A-Decision-Support-System-for-Managing-Behavioral-Patterns-of-Faculty-Members-Engagement-in-Research-Activities-Using-Data-Mining-Technique.pptx

Capstone project presentation

1. A Decision Support System for Managing Behavioral Patterns of Faculty Members' Engagement in Research Activities Using Data Mining Technique

2. Rationale Decision support systems (DSS) have gained attention for their capacity to analyze vast amounts of data and aid decision-making. Alfsai (2023) points out that data mining techniques can offer universities and academic institutions valuable insights into the research engagement of their faculty members when used in decision support systems. Consequently, it can result in enhanced research outcomes and informed decision-making. The RDET office of Isabela State University Cauayan Campus oversees the research and development programs and projects, including planning, implementation, monitoring, and evaluation. It offers technical support to faculty members for their research endeavors. This study aims to develop a predictive model using the Research and Development, Extension and Training (RDET) office records of Isabela State University Cauayan Campus faculty members' research engagement data. The model will serve as a decision support tool for the system, aiding in decision-making. Implementing a decision support system that utilizes data mining techniques to manage faculty members' research engagement patterns provides numerous advantages. This study aims to identify the factors that affect faculty members' engagement in research activities, aiding administrators and decision-makers in their understanding of the issue. The system can employ data mining techniques to scrutinize data from diverse sources, including research grants, publications, and other sources. This can aid higher education institutions in identifying the determinants of faculty members' research engagement and devising measures to enhance it.

3. Objectives Identify the primary factors and barriers affecting faculty members' engagement in research activities within the institution. Develop a predictive model to evaluate faculty members' research engagement using their profile information, facilitating precise evaluations of their potential contributions. Assess the effectiveness of the decision support system in improving faculty members' research productivity and engagement through a comparative analysis of pre-and post-implementation data and; Evaluate the extent of compliance of the system based on the ISO 25010 Software Quality Standard in terms of: 4.1 functional suitability; 4.2 performance efficiency; 4.3 compatibility; 4.4 usability; 4.5 reliability; 4.6 security; 4.7 maintenance and; 4.8 portability.

4. Scope and Delimitation This research will focus on the behavioral patterns of faculty members' engagement in research activities and the development of a decision support system (DSS). The study will be conducted at the Research and Development, Extension and Training (RDET) office of the Isabela State University Cauayan Campus and include faculty members from various disciplines. The research will cover the identification of barriers to research engagement, the development of a framework for a DSS, and the evaluation of the effectiveness of the system in promoting research engagement among faculty members. This research will not include an in-depth analysis of the specific research activities of faculty members or the quality of their research output. Instead, the focus will be on the factors that hinder or facilitate research engagement and the development of a decision support system. The study will also be limited to academic institutions and may not be applicable to other settings, such as industry or government organizations. Furthermore, the study will not include an analysis of the financial or economic aspects of the DSS implementation.

5. Conceptual Framework

6. Agency/Respsondents The study will be conducted at the Research and Development, Extension and Training (RDET) office of the Isabela State University Cauayan Campus and include faculty members from various disciplines. The RDET office is responsible for the planning, implementation, monitoring and evaluation of research and development programs and projects. It also provides technical assistance to faculty members in their research activities. This research aims to develop a decision support system within the agency to evaluate faculty members' challenges and restrictions in participating in research activities. The system intends to provide significant conclusions and recommendations using data mining techniques, allowing for a better understanding of faculty members' research activity. This research project aims to increase the overall efficacy of managing faculty members' research activities, eventually leading to enhanced research outputs and productivity.

7. System Architecture

8. System Features Predictive Analytics: Utilize predictive analytics to forecast faculty members' future research engagement and identify potential areas for improvement. Visualization Tools: Create intuitive visualizations and dashboards to present research engagement patterns and facilitate decision-making processes. Intervention Strategies: Generate insights to develop intervention strategies and support programs to enhance faculty members' research engagement and productivity. Faculty Performance Evaluation: Analyze and evaluate the engagement of faculty members in research activities based on their behavioral patterns.

9. Sample GUI and Database Tables

10. THANK YOU!