Course Evaluations

Every class includes an evaluation of the students by the instructor and an evaluation of the instructor by the students. This page presents summaries of these two evaluations to help you understand what to expect when taking this course. For the evaluation done by the instructor the grade distribution is presented. The evaluation done by students includes a group of numeric ratings and a set of written comments.

Past grade distributions

The stated grading policy for the class is that everyone that wants an A, gets an A. Despite this clarity of purpose, some students get anxious and complain about their homework grades and the fact that it is unusual to have classes graded in an absolute scale. In the previous version of this course 71% of students got an A (between A+ and A-), 15% got Bs, and 10% got Cs. There was one D and 1 student failed the course. The complete grade distribution follows.

A+	0	0%	B+	1	2%	C+	3	6%	D+	1	2%
A	21	44%	B	4	8%	C	1	2%	D	0	0%	F	1	2%
A-	13	27%	B-	2	4%	C-	1	2%	D-	0	0%
Total As	34	71%	Total Bs	7	15%	Total Cs	5	10%	Total Ds	1	2%	Total Fs	1	2%

It can be observed that, consistent with stated policy, a majority of students got As in the class. Of course, wanting an A means that you do your work and learn. The grades above are not a consequence of lax grading, but testament to the fact that the students at Penn are hard working, smart, and well qualified.

Numeric evaluations of course and instructor

Students have a generally positive opinion of the class. Most believe they have learned a good deal of useful material and recommend the class to peers. There is a uniform complaint that the work demanded is excessive, and that grading is too tough. Future iterations of the class will include measures to reduce the amount of work required. However, note that 1 credit unit is supposed to be around 10 hours per week of work. I do not believe that grading in the class is tough, since a clear majority of students get excellent and well deserved grades. The student evaluations follow.

	Grade (out of 4)	Poor (0)	Fair (1)	Good (2)	Very Good (3)	Excellent (4)
Quality of the instructor	3.36	2 (4%)	0 (0%)	3 (7%)	15 (33%)	25 (56%)
Quality of the course	3.16	2 (4%)	1 (2%)	5 (11%)	17 (38%)	20 (44%)
Would you recommend this course?	3.71	1 (3%)	0 (0%)	1 (3%)	5 (13%)	31 (82%)
Instructor’s ability to explain material	3.38	0 (0%)	1 (3%)	4 (10%)	13 (33%)	21 (54%)
Instructor’s ability to stimulate interest	3.36	0 (0%)	2 (5%)	4 (10%)	11 (28%)	22 (56%)
Instructor’s accessibility	3.31	0 (0%)	2 (5%)	5 (13%)	11 (28%)	21 (54%)
Amount learned in this course	3.37	0 (0%)	1 (3%)	2 (5%)	17 (45%)	18 (47%)
Difficulty of this course	3.38	0 (0%)	0 (0%)	2 (5%)	20 (51%)	17 (44%)
Amount of work required	3.72	0 (0%)	0 (0%)	1 (3%)	5 (13%)	31 (82%)

There were 49 students registered for the class of which 46 completed this course evaluation. A total of 31 students attended almost all of the lectures, 9 students attended around 2/3 of the lectures, 7 students attended about half of the lectures, and 2 students never showed up in class. I do not know in which direction absentees skew the evaluation.

Comments from students

Comments below are attached to the numeric evaluations received at the end of the semester. I only attach the commentaries from the previous year, so if you took this class prior to 2011 your comments will not appear here. These comments have not been edited, selected, or censored.

