Mapping utopian art: alternative political imaginaries in new media art (2008-2015)

This thesis investigates the proliferation of alternative political imaginaries in the Web-based art produced during the global financial crisis of 2008 and its aftermath (2008- 2015), with a particular focus on the influence of communist utopianism. The thesis begins by exploring the continuous relevance of utopianism to Western political thought, including the historical context within which the financial crisis of 2008 occurred. This context has been defined by the new political, social and cultural milieu produced by the development of Data Capitalism – the dominant economic paradigm of the last two decades. In parallel, the thesis identifies the “organic” connections between leftist utopian thought and networked technologies, in order to claim that the events of 2008 functioned as a catalyst for their reactivation and expansion. Following this analysis, the thesis focuses on how politically engaged artists have reacted to the global financial crisis through the use of the World Wide Web. More specifically, the thesis categorises a wide range of artworks, institutional and non-institutional initiatives, as well as theoretical texts that have either been written by artists, or have inspired them. The result of this exercise is a mapping of the post-crisis Web-based art, which is grounded on the technocultural tools employed by artists as well as on the main concepts and ideals that they have aimed at materialising through the use of such tools. Furthermore, the thesis examines the interests of Data Capitalists in art and the Internet, and the kinds of restrictions and obstacles that they have imposed on the political use of the Web in order to safeguard them. Finally, the thesis produces an overall evaluation of the previously analysed cultural products by taking into account both the objectives of their creators and the external and internal limitations that ultimately shape their character. Accordingly, the thesis locates the examined works within the ideological spectrum of Marxist and post-Marxist thought in order to formulate a series of proposals about the future of politically engaged Web-based art and the ideological potentialities of networked communication at large

An aesthetics of touch: investigating the language of design relating to form

How well can designers communicate qualities of touch? This paper presents evidence that they have some capability to do so, much of which appears to have been learned, but at present make limited use of such language. Interviews with graduate designer-makers suggest that they are aware of and value the importance of touch and materiality in their work, but lack a vocabulary to fully relate to their detailed explanations of other aspects such as their intent or selection of materials. We believe that more attention should be paid to the verbal dialogue that happens in the design process, particularly as other researchers show that even making-based learning also has a strong verbal element to it. However, verbal language alone does not appear to be adequate for a comprehensive language of touch. Graduate designers-makers’ descriptive practices combined non-verbal manipulation within verbal accounts. We thus argue that haptic vocabularies do not simply describe material qualities, but rather are situated competences that physically demonstrate the presence of haptic qualities. Such competencies are more important than groups of verbal vocabularies in isolation. Design support for developing and extending haptic competences must take this wide range of considerations into account to comprehensively improve designers’ capabilities

Non-Knowledge and Digital Cultures

Making available massive amounts of data that are generated, distributed, and modeled, digital media provide us with the possibility of abundant information and knowledge. This possibility has been attracting various scenarios in which technology either eliminates non-knowledge or plants it deep within contemporary cultures through the universal power and opacity of algorithms. This volume comprises contributions from media studies, literary studies, sociology, ethnography, anthropology, and philosophy to discuss non-knowledge as an important concept for understanding contemporary digital cultures

Non-Knowledge and Digital Cultures

Making available massive amounts of data that are generated, distributed, and modeled, digital media provide us with the possibility of abundant information and knowledge. This possibility has been attracting various scenarios in which technology either eliminates non-knowledge or plants it deep within contemporary cultures through the universal power and opacity of algorithms. This volume comprises contributions from media studies, literary studies, sociology, ethnography, anthropology, and philosophy to discuss non-knowledge as an important concept for understanding contemporary digital cultures

Non-Knowledge and Digital Cultures

Making available massive amounts of data that are generated, distributed, and modeled, digital media provide us with the possibility of abundant information and knowledge. This possibility has been attracting various scenarios in which technology either eliminates non-knowledge or plants it deep within contemporary cultures through the universal power and opacity of algorithms. This volume comprises contributions from media studies, literary studies, sociology, ethnography, anthropology, and philosophy to discuss non-knowledge as an important concept for understanding contemporary digital cultures

Abstracts: HASTAC 2017: The Possible Worlds of Digital Humanities

The document contains abstracts for HASTAC 2017

A Model for Mapping Interactivity in Learning Experiences

This research is situated at the intersection of technology, education, and design. A design methodology was applied to examine the issues relating to interactivity within these disciplines. The result of this research is a working definition of interactivity aesthetics that can be used across multiple disciplines, and a model of interactivity as a practical means of evaluating the interactivity in any given learning experience

