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Joseph P. Messina

GEO826: Geocomputation
Honorable Mention - Enhanced
“Technology enables transition from static to dynamic”
- Joseph P. Messina -

GEO826 transitioned from static and traditional to dynamic and web-enabled. The instructor converted every PowerPoint lecture (except one) into a Mathematica web enabled notebook that was used for live lectures and student assignments.

What this means is that every embedded programmatic example was dynamic, using computable document (CDF) technology. Instead of providing a limited set of examples in text form, the student now could dynamically alter the programs or run the demonstration projects from any CDF enabled (free-download) browser. This dramatically enhanced programming fundamentals comprehension.

The students unanimously liked the software and mechanism for delivery. One significant change was that the students were now expected to write their entire lab assignments within the dynamic Mathematica notebook structure. This afforded the instructor an immediate test of successful completion and easy assessment of embedded work.

The computable document format developed with rich and dynamic content allowed for truly interactive learning objects and direct student interaction. The instructor and students can change any parameter and instantly visualize the impact. All selected their respective hometowns and explored the “neighborhood graph” models using familiar places.

The natural language processor also proved very useful for student learning. There is no programming prerequisite for the course, and in prior semesters the traditional geographic information programming language (IDL) was a contributing factor to all who fell behind. After the conversion to Mathematica, the amount of class time devoted to teaching programming was reduced by ~50% and that time could instead be spent teaching geocomputation.

A third primary advantage of this transition was that the instructor was able to increase the sophistication and total content of the course. He added new lectures, notably one on graph theory and another on data mining, that there had not been time to cover in the past.

The most important outcome was that for the first time no student fell significantly behind. Performance gains by the students, none of whom had any prior Mathematica experience, were substantial. All of the students meaningfully advanced during the semester.

The instructor’s ultimate goal with this course and software combination is to make it largely self-contained and modular where a student, particularly a non-traditional learner, might be able to reconfigure the course elements and still gain equivalent proficiency and learning outcomes as traditionally trained students.