35,413 research outputs found

    Assessing a Collaborative Online Environment for Music Composition

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    The current pilot study tested the effectiveness of an e-learning environment built to enable students to compose music collaboratively. The participants interacted online by using synchronous and asynchronous resources to develop a project in which they composed a new music piece in collaboration. After the learning sessions, individual semi-structured interviews with the participants were conducted to analyze the participants\u2019 perspectives regarding the e-learning environment\u2019s functionality, the resources of the e-learning platform, and their overall experience with the e-learning process. Qualitative analyses of forum discussions with respect to metacognitive dimensions, and semi-structured interview transcriptions were performed. The findings showed that the participants successfully completed the composition task in the virtual environment, and that they demonstrated the use of metacognitive processes. Moreover, four themes were apparent in the semi-structured interview transcriptions: Teamwork, the platform, face-to-face/online differences, and strengths/weaknesses. Overall, the participants exhibited an awareness of the potential of the online tools, and the task performed. The results are discussed in consideration of metacognitive processes, and the following aspects that rendered virtual activity effective for learning: The learning environment, the platform, the technological resources, the level of challenge, and the nature of the activity. The possible implications of the findings for research on online collaborative composition are also considered

    AtomsMasher: Personal Reactive Automation for the Web

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    The rise of "Web 2.0" has seen an explosion of web sites for the social sharing of personal information. To enable users to make valuable use of the rich yet fragmented sea of public, social, and personal information, data mashups emerged to provide a means for combining and filtering such information into coherent feeds and visualizations. In this paper we present AtomsMasher (AM), a new framework which extends data mashups into the realm of context-aware reactive behaviors. Reactive scripts in AM can be made to trigger automatically in response to changes in its world model derived from multiple web-based data feeds. By exposing a simple state-model abstraction and query language abstractions of data derived from heterogeneous web feeds through a simulation-based interactive script debugging environment, AM greatly simplifies the process of creating such automation in a way that is flexible, predictable, scalable and within the reach of everyday Web programmers

    Designing and evaluating the usability of a machine learning API for rapid prototyping music technology

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    To better support creative software developers and music technologists' needs, and to empower them as machine learning users and innovators, the usability of and developer experience with machine learning tools must be considered and better understood. We review background research on the design and evaluation of application programming interfaces (APIs), with a focus on the domain of machine learning for music technology software development. We present the design rationale for the RAPID-MIX API, an easy-to-use API for rapid prototyping with interactive machine learning, and a usability evaluation study with software developers of music technology. A cognitive dimensions questionnaire was designed and delivered to a group of 12 participants who used the RAPID-MIX API in their software projects, including people who developed systems for personal use and professionals developing software products for music and creative technology companies. The results from the questionnaire indicate that participants found the RAPID-MIX API a machine learning API which is easy to learn and use, fun, and good for rapid prototyping with interactive machine learning. Based on these findings, we present an analysis and characterization of the RAPID-MIX API based on the cognitive dimensions framework, and discuss its design trade-offs and usability issues. We use these insights and our design experience to provide design recommendations for ML APIs for rapid prototyping of music technology. We conclude with a summary of the main insights, a discussion of the merits and challenges of the application of the CDs framework to the evaluation of machine learning APIs, and directions to future work which our research deems valuable

    Creativity, Free Expression, and Professionalism: Value Conflicts in U.S. Community Radio

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    This study investigates how the values of free expression and professionalism provide the basis for interpersonal and organizational conflict in U.S. community radio stations, and shape divergent approaches to audience service. Using qualitative methods, the project examines the motivations, expressions, and behaviors of producers and managers to establish how their values contribute to cooperation and dissention within these organizations. The study illustrates the delicate balance that exists between content-centered and audience-centered objectives, concluding that these core values have a pervasive effect on community radio’s capacity to reach audiences and promote social change through the media

    Mixing the reactive with the personal: Opportunities for end-user programming in personal information management

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    The transition of personal information management (PIM) tools off the desktop to the Web presents an opportunity to augment these tools with capabilities provided by the wealth of real-time information readily available. In this chapter, we describe a personal information assistance engine that lets end-users delegate to it various simple context- and activity-reactive tasks and reminders. Our system, Atomate, treats RSS/ATOM feeds from social networking and life-tracking sites as sensor streams, integrating information from such feeds into a simple unified RDF world model representing people, places and things and their time-varying states and activities. Combined with other information sources on the web, including the user's online calendar, web-based e-mail client, news feeds and messaging services, Atomate can be made to automatically carry out a variety of simple tasks for the user, ranging from context-aware filtering and messaging, to sharing and social coordination actions. Atomate's open architecture and world model easily accommodate new information sources and actions via the addition of feeds and web services. To make routine use of the system easy for non-programmers, Atomate provides a constrained-input natural language interface (CNLI) for behavior specification, and a direct-manipulation interface for inspecting and updating its world model

    Improving Teen Engagement in Buffalo and Erie County

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    Erie County offers many opportunities for teen engagement through afterschool programs, summer jobs programs, and internships. National research reveals many benefits from these programs, such as improved academic achievement, better health outcomes, and reductions in violence. Participation, however, often drops significantly after youth enter high school. A better understanding of adolescent development and youth engagement strategies, ranging from active participation to shared leadership, will draw more teens into programs and maximize their impact
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