teaching portfolio 1998kevin d - engr.uky.edudonohue/resume/teaching portfolio 2006.doc · web...

Teaching Portfolio 2005/06Kevin D. Donohue

ProfessorElectrical Engineering Department

University of KentuckyLexington, KY [email protected]

TABLE OF CONTENTS

Subject Page

Teaching Evaluation............................................................................................................1

Changes to Portfolio since Last Review:.......................................................................1Philosophy and Goals....................................................................................................1Course Characteristics...................................................................................................1Teaching Performance and Outcome Assessment.........................................................2

EE 101 Electrical Engineering Professions Seminar(outcome assessment)............3EE 211 Circuits I (outcome assessment)................................................................4 EE221 Circuits II (outcome assessment)................................................................6 EE222 Electrical Engineering Laboratory I............................................................9 EE307 Circuit Analysis with Applications..............................................................9EE380 Microcomputer Organization.......................................................................9EE421 Signals and Systems I................................................................................10EE422 Signals and Systems II...............................................................................10EE462G Electronic Circuits Laboratory (outcome assessment)............................10EE 499 Senior Design (outcome assessment)........................................................13EE 599 Audio Signals and Systems.......................................................................15

New course EE513 Proposed...........................................................................16EE611 Deterministic Systems................................................................................18EE630 Digital Signal Processing...........................................................................19EE 639 Adv. Topics in Com. and Signal Processing (outcome assessment)........19Sponsored Independent Study Courses..................................................................20Sponsored Internships............................................................................................23

Student Evaluation Summary............................................................................................24

Advising Evaluation...........................................................................................................24

Appendix A – Course Outcome Assessment Forms..........................................................25Appendix B - Student Evaluations of Courses and Teaching............................................34

Teaching Portfolio: Kevin D. Donohue, December 20061

TEACHING EVALUATION:

Changes to Portfolio Since Last Review:

I have updated based on new courses I taught, including a new course EE513 currently being considered as a new course offering in signals and systems.

Philosophy and Goals:

My teaching assignment consists of undergraduate and graduate courses in the electrical engineering department with specialty courses in the signals and systems area (statistical signal processing, digital signal processing (DSP), and communication systems). These courses emphasize applying mathematical models for relating information to signals and systems, and using these models to solve engineering problems in control, communications, and signal processing.

After about 20 years of teaching on the college level, I believe most of my effort needs to go into getting students excited about the subject. While there is a basic knowledge and skill set that students need to achieve to pass the course, I consider digressions in the material presentation to stories that somehow show the importance of human creativity, ingenuity, engineering, and relate them to the concepts or outcomes of the course. Information presented to a motivated student make my job more interesting and enhances students’ creativity and problem solving skills. Information presented to an unmotivated student is at best regurgitated back on an exam and bears little fruit. While I like this as a goal, I still feel that over 50% of the students in my classes do not catch that spark, so I still have a lot of work ahead of me.

Course Characteristics:

My classroom activities are strongly influenced by student feedback, which I get directly from the students or through the teacher/course evaluations. As a result of student feedback over the years, the characteristics of my classroom are as follows. I give many quizzes throughout the course rather than a few midterms. The quizzes are graded by me are returned promptly with comments). I assign, collect, and grade homework (homework assignments are graded by the teaching assistant, if one is provided for the course). I give projects that sometimes involve students working in groups. I make class materials available on the Word Wide Web (see http://www.engr.uky.edu/~donohue/courses.html ). I do a lot of information broadcasts using class email lists the college of engineering computing services set up for me. I make students orally present project results or explain homework solutions to the rest of the class. In regards to student presentations, I get negative feedback primarily because students do not like to speak publicly and they don’t like listening to a classmate who is doing a poor job at it. I try to minimize the pain of the experience by moderating the event; however, I continue having student presentations because I think it helps them in

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http://www.engr.uky.edu/~donohue/courses.html


the long run. The primary complaint (feedback) from industry about engineering students concerns their poor communication skills. So I don’t weigh in negative student comments enough to drop oral presentations from my classroom activities yet.

In lab courses I emphasize experimental design skills and written explanations (how to write and communicate technical information). Therefore, I try not to provide a lot of detail in the lab assignment on how to make a measurement. This frustrates some students, however rather than learning a particular instrument, I am hopeful that they will learn instrumentation skills applicable to broader setting. I encourage writing more concisely through the use of figures, graphs, and equations. I think by now most of my students see the value in developing their writing skills and appear to be improving at it.

Teaching Performance and Outcome Assessment

In order to determine how well students are achieving the course outcomes, I have started a system (since Spring 1999) for grading each assignment according to the outcomes listed for the course. If a single assignment has multiple outcomes, it will be graded in separate components and recorded as separate components in the class spreadsheet. So each column relates to the performance of one outcome. Scores are then averaged over all students and a class grade assigned for each outcome. This way I can track student outcome achievements vs. what I do in the classroom from semester to semester. The courses taught before 1999 just have a brief description of the course with a list of student evaluations on the teaching quality and course value for each time I taught the course. As of 2002 the outcome tables are more streamlined to show development of student self assessment of their outcome achievement as well as my assessments. The actual forms used to keep record of outcome achievement and improvements are also included in Appendix B.

EE 101 Electrical Engineering Professions Seminar Subjects Covered: Professional practice, growth, conduct, ethics, computers in electrical engineering, the University computer system, careers in engineers, and professional societies.

This is a one hour seminar course (taken Pass/Fail) designed to help freshmen become familiar with the electrical engineering profession and learn basic skill for enhancing their time as an undergraduate at the University of Kentucky.

Teacher/Course Evaluation (by student):

Student Ratings of Instructor and Course (Scale 1-4 with 4 being the best)Term Enrollment Value of Course Quality of TeachingFall 2000 92 3.2 3.5Fall 2001 102 3.1 3.4Fall 2002 107 3.2 3.4

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Course Outcome Assessment:Two evaluations of each course outcome is performed. One is a self-evaluation that reflects the student confidence level, and the other is by the instructor derived from the average score on course assignments related to each outcome.

