James Atlas

A complete distributed constraint optimization method for non-traditional pseudotree arrangements

Distributed Constraint Optimization (DCOP) is a general framework that can model complex problems in multiagent systems. Several current algorithms that solve general DCOP instances, including ADOPT and DPOP, arrange agents into a traditional pseudotree structure. We introduce an extension to the DPOP algorithm that handles an extended set of pseudotree arrangements. Our algorithm correctly solves DCOP instances for pseudotrees that include edges between nodes in separate branches. The algorithm also solves instances with traditional pseudotree arrangements using the same procedure as DPOP. We compare our algorithm with DPOP using several metrics including the induced width of the pseudotrees, the maximum dimensionality of messages and computation, and the maximum sequential path cost through the algorithm. We prove that for some problem instances it is not possible to generate a traditional pseudotree using edge-traversal heuristics that will outperform a cross-edged pseudotree. We use multiple heuristics to generate pseudotrees and choose the best pseudotree in linear space-time complexity. For some problem instances we observe significant improvements in message and computation sizes compared to DPOP.

Balancing Scientist Needs and Volunteer Preferences in Volunteer Computing Using Constraint Optimization

BOINC is a middleware for Volunteer Computing. In BOINC projects, heterogeneous resources distributed across the Internet are used for large-scale scientific simulations. The large need for resources in BOINC projects often competes with volunteer preferences: volunteers can impose limits on the use of their idle resources. Most of the time, maximum project performance can be achieved only when volunteer preferences are neglected. To address this problem, we propose a novel optimization procedure based on constraint optimization techniques that actively allocates volunteer resources to improve project throughput and, at the same time, aims to preserve volunteer preferences. We show the increase in project throughput obtained with our approach and discuss the trade-off between volunteer preferences and project throughput.

Teacher Feedback on Delivering Computational Thinking in Primary School

We report on the preliminary results of an ongoing study examining the teaching of new primary school topics based on Computational Thinking in New Zealand. We analyse detailed feedback from 13 teachers participating in the study, who had little or no previous experience teaching computer science and related topics. From this we extract key themes identified by the teachers that are likely to be encountered deploying a new curriculum, including unexpected opportunities for cross-curricula learning, development of social skills, and engaging a wide range of students.

Implementation and Outcomes of a Three-Pronged Approach to Professional Development for CS Principles

One of the greatest challenges in broadening participation in computer science is teacher preparation, as few middle and high school teachers have a formal background in computing. Further, without a credentialing program, there are limited ways to learn content and pedagogical strategies for effective computer science instruction. As a result, professional development is key to successful reform in the teaching of computer science. In this paper, we describe our three-pronged approach to the design of a professional development model for middle and high school teachers interested in implementing the Computer Science Principles (CSP) curriculum in their classrooms or infusing CSP modules into STEM curricula. We describe our model focusing on content, pedagogical strategies and follow-up classroom support during the academic year. We subsequently report on participating teacher outcomes, in terms of self-rated understandings, attitudes and implementation practices. We share lessons learned and offer recommendations for professional development designers.

If Memory Serves: Towards Designing and Evaluating a Game for Teaching Pointers to Undergraduate Students

Games can serve as a valuable tool for enriching computer science education, since they can facilitate a number of conditions that can promote learning and instigate affective change. As part of the 22nd ACM Annual Conference on Innovation and Technology in Computer Science Education (ITiCSE 2017), the Working Group on Game Development for Computer Science Education convened to extend their prior work, a review of the literature and a review of over 120 educational games that support computing instruction. The Working Group builds off this earlier work to design and develop a prototype of a game grounded in specific learning objectives. They provide the source code for the game to the computing education community for further review, adaptation, and exploration. To aid this endeavor, the Working Group also chose to explore the research methods needed to establish validity, highlighting a need for more rigorous approaches to evaluate the effectiveness of the use of games in computer science education. This report provides two distinct contributions to the body of knowledge in games for computer science education. We present an experience report in the form of a case study describing the design and development of If Memory Serves, a game to support teaching pointers to undergraduate students. We then propose guidelines to validate its effectiveness rooted in theoretical approaches for evaluating learning in games and media. We include an invitation to the computer science education community to explore the games potential in classrooms and report on its ability to achieve the stated learning outcomes.