This project investigates the gleam-glum effect, a well-replicated phonetic emotion association in which words with the [i] vowel-sound (as in “gleam”) are judged more emotionally positive than words with the [Ʌ] vowel-sound (as in “glum”). The effect is observed across different modalities and languages and is moderated by mouth movements relevant to word production. This research presents and tests an articulatory explanation for this association in three experiments. Experiment 1 supported the articulatory explanation by comparing recordings of 71 participants completing an emotional recall task and a word read-aloud task, showing that oral movements were more similar between positive emotional expressions and [i] articulation, and negative emotional expressions and [Ʌ] articulation. Experiment 2 partially supported the explanation with 98 YouTube recordings of natural speech. In Experiment 3, 149 participants judged emotions expressed by a speaker during [i] and [Ʌ] articulation. Contradicting the robust phonetic emotion association, participants judged more frequently that the speaker’s [Ʌ] articulatory movements were positive emotional expressions and [i] articulatory movements were negative emotional expressions. This is likely due to other visual emotional cues not related to oral movements and the order of word lists read by the speaker. Findings from the current project overall support an articulatory explanation for the gleam-glum effect, which has major implications for language and communication.

A great deal of contemporary research argues that humans learn from experience. This research, however, rarely explicates what constitutes an experience for humans, let alone experiences that lead to deep learning for human flourishing. Experience is constituted of inner and out sensations processed in certain ways. Thus, a biologically realistic theory of learning must be based on a theory of sensation and how sense making derives from sensation. This dissertation seeks such a theory in the emerging literature on what kinds of creatures humans are and what this implies about how they learn and flourish. This literature ranges across several different disciplines, including neuroscience, evolutionary biology, and work on how affect guides cognition and action. Humans are as able to learn from experiences they have had in media as they are from experiences they have had in the real world. In either case, however, humans do not learn deeply from random experiences. They learn best from experiences that have been designed to recruit affect, help them manage their attention, and give them ways to assess the success of actions they take toward goals. Thus, teaching in the sense of experience design—a task for teachers in schools, as well as media designers and artists of all different sorts—is fundamental to human learning and flourishing. The dissertation defines flourishing in terms of the state of a human being’s allostatic load, a variable which can be measured. Since I am interested how experience designers design sensation to create sense making and sense making that can enhance human flourishing, I am interest in experience design in the arts, a domain that has traditionally been seen as an important source of insight built on sensation. I use examples from traditional and contemporary art in the dissertation. The last chapter is an extended study of the anime Attack on Titan I show how the design of Attack on Titan uses sensation to engender deep contemplation and discussion of complex political, historical, and philosophical issues. The way it achieves this goal has important implications for teaching and learning in and out of school.

In order to perceive the heaviness of an object, one must wield it. This requires muscle activity and its resulting movements. Research has shown that muscle activity and movement combine for this perception in a manner inspired by Newton’s 2nd Law of Motion. Research in this area has relied on specific movement and muscle activity measures that often capture one moment of a lift. The current set of experiments set out to determine which measures best capture the underlying phenomena that lead to heaviness perception during a lift. In the first experiment, participants lifted stimuli with an elbow flexion lift while their muscle activity and movement were recorded. Participants reported their perceived heaviness of the stimuli as soon as they reached it, which resulted in an average decision angle of around 30-degrees. In the second and third experiments, participants the same stimuli with the same elbow flexion lift in four perturbation conditions – they experienced perturbations at 15-degrees of the lift, 30-degrees, 45-degrees, and with no perturbation. In the second experiment, participants experienced a physical perturbation and a cognitive perturbation in the third experiment. Across Experiments 2 and 3, the pattern of results suggested that the more time participants have in a lift, the more proportion correct, muscle activity, and movement measures appears like they do in the no perturbation condition. Additionally, a logistic least absolute shrinkage and selection operator (LASSO) regression was used to determine which measures best predicted perception. Results show that the integrated electromyogram of the biceps brachii that occurs after peak acceleration (iEMG BB after pACC) and Average Acceleration, which are both measures that capture more than one point of a lift, predicted heaviness perception. A new model of heaviness perception was then developed, using these new measures. Comparing this New Model to an Original Model from Waddell et al., 2016 resulted in better prediction from the New Model – suggesting that measure that capture more of a lift better predict heaviness perception, meaning that an entire ongoing action event is important for perception.