Course Outcome List:1. Know the academic requirement for an undergraduate degree in Electrical Engineering.2. Understand ethical and professional issues associated with the electrical engineering profession.3. Able to use word processing spreadsheets, computer networks, literature search techniques, e-

mail, and very simple electric networks.

Student Self-Assessment:Students rated their own ability relative to each course outcome on a scale from 1 (no confidence) to 5 (most confident). The mean was taken over all students and converted to a percentage (out of 5), which is reported in the table below in terms of percent 100*(score-1)/4.

Table EE101 Student Confidence Level Percentage

Semester Respondents Course Outcome1 2 3

Fall 00 52 87.5 85 90Fall 01 52 -- 85 85Fall 02 35 82 80 77.5

The dropping trend in Outcome 3 is not good. I need to give more assignments associated with this outcome. I originally dropped some because I did not want the course to burden the freshmen over their more important academic subjects; however I probably need to give smaller and possibly in-class assignments so students can gain more confidence in their abilities with these outcomes.

Assessment by Instructor:The following assessment tools were used throughout the class:

Homework assignments In-class assignments

Table EE101 Student Performance Level Percentage

Semester Enrollments Course Outcome1 2 3

Fall 00 91 50 75 75Fall 01 102 -- 75 62.5Fall 02 107 -- 87 87

Feedback and Improvement:

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While I felt their performance has improved, it is hard to report a finer scale with a pass-fail grading system. I can only go by number of acceptable assignments turned in. The greater weight of outcome assessment for this course has to be the student self assessments rather than the faculty numbers. The increase in performance for outcomes in the Fall 02 is most likely the result of giving few assignments. Student confidence level has held steady.

For outcome 2, I am finding that my senior exit interviews reveal almost 100% of our students remember seeing the IEEE code of ethics. Most had seen this for the first time in EE101. In 1997 though 2000 many of our graduating seniors (more than 50%) did not recalled seeing the IEEE code of ethics before.

I also feedback information from interviews I do with students on probation and the senior interview to help advise students on strategies for successfully completing the curriculum. I continue to provide this information to all faculty and especially those teaching EE101. Over the last 6 year we have seen over a 100% improvement in retention rates. Will EE101 was on the only factor, I do think it played a significant part in this success.

EE 211 Circuits I Subjects Covered: AC and DC analysis of linear circuits including transient and steady-state analysis.

This is the students’ first technical course in electrical engineering. This focus in on fundamental circuit analysis and circuit simulation software.


Student Ratings of Instructor and Course (Scale 1-4 with 4 being the best)Term Enrollment Value of Course Quality of TeachingSpring 02 33 3.6 3.8Fall 01 55 3.7 3.8Spring 01 27 3.8 3.9Fall 00 45 3.5 3.6Spring 00 29 3.6 3.7

Course Outcome EvaluationTwo evaluations of each course outcome is performed. One is a self-evaluation that reflects the student confidence level, and the other is by the instructor derived from the average score on course assignments related to each outcome.

Outcome list:1. Analyze simple resistive circuits including those containing operational amplifiers and

controlled sources with loop and nodal analysis

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2. Analyze RLC circuits containing switches, independent sources, dependent sources, resistors, capacitors, inductors, and operational amplifiers for transient response using loop and nodal analysis

3. Analyze RLC circuits with sinusoidal excitation sources for steady-state response using loop and nodal analysis

4. Compute Thévenin and Norton equivalent circuits5. Use SPICE (computer simulation package) to compute voltages, currents, transient responses,

and sinusoidal steady-state responses

Student Self-Assessment:Students rated their own ability relative to each course outcome on a scale from 1 (no confidence) to 5 (most confident). The mean was taken over all students and converted to a percentage (out of 5), which is reported in the table below.


Semester Respondents Course Outcome1 2 3 4 5

Spring 00Fall 00 23 88 80 88 76 90

Spring 01 17 90 76 82 82 90Fall 01 34 90 80 82 76 90

Spring 02 25 84 76 78 72 84


Homework assignments In-class and take-home quizzes Final exam

The complex assignments that involved multiple outcomes were graded and recorded in components. The average score was computed over all students and assessment tools related to each outcome. The percentage for each outcome is listed in the table below.


Semester Enrollment Course Outcome1 2 3 4 5

Spring 00 29 81 74 75 48 81Fall 00 23 88 71 72 60 73

Spring 01 27 82 84 84 74 87Fall 01 45 80 79 81 76 90

Spring 02 29 85 80 71 83 78

Feedback and improvement:

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When I started to collect these statistics I realized the outcome number 4 was in definite need of improvement with a 48% average score on problems related to this outcome. I began to focus on this component and give more class time to it and more homework problems and special exercises. As a result there has been a steady improvement in this outcome until it is now comparable to the other outcomes. Student confidence in this outcome is still low, however. This indicates that while I may have been successful in teaching the mechanics of the problem, they lack the understanding and purpose of the analysis and confidence. I will work on this next time I teach the course. Outcomes 2 and 3 are now of my greatest concern. The next time I teach the course I will focus on better examples for the lecture. I will also work on special exercises to use during recitation.

EE221 Circuits IISubjects covered: Transfer functions of circuits, singularity functions, differential equation representations and solutions for circuits, two-port parameter representations of circuits, and design project organization.

My main addition to the course was a hearing aide design project which I added in 1994 and is still being used in this course to develop and evaluate student outcomes related to open-ended design and team work. The web page of Drs. Gedney and Donohue have various version of this project described. I also have a link so that students can evaluate their own hearing loss and develop the filters and amps to compensate for their own deviation from normal hearing.


