Teaching

“If you are not confused, you are not paying attention” — Tom Peters

Teaching Portfolio

In August 2019, I was awarded a 2019 UT Regents’ Outstanding Teaching Award. I am happy to share my application to this award.


Resource: It can feel overwhelming to become a college student and time management skills can come in handy.  For all students in need of help regarding time management, please take 5 minutes to visit this link to a time management diagnostic tool.


Courses I teach: Over the years I have spent at UTEP (since 2003), I have taught a number of courses. At the undergraduate level: Introduction to Computer Science, Elementary Data Structures, Automata, Programming Languages, Problem Solving. At the graduate level: Algorithms, Logical Foundations of Computer Science, Algorithms. More recently, I have focused my effort on the introductory CS courses, taking a close look at what we teach and how we teach it, in a constant effort to enhance our students’ success and in particular, to increase retention. I have also designed two courses in problem solving and a 1CH+2CH sequence in discrete structures (formerly 3CH discrete math). Below, you can find the list of courses, per semester, that I have taught recently.

All of the information related to my courses, including material, assignments, etc., are available on piazza.

Fall 2019:

Maymester 2019:

Spring 2019:

Fall 2018:

Spring 2018:

  • CS1301/1101 — Intro to Computer Science
  • CS5303 — Logical Foundations of Computer Science

Fall 2017:

11/17/17 presentation

  • CS1301/1101 — Intro to Computer Science
  • CS1190 — Problem Solving: offered twice in fall 2017 (2 times 6 weeks)
  • Wintermester: CS1101 — Intro to Computer Science

Spring 2017:

  • CS1301/1101 — Intro to Computer Science

Fall 2016:

  • CS1401 — Intro to Computer Science: TR 10:30am – 11:50am (information available on piazza.com for students of this course)

Summer 2016: Summer I (June 6 to July 1, 2016)

  • Article for Dr. Kreinovich’s class: here
  • CS4365/5314 — Topics in Soft Computing — Problem Solving and Algorithm Design: MTWRF 7:00am- 9:10am

This course is intended to enhance students’ problem solving abilities. Through problem solving, they will learn an array of general strategies for algorithm design, they will practice performance analysis and develop critical thinking skills. They will review and apply in context notions about data structures, algorithms, discrete math, and logical foundations of computer science.

Required Textbooks: 1/ Algorithmic Puzzles, by Levitin & Levitin. Oxford Press; 2/ Problem Solving Through Recreational Mathematics, by Averbach & Chein. Dover.

Spring 2016:

  • CS1401 — Intro to CS: TR 10:30am- 11:50am (information available on piazza.com for students of this course)

Fall 2015 and prior: see Teaching Archives


General information:


“Computer science is no more about computers than astronomy is about telescopes.” E. W. Dijkstra
“There is no “have to” in the journey of life. You don’t “have to” do anything… nothing, nada, zip, zilch. You can either choose to do it or you can choose the consequences.” Pat Croce

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