Below is a selection of dissertations from the Master of Science in Computational and Data Sciences program in Schmid College that have been included in Chapman University Digital Commons. Additional dissertations from years prior to 2019 are available through the Leatherby Libraries' print collection or in Proquest's Dissertations and Theses database.

If you are a previous student and would like to include your thesis in Chapman University Digital Commons, please contact Kristin Laughtin-Dunker at laughtin@chapman.edu.

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Theses from 2019

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Classifying Challenging Behaviors in Autism Spectrum Disorder with Neural Document Embeddings, Abigail Atchison

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A Machine Learning Approach to Predicting Alcohol Consumption in Adolescents From Historical Text Messaging Data, Adrienne Bergh

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Exploring the Impact of Challenging Behaviors on Treatment Efficacy in Autism Spectrum Disorder, Juliana Hoag

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Exploring Age-Related Metamemory Differences Using Modified Brier Scores and Hierarchical Clustering, Chelsea Parlett

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De novo Sequencing and Analysis of Salvia hispanica Transcriptome and Identification of Genes Involved in the Biosynthesis of Secondary Metabolites, James Wimberley

Theses from 2016

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Assisting Children Action Association Through Visual Queues and Wearable Technology, Anthony Young

Theses from 2015

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An Application of the Autism Management Platform to Tracking Student Progress in the Special Education Environment, Ryan Thomas Burns