Matches in SemOpenAlex for { <https://semopenalex.org/work/W2760241489> ?p ?o ?g. }
Showing items 1 to 90 of
90
with 100 items per page.
- W2760241489 endingPage "120" @default.
- W2760241489 startingPage "109" @default.
- W2760241489 abstract "Training time is a costly, scarce resource across domains such as commercial aviation, healthcare, and military operations. In the context of military applications, serious gaming—the training of warfighters through immersive, real-time environments rather than traditional classroom lectures—offers benefits to improve training not only in its hands-on development and application of knowledge, but also in data analytics via machine learning. In this paper, we explore an array of machine learning techniques that allow teachers to visualize the degree to which training objectives are reflected in actual play. First, we investigate the concept of discovery: learning how warfighters utilize their training tools and develop military strategies within their training environment. Second, we develop machine learning techniques that could assist teachers by automatically predicting player performance, identifying player disengagement, and recommending personalized lesson plans. These methods could potentially provide teachers with insight to assist them in developing better lesson plans and tailored instruction for each individual student." @default.
- W2760241489 created "2017-10-06" @default.
- W2760241489 creator A5008211323 @default.
- W2760241489 creator A5042522450 @default.
- W2760241489 creator A5087532997 @default.
- W2760241489 date "2019-06-01" @default.
- W2760241489 modified "2023-09-29" @default.
- W2760241489 title "Machine Learning Techniques for Analyzing Training Behavior in Serious Gaming" @default.
- W2760241489 cites W1490094820 @default.
- W2760241489 cites W1583700199 @default.
- W2760241489 cites W1601596542 @default.
- W2760241489 cites W1952084123 @default.
- W2760241489 cites W1964716415 @default.
- W2760241489 cites W1985690171 @default.
- W2760241489 cites W1987971958 @default.
- W2760241489 cites W1989249972 @default.
- W2760241489 cites W1995331732 @default.
- W2760241489 cites W2005201111 @default.
- W2760241489 cites W2006444123 @default.
- W2760241489 cites W2006507204 @default.
- W2760241489 cites W2007321142 @default.
- W2760241489 cites W2013363278 @default.
- W2760241489 cites W2014915963 @default.
- W2760241489 cites W2022573990 @default.
- W2760241489 cites W2034731598 @default.
- W2760241489 cites W2051812123 @default.
- W2760241489 cites W2063043509 @default.
- W2760241489 cites W2065135792 @default.
- W2760241489 cites W2079022890 @default.
- W2760241489 cites W2096981866 @default.
- W2760241489 cites W2099465598 @default.
- W2760241489 cites W2114655791 @default.
- W2760241489 cites W2126443315 @default.
- W2760241489 cites W2134300284 @default.
- W2760241489 cites W2135046866 @default.
- W2760241489 cites W2141104189 @default.
- W2760241489 cites W2143672067 @default.
- W2760241489 cites W2148633389 @default.
- W2760241489 cites W2154053567 @default.
- W2760241489 cites W2163671549 @default.
- W2760241489 cites W30644918 @default.
- W2760241489 doi "https://doi.org/10.1109/tciaig.2017.2754375" @default.
- W2760241489 hasPublicationYear "2019" @default.
- W2760241489 type Work @default.
- W2760241489 sameAs 2760241489 @default.
- W2760241489 citedByCount "7" @default.
- W2760241489 countsByYear W27602414892019 @default.
- W2760241489 countsByYear W27602414892020 @default.
- W2760241489 countsByYear W27602414892021 @default.
- W2760241489 countsByYear W27602414892023 @default.
- W2760241489 crossrefType "journal-article" @default.
- W2760241489 hasAuthorship W2760241489A5008211323 @default.
- W2760241489 hasAuthorship W2760241489A5042522450 @default.
- W2760241489 hasAuthorship W2760241489A5087532997 @default.
- W2760241489 hasConcept C119857082 @default.
- W2760241489 hasConcept C153294291 @default.
- W2760241489 hasConcept C154945302 @default.
- W2760241489 hasConcept C15744967 @default.
- W2760241489 hasConcept C205649164 @default.
- W2760241489 hasConcept C2777211547 @default.
- W2760241489 hasConcept C41008148 @default.
- W2760241489 hasConceptScore W2760241489C119857082 @default.
- W2760241489 hasConceptScore W2760241489C153294291 @default.
- W2760241489 hasConceptScore W2760241489C154945302 @default.
- W2760241489 hasConceptScore W2760241489C15744967 @default.
- W2760241489 hasConceptScore W2760241489C205649164 @default.
- W2760241489 hasConceptScore W2760241489C2777211547 @default.
- W2760241489 hasConceptScore W2760241489C41008148 @default.
- W2760241489 hasFunder F4320337345 @default.
- W2760241489 hasIssue "2" @default.
- W2760241489 hasLocation W27602414891 @default.
- W2760241489 hasOpenAccess W2760241489 @default.
- W2760241489 hasPrimaryLocation W27602414891 @default.
- W2760241489 hasRelatedWork W2748952813 @default.
- W2760241489 hasRelatedWork W2899084033 @default.
- W2760241489 hasRelatedWork W2961085424 @default.
- W2760241489 hasRelatedWork W3046775127 @default.
- W2760241489 hasRelatedWork W3107474891 @default.
- W2760241489 hasRelatedWork W4205958290 @default.
- W2760241489 hasRelatedWork W4286629047 @default.
- W2760241489 hasRelatedWork W4306321456 @default.
- W2760241489 hasRelatedWork W4306674287 @default.
- W2760241489 hasRelatedWork W4224009465 @default.
- W2760241489 hasVolume "11" @default.
- W2760241489 isParatext "false" @default.
- W2760241489 isRetracted "false" @default.
- W2760241489 magId "2760241489" @default.
- W2760241489 workType "article" @default.