Pedagogical Pattern #3
Lecture-Examples-Activity-Student Presentation-Evaluation

(Version 2.0)
Martin L. Barrett
Department of Computer and Information Sciences
East Tennessee State University
Box 70711
Johnson City, TN 37614-0711 USA
barrettm@etsu.etsu-tn.edu

Intent:

To introduce class modeling.

Motivation:

Few students in an introductory class have experience with data modeling. When presented with a modeling task, their main problem is where to begin. Some introductory instruction followed by group work and evaluation can provide a framework for modeling.

Applicability:

The pattern is used to introduce class modeling. It can be reused as students gain more experience for high level program design and implementation.

Structure:

Lecture: An overview of class modeling using language-based recognition techniques, followed by ratings of importance and by classification, is given in a short lecture. Natural language-based recognition translates certain parts of speech into candidate classes, objects, methods, and attributes.

Examples: Several example analysis models are done with the whole class, with discussions of other possible choices and rationales given for the decisions made. Brainstorming is used for data gathering, followed by analysis, and finally an evaluation of the proposed solution. This method is based on entity-relationship modeling as done in the Shlaer-Mellor methodology.

Repeated Activity: Students work in a small group setting. Several analysis problems are used. Each consists of requirements statements for a real world problem. The group must work out a reasonable class structure with the methods used in the examples. Again, emphasis is on brainstorming for the data and the proposed class structures. As students gain experience with the method, more complicated problems using more complex class relationships can be used.

Student Presentation: One student from each group presents her/his group's solution, including justifications for each decision. Only one sample answer to each problem is given unless a group feels its answer is significantly different from the presented answer. Students analyze and critically evaluate the proposed solutions.

Evaluation: The entire class, led by the instructor, discusses each solution and suggests possible alternatives. The following are among the points to evaluate: the translation from words to OO entities; the relative weighting of importance of the entities; the relationships among the entities; the level of detail of the model; and the feasibility of the proposed solution.

Consequences:

This pattern:
  1. Gives students a low-risk method for proposing solutions to analysis problems through brainstorming and repeated problems.
  2. Emphasizes analysis as a group activity.
  3. De-emphasizes implementation as the main programming activity.
  4. Provides students with opportunities to present and defend their work.
  5. Exposes students to other's solutions and thoughts on similar problems.

Implementation:

  1. Instructor needs to encourage full participation in group activities.
  2. A good set of problem specifications must be developed. They may include non-computing real world problems. However, their scope should remain small enough to be tractable.
  3. Class time for this activity must be allocated from other activities; in particular, this activity, as will most small group activities, will take more time relative to the outcomes gained than lecturing on the same material.
  4. The activity's emphasis is on data modeling and class/object relationships at the expense of modeling control, timing, and algorithms. Other activities must be used to cover this material.

Example Instances:

This pattern has been used to teach:

Resources Needed

None.

Related Pattern:

LASD


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