The goal of this study was to look at touch and dance from different views to gain a better perspective on the benefits of touch, mainly when used in dance and also perhaps in broader contexts. Part of this investigation also looked at the stigmatized view of touch in the American culture and in turn the lack of knowledge about, and comfort with touch in our society. A personal research component involved the creation of a solo reflecting about the question of why I connect with touch so intensely. The bulk of the study involved facilitating touch experiences in two introductory level dance classes for high school students. Daily journal entries were collected from each of the eighty students that focused on their personal experiences with touch in a series of six movement sessions. The study shows that bringing touch to the dance classroom has multiple benefits, including promoting a greater understanding and acceptance of the sense of touch, a positive impact on students' views about dance, and a break down of preconceived notions about the mind and the body.

A dynamical approach is used to avoid isolating systems and instead view systems as interacting together. The current study applied a dynamical approach to heart rate variability and personality. There were two main research questions that this study sought to answer with a dynamical analysis of heart rate variability and personality: “Can we listen to a heartbeat and draw connections to behavior and personality?” and “Is dynamical analysis more effective than traditional analysis at finding correlations between heart rate variability and personality?” To answer these questions a dynamical analysis of heart rate variability was conducted (detrended fluctuation analysis; DFA) along with traditional analysis (standard deviations of NN intervals, SDNN, and root mean squared of successive deviations, RMSSD) and then correlations between heart rate variability measures and personality traits from the Big Five Inventory, Positive and Negative Affect schedule, and State-Trait Anxiety Inventory were examined. Data for this study came from the Rapid Automatic & Adaptive Model for Performance Prediction (RAAMP2) Dataset that was part of The Multimodal Objective Sensing to Assess Individuals with Context (MOSAIC) project. There were no statistically significant correlations between heart rate variability and personality. However, there were notable correlations between extraversion and SDNN and RMSSD and between positive affect and SDNN and RMSSD. We found that SDNN and RMSSD were more closely correlated to each other compared to DFA to either measure. This suggests that DFA can provide information that SDNN and RMSSD do not. Future research can explore dynamic analysis of heart rate variability and other nested systems.