The benefits of working in a research group are clear: students develop domain expertise, gain an understanding and appreciation of the research process and its practice, and acquire team, communication, problem‐solving, and higher‐level thinking skills. Students with this experience are better equipped to make informed judgements about technical matters and to communicate and work in teams to solve complex problems. Clearly, this type of research experience must be made available to a broader population. This paper discusses how the Systems and Software Engineering Affinity Research Group model provides a socialization mechanism and infrastructure that supports the development and management of large research groups that engage undergraduate and graduate students, who have a wide range of skill levels and experiences, in research and projects. This non‐hierarchical model, which is based on the cooperative paradigm, integrates students into small research groups and an encompassing large research group, and uses structured activities to develop their research, technical, communication, and group skills.
The wide use of performance counters by application developers and benchmarking teams gives evidence that performance counters are well worth the silicon and design time required to include them on modern microprocessors. These counters provide rudimentary performance measurements that may or may not be accurate. This paper presents our methodology for determining the accuracy of these counters as well as preliminary results of a study that, using this methodology, evaluates the accuracy of the R12000 performance counters with respect to eight of 30 measurable events. The results indicate that care must be taken when using data generated by performance counters because, in some cases, this data may lead to erroneous conclusions. This can occur when the granularity of the measured code is not suflcient to ensure that the overhead introduced by counter interfaces does not dominate the event counts.
The Affinity Research Group model is an attractive vehicle for involving undergraduates in research, retaining them, and fostering their interest in higher education. Using this model, students are given opportunities to develop, employ, and integrate knowledge and skills required for research with knowledge and skills required for cooperative work. Potential adopters of the model often inquire about the feasibility of applying the model in a field like computer science, in which it often is the case that a student must have a solid academic foundation in order to be involved in research. This paper addresses this question by illustrating how the model has been applied to computer science research projects that involve students with different skill levels and experience. In particular, the paper presents example structured tasks and related activities that demonstrate how students develop domain expertise, gain an understanding and appreciation of the research process and its practice, and acquire technical, team, communication, problem‐solving, and higher‐level thinking skills.
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