The engineering technology department at ETSU currently lacks a modern method to teach digital circuits. The aim of this thesis is to convert our current digital circuits labs to equivalent labs suited to run on the Basys 3. The Basys has several advantages over the aging NI Elvis boards (and now just breadboards) currently in use. The first advantage is that the Basys gives students a taste of FPGA programming without being overwhelmingly; like the systems currently in place for the digital signal processing class. The Basys is also a more modern system; our current integrated circuit and breadboard system is from the 70’s and has little to do with the modern world of electronics. There are several major difficulties with moving towards the Basys 3. It requires several tweaks to the current computer security setting of the lab computers. The other issue to be solved is that very few people in the department have even an inkling of how to program in VHDL and most of them are outgoing students. This lack of skills could be a threat to the class but I have included an appendix and a few recommendations for books on the subject to ensure that system development can continue. The other objective of this project was to see if there were ways to incorporate new educational techniques into the engineering technology curriculum. While there have been no actual tests on students, the groundwork has been laid to use some new ideas in the classroom. All of these new systems are designed to get students to think about how devices actually work and develop models to help them fully understand what is being taught.

This project compared the performance of the correlation coefficient to show similarities in annotations between a predictive automated bacterial annotation database and the curated EcoCyc database. EcoCyc is a conservative multidimensional annotation system that is exclusively based on experimentally validated findings by over 15,000 publications. The automated annotation system, used in the comparison was BASys. It is often used as a first pass annotation tool that tries to add as many annotations as possible by drawing upon over 30 information sources. Gene ontology served as one basis of comparison between these databases because of the limited common terms in the ontology annotations. Translation libraries were used to extend the number of BASys terms that could be compared to the gene ontology terms in EcoCyc. Additional, non-ontology terms and metadata in BASys were compared to EcoCyc terms after parsing them into root words. The different term sources were quantitatively compared by using the correlation coefficient as the evaluation metric. The direct gene ontology comparison gave the lowest correlation coefficient. The addition of gene ontology terms to BASys by using translation tables of metadata greatly increased the correlation coefficient, which was comparable to the parsed word comparison. The combination of enhanced gene ontology and parsed word methods gave the highest correlation coefficient of 0.16. The controlled vocabulary system of gene ontology was not sufficient to compare two annotated databases. The addition of gene ontology terms from translation libraries greatly increased the performance of these comparisons. In general, as the number of comparison terms increased the correlation coefficient increased. Future comparisons should include the enhanced gene ontology dataset in order to monitor the organization pertaining to formal nomenclature and the datasets generated from Word parsing can be used to monitor the degree of additional terms might be incorporated with translation libraries.