Exploring the use of Artificial Intelligent Systems in STEM Classrooms

Human beings by nature have a predisposition towards learning and the exploration of the natural world. We are intrinsically intellectual and social beings knitted with adaptive cognitive architectures. As Foot (2014) succinctly sums it up: “humans act collectively, learn by doing, and communicate in and via their actions” and they “… make, employ, and adapt tools of all kinds to learn and communicate” and “community is central to the process of making and interpreting meaning—and thus to all forms of learning, communicating, and acting” (p.3). Education remains pivotal in the transmission of social values including language, knowledge, science, technology, and an avalanche of others. Indeed, Science, Technology, Engineering, and Mathematics (STEM) have been significant to the advancement of social cultures transcending every epoch to contemporary times. As Jasanoff (2004) poignantly observed, “the ways in which we know and represent the world (both nature and society) are inseparable from the ways in which we choose to live in it. […] Scientific knowledge [..] both embeds and is embedded in social practices, identities, norms, conventions, discourses, instruments, and institutions” (p.2-3). In essence, science remains both a tacit and an explicit cultural activity through which human beings explore their own world, discover nature, create knowledge and technology towards their progress and existence. This has been possible through the interaction and applications of artifacts, tools, and technologies within the purviews of their environments. The applications of technologies are found across almost every luster of organizational learning especially teacher education, STEM, architecture, manufacturing, and a flurry of others. Thus, human evolution and development are inexplicably linked with education either formally or informally. The 21st century has however seen a surge in the use of artificial intelligence (AI) and digital technologies in education. The proliferation of artificial intelligence and associated technologies are creating new overtures of digital multiculturalism with distinct worldviews of significance to education. For example, learners are demonstrating digital literacy skills and are knowledgeable about AI technologies across every specter of their lives (Bennett et al., 2008). It is also opening new artesian well-springs of educational opportunities and pedagogical applications. This includes mapping new methodological pathways, content creation and curriculum design, career preparations and indeed a seemingly new paradigm shift in teaching STEM. There is growing scholarly evidence about the use and diffusion of these technologies in K-12 and higher education (Bonk & Graham, 2012; Hew & Brush, 2007; Langer, 2018; Mishra & Koehler, 2006). Some of these include the Sphero robots, Micro Bit, Jill Watson, BrickPi3 Classroom kit, Engino STEM Mechanic, Lego Education WeDo Core Set and Spike. Both educators and learners are using these in STEM programs as well as other education related activities. Just as human activities and interactions with artifacts and tools shaped and redefined the scientific-technological feat of previous generations, so the contemporary digital technological era seems to be on a similar trajectory. However, there is sparsity of empirical scholarship on the pedagogical prospects and effectiveness of artificial intelligence in STEM classrooms. Also, it should be noted that scholarship on how AI impacts pedagogical content knowledge of STEM educators and how learners perceive these technologies are just emerging. In addition, the recent COVID-19 pandemic (Ghandhi et al., 2020; Rasmussen et al., 2020) has unexpectedly created a renewed synergy towards the applications of digital technologies in teaching STEM. In the context of this force majeure (COVID-19), the traditional brick and mortar educational spaces metamorphosed into digital spaces with the applications of many artificial intelligent technologies and resources in the arena of education. This doctoral dissertation study examined these enigmas including how educators use these technologies in STEM classrooms. The study is informed by activity theory or cultural-historical activity theory (Engeström et al., 2007; Hasan et al., 2014; Krinski & Barker, 2009; Oers, 2010; Vygotsky,1987). The study participants will be selected from educators currently integrating artificial intelligent systems and digital technologies in their respective STEM classrooms. Pre-data survey inquiry has shown that many educators were incorporating some forms of AIS into their STEM classrooms. In view of these, I have explored Sphero educational robots to interrogate the research topic. The Sphero Edu described as a “…STEAM-based toolset that weaves hardware, software, and community engagement to promote 21st century skills. While these skills are absolutely crucial, our edu program goes beyond code by nurturing students’ creativity and ingenuity like no other education program can” (Sphero, April 2020). The Sphero robots also have features and applications for designing and teaching STEM topics such as nature, space science, geometry, and other activities of pedagogical significance. Users could also design and write advanced engineering programs in JavaScript during STEM educational activities formally and outside of the classrooms. In essence, educators and students can learn designing, programming, engineering, mathematics, computational thinking, and hands-on skills reflective of the 21st century. In brief, the dissertation study research has explored artificial intelligence and emerging technologies and how these could transform and advance teaching and learning of STEM hence the research topic: Exploring the use of Artificial Intelligent Systems in STEM Classrooms. Methodologically, this is a qualitative study through the theoretical frameworks of activity theory as applicable to STEM education. The main research questions are: 1) Given that artificial intelligent systems and digital technologies have been applied in STEM educational domains (content, pedagogy, student learning, assessment). How does the application of AIS and digital technologies impact pedagogy in STEM educational activities? 2) Given that digital technology is transforming contemporary society in every facet. How/What does AIS tell us about how digital technology impacts STEM pedagogy? Data was collected from the study participants, archival sources, and others for analyses. It is hoped that the findings will inform and address theories of learning and teaching, policy and praxis in science education, teacher preparatory and professional development programs as it relates to STEM classroom

Measuring Expressive Music Performances: a Performance Science Model using Symbolic Approximation

Music Performance Science (MPS), sometimes termed systematic musicology in Northern Europe, is concerned with designing, testing and applying quantitative measurements to music performances. It has applications in art musics, jazz and other genres. It is least concerned with aesthetic judgements or with ontological considerations of artworks that stand alone from their instantiations in performances. Musicians deliver expressive performances by manipulating multiple, simultaneous variables including, but not limited to: tempo, acceleration and deceleration, dynamics, rates of change of dynamic levels, intonation and articulation. There are significant complexities when handling multivariate music datasets of significant scale. A critical issue in analyzing any types of large datasets is the likelihood of detecting meaningless relationships the more dimensions are included. One possible choice is to create algorithms that address both volume and complexity. Another, and the approach chosen here, is to apply techniques that reduce both the dimensionality and numerosity of the music datasets while assuring the statistical significance of results. This dissertation describes a flexible computational model, based on symbolic approximation of timeseries, that can extract time-related characteristics of music performances to generate performance fingerprints (dissimilarities from an ‘average performance’) to be used for comparative purposes. The model is applied to recordings of Arnold Schoenberg’s Phantasy for Violin with Piano Accompaniment, Opus 47 (1949), having initially been validated on Chopin Mazurkas.1 The results are subsequently used to test hypotheses about evolution in performance styles of the Phantasy since its composition. It is hoped that further research will examine other works and types of music in order to improve this model and make it useful to other music researchers. In addition to its benefits for performance analysis, it is suggested that the model has clear applications at least in music fraud detection, Music Information Retrieval (MIR) and in pedagogical applications for music education