Student Ratings of Instructor and Course (Scale 1-4 with 4 being the best)Term Enrollment Value of Course Quality of TeachingSpring 2005Fall 98 34 3.4 3.5Fall 97 44 Team Taught 50% 3.0 3.2Summer 97 19 No Evaluation No EvaluationFall 96 41 3.5 3.6Summer 96 19 No Evaluation No EvaluationSpring 96 59 3.3 3.2Fall 95 61 3.2 3.3Fall 94 26 3.5 3.6Summer 94 10 No Evaluation No EvaluationSpring 93 71 3.4 3.6Spring 92 58 3.5 3.5Fall 91 51 3.6 3.6

In 2001 the outcomes for this course changed. Below are new outcomes along with the times I taught the course based on these new outcomes. Following these are for the outcomes prior to 2001.

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Course Outcome EvaluationTwo evaluations of each course outcome is performed. One is a self-evaluation that reflects the student confidence level and the other is by the instructor derived from the average score on course assignments related to each outcome.

Outcome list:1. Perform an AC steady-state power analysis on single-phase circuits.2. Perform an AC steady-state power analysis on three-phase circuits.3. Analyze circuits containing mutual inductance and ideal transformers.4. Derive transfer functions (variable-frequency response) from circuits containing independent

sources, dependent sources, resistors, capacitors, inductors, operational amplifiers, transformers, and mutual inductance elements.

5. Derive two-port parameters from circuits containing resistive and impedance elements.6. Use SPICE to compute circuit voltages, currents, and transfer functions.7. Describe a solution with functional block diagrams (top-down design approach).8. Work as a team to formulate and solve an engineering problem.9. Use computer programs (such as MATLAB and SPICE) for optimizing design parameters and

verify design performance.


Student Self-Assessment:Students rated their own ability relative to each course outcome on a scale from 1 (no confidence) to 5 (most confident). The mean was taken over all students and converted to a percentage (out of 5) reported in the table below.


Semester Respondents Course Outcome1 2 3 4 5 6 7 8 9

Spring 05 34 82 77.5 77.5 77.5 77.5 77.5 77.5 77.5 75


Homework assignments Team-design project In-class and take-home quizzes Final exam

The complex assignments that involved multiple outcomes were graded and recorded in components. The average score was computed over all students and assessment tools related to each outcome. The percentage for each outcome is listed in the table below.

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Semester Enrollment Course Outcome1 2 3 4 5 6 7 8 9

Spring 00 42 81.8 71.7 79.0 79.6 76.5 77.4 84.3 90.6 85.0

Feedback and Improvement: Since this was the first time I taught the course the above numbers provide a baseline for the next time I teach the course. I did try new things with the project to enable more feedback and comments from me in the design process. I had the student hand in a proposal, and intermediate draft of the final report and then a final report. I think this was helpful, but I ran into problems scheduling due dates on the project material along with their other homework. As a results students did not work as efficiently as they could have. There is a disparity between my rating on outcome 8 and their self rating. I mainly graded the teamwork component based on their initial proposal and effort plan. I really do not have a good way to assess the team elements after the project is done. Next time I will try get more discussion going on team issues while the project is in progress, and plan out assignments and due dates better. I may even try a peer review from each group to assess the team skills.

Student Self-Assessment:

Course OutcomesFall 98

StudentsResponding

ExpectedGrade

Level ofconfidence

Ability to derive transfer functions, differential equation representations, and two-port parameters from circuits containing independent sources, dependent sources, resistors, capacitors, inductors, operational amplifiers, transformers, and mutual inductance elements.

28 3.32 86.00%

Ability to solve for circuit outputs (voltages and currents) when circuit is driven by combinations of DC, sinusoidal, and singularity function sources, and the ability to apply superposition for multiple or complex sources.

28 3.32 86.00%

The ability to use SPICE for determining circuit outputs (voltages and currents) when combinations of DC, sinusoidal, and singularity function sources drive circuit.

28 3.32 88.00%

Ability to describe a solution with functional block diagrams (top-down design approach). 28 3.32 80.00%

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Ability to work as a team to formulate and solve an engineering problem 28 3.32 82.00%

Ability to use computer programs (such as MATLAB and SPICE) for optimizing design parameters and verify design performance.

28 3.32 80.00%

For the Spring 2004/05 semester this course is current in progress with and will be subsequently update with new format with new outcomes and student self-assessments. Assessment tools:Optional questions on teacher/course evaluation that asked to student the rate their own ability to perform each of the course outcomes

EE222 Electrical Engineering Laboratory ISubjects covered: Basic measurement and characterization of DC and AC voltages, currents, and power. Enrollment: 45 Students.

Student Ratings of Instructor and Course (Scale 1-4 with 4 being the best)Term Enrollment Value of Course Quality of TeachingFall 96 44 3.2 3.6

EE307 Circuit Analysis with ApplicationsSubjects covered: Basic AC and DC circuit analysis techniques (mesh and nodal analysis with circuit elements comprised of resistors, capacitors, inductors, op amps, and transformers). Examples in instrumentation, electro-mechanical, and power transfer circuits.

Student Ratings of Instructor and Course (Scale 1-4 with 4 being the best)Term Enrollment Value of Course Quality of TeachingSummer 96 40 No Evaluation No EvaluationSummer 95 41 No Evaluation No Evaluation

EE380 Microcomputer OrganizationSubjects covered: General Architecture of Microcomputer, 8086 instruction set and programming concepts


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Spring 93 47 3.3 3.1

EE421 Signals and Systems I Subjects covered: Modeling and analysis of signals and systems using convolution, Fourier series, Fourier Transform bandwidth, basic filter design, modulation techniques, random variables and random processes and spectral density.

Student Ratings of Instructor and Course (Scale 1-4 with 4 being the best)Term Enrollment Value of Course Quality of TeachingSpring 98 29 3.2 3.0Spring 97 50 3.1 3.4

EE422 Signals and Systems IISubjects covered: Discrete-time system models, Laplace and Z-transforms for analyzing system and signal dynamics, Block-diagrams and feedback analysis, Digital Filter design.


