About the NSF Project

Project Summary

Overview.

The focal area of this Level I project is Broadening Participation in STEM. This project aims to fill in three gaps in the current state of knowledge about engineering retention and success:

1. lack of knowledge about engineering retention and success characteristics based on interactive, concurrent effects of multiple factors,
   
2. lack of knowledge about engineering retention and success characteristics based on the modeling of variable relations that exist for some but not all values of variables or are different for different value ranges of variables, and
3. lack of knowledge about uncommon engineering retention and success characteristics of “outlier” students who do not fall into common characteristics of engineering retention and success.

This project will employ the new Partial-Value Association Discovery (PVAD) algorithm to identify:

1. common characteristics of engineering retention and success, and
2. uncommon characteristics of engineering retention and success for “outlier” students who do not fall into common student profiles of engineering retention and success,
   based on both individual and interactive effects of various variables covering both partial-value and all-value associations of variables.

Hence, new findings from this project will enrich the understanding and knowledge of engineering retention and success, in comparison with existing findings based on effects of individual variables and all-value variable relations. The intervention with an engineering counseling and tracking program to help students’ development of the newly identified engineering retention and success characteristics will be developed and implemented. The intervention effects on students will be observed and analyzed to validate the new findings of engineering retention and success characteristics. The identification and validation of new engineering retention and success characteristics will provide guidelines to help more students achieve engineering retention and success across the nation, thus broadening the participation of more students in engineering fields. 

Intellectual merit.

This project will produce new knowledge about common and uncommon characteristics of engineering retention and success covering both individual and interactive effects of various variables and both partial-value and all-value associations of variables.  Hence, this project will fill in the following three gaps in the current state of knowledge about engineering retention and success.

• Lack of knowledge about uncommon engineering retention and success of “outlier” students who do not fall into common characteristics of engineering retention and success
• Lack of knowledge about common and uncommon characteristics of engineering retention and success based on interactive, concurrent effects of multiple factors,
• Lack of knowledge about common and uncommon characteristics of engineering retention and success based on the modeling of both partial-value and all-value associations of variables,

The application and validation of the new PVAD algorithm using large-scale education data in this project will facilitate the impact of the PVAD algorithm on data mining in many application fields including the education field.

 

Broader impacts.

Both common and uncommon characteristics of engineering retention and success and the intervention of the engineering counseling and tracking program based on those characteristics will define various models and paths for more students with various conditions and diverse characteristics (e.g., educational and social backgrounds, and skills) to achieve engineering retention and success, and thus broaden the participation, retention and success of students in engineering. This will promote a healthy development and growth of human resources in the society, thus benefiting the public good and contributing to economic, social, and cultural vitality as well as health and well-being of local, regional and national communities. The identification and validation of new engineering retention and success characteristics in this project will provide guidelines to help more students achieve engineering retention and success across the nation, thus broadening the participation of more students in engineering fields.

 

Published papers

Papers published for this project are listed here.

 

Dataset.

Three sets of data were collected in this project. Details are given here.