Artbotics: Challenges and Opportunities for Multi-Disciplinary, Community-Based Learning in Computer Science, Robotics, and Art

نویسندگان

  • Fred Martin
  • Hyun Ju Kim
  • Linda Silka
  • Holly Yanco
  • Diana Coluntino
چکیده

Artbotics is a collaboration between faculty in computer science, the arts, and the social sciences. It is a complex project that involves the following elements: • High school and university students with diverse backgrounds coming together to create interactive, microprocessor-enabled installation art. • A collaboration among faculty from different departments and intersecting interests who are facilitating a learning experience for their students. • A collaboration between a university, a metropolitan art gallery, and a public high school. • Students who are participating in different roles— learners, mentors, collaborators, and research assistants. This paper explores issues in interdisciplinary teaching and learning, as well as community-based collaborations and service learning, which are major themes in the Artbotics project. In past publications, we have described results from the summer pilot and first after-school session with high school students, and the planned design for our university course [4]. We described initial results from the university course, including a discussion and photographs of several student artworks [2]. In [3], we focused on the challenge of forming partnerships across academic departments and external institutions. In this paper, we extend this earlier work in several ways. The full challenge of operating a multi-faculty, multi-disciplinary, project-oriented, community-based university course, over a 15-week period, is now apparent to us and there are some areas for improvement. These observations are likely to be independent of subject matter and therefore may be of value to educators with courses with similar structure or themes regardless of content. This paper also includes samples software code written by students as part of their exhibits, and an analysis of the ideas that are represented in this code. One of the persistent challenges of project-based work is achieving a good balance between theoretically interesting student work and timeconsuming production work. Student-created software code is one place where we can find evidence of learning of ideas that are important in computer science. We also describe benefits of this work from the standpoint of the faculty who are involved. Operating the undergraduate course entailed a weekly planning meeting in addition to contact hours with students in lecture/discussion and laboratory sessions. We co-taught the course, with all faculty members present whenever possible. The workload was significant, but the benefits were real, including meaningful, contextualized exposure to each other’s fields.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Artbotics: Combining Art and Robotics to Broaden Participation in Computing

The Artbotics program is a collaboration between artists and computer scientists which uses robotics technologies to teach computer science to undergraduates and high school students. Project-based courses culminate in public exhibitions at a local museum. This paper describes the curriculum developed for the course, the technology used and lessons learned.

متن کامل

MMDT: Multi-Objective Memetic Rule Learning from Decision Tree

In this article, a Multi-Objective Memetic Algorithm (MA) for rule learning is proposed. Prediction accuracy and interpretation are two measures that conflict with each other. In this approach, we consider accuracy and interpretation of rules sets. Additionally, individual classifiers face other problems such as huge sizes, high dimensionality and imbalance classes’ distribution data sets. This...

متن کامل

Improving Agent Performance for Multi-Resource Negotiation Using Learning Automata and Case-Based Reasoning

In electronic commerce markets, agents often should acquire multiple resources to fulfil a high-level task. In order to attain such resources they need to compete with each other. In multi-agent environments, in which competition is involved, negotiation would be an interaction between agents in order to reach an agreement on resource allocation and to be coordinated with each other. In recent ...

متن کامل

Machine Learning and Citizen Science: Opportunities and Challenges of Human-Computer Interaction

Background and Aim: In processing large data, scientists have to perform the tedious task of analyzing hefty bulk of data. Machine learning techniques are a potential solution to this problem. In citizen science, human and artificial intelligence may be unified to facilitate this effort. Considering the ambiguities in machine performance and management of user-generated data, this paper aims to...

متن کامل

Utilizing Generalized Learning Automata for Finding Optimal Policies in MMDPs

Multi agent Markov decision processes (MMDPs), as the generalization of Markov decision processes to the multi agent case, have long been used for modeling multi agent system and are used as a suitable framework for Multi agent Reinforcement Learning. In this paper, a generalized learning automata based algorithm for finding optimal policies in MMDP is proposed. In the proposed algorithm, MMDP ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2007