

Volume

10285 11th International Conference, AC 2017, Held as Part of HCI International 2017, Vancouver, BC, Canada, July 9-14, 2017, Proceedings, Part II

Start / End Page

148 / 161

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 46 Information and computing sciences
 

Citation

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Jastrzembski, T. S., Walsh, M., Krusmark, M., Kardong-Edgren, S., Oermann, M., Dufour, K., … Stefanidis, D. (2017). Personalizing training to acquire and sustain competence through use of a cognitive model. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10285 11th International Conference, AC 2017, Held as Part of HCI International 2017, Vancouver, BC, Canada, July 9-14, 2017, Proceedings, Part II, pp. 148–161). https://doi.org/10.1007/978-3-319-58625-0_10
Jastrzembski, T. S., M. Walsh, M. Krusmark, S. Kardong-Edgren, M. Oermann, K. Dufour, T. Millwater, et al. “Personalizing training to acquire and sustain competence through use of a cognitive model.” In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10285 11th International Conference, AC 2017, Held as Part of HCI International 2017, Vancouver, BC, Canada, July 9-14, 2017, Proceedings, Part II:148–61, 2017. https://doi.org/10.1007/978-3-319-58625-0_10.
Jastrzembski TS, Walsh M, Krusmark M, Kardong-Edgren S, Oermann M, Dufour K, et al. Personalizing training to acquire and sustain competence through use of a cognitive model. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2017. p. 148–61.
Jastrzembski, T. S., et al. “Personalizing training to acquire and sustain competence through use of a cognitive model.” Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10285 11th International Conference, AC 2017, Held as Part of HCI International 2017, Vancouver, BC, Canada, July 9-14, 2017, Proceedings, Part II, 2017, pp. 148–61. Scopus, doi:10.1007/978-3-319-58625-0_10.
Jastrzembski TS, Walsh M, Krusmark M, Kardong-Edgren S, Oermann M, Dufour K, Millwater T, Gluck KA, Gunzelmann G, Harris J, Stefanidis D. Personalizing training to acquire and sustain competence through use of a cognitive model. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2017. p. 148–161.

Published In

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

DOI

EISSN

1611-3349

ISSN

0302-9743

Publication Date

January 1, 2017

Volume

10285 11th International Conference, AC 2017, Held as Part of HCI International 2017, Vancouver, BC, Canada, July 9-14, 2017, Proceedings, Part II

Start / End Page

148 / 161

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 46 Information and computing sciences