Research Interests:
With the advent of technology, learning becomes more accessible. With the pandemic brought about by Covid 19, the educational system in the Philippines shifted from traditional face-to-face to online learning. Not being prepared for the... more
With the advent of technology, learning becomes more accessible. With the pandemic brought about by Covid 19, the educational system in the Philippines shifted from traditional face-to-face to online learning. Not being prepared for the sudden shift, many students are being affected. In this study, significant factors affecting students' e-learning are determined. Exploratory Factor Analysis (EFA) was used to determine the factors that affect University students' e-learning. This statistical technique used to reduce data to a smaller set of summary variables and investigate the phenomenon's underlying theoretical structure, and determine the form of the variable-respondent relationship. Data sets were gathered through Google Form with twenty-two (22) observable variables. A subset of the entire data is the factors affecting students' e-learning activities. Based on the results, there are three underlying factors namely (F1) App Used, Course Content and Design, and Faculty/Student's Capability Factors, (F2) E-learning, Mental Health and Home Environment Problems, (F3) Social/Media Influence and Student's Mannerism Factors. Different goodness of fit tests was employed to validate the final model. The final model satisfies all the criteria needed for model validation. Hence, the model is accurate and fits with the variables considered in the study.
Research Interests:
When the Covid-19 pandemic hit the world, everything changed. This includes the global education system. All establishments, including schools and universities, were forced to close as a result. To continue delivering education and... more
When the Covid-19 pandemic hit the world, everything changed. This includes the global education system. All establishments, including schools and universities, were forced to close as a result. To continue delivering education and maintaining academic progress, all teaching and learning activities were immediately converted to E-learning or Online learning. Even training and seminars for teachers and students were conducted through online platforms. This study aims to identify the challenges encountered by teachers during online research caability training conducted by the
Research Interests:
Censoring of the dependent variable is a very common problem with micro data where under certain conditions, only the observable values of the dependent variables are the ones being recorded and not the true data points. Thus,... more
Censoring of the dependent variable is a very common problem with
micro data where under certain conditions, only the observable values
of the dependent variables are the ones being recorded and not the
true data points. Thus, ignoring censoring will generally lead to
inconsistent estimators [2, 9]. As a result, the standard ordinary least
squares regressions can come up with bias and inconsistent estimates
[7-9]. In handling censored data, the commonly used estimators in the
literatures were Tobit and CLAD. However, they were only tested for interval-censored data [8]. This paper extends the work to left�censored data and presents the finite sample performances of these
estimators for left-censored regression model including the new
estimator which is based from a new imputation approach. Simulation
results showed that as in the case of normal errors in the univariate
regression case, the Tobit, CLAD, and the new estimator were
consistent estimators for left censored regression model. It is also
showed that Tobit is superior among the others when the errors are
normal. Results also showed that the CLAD estimator is consistent for
normal errors. Meanwhile, the new imputation approach produced a
consistent estimator for normal errors. Although, it did not out
performed Tobit and CLAD, it showed a favourable results in terms of
its variance as n gets higher.
micro data where under certain conditions, only the observable values
of the dependent variables are the ones being recorded and not the
true data points. Thus, ignoring censoring will generally lead to
inconsistent estimators [2, 9]. As a result, the standard ordinary least
squares regressions can come up with bias and inconsistent estimates
[7-9]. In handling censored data, the commonly used estimators in the
literatures were Tobit and CLAD. However, they were only tested for interval-censored data [8]. This paper extends the work to left�censored data and presents the finite sample performances of these
estimators for left-censored regression model including the new
estimator which is based from a new imputation approach. Simulation
results showed that as in the case of normal errors in the univariate
regression case, the Tobit, CLAD, and the new estimator were
consistent estimators for left censored regression model. It is also
showed that Tobit is superior among the others when the errors are
normal. Results also showed that the CLAD estimator is consistent for
normal errors. Meanwhile, the new imputation approach produced a
consistent estimator for normal errors. Although, it did not out
performed Tobit and CLAD, it showed a favourable results in terms of
its variance as n gets higher.
Research Interests:
The crisis we encounter in the global community is paramount to all species of social interaction. COVID-19, previously known as 2019 nCoV has devastated our day-today lives from our financial capability to our emotional condition.... more
The crisis we encounter in the global community is paramount to all species of social interaction. COVID-19, previously known as 2019 nCoV has devastated our day-today lives from our financial capability to our emotional condition. According to Rubin and Wessely (2020), the widespread contagion will inevitably have a psychological effect. This study aims to explore the different coping mechanisms among university students with the current global crisis, determine the significant difference of coping among gender preferences, and identify to what extent university students have been able to cope. Data was collected through a researcher-made survey questionnaire and an instrument adapted from Carver (1997). The survey was administered to university students. Students who responded and gave their consent were included in the study. Based on the results, the top five coping strategies that the students use as per experience are "listening to music", "sleeping", "social media", "movie/Netflix", and "online games". However, it is also notable that none of the students believed that using "prohibited drugs" or "substance use" is an option in coping with this pandemic. Moreover, there is no significant difference in coping among gender preferences which implies that regardless of your gender preference, orientation, and identity, all want to deal with their problems, hardships, or stresses in life. Hence, diverting one's attention to other things somehow is the students' best way of coping, armoured with positivity and faith.