EE 462 Electronic Circuits Laboratory

Subjects Covered: Experimental Exercises in the design and analysis of useful electronic circuits incorporating transistors, zener diodes, integrated circuits, and operational amplifiers.

This is the students’ second required lab focusing on nonlinear circuit elements. Writing and instrumentation skills are emphasized.


Student Ratings of Instructor and Course (Scale 1-4 with 4 being the best)Term Enrollment Value of Course Quality of TeachingFall 2002 18 3.5 3.7Spring 2003 45 3.5 3.8Fall 2003 23 3.5 3.6Summer 2004 15 3.7 3.9Fall 2004 39 3.5 3.6Summer 2005 8 Not Available Not Available

Course Outcome Evaluation

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Two evaluations of each course outcome is performed. One is a self-evaluation that reflects the student confidence level and the other is by the instructor derived from the average score on course assignments related to each outcome.

Outcome list:1. Analyze circuits with nonlinear elements using semiconductor characteristics. 2. Measure relevant quantities and parameters in electronic circuits using oscilloscopes, multimeters,

function generators, power supplies, and curve tracers.3. Analyze electronic circuits with computer simulation programs (SPICE).4. Describe an experimental procedure involving circuits with semiconductor devices.5. Interpret experimental measurements involving circuits with semiconductor devices



Semester Respondents Course Outcome1 2 3 4 5

Fall 2002 18 87.5 92.5 87.5 92.5 82.5Spring 2003 45 75 87.5 75 85 77.5Fall 2003 23 67.5 87.5 67.5 77.5 85Summer 2004 15 90 90 90 92.5 90Fall 2004 39 77.5 85 75 80 77.5NAY => Not Available Yet, IP=> In Progress

Only outcomes appear to be holding a steady rating with stronger fluctuations in outcomes 1 and 3. With a recent change I have made in Summer 2004 to give less detail on how to make the measurements for a given lab exercise, and more emphasis on discussing the differences between their theoretical and experimental findings, I suspect that these numbers will also fall. However there was a significant spike upwards. Part of this was due to a Summer lab where we met every day that help student become more comfortable with the equipment. I also tended to be in the lab with the students rather than a TA. This will be explained more in the feedback and improvement section.


Pre-lab assignments In-lab data sheets Lab written reports Final lab demonstrations

The lab reports involving multiple outcomes were graded and recorded in components corresponding to each outcome. The average score was computed over all students and

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assessment tools related to each outcome. The percentage for each outcome is listed in the table below.


Semester Enrollments Course Outcome1 2 3 4 5

Fall 2002 18 91 98.25 91 87.2 81.75Spring 2003 45 74.5 96.5 80.25 97.5 88.5Fall 2003 23 74 90.25 60.25 90.75 94.25Summer 2004 15 75.5 85.75 76.25 86.25 66Fall 2004 39 90.7 92.5 82.75 89 99.75IP=> In ProgressThe number from Fall 2002, represent the first time I taught the course with a relatively small class. In some way I did not feel the grades really reflected the actual performance. So some changes were make to grade more rigorously in the subsequent semester. From Spring 2003 steady or falling outcome are observed. Some changes have been make in the Summer of 2004. This will be explained in the feedback and improvement section.

Feedback and improvement:Lab infrastructure development: Over the course of teaching this lab in the last 2 years, I have help to upgrade the oscilloscopes and curve tracer. The curve tracer was over 18 years old and outdated, the oscilloscopes were over 4 years old and were the oldest scopes in all our teach labs, even having less feature than the oscilloscopes used in the sophomore labs. In addition I have PC at all lab stations and GPIB interfaces for automated instrumentation. The newer equipment has enabled new labs to be designed that get the students more involved in programming and advanced data analysis.

The outcomes started off high because the grading standard was not as rigorous the first year. The TAs do a lot of grading and my ability to train them was limited, since it was my first time teaching the course. My first priority was having students write procedures, which they seem to rank high even from the beginning. I have been working on being more general in the lab assignments so the students are doing more experimental design and less cookbook lab assignments. These were changes to enforce a standard that I feel is important and in the students and professions best interest. My work to help students in their achievement of these outcomes has not been all that successful as indicated from the outcomes on both the instructor and student assessments. I have recently made several change with the hope of improving performance. I felt that many of the lab originally developed by Dr. Radun were high quality; however they took more time that expected for a 2 credit hour lab for the students to complete and write up. As a result students were skipping or doing substandard work on critical parts of the lab just to get the assignment done. Since summer of 2004 I have reduced the number of labs and now only required only one lab report and one pre-lab assignment from each team, so that students can put more effort into the writing process (one writes

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and the other edits or checks prelab work, and then they switch off for subsequent labs). I am hoping they will learn from each other better in this approach and take more time to do the assignments well.

The biggest and most recent drop is in interpretation of the data. Students have always rated themselves relatively low on this and the grading has caught up with that based giving more weight to the discussion section. With the new equipment I have been lecturing more on computing statistics and relating that to the circuit and instrumentation properties. I hope to focus on this and include experiments where students can collect large data sets and analyze the variability of an experimental measurement. And compare measurement procedures based on repeatability. I hope with the fewer labs and more automated data collections, the students can focus their attentions more on the critical outcomes of this course. More information from the outcome assessment sheets detailing the feedback and improvement process are in Appendix A.

EE 499 Senior DesignSubjects Covered: A course for senior students in electrical engineering with an emphasis on the engineering design processes requiring the creative involvement of students in open-ended problems relating to actual designs that are appropriate to the profession of electrical engineering.

