@proceedings {2022,
	title = {Engaging deeply with cognitive science in a conservatory of music: Using student-centered learning to enhance learning outcomes in music students},
	year = {2022},
	month = {07/2022},
	pages = {1-15},
	abstract = {Concepts from cognitive science (CS), including music psychology and performance science, are rarely taught to conservatory students, even though these topics are likely useful for their practice and performance of music. This study examines the effectiveness of student-centered learning (SCL) and project-based learning (PBL) methods for teaching CS to undergraduate conservatory students in a module on The Psychology of Music Performance. The results gleaned from student assignments and feedback show that the module activities, especially the SCL and PBL components, were largely successful in deeply engaging the students, resulting in knowledge acquisition as well as critical thinking. The findings suggest that a well-balanced teaching approach incorporating elements of SCL and PBL is capable of instilling both breadth and depth of learning of relevant CS findings in the music conservatory context.},
	keywords = {cognitive science, ISME conference, music education},
	author = {Kat R Agres and Natasha Ureyang}
}
@proceedings {2016,
	title = {The Effect of Repetitive Structure on Enjoyment in Uplifting Trance Music},
	year = {2016},
	month = {07/2016},
	pages = {280-282},
	address = {San Francisco},
	isbn = {1-876346-65-5},
	author = {K. Agres and L. Bigo and D. Herremans and D. Conklin}
}
@article {9999,
	title = {Entraining IDyOT: timing in the information dynamics of thinking},
	journal = {Frontiers in Psychology: Auditory Cognitive Neuroscience},
	volume = {7:1575},
	year = {2016},
	abstract = {We present a novel hypothetical account of entrainment in music and language, in context of the Information Dynamics of Thinking model, IDyOT. The extended model affords an alternative view of entrainment, and its companion term, pulse, from earlier accounts. The model is based on hierarchical, statistical prediction, modeling expectations of both what an event will be and when it will happen. As such, it constitutes a kind of predictive coding, with a particular novel hypothetical implementation. Here, we focus on the model{\textquoteright}s mechanism for predicting when a perceptual event will happen, given an existing sequence of past events, which may be musical or linguistic. We propose a range of tests to validate or falsify the model, at various different levels of abstraction, and argue that computational modeling in general, and this model in particular, can offer a means of providing limited but useful evidence for evolutionary hypotheses.},
	keywords = {anticipatory cognition, cognitive architecture, evolutionary psychology, language, music perception, timing},
	author = {Jamie Forth and Kat Agres and Matt Purver and Geraint Wiggins}
}
@article {2017,
	title = {Evaluation of Musical Creativity and Musical Metacreation Systems},
	journal = {ACM Comput. Entertain.},
	volume = {14},
	year = {2016},
	month = {12/2016},
	pages = {3:1{\textendash}3:33},
	abstract = {The field of computational creativity, including musical metacreation, strives to develop artificial systems that are capable of demonstrating creative behavior or producing creative artefacts. But the claim of creativity is often assessed, subjectively only on the part of the researcher and not objectively at all. This article provides theoretical motivation for more systematic evaluation of musical metacreation and computationally creative systems and presents an overview of current methods used to assess human and machine creativity that may be adapted for this purpose. In order to highlight the need for a varied set of evaluation tools, a distinction is drawn among three types of creative systems: those that are purely generative, those that contain internal or external feedback, and those that are capable of reflection and self-reflection. To address the evaluation of each of these aspects, concrete examples of methods and techniques are suggested to help researchers (1) evaluate their systems{\textquoteright} creative process and generated artefacts, and test their impact on the perceptual, cognitive, and affective states of the audience, and (2) build mechanisms for reflection into the creative system, including models of human perception and cognition, to endow creative systems with internal evaluative mechanisms to drive self-reflective processes. The first type of evaluation can be considered external to the creative system and may be employed by the researcher to both better understand the efficacy of their system and its impact and to incorporate feedback into the system. Here we take the stance that understanding human creativity can lend insight to computational approaches, and knowledge of how humans perceive creative systems and their output can be incorporated into artificial agents as feedback to provide a sense of how a creation will impact the audience. The second type centers around internal evaluation, in which the system is able to reason about its own behavior and generated output. We argue that creative behavior cannot occur without feedback and reflection by the creative/metacreative system itself. More rigorous empirical testing will allow computational and metacreative systems to become more creative by definition and can be used to demonstrate the impact and novelty of particular approaches.},
	keywords = {artificial intelligence, Music perception and cognition},
	issn = {1544-3574},
	doi = {10.1145/2967506},
	url = {http://doi.acm.org/10.1145/2967506},
	author = {Agres, Kat and Forth, Jamie and Wiggins, Geraint A.}
}
