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This paper describes the recent activities of Electrical and Computer Engineering doctoral students in the design, development, and implementation of lessons for high school mathematics and science classes. The graduate students, called Fellows, worked in secondary classrooms in the Cincinnati Public Schools District as a part of Project STEP at the University of Cincinnati, which is funded by the National Science Foundation GK-12 Program.The Fellows formed partnerships with secondary math and science teachers to generate new lessons, activities, and resources to enhance the STEM skills of high school students. Additionally, the Fellows used their engineering expertise to bring authentic learning experiences into the classroom and introduced concepts in their field of engineering to underserved student populations. This paper discusses observations and reflections by the Fellows regarding aspects of the activities that had the most impact on student learning and interest in engineering, which was measured by selfreported student surveys.

This paper describes activities of two graduate students in creating, delivering, and assessing engineeringbased lessons in secondary science and mathematics classes. The students are Fellows in an NSF-funded program called Project STEP at the University of Cincinnati; the program partners graduate students with secondary educators to create resources for teaching science, technology, engineering and mathematics (STEM) skills. The lessons are relevant to students' lives as well as aligned with academic standards. The Fellows bring authentic engineering backgrounds and expertise into the classroom to encourage students to consider engineering as a future field of study.

This paper describes the impact of a new course in elementary programming on retention and recruitment of technology majors. This new course, Elementary Programming (EP), was added as a precursor to a computer science course, Object Oriented Programming (OOP), in order to recruit and retain technology majors. This study evaluates the course's effectiveness of its mission by analyzing student's success rates in both courses and examining factors known to contribute to declining enrollment. The cause of recruitment and retention issues are examined using computer attitude and computer experience surveys that are made available to all students enrolled in the EP course and the OOP course. The results from the fall 2006 surveys and enrollment results for the past five years support the need for the EP course and continued evaluation.

The Semantic Web is the next step in the Internet's evolution. In order to facilitate autonomous information retrieval, it is necessary to create a standard framework for the Semantic Web. The existing Web contains a considerable amount of data. It is an alluring target for data mining. Most of the data stored on web pages is weakly structured. Mining or otherwise accessing the data in context from multiple sites is diffcult; particularly when others construct the web pages and their internal structure is not clearly understood. A standard way of viewing and organizing data into an ontology is essential for sharing data and interoperability between web sites. A Semantic Web standard bas evolved through extensive iteration and was approved in late 2003. Fully autonomous or semi-autonomous discovery and development of ontologies is the only feasible way to transition to the Semantic Web. One enabling strategy is to merge existing, vetted ontologies into a single ontology. The pre-merged ontologies would likely be similar in some respects and distinct in others. This paper discusses bow to possibly merge multiple ontologies into a single viable ontology. It seeks an effective way to merge ontologies without losing any information (and possibly gaining some information in the process). When comparing ontologies, a similarity measure will be necessary. The measure will be used to measure the similarity two existing ontologies. This similarity measure is necessarily imprecise.