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Accelerating, Connecting, and Evaluating Student Success

Graduate #58
Discipline: Computer Sciences and Information Management
Subcategory: Computer Science & Information Systems

Wai Yai Elsa Tai - University of Texas at El Paso


Increasing enrollment and retention in science, technology, engineering, and mathematics programs has become a national priority and has given rise to a number of initiatives. One challenge is that initiatives are typically discipline specific with little interaction and complimentary efforts outside of the sponsoring department or college. Such isolation can hinder data discovery, data integration, data analysis, and learning from related initiatives. The goal of this research is to establish a framework for retrieving, discovering, integrating, and analyzing data collected by or related to student success initiatives across campus. There is a collaborative effort with Virginia Tech on the use of digital library approaches to assist with integration and dissemination challenges associated with disparate data. The long term goal is to extend the framework that will learn and make recommendations regarding evaluations, policies, metadata standards, and other relevant information related to student success. This work presents the methodology used to address challenges faced in this problem: data inconsistency, data security, data integration, and usability. Use case and class diagram modeling techniques are used to elicit entities relevant to student success and their respective relationships. These techniques assist in the discovery of data inconsistency, data privacy and confidentiality issues, and the means to integrate data from disparate sources. Prototyping, scenarios, and walkthroughs are used to capture behaviors of and knowledge from stakeholders with the goal of improving user experience. Analysis of the use case and class models illustrate what data is discoverable, inferable, and lacking. It also leads to the discovery of redundant data being stored in various data sources. Analysis of the captured behaviors and knowledge yield what a user-centered interface should look like and how it should function so that it will be efficient, effective, and provide ease of use from the stakeholders’ perspective. The work yields a prototype system that allows for registration of student success initiatives and activities on campus; discovery of student success initiatives and activities, as well as associated documentation; resource sharing; impact analysis of an activity or collection of disparate activities on student success; and report generation. Future work includes continuous validation and verification of the framework, further investigation into the expressive power of queries handled by the analytical component, and the construction of a recommendation engine.

Funder Acknowledgement(s): This student is supported by NSF grant HRD #1242122 awarded to CREST-funded Cyber-ShARE Center of Excellence at the University of Texas at El Paso. This student is supported by NSF grant DUE #0963648 awarded to I3: A Cyberinfrastructure and Communication-Based Model to Foster Innovation that Broadens Participation in STEM Fields through Institutional Integration.

Faculty Advisor: Ann Gates, agates@utep.edu

Role: I am the primary researcher. I created the models, performed analysis on the models, and created the prototype system.

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This material is based upon work supported by the National Science Foundation (NSF) under Grant No. DUE-1930047. Any opinions, findings, interpretations, conclusions or recommendations expressed in this material are those of its authors and do not represent the views of the AAAS Board of Directors, the Council of AAAS, AAAS’ membership or the National Science Foundation.

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