Student Ratings of Instructor and Course (Scale 1-4 with 4 being the best)Term Enrollment Value of Course Quality of TeachingSpring 99 8 3.3 3.6

Spring 99 Project Description: The following design project requires a good understanding of the concepts presented in EE380, EE421, and EE422 (some of EE461). The skills most often required for typical project tasks include programming (in Matlab, C, and assembly language) and teamwork. This design project focuses on a system that processes a voiced melody and synthesizes sounds in real-time to create a harmony. The critical element for the design solution involves programming a TMS320C3x floating-point DSP chip. Subtasks include designing simple audio amps (microphone and speaker circuits), and analyzing sounds from various voices and instruments.


Course OutcomesSpring 99

Students Responding Expected Grade Level of confidence

effectively work in groups to propose and develop engineering solutions. 6 3.2 76.00%

apply previously acquired engineering principles as well as learn new principles in solving a large engineering design problem.

6 3.2 84.00%

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communicate and thoroughly document the results of an engineering design project to the engineering community using a variety of media (report, web page).

6 3.2 74.00%

Assessment tools:Optional questions on teacher/course evaluation that asked to student the rate their own ability to perform each of the course outcomes

Assessment by Instructor:

Course OutcomesSpring 99

Students Evaluated Percent of total Grade Assessment Score

effectively work in groups to propose and develop engineering solutions. 8 0.25 90.37%

apply previously acquired engineering principles as well as learn new principles in solving a large engineering design problem.

8 0.3 95.33%

communicate and thoroughly document the results of an engineering design project to the engineering community using a variety of media (report, web page).

8 0.45 88.50%

Assessment tools: Group written pre proposals for solving the design problem that included a

breakdown into subtasks, a timetable for completion, and division of effort among the team members

Individual oral presentations where each person explains the overall objective of the team and their individual role in the project including the individual tasks they need to accomplish (presentation are 50% peer rated)

Individual engineering notebooks where the students log their work on the project Group presentation of the final product (demonstrate performance) Group written final report documenting the design and the design process

Feedback and improvement:This is the first time I am using this style of assessment and the first time I taught this course. The numbers above represent a baseline score, and more data are required to draw specific conclusions about what should be improved. Since this was my first time teaching the course, I do have quite a few ideas on how to make it better. Students liked learning about programming the DSP hardware and were frustrated that all students did not get a chance to learn it (effort was divided up where some group member were primarily working on the algorithms and supporting analog hardware). As a result I have a have developed a set of 5 lab experiments designed to introduce the student to program and debug the C31 DSP chip. I will use this that next time I teach a DSP related course using the C30.

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EE 599 Audio Signals and Systems (A potential new course)

Subjects Covered: Audio system and signal models, analysis and design of audio systems.

This is a potentially new senior-level course. I recently put in a proposal for it to be a new courses as EE513. I am currently teaching this course as an EE599 for the final time. I had the idea to offer a course like this for a long time. I finally followed through on it when a group of students presented me with a petition to offer a course in audio systems. With many interested students on hand, I decided to offer this course the following year in the summer so as not to burden the department with one more 500-level course in the regular year. I also felt this course was a good idea because there are currently no senior-level courses offered in signal processing and audio is a good application through which to teach several popular analyses and design approaches in signal processing. Signal processing make up a signal part of the electrical engineering profession and with the information age taking us to a place of “sensors everywhere,” signal processing will continue to be an important component of the electrical engineering community.


Student Ratings of Instructor and Course (Scale 1-4 with 4 being the best)Term Enrollment Value of Course Quality of TeachingSummer 2003 14 3.7 3.9Spring 2004 7 3.3 3.5Fall 2006 15 IP IP

Course Outcome Evaluation No formal outcome evaluation was done on this course since it is not an official course and both the content and outcomes are in a state of flux.

Outcome list:1. Characterize digital audio systems with difference equations and transfer functions.2. Characterize digital audio signals with correlation functions and power spectra.3. Design systems for processing audio data for applications such as filtering, audio effects, and

signal classification.4. Know the fundamental principles of acoustic energy generation and propagation.5. Program with mathematics software to implement and evaluate designs.6. Work as a team to solve multi-component problems.

Feedback and Improvement:This course appeared to be well-liked by the students taking it. This was difficult fitting everything in. I hoped to get to some DSP hardware issues, but never did. I spent 4 weeks with psychoacoustics, because of all the component in the audio system the human ear is the more interesting and I felt students would benefit from the experimental design

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issues associated with modeling the functions of the ear. Students really did not like this section as much as I thought they would. Therefore, in the current version of the course I am focuses on what seem to be weak areas for the students in our program (programming and filter design concepts from EE422). So I have focused the course on these issues and made it a studio model so I can interact with students as they work on programming systems to do specific tasks.

The syllabus template for the currently proposed course is as follows:

EE513 Audio Signals and Systems

Expected Student Outcomes:A student who has successfully completed this course should be able to:7. Characterize digital audio systems with difference equations and transfer functions.8. Characterize digital audio signals with correlation functions and power spectra.9. Design systems for processing audio data for applications such as filtering, audio effects, and

signal classification.10. Know the fundamental principles of acoustic energy generation and propagation.11. Program with mathematics software to implement and evaluate designs.12. Work as a team to solve multi-component problems.

Text: Speech and Audio Signal Processing (Processing and Perception of Speech and Music), Ben Gold and Nelson Morgan, John Wiley & Sons, 2000.Class Email List: To receive relevant communications and homework assignments for this class you must register for the list at the following web site: http://lists.engr.uky.edu/mailman/listinfo/ee599-2Materials: Matlab will be use extensively and is on all university computers. A student edition of Matlab is also available see http://www.mathworks.com/support/product/SV/ for more information.

Grading: Final Exam (1) 31%Quizzes (5) 25%Studio Assignments (4) 32%Homework (10) 12% for undergraduate students

6% for graduate studentsPaper Review (1) 6% for graduate students (not required for undergraduate

students)Grading scale: For undergraduates 100-90% = A, 90-80% = B, 80-70% =C, 70-60% = D, and 60-0% E. For graduates 100-90% = A, 90-80% = B, 80-70% =C, 70-0% E.