Research Interests:
Electricity plays a vital role in this modern world. It is considered the backbone of an economy's prosperity and progress. The availability of a huge amount of energy has resulted in a shorter working day, higher agricultural and... more
Electricity plays a vital role in this modern world. It is considered the backbone of an economy's prosperity and progress. The availability of a huge amount of energy has resulted in a shorter working day, higher agricultural and industrial production, and have better transportation facilities. Modern society is so much dependent upon the use of electrical energy that it has become part of our life. It forms a key part of human everyday life. As the economy grows, demand for energy increases. Cagayan de Oro City's growing population and developing technology have demanded increasing consumption of electrical energy to provide light, heat, and power for the countless machines that are essential to the life and work of the residents. Usage will continue to increase because of rising living standards but higher costs may act to reduce the rate of rising. With the premise, there is a need to predict the future electrical power consumption to help CEPALCO to be prepared and for them to provide sufficient electrical energy for Cagayan de Oro City. Statistical forecasting is a method that uses the past to predict the future by identifying trends and patterns within the data to develop a forecast. The study deals with the application of autoregressive integrated moving average (ARIMA) for electrical power consumption in Cagayan de Oro City. After obtaining the results of ARIMA, it shows that ARIMA accumulates less absolute percentage error. The reason why ARIMA performed well is that the nature or behavior of the data that have been gathered contains linear trends although the data are fluctuating still the behavior is increasing which implies that the data of the monthly electricity consumption are more likely linear. Hence, the more the behavior of the data becomes linear, the more ARIMA is effective in forecasting.
Research Interests:
Extension programs are implemented to help elevate the lives of the people in the community. University of Science and Technology of Southern Philippines through the College of Science and Technology Education conducted a research... more
Extension programs are implemented to help elevate the lives of the people in the community. University of Science and Technology of Southern Philippines through the College of Science and Technology Education conducted a research capability training to Department of Education, El Salvador City Division Teachers last July 2020. The main objective of the program is to empower teachers by equipping them with the necessary skills for them to be capacitated in conducting research. To determine the impact of this extension program, this impact study was conducted with the select participants who participated in the training. A survey questionnaire and focus group discussion were employed to collect the necessary data for analysis. The results show that the participants were able to learn, acquire skills, and gain knowledge in conducting research. Some participants were able to produce research papers after the training. However, the research output among teachers after the training was not high due to several reasons such as heavy workload, funding support, lack of motivation, and lack of relevant experience. Thus, it is recommended that the school administrations should provide research incentives to encourage the active participation of the teachers in research. It is also suggested that future trainers' training will be conducted to the teachers to strengthen the skills and to create mentoring system among schools in DepEd El Salvador.
Research Interests:
The number of people suffering from kidney failure who underwent hemodialysis is alarmingly increasing. Insufficient information on factors that affects the survival of hemodialysis patients may lead to negligence and death rate. A... more
The number of people suffering from kidney failure who underwent hemodialysis is alarmingly increasing. Insufficient information on factors that affects the survival of hemodialysis patients may lead to negligence and death rate. A 24-month study period was conducted at the Nephrology Center of Cagayan de Oro (NCCDO) to determine the survival rate and factors affecting the survival among patients on maintenance hemodialysis. The Kaplan-Meier method result showed that out of 91 patients studied, 50.0% were still alive with a mean survival time of 15.051 months. Log-rank test result showed that there is a significant survival difference between different groups of ages and different diagnoses. Cox proportional hazard regression result showed that as the patient's age increases, the probability of survival decreases. Subsequently, patients who were diagnosed with Chronic
Research Interests:
Theoretically, the partially linear model is a special case of the additive regression models (Hastie and Tibshirani [16], and Stone [30]), which allows easier interpretation of the effect of each variable and may be preferable to a... more
Theoretically, the partially linear model is a special case of the additive regression models (Hastie and Tibshirani [16], and Stone [30]), which allows easier interpretation of the effect of each variable and may be preferable to a completely nonparametric regression because of the well-known curse of dimensionality. Well known applications of semiparametric models are the analysis of the relationships between temperature and electricity usage (Engle et al. [12]), the wage curve (Blanchflower and Oswald [5]), the analysis of the household gasoline consumption in the United States (Schmalensee and Stoker [28]), and many others. In this paper, we assessed the asymptotic properties of an estimate of the unknown function . g We consider its consistency, convergence rate, and asymptotic normality.
