OR/MS Today - February 1998 - Issues in Education

February 1998

Issues in Education:
Professor Liebman, Will This Be On the Test?

By Judith S. Liebman

For years I assumed that students asking "Professor Liebman, will this be on the test?" wanted to learn only material that would be on a forthcoming examination. I have concluded that many students lack confidence in their ability to learn and are overwhelmed by the deluge of material .

Now, for every classroom session, reading assignment and homework assignment, I give the students an explicit list of "learning objectives" — the concepts important for them to learn. This list establishes a framework into which the students fit bits of knowledge as they encounter them. A side benefit is that the list also forces me to keep my classroom sessions on target. Rather than providing a brain dump of all that I know and enjoy about a particular topic (an unfortunate practice of mine), I now focus on the listed concepts. If I am lecturing, I put the list on the board and check off each concept as I discuss it.

Does this mean I never discuss side issues or provide students with reading assignments on related material? Of course not. Now, however, students no longer become lost in a boundless forest of knowledge. The lists of learning objectives serve as useful guides. Talented, energetic students explore side pathways. Struggling students stay on the main trail.

I have successfully used this approach in our first undergraduate operations research course in an industrial engineering program.. The course introduces both deterministic and stochastic operations research and covers a lot of ground in a short time period. I have taught the course in two formats: a lecture format and in a format with active learning groups replacing lectures. In course evaluations at the end of the semester, the students have rated the learning objective lists highly for both formats.

For this course, the primary instructional goal is to have students learn the fundamental concepts of operations research: basic definitions, how to build simple models and how to apply existing algorithms. In order to accomplish this goal, the regular homework problems cover the fundamental concepts and provide opportunities for simple modeling and algorithmic computations. In my experience it is counterproductive to include extremely challenging problems in the regular homework of an introductory undergraduate course. If an assigned problem is too hard, students spend most of their time struggling with that problem and not enough time on learning and using the fundamental concepts.

The course begins with a two-hour classroom session introducing operations research and modeling and graphical solutions to linear programming problems. I will illustrate my use of learning objectives by discussing this session. The assigned reading before this session covers several chapters in the text. The explicit objectives provided to the students for the reading assignment (and for the class session and homework that follow) are to learn:

The basic phases of an operations research study (defining the problem, gathering data, formulating a model, etc.)
Basic definitions: decision variables, objective function, constraints, parameters, algorithm, optimal solution, satisficing, heuristic procedure and feasible region.
The algebraic representation of a linear programming model.
The translation of a linear programming word problem into the algebraic model.
The graphical solution procedure for two-variable linear programming problems.

The assigned reading for this session also covers many other important and interesting topics, including the origins of operations research and a discussion of the impact of operations research. Definitions that appear in the reading assignment but are not in the learning objective list for the first session include sensitivity analysis, post-optimality analysis, sensitive parameters and decision support systems. Reading assignments often include material that is nice to know, material that will be covered later in more detail and material not very important, given the scope of the course. Learning objectives identify for the students which material is important at the moment.

Expectations for student performance (the level of achievement associated with a grade of A, B, etc.) need to be explicit. Recall that the primary objective for my introductory undergraduate course is that students attain a basic understanding and appreciation of operations research. A student can achieve an A if they demonstrate that they have learned at least 90 percent of the basic concepts, a B if they have learned at least 80 percent of the basic concepts, etc.

In most graduate courses, the primary course objective is to seek knowledge beyond the fundamental concepts. A possible grading approach assigns a grade of B, rather than an A, to students who learn 90 percent or more of the basic concepts but do not demonstrate sufficient additional competencies.

In summary, we should tell undergraduate and graduate students explicitly what we expect them to learn. What we expect students to learn should be based upon the instructional goals for the course. Expectations for a course introducing students to operations research should be quite different from expectations for a course providing doctoral students with advanced research skills. Finally, instructional goals should have a greater influence on how we evaluate student performance.

Judith S. Liebman is a professor in the department of mechanical and industrial engineering at the University of Illinois at Urbana-Champaign. She can be reached via e-mail at jliebman@uiuc.edu

This is a regular column sponsored by INFORMED, the INFORMS Forum on Education. If you wish to contribute an article to this column, contact Armann Ingolfsson at armann.ingolfsson@ualberta.ca

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