Final Exam: The final exam will be comprehensive and similar in complexity to in-class quiz problems, homework problems, and subcomponents of the studio assignments. The final exam primarily assesses course outcomes 1 through 4.

Quizzes: Quizzes will be given throughout the semester to test recently acquired skills / knowledge. In-class quizzes will typically involve problems that can be solved without the help of specialized computer software. Take-home quizzes will require the use of specialized software and the solutions are to be completed independently. There will likely be 6 quizzes, and the 5 highest quiz scores will be taken to

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http://www.mathworks.com/support/product/SV/

http://lists.engr.uky.edu/mailman/listinfo/ee599-2


compute the final grade. No makeup quizzes will be given. The quizzes primarily assess course outcomes 1 through 4.

Studio Assignments: Studio assignments involve designing, implementing, and demonstrating a solution to a posed problem with students working in teams (typically 2 to 3). Time will be given in class (location will be in a lab with workstations) to work on the problem with instructor present for interactions. The assignment may extend over several class periods. Some assignments may require a short description of the results (a few paragraphs and figures), but all will require a short demonstration to the class and oral questions from the instructor directed to individual group members. The final grade will have a common component based on the solution and how effectively the group worked together, and an individual component based on responses to questions/contributions. The studio assignments primarily assess all course outcomes.

Homework: Homework primarily involves responding to problems posed in the textbook or in the lecture. Homework assignments focus on the assessment of outcomes 1 through 4. Late homework assignments will not be accepted.

Paper Review: For graduate students only, read a research paper (approved first by instructor) on audio signals/systems and write a critical report on it. The report must accurately summarize what the authors claim to show, describe their methods, site other related works that support/contradict the findings, and critically assess the degree to which they established their claims. The paper review primarily assesses outcomes 1 through 4.Unethical behavior (cheating): Unethical behavior includes using/reporting false data, copying another student’s work, and claiming a piece of someone else's work as your own. Any of these infractions can result in an E for the course and the university may pursue further disciplinary actions (see http://www.uky.edu/StudentAffairs/Code/ ).

Tentative Course Schedule EE599

Lecture Dates Text Section

Problems Lecture Topics

1 8-23,25,28,30 Chapters1-5

Text: 2.4,3.1,3.5,5.1,5.4class: (Matlab)

History/Introduction to Matlab’s sound functions

2 9-1,6,8 Chapter 6 Text: 6.1,3,4,7,8,9,10,11,12, 13Class: (Matlab)

DSP general models (Z-transforms and difference equations)

3 9-11,13,15 Chapter 6(Notes)

Studio Assignment 1: Digital oscillator for a complex tone

Digital oscillators, Complex tones (Quiz 1)

4 9-18,20,22 Chapter 7.1-7.5

Text: 7.1,2Class: (Matlab)

Digital filters (graduate students: select review paper)

5 9-25,27,29 Chapter 7.6-7.8(Notes)

Text: 7.4, 6, 7, 10Class: (special problems)

DFTs, Power spectra, Spectrograms, and correlation functions (Analysis and design of audio signals and systems), (Quiz2)

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http://www.uky.edu/StudentAffairs/Code/


6 10-2,4 Chapter 7(notes)

Studio Assignment 2: Characterize noise (room,/quantization) distortion (sampling/amplifier)

Noise, distortion, and sampling

7 10-9,11,13 Chapter 7(notes)

Studio Assignment 3: Filter design for signal enhancement

Filter design, Optimal filtering (Quiz 3)

8 10-16,18,20 Chapter 8 8.1,2,3,4,5Class: (special problems)

Feature vectors, Pattern classification, Neural networks (Quiz 4)

9 10-23,25,27 Chapter 99.1-9.7

9.1,2,3Class: (special problems)

Classifiers: Maximum likelihood, Bayes, Linear discriminants

10 10-20,11-1,3 Chapter 10 10.1,4,5,7,8,10,12,13 Acoustic energy generation and propagation

11 11-6,8,10 Chapter 11 11.2,3,4,5,6,7 Speech (modeling sounds from human voice mechanics) (Quiz 5)

12 11-13,15,17 Studio Assignment 4: Design, build, and test a word classifier

13 11-20,22 Chapter 12.1-12.6

12.1,2,4,5 Music (tonal and percussive sounds, timbre, harmonic analysis, stringed instruments)

14 11-27,29,12-1 Chapter 12.7-12.8

12.6,7,8,9 Music (percussive and wind instruments) (Quiz 6) (graduate students: Hand in paper review)

15 12-4,6,8 Review

16 12-11:15 Final Exam

EE611 Deterministic SystemsSubjects covered: Linear system models and solutions for multiple-input-output systems, System model controllability, System model observability, State-feedback design.


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EE630 Digital Signal ProcessingSubjects covered: Z-transforms, Digital Filter Design, and Analog-to-Digital and Digital-to-Analog Conversion, lab component Filter implementation on DSP hardware.

Student Ratings of Instructor and Course (Scale 1-4 with 4 being the best)Term Enrollment Value of Course Quality of TeachingFall 95 11 3.6 3.6Fall 94 14 3.6 3.7Fall 93 9 3.4 3.7

EE 639 Advanced Topics in Communications and Signal Processing

Subjects Covered: Advanced topics in signal processing and communications research and design topics of current interests. A review and extension of current literature and selected papers and reports. Spring 2002 Subjects Covered: Statistical Modeling by Wavelets, Estimation Theory for Signal Processing and Communications, and DSP implementationFall 99 Subjects Covered: Statistical Modeling by Wavelets, Estimation Theory for Signal Processing and CommunicationsSpring 96 Subjects Covered: Modern Spectral Estimation and Optimal FilteringSpring 95 Subjects Covered: Wavelets and Higher Order StatisticsSpring 94 Subjects Covered: Modern Spectral Estimation and Optimal Filtering

