http://hdl.handle.net/2440/1078 2013-05-23T07:03:46Z http://hdl.handle.net/2440/77923 Title: Teaching puzzle-based learning: development of transferable skills Author: Falkner, Nickolas John Gowland; Sooriamurthi, Raja; Michalewicz, Zbigniew Abstract: While computer science and engineering students are trained to recognise familiar problems with known solutions, they may not be suciently prepared to address novel real-world problems. A successful computer science graduate does far more than just program and we must train our students to reach the required levels of analytical and computational thinking, rather than hoping that it will just 'develop'. As a step in this direction, we have created and experimented with a new rst-year level course, Puzzle-based Learning (PBL), that is aimed at getting students to think about how to frame and solve unstructured problems. The pedagogical goal is increase students' mathematical awareness and general problem solving skills by employing puzzles, which are educational, engaging, and thought provoking. In this paper we continue sharing our experiences in teaching such a course. Whereas a brief discussion on our pedagogical objectives were covered in the rst paper together with the material of the rst of two lectures on pattern recognition, this follow-up paper presents the material of the second of two lectures, in which additional exercises are discussed to reinforce the lesson. Along the way we provide a glimpse of some foundational ideas of computer science such as incomputability and general system development strategies such as incremental and iterative reasoning. This paper discusses the outcomes of PBL courses, which include expected improvement in the overall results achieved by students who have undertaken PBL courses, compared to those students who have not. 2011-12-31T13:30:00Z http://hdl.handle.net/2440/77911 Title: Teaching puzzle-based learning: development of basic concepts Author: Falkner, Nickolas John Gowland; Sooriamurthi, Raja; Michalewicz, Zbigniew Abstract: While computer science and engineering students are trained to recognise fa- miliar problems with known solutions, they may not be sufficiently prepared to address novel real-world problems. A successful computer science graduate does far more than just program and we must train our students to reach the required levels of analytical and computational thinking, rather than hoping that it will just 'develop'. As a step in this direction, we have created and experimented with a new rst-year level course, Puzzle-based Learning (PBL), that is aimed at getting students to think about how to frame and solve unstructured problems. The pedagogical goal is increase students' mathematical awareness and general problem solving skills by employing puzzles, which are educational, engaging, and thought provoking. We share our experiences in teaching such a course {apart from a brief discussion on our pedagogical objectives, we concen- trate on discussing the presented material which covers (in two lectures) just one selected topic (pattern recognition). In this paper we present the ideas behind foundations for PBL and the material of the rst of two lectures on pattern recognition, in which we address core concepts and provide students with sufficient exemplars to illustrate the main points. 2011-12-31T13:30:00Z http://hdl.handle.net/2440/77859 Title: Foundations of search: a perspective from computer science Author: Marshall, James A. R.; Neumann, Frank 2011-12-31T13:30:00Z http://hdl.handle.net/2440/77799 Title: PerCAS: an approach to enabling dynamic and personalized adaptation for context-aware services Author: Yu, Jian; Han, Jun; Sheng, Quanzheng; Gunarso, Steven O. Abstract: Context-aware services often need to adapt their behaviors according to physical situations and user preferences. However, most of the existing approaches to developing context-aware services can only do adaptation based on globally defined adaptation logic without considering the personalized context-aware adaptation needs of a specific user. In this paper, we propose a novel model-driven approach called PerCAS to developing and executing personalized context-aware services that are able to adapt to a specific user’s adaptation needs at runtime. To enable dynamic and personalized context-aware adaptation, user-specific adaptation logic is encoded as rules, which are then weaved into a base process with an aspect-oriented mechanism. At runtime, the active user-specific rule set will be switched depending on who is using/invoking the service. A model-driven platform has been implemented to support the development and maintenance of personalized context-aware services from specification, design, to deployment and execution. Initial in-lab performance experiments have been conducted to demonstrate the efficiency of our approach. 2011-12-31T13:30:00Z