A very useful course teaching the students Markov Chains and Gaussian processes in great depth. However, I believe that because there are a lot of topics that the end of class is a bit rushed and there is a very limited time for students to learn that many topics. For example, Fourier Analysis at the end of the course was not a good idea because most of the Systems Engineering students do not have a background in Fourier. A background course before this should be offered that gives a background to students on Fourier and Laplace transforms.
Difficult, but worth the work.
The course was very interesting from a CIS perspective, since the material covered has such broad applicability; many interesting applications are examined such as Google’s PageRank. Some information about the algorithmic complexity of the modeling methods used throughout the course would be interesting but might be beyond the course’s scope. From a psych/neuroscience perspective the material is also very interesting and has many relevant applications (e.g. in modeling decision making, neuronal activation etc) even though these weren’t mentioned in the course.
I thought the final section of the course seemed cut a bit short–covering an example application would be very helpful in reinforcing concepts.
While there is an emphasis on learning, there is still a significant jump between the homework/midterms to the closed-note final. While the concepts were in place for the final, the applications to specific examples were not necessarily there as a result of the practice we had with these applications. Overall, one of the best courses in ESE, etc.
First half of homeworks are WAAAAY too time intensive. Spent >10 hrs each. Even though Ribeiro is flexible with late submissions.
The material and presentation of material within this class are both awesome. I’ve found it rare to have a good professor and good subject matter within the same class, but this class easily achieves it. The problem sets are a little long with senior design and the job search, but I think it would have been quite manageable if I had taken it junior year.
Lot of MATLAB coding involved in this class. Intimidating class at first, but tools and skills acquired throughout the semester are very useful.
Great course that opens eyes to a whole new way of modeling systems. One area for improvement is to ask students themselves to think about how they can model a system and design it because everything in the class comes with parameters pre-set for the most part (i.e. figure out the constant, c1, for the hazard rate empirically given data)
This class was very challenging but also my favorite systems engineering class.
I really wished this professor would stop cold-calling on students! He’s an awesome guy and 90% of the students called on wouldn’t know the answer so you could always say “I don’t know”, but really, at 10 in the morning I’m not fully awake! Beyond that the course is great. Homework is lengthy, and given once a week without exception, but you can turn it in late at no penalty. Students coming into this course need a solid programming background, because Matlab is used extensively and no introduction is given. I wouldn’t recommend taking this and 210 at the same time as they are both intense courses. Homework answers are posted online, which is helpful to understand what the question is asking.
The course is very useful for frankly anyone. It is work intensive but the instructor is very helpful. I learnt a lot from the course and enjoyed it too.
ESE 303 covers a lot of material in a short amount of time. In order to be prepared for this class, it is important to have a very strong background in probability. Some experience in MATLAB is also very important; the MATLAB learning curve for this class is too steep otherwise. The most useful parts of the course involved the practical applications of the material we learned – modeling cheical reactions, looking at stock pricing, analyzing queues, and ranking nodes in networks. As a Wharton student with essentially no engineering background, I found the class to be very accessible. (I would encourage my colleagues who are interested in statistics to take it.) There was one topic, however, that I felt completely lost on: linear filtering. No background was given on this topic, so I still have essentially no idea what that lecture was about. I found the midterm to be very fair, and I thought the homeworks were very useful. My major complaint is with the final exam. The exam itself was fair, but preparing for it was difficult because there were NO PRACTICE PROBLEMS. I have never encountered a quantitative course that did not at least provide a few example problems to help students prepare for the exam. Essentially the whole class went into the final blind, leading to our “dismal” performance. If practice problems had been provided, this course would have been near perfect.
A very good and engaging instructor. Only flaw that I can state would be the typos in the lecture slides, which are not corrected.
Professor Ribeiro is a great professor who genuinely wants his students to do well. His love for the course enables a course with material that could inevitably dry to be much more interesting and exciting. Professor Ribeiro is truly one of the best professors I have encountered at Penn.
Excellent professor. I would only request that he not try to use scare tactics to intimidate the lesser motivated students. Doesn’t seem to be effective and puts unneccessary stress in email communication.
An extraordinary professor. He has placed an immense amount of effort into producing this course, and his one goal is for students to learn. There is certainly a focus on learning rather than on grades. This is an example of how courses should be taught.
Probably one of the best professors I have ever had. Too much good stuff to say. Literally every professor should be like Dr. Ribeiro.
The best professor that I have had at Penn.
I love the guy. He communicates the material in a great manner including lots of funny turns of phrase like “lipstick on a pig” that are amusing. His references to his daughter and his self-deprecating demeanor break up the challenging lecture material. I like that he calls on people to keep them paying attention, and it makes the class more interactive and fun.
The homeworks took too long. There could have been less homeworks to balance the workload. If u missed even one class you would be lost. The professor should recap the previous class at the beginning of the lecture.
He should be teaching more class. ESE needs more professor who cares as much about teaching students as he does.
Excellent Professor. Very fair with grading and deadlines for homework assignments. Very understanding when it comes to class/homework/assignment conflicts.
Excellent instructor who is passionate about the material and able to identify with the student, though the joking rudeness/sarcasm passes bearable bounds at times
Alejandro has been the best professor I’ve had in the engineering school thus far. The time and effort he puts into each class is evident and he does a great job communicating the subject material. His sincerity and enthusiasm for the course made lectures enjoyable and engaging.
Professor Ribeiro is extremely passionate, well prepared, and engaging professor . He articulates the information well and makes it interesting.
Hilarious, although sometimes it’s completely unintentional. He’s fairly laid back as a professor and tends to joke that he’s condescending to his students – but really, the man is so smart that I could usually only following what was going on when he was being “condescending.” Also, don’t play on your laptop or read the newspaper in class because he will call you on it!
Extremely good professor. Very intelligent and has a great sense of humour. Best part is that he understands that the material is tough and the amount of work required is high so he gives ample time and opportunity to make up for it. He is very flexible in this regard and makes the class enjoyable. In addition, he makes an effort to get to know everyone in class and that makes the class very interactive. Moreover, he loves soccer just like me so that’s another thing which makes him cool.
Would be nice if typos in slides were corrected. Otherwise. Prof. Ribeiro was a great instructor, and cared a lot about the students in the class. Was flexible about handing in homeworks, and overall seemed to want us to actually know the material.
Great instructor, stimulates a lot of interest in the class, even though the class is very early, every time I woke up I looked forward to going to a class taught by him
Professor Ribeiro is an incredibly dedicated instructor. The level of work he puts into the course – preparing very detailed lecture slides, writing homeworks and homework solutions, communicating with the class very frequently, etc. – is greater than I have ever seeen in my time at Penn. It is evident that Professor Ribeiro cares about his students and their success. My one complaint about Professor Ribeiro is that his lectures were often too conceptual and not practical enough. We rarely did computational examples in class and, were it not for the homeworks, we would have had no sample problems for the midterm and final. Spending less time on proofs (that were way above our level and that we didn’t really need to know anyway) and more time on sample problems would have made the class better.