Student Ratings of Instructor and Course (Scale 1-4 with 4 being the best)Term Enrollment Value of Course Quality of TeachingSpring 02 14 3.8 3.8Fall 99 5 3.5 3.5Spring 96 3 No Evaluation No EvaluationSpring 95 8 3.9 3.9Spring 94 9 3.2 3.7


Course OutcomesFall 99 Spring 02

Students Evaluated

Assessment Score

Percent of total Grade

Students Evaluated

Assessment Score


Ability to read and critically evaluate research in selected areas of communications and signal processing

5 80.66% 27.50% 7 4 10%

Ability to mathematically model communication and signal processing systems

5 78.81% 45.00% 7 3.86 27.5%

Ability to design a Monte Carlo simulation for performance analysis of communications and signal processing systems

5 79.93% 27.50% 7 4.36 27.55

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Ability to implement signal processing algorithms with modern hardware NA NA NA 7 4.14 35%

Assessment by Instructor:

Course OutcomesFall 99 Spring 02

Students Evaluated

Assessment Score


Students Evaluated

Assessment Score


Ability to read and critically evaluate research in selected areas of communications and signal processing

5 80.66% 27.50% 14 91% 10%

Ability to mathematically model communication and signal processing systems

5 78.81% 45.00% 14 89% 27.5%

Ability to design a Monte Carlo simulation for performance analysis of communications and signal processing systems

5 79.93% 27.50% 14 88% 27.55

Ability to implement signal processing algorithms with modern hardware NA NA NA 14 99% 35%

Assessment tools: Literature review on designated topic of interest A Monte Carlo simulation design homework assignment Oral presentations explaining a result in the literature they want to challenge or

confirm with a Monte Carlo simulation. (presentations are peer and instructor rated)

Written final report documenting the research and conclusions

Feedback and improvement:Between the two times I have taught this course, I added an additional outcome as a result of responding to an employers survey indicating that they like to see the graduates aware of how to implement the signal processing algorithm they learn the theory on. Therefore, NA is present in the 4th outcome for the Fall 99 class. There appears to be an improvement in the Monte Carlo methods. I have provided better examples and teaching material in the Spring 2002 class, since I was able to build on the material presented in previous classes. I also worked harder with the students to help them find reasonable projects to work on for the class. This may have been the reason for the increase. Overall I think as an advanced topics course I try to cover too much since we have a significant gap in our grad program for signal processing courses. It may best to create an EE631 course as a sequel to EE630 and teach more fundamental concepts where they can focus on intermediate theory required to tackle more advanced concepts.

Sponsored Independent Study CoursesI have taught independent study courses for students with special interests. Enrollment for each course listed below involves 1 or 9 students. The courses typically resulted in

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computer programs, circuits, papers, or lecture presentations by the student, or laboratory exercises, which are used to assess the students’ grade.

Fall 2004EE595 Independent Problems (6 Students)Objective: Design and build an active noise canceling system.

Spring 2004EE395 Independent Problems (6 Students)Objective: Offer the same content as EE462 (electronic laboratory) for student who needed the course to graduate. We no longer offer EE462 every semester, because of reduced teaching resources and the expectation of starting a computer engineering program. This helped students in the transition to get the courses they needed to graduate.

Fall 2003EE595 Independent Problems (1 students)Objective: Design and implement a simulated drum kit through pressure sensing resistors and a PIC microprocessor.

Fall 2002EE595 Independent Problems (9 students)Objective: Implement a series of real-time DSP project involving the Texas Instruments C6000 series chip.

Spring 98EE395 Independent ProblemsObjective: Develop programs to compute spectral parameters from EEG signals from anesthetized humans and correlate changes in parameters to changes in anesthetic gas concentration (funded through HHMI Undergraduate Initiative 1997-1998 Academic Year Research Projects)

Fall 97EE395 Independent ProblemsObjective: Develop programs to process and manage large sets of EEG signals (over 1 Gigabyte of data) over several computer systems.

Fall 96EE595 Independent Problems (2 students)Objective: Implement a real-time statistical spectrum analyzer and deconvolution algorithm on the Texas Instrument evaluation modules for the C26 and C50.

Spring 96

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EE595 Independent ProblemsObjective: Debug and further develop instructional laboratories for the Texas Instrument TMS320C26 and TMS320C50. Labs are available in the web. See my web page and look under DSP lab assignments.

Fall 95EE595 Independent ProblemsObjective: Examine the feasibility of implement an inexpensive image compression board using the TMS320 chip. Project resulted in industrial function through CRMS.

Summer 95EE595 Independent ProblemsObjective: Develop a set of laboratory experiments for learning how to implement FIR and IIR filters on DSP hardware. Experiments were first used in the EE630 course taught in Fall 95.

Fall 94EE595 Independent ProblemsObjective: Design and build a Satellite Receiver

Spring 94EE595 Independent ProblemsObjective: Design digital circuitry to process signals from an ultrasonic wind velocity meter.EE395 Independent ProblemsObjective: Modify an FM receiver to change the band of frequencies it can receive.

Fall 93:EE 595 Independent ProblemsObjective: Do a literature Review of Signal Processing Methods used in MRI, and write a report highlighting the critical issues for future research in MRI signal processing.

Summer 93:EE595 Independent ProblemsObjective: Develop a set of modular C-functions to read data compatible with an ultrasonic data acquisition system and perform simple filtering tasks over two dimensions.EE595 Independent ProblemsObjective: Present a series of lectures that review techniques used in spectral estimation (by student).

Spring 93:EE595 Independent ProblemsObjective: Develop a set of Matlab functions for filtering ultrasonic B-scans.

Fall 92:

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EE783 Special Problems in Electrical EngineeringObjective: Build a PC-based digital signal processing system for analyzing motor currents.EE784 Research Project in Electrical EngineeringObjective: Complete a paper on reluctance motor and build a computer simulator.EE783 Special Problems in Electrical EngineeringObjective: Present a series of lectures on fading channels (by student).EE595 Independent ProblemsObjective: Build a circuit to process ultrasonic signals.EE595 Independent ProblemsObjective: Present a written report on laboratory project for distributed network management systems.

