— By fitting a linear equation to observable values, linear regression determines the relationship between two variables. The Department of Education enrollment data in the Philippines, specifically in the School Division of Batangas, is needed to produce modules. The data collected is from the division office, where data cleaning was applied. Deep Learning, Decision Tree, Random Forest, Gradient Boosted Tree, Support Vector Machine, and Linear Regression were used to perform the prediction, and linear regression performed the best with an absolute value of 14.465 and a relative error of 84.81%. Keywords— Prediction, Information Management, Linear Regression, Cloud Computing, LDM

The use of Linear Regression in predicting enrolment has been shown to be beneficial, although it varies with various datasets and attributes; varying weights of the correlation of the attributes can be discarded if they do not impact the prediction. Data collecting had grown since prior investigations, resulting in a more complicated dataset with many varieties. As a result of the data being created by multiple clerks, cleaning and combining proved tough; nonetheless, the fundamental parameters remain intact. Different algorithms were examined but Linear Regression obtained the highest accuracy with a 12.398 percentage for the absolute error and a root mean squared of 26.936 to create a tangible model to anticipate the enrolment of Region IVA CALABARZON in the Philippines. This demonstrates that it was 2.067 percentage points more than the prior research.

The effect of department heads' transformational leadership behavior and ICT integration of faculty members on research productivity at Bulacan State University utilized three standardized instruments. The first instrument on transformational leadership is highly reliable as evidenced by the Cronbach's alpha of .91. The second instrument on ICT integration was tested by [6] for its validity and reliability. Meanwhile, the questionnaire on faculty member's research productivity was adapted from [7].The major problem of the study was to appraise the impact of transformational leadership behavior and ICT integration on the research productivity of faculty members at Bulacan State University. The outcomes showed that for every unit increase in holding high performance expectations and providing intellectual stimulation can produce a .356 also .674 growth in faculty members' research efficiency. Factors such as "nature of school leadership", "modeling behavior", "providing individual support", and "strengthening school culture" likewise contributed to faculty members' research production but not to a significant level. The 10.31 F-ration obtained was found crucial with .05 alpha shows that school heads' transformational leadership behavior formed a very substantial set of predictors for the research production of faculty at Bulacan State University.

The primary concern of this research study is the acceptance of a course managing system and its significant effect on students’ learning in the graduate school. This study used the descriptive correlational method that make use of validated questionnaire as a source of data-gathering tool, demonstrated by extensive documentary analysis. The target client of the study were 225 graduate school students and 15 graduate school professors. The results were processed using the Statistical Packages for Social Sciences (SPSS) and the data were evaluated and interpreted using regression analysis in determining the acceptance of integrating a course managing system and its influence in the teaching and learning of students in the graduate school department. Using the said method, the outcomes of the study have shown that students from the graduate school is relatively ready to face the challenges of the fourth industrial revolution as proven by the utilization of cybergogy and level of acceptance of the course managing system. The academic profile of graduate school students demonstrates significant learning because of their efforts to do well in their academic subjects. In this study null hypothesis, states that the acceptance of using a course managing system does not significantly affect students’ learning in the graduate school is rejected. The difficulties presented if recognized could lead to many opportunities design for innovative approach in teaching and learning. The implications derived based in the findings of the study are significant observations that can be considered in further advancement of the quality of teaching and learning in the graduate school. Keywords: Integration of Course Management, Technology-Based Education, Online Learning,