A Value-Based Approach for Quantifying Problem Solving – UA09-TLC

Analysis of student data indicates, according to one definition of learning styles, that global learners respond more favorably to an online, open-ended learning environment than sequential learners. Industrial engineering students were observed before, during, and after engagement in an online forecasting module. Simple ordered logistic regression models of attitudes were found to be consistent functions of the extent to which students are considered to be global versus sequential learners. Furthermore, significance can be observed even when controlling for additional factors such as gender, other learning style dichotomies, preliminary confidence about forecasting knowledge, and problem solving performance.

Sponsor:

The Learning Chameleon

Research Team:

Edward A. Pohl

Universities Involved:

University of Arkansas

Start Date:

08/15/09

End Date:

08/14/11

Summary:

Problem solving is a critical skill for all engineers, and opportunities for accurately assessing as well as improving student performance in this area would benefit the student as well as the profession. Technology developed by the Learning Chameleon provides such an opportunity in engineering problem solving assessment and learning.