Summer 92:EE595 Independent ProblemsObjective: Write computer program to display ultrasonic images on PC.

Spring 92:EE783 Special Problems in Electrical EngineeringObjective: Complete a paper and computer simulation on nonparametric detection

Sponsored Internships:I encourage students to get as much practical experience as possible to put their learning in perspective. Therefore, I have sponsored four students with internships in national industries through the Office of Experiential Education. These internships are listed under course number EXP396.

Fall 00:Yazzine Herraz: Placement: Kentucky Traffic Signal Division, Frankfort, KY

Fall 98:Jose Rivera. Placement: The Kentucky Network (KET), Lexington, KYSummer 93:Howard Keitz. Placement: GE glass plant, Lexington, KY

Fall 92:Jerry Daugherty. Placement: GE lamp plant, Lexington, KY

Summer 92:P. Gopalakrishnan. Placement: Belcore, Red Bank, NJMark Tran. Placement: GE glass plant, Lexington, KY

STUDENT EVALUATION SUMMARY:

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My student evaluations have been consistently positive over my career ( ranging from 2.9 to 3.9 on a 4 point scale). This is typically equal to or greater than the college average. However, there was a relative dip in ratings between 1997 and 1999. This I believe was more a function of distractions from my increased administrative duties (Interim Chair) and decreased margins in my personal life, rather than something systematic in my teaching style. Both sources of distraction have changed significantly, and my teaching ratings have gone back up. I take most student praise and criticisms seriously as listed in their comments and have accommodated when it felt benefit both the students and profession which they desired to work in. Since 2003 my teaching rating have been above 3.3 college average near 3.1.

ADVISING EVALUATION:

As Director of Undergraduate Studies (DUGS) I am the advisor’s advisor to the department. I advise all students who are transferring in and help new faculty understand the curriculum and their advising responsibilities. I regularly train new faculty and remind old faculty in regards to the curriculum and their advising duties. I have not collected any data to quantitatively assess my performance or the department’s performance in this area. I am not aware of any consistent complaints from the faculty or the students on the way I perform my advising duties as DUGS.

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Appendix A

Outcome Assessment Sheets from Fall 2002 to Present

Courses:EE462GSample outcome map.........................................................................................................25Fall 2002 ..........................................................................................................................28Spring 2003........................................................................................................................29Fall 2003 ..........................................................................................................................30Summer 2004....................................................................................................................31 Fall 2004 ..........................................................................................................................32Spring 2005.......................................................................................................................33

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APPENDIX B

Student Evaluations of Courses and TeachingFrom Fall 1991 through Spring 2006

Following the summary table, the original student evaluations are arranged in reverse chronological order (most recent first) with student comments first and then the numerical ratings.

Table 1. Summary of course taught with Course/Teaching RatingEE101Term Enrollment Value of Course Quality of TeachingFall 2000 92 3.2 3.5Fall 2001 102 3.1 3.4Fall 2002 107 3.2 3.4EE211 Term Enrollment Value of Course Quality of TeachingSpring 02 33 3.6 3.8Fall 01 55 3.7 3.8Spring 01 27 3.8 3.9Fall 00 45 3.5 3.6Spring 00 29 3.6 3.7EE221 Term Enrollment Value of Course Quality of TeachingSpring 05 42 3.3 3.1Fall 98 34 3.4 3.5Fall 97 44 Team Taught 50% 3.0 3.2Summer 97 19 No Evaluation No EvaluationFall 96 41 3.5 3.6Summer 96 19 No Evaluation No EvaluationSpring 96 59 3.3 3.2Fall 95 61 3.2 3.3Fall 94 26 3.5 3.6Summer 94 10 No Evaluation No EvaluationSpring 93 71 3.4 3.6Spring 92 58 3.5 3.5Fall 91 51 3.6 3.6EE222 Term Enrollment Value of Course Quality of TeachingFall 96 44 3.2 3.6EE307 Term Enrollment Value of Course Quality of TeachingSummer 96 40 No Evaluation No EvaluationSummer 95 41 No Evaluation No EvaluationEE380 Term Enrollment Value of Course Quality of TeachingFall 93 41 2.9 3.0Spring 93 47 3.3 3.1

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EE421 Term Enrollment Value of Course Quality of TeachingSpring 98 29 3.2 3.0Spring 97 50 3.1 3.4EE422 Term Enrollment Value of Course Quality of TeachingFall 92 20 3.7 3.7EE462GTerm Enrollment Value of Course Quality of TeachingFall 2006 13 IP IPSpring 2006 20 (lost records) (lost records)Fall 2005 51 3.4 3.5Summer 2005 8 4 4Fall 2004 39 3.5 3.6Summer 2004 15 3.7 3.9Fall 2003 23 3.5 3.6Spring 2003 45 3.5 3.8Fall 2002 18 3.5 3.7EE499 Term Enrollment Value of Course Quality of TeachingSpring 99 8 3.3 3.6EE599 Term Enrollment Value of Course Quality of TeachingFall 2006 15 IP IPSpring 2004 7 3.3 3.5Summer 2003 14 3.7 3.9EE611 Term Enrollment Value of Course Quality of TeachingFall 92 37 3.5 3.7EE630 Term Enrollment Value of Course Quality of TeachingFall 95 11 3.6 3.6Fall 94 14 3.6 3.7Fall 93 9 3.4 3.7EE 639 Term Enrollment Value of Course Quality of TeachingSpring 02 14 3.8 3.8Fall 99 5 3.5 3.5Spring 96 3 No Evaluation No EvaluationSpring 95 8 3.9 3.9Spring 94 9 3.2 3.7

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teaching portfolio 1998kevin d - engr.uky.edudonohue/resume/teaching portfolio 2006.doc · web...

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