=Paper=
{{Paper
|id=Vol-2028/paper32
|storemode=property
|title=None
|pdfUrl=https://ceur-ws.org/Vol-2028/paper32.pdf
|volume=Vol-2028
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==None==
<pdf width="1500px">https://ceur-ws.org/Vol-2028/paper32.pdf</pdf>
<pre>
                                                                                                   289




                                            MonitAR?

                                              Hayley Borck

                                           Adventium Labs,
                         111 Third Ave South Suite 100, Minneapolis, MN 55401



                 Abstract. In this video we present a novel application of Case-based
                 Reasoning (CBR) that combines Intelligent Tutoring Systems (ITS) us-
                 ing Augmented Reality (AR) and prediction. The MonitAR system is an
                 intelligent guidance system for users conducting procedures during peri-
                 ods when a human expert has limited or no availability to assist the user.
                 Our approach takes advantage of the relational nature of time-series data
                 to detect a task that the user is completing and diagnose the issue when
                 the user is about to make a mistake. MonitAR uses AR cues to guide
                 the user away from these potential mistakes. Using proven pedagogical
                 models, MonitAR is able to effectively assist, train, or retrain users in
                 domains ranging from astronauts to mechanics.

                 Keywords: Intelligent Tutoring System, Task Prediction, Augmented
                 Reality




         ?
             This video accompanies the paper: Borck, H., Johnston, S., Southern, M., and Boddy,
             M. (2016). Exploiting Time Series Data for Task Prediction and Diagnosis in an
             Intelligent Guidance System. In Proceedings of the Workshop on Reasoning about
             Time in CBR at the 24th International Conference on Case-based Reasoning.



Copyright © 2017 for this paper by its authors. Copying permitted for private and
academic purpose. In Proceedings of the ICCBR 2017 Workshops. Trondheim, Norway

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