Assessing students' learning and decision-making skills using high performance web -based computational tools

2005 2005

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Abstract (summary)

Using web-based computational tool in classrooms in conjunction with advanced computing models provide the opportunity for students to learn large scale processes, such as state, regional, and global environmental issues that are difficult to incorporate into student learning exercises with present basic models. These tools aided in bridging the gap between multi-field scale models and enhanced student learning. The expectations were that students would improve their decision-making skills by solving realistic and large scale (multi-field conditions) environmental issues that were made possible through faster computation time, larger datasets, larger scale (multi-field), and predictions over longer time periods using the Century soil organic carbon model. The Century Model was linked to a web-based series of functional pages through which students could run the model through. In this project, 239 undergraduate students' learning and decision-making skills using high performance classroom computing tools were assessed. Among the many Century Model parameters, the students were able to alter four variables (climate, crop, tillage, and soil texture). Students were able to simulate several scenarios simultaneously. The results of the study revealed that pretest for the four courses combined was found significant (P < 0.05), meaning that the pretest was a major contributor to their increased posttest score. Although, the scenario scale (multi-field conditions vs. single field conditions) factor was not statistically significant, the students completing the multi-field scenario assignment scored higher on the posttest and also had a higher increase in points from pretest to posttest. Overall, these results revealed that the tool provided had a positive impact on the students' learning which was evident in their enhanced pretest to posttest score and also their perceptions from the written evaluation they provided. Most students felt that the project was a good learning experience and aided in enhancing their decision-making skills. In the long-term retention study, results showed that the students increased their knowledge as well as enhanced their decision-making skills throughout the project. Written evaluations as well as oral responses displayed that they learned an abundance of knowledge while completing the project and that their decision-making skills were enhanced due to the modeling tool provided.

Indexing (details)

Environmental engineering;
Science education
0775: Environmental engineering
0714: Science education
Identifier / keyword
Education; Applied sciences; Environmental modeling; Soil organic carbon; Web-based
Assessing students' learning and decision-making skills using high performance web -based computational tools
Martin, Akilah
Number of pages
Publication year
Degree date
School code
DAI-B 66/10, Dissertation Abstracts International
Place of publication
Ann Arbor
Country of publication
United States
9780542352607, 0542352605
Mohtar, Rabi H.
Purdue University
University location
United States -- Indiana
Source type
Dissertations & Theses
Document type
Dissertation/thesis number
ProQuest document ID
Database copyright ProQuest LLC; ProQuest does not claim copyright in the individual underlying works.
Document URL
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