Research Interests:
The unplanned occurrence of vehicular crash that may result to loss of lives, damage to properties, and/or injuries is said to be a Road Accident. Minimization of the occurrence of road accidents can, perhaps be aided through the... more
The unplanned occurrence of vehicular crash that may result to loss of lives, damage to properties, and/or injuries is said to be a Road Accident. Minimization of the occurrence of road accidents can, perhaps be aided through the information on the factors that causes such incidents. Exploratory Factor Analysis (EFA) was used to address the problem of determining such factors. The data sets used are the road accidents which consists twenty-three observed variables (2,213 road accidents) consisting the overall road accidents in the year 2016. The data sets were subjected to the Ordinary Least Squares (Minimum Residual) Method for determining the factor loadings, matched with an oblimin rotation to achieve a simple structure (final model). The final model determined consists of four underlying factors, namely the "Weather and Road Surface Condition Factor", the "Visibility and Time Factor", the "Road Separation and Repairs Factor", and the "Traffic and Location Factor". The final model was subjected to goodness-of-fit statistics and was determined to be of good fit.
Research Interests:
Family planning is a larger concept involving preparation and knowledge around a "family future". It allows people to attain their desired number of children and determine the spacing of pregnancies, reduces the need for abortion,... more
Family planning is a larger concept involving preparation and knowledge around a "family future". It allows people to attain their desired number of children and determine the spacing of pregnancies, reduces the need for abortion, especially unsafe abortion. On the other hand, contraceptives are the group of methods you use or steps you take to avoid pregnancy before you are ready. Contraceptives, one of the methods of family planning, helps prevent the transmission of other sexually transmitted infections. Moreover, it can help slow down population growth thereby contributing to economic benefits such as poverty reduction. It is also a very helpful way to improve the health of mothers and childrens through birth spacing and avoiding high risk pregnancies. In this study, significant factors in using contraceptives are determined. Based on the results from the conducted survey, three out of ten variables were considered as significant factors namely: desire of having more children, religion, and employment status (having p-values of 0.005, 0.008, and 0.000 respectively). These significant factors were used in formulating the model to predict the probability of using contraceptives among married women. Using Hosmer and Lemeshow Test of goodness-of-fit, the p-value of the model is 0.728. Thus, the model is a good fit. A re-survey was conducted to validate the model and 88% of the married women were correctly classified. Hence, the model will be very useful in predicting the probability of contraceptive use among married women.
Research Interests:
Communication is essential toward all families and given the technology that we have today, Facebook has been one of many social media sites that lets people stay connected whereever they may be, although, not all members of the family... more
Communication is essential toward all families and given the technology that we have today, Facebook has been one of many social media sites that lets people stay connected whereever they may be, although, not all members of the family are in to using Facebook to communicate with their loved ones. This study aims to determine the effects of social media on interpersonal communication among family members, in particular, it analyzes the effectiveness of Facebook and family communication. In connection with this, the emphasis of this study is the effects of social media on the quality of interpersonal communication skills among family members. A sample of 25% of 120 individuals from four different colleges during the 2016-17 school year were the respondents of this study. A questionnaire was given to the respondents which included their profile, number of hours and activities on Facebook, and lastly the quality of their interpersonal communications with their family members. The results of the study show that communicating through Facebook more than likely leads to misunderstandings among family members as the messages are not expressed properly. Hence, a family must take time to talk and interact with each other personally in order to avoid these kinds of conflicts and maintain a good family relationship.
Research Interests:
Linear Discriminant Analysis can be used to determine which variable discriminates between two or more classes and to derive a classification model for predicting the group membership of new observations. For each of the groups, LDA... more
Linear Discriminant Analysis can be used to determine which variable discriminates between two or more classes and to derive a classification model for predicting the group membership of new observations. For each of the groups, LDA assumes the explanatory variables to be normally distributed with equal covariance matrices. The simplest LDA has two groups. To discriminate between them, a linear discriminant function that passes through the centroids of the two groups can be used. The study used Linear Discriminant Analysis in classifying a student as addicted or non-addicted in computer games. The study surveyed in the form of questionnaire to the students who are playing computer games and a student at Mindanao University of Science and Technology (MUST). Young Diagnostic Test (eight-item questionnaire) was adopted and used Likert Scale to answer the survey questionnaire. The researcher was able to classify 100 students by using Linear Discriminant Analysis. It was found out that 61 out of 63 or 96.83% is correctly classified as non-addicted and 35 out of 37 or 94.59% is correctly classified as addicted to computer games. Moreover, the study has 4.29% of average misclassification probability which implies that the Linear Discriminant Analysis performs better in classifying behavioral addiction. The study further showed that the students in MUST can manage their time properly as to when to study and when to play computer games as part of their recreational past time.