Artificial Intelligence and Thomistic Angelology: a Rejoinder

My paper analyses the analogy between Computers and the Thomistic separate substances, and argues that Aquinas' account of angels as cognitively intuitive and non-discursive makes the analogical gap between these impossible to bridge. From there, I point the direction away from computers as the way for us to move up the order of cognitive excellence. Instead, the gifts of the Holy Spirit are the way to go, since by them we participate in this intuitivity. I then lay out the ascetical presuppositions for the successful participation of this gifts, in particular the necessity for the passive purgations, according to the division of the ascetical life into three stages by Garrigou-Lagrange O

Excursions on the way: A comparative study of Wang Bi's Laozi and John Finnis' new classical natural law theory with special attention to the relations between metaphysical speculation and political theorizing

Ph.DDOCTOR OF PHILOSOPH

Addressing the Poor Science Performance of Filipino Learners: Beyond Curricular and Instructional Interventions

The Philippines performed abysmally in Programme for International Student Assessment (PISA) 2018 science literacy assessment: only 22% of the 7,233 15-year-old Filipino students who participated in PISA achieved the minimum level of competency (Level 2) in science literacy (Organisation for Economic Cooperation and Development [OECD], 2019). This performance in the science assessment places the Philippines near the bottom of the 79 countries and economies that participated in PISA 2018. In a study that used a machine learning approach, we identified 15 variables that identified the poor-performing students in science literacy. These variables can be grouped into four clusters, namely, metacognitive reading strategies, classroom and school experiences, students’ affect and motivation, and their family experiences and learning resources at home. Based on these results, we suggest a number of interventions that can address these non-cognitive variables that predict poor performance in science literacy

Addressing the Poor Reading Performance of Filipino Learners: Beyond Curricular and Instructional Interventions

In the 2018 Programme for International Student Assessment (PISA), 15-year old Filipino students ranked last in reading proficiency among all countries/territories, with only 19% meeting the minimum (Level 2) standard. It is important to understand the different factors that contribute to the low reading performance and proficiency of these students, specifically the interventions that may help address this learning problem. Based on the result of a study using machine learning approaches, specifically binary classification methods, to identify the variables that best predict low (Level 1b and lower) vs. higher (Level 1a or better) reading proficiency using the Philippine PISA data, 20 variables that discriminated low reading proficiency students were identified. The results reflect aspects of the students’ psychosocial experiences at home, the classroom, and in the schools that relate to their poor reading proficiency. The results point to how interventions to address poor reading proficiency need to go beyond the curriculum and instructional interventions. What is needed are localized interventions that try to improve the psychosocial experiences of students in school, and that involve stakeholders from the local communities

Addressing the Poor Mathematics Performance of Filipino Learners: Beyond Curricular and Instructional Interventions

This study aimed to determine predictive models that would identify the most important predictor variables for students in the lowest proficiency group in public schools and private schools. After experimenting with different machine learning approaches, the random forest classifier (SVM) models were found to perform most accurately (Lundberg & Lee, 2017). To identify the most important predictors of being a poor performer in mathematics, Shapley values were generated, which produces a ranked list of several features in descending order. To manage complexity in comparing the key variables for private and public student performance classification, the 10 most significant features for the public and private school groups are analyzed and illustrated in Figure 1. Red bars represent direct relationships, whereas blue bars represent inverse relationships with identifying the poor-performing students in mathematics. Shapley Additive exPlanations (SHAP) values represent the level of variable importance relative to other variables. The bar length of each variable corresponding to the x-axis values shows the strength of the variable’s influence in the prediction of the model. The meanings of each important variable are summarized in Table 1, which also highlights the similar and contrasting results for private and public schools

Using Machine Learning Approaches to Explore Non-Cognitive Variables Influencing Reading Proficiency in English Among Filipino Learners FINAL REPORT

Filipino students ranked last in reading proficiency among all countries/territories in the PISA 2018, with only 19% meeting the minimum (Level 2) standard. It is imperative to understand the range of factors contributing to low reading proficiency, specifically variables that can be the target of interventions to help the students with poor reading proficiency. We used machine learning approaches, specifically binary classification methods, to identify the variables that best predict low (Level 1b and lower) vs. higher (Level 1a or better) reading proficiency using the Philippine PISA data from a nationally representative sample of 15-year-old students. Several binary classification methods were applied, and the best classification model was derived using support vector machines (SVM), with 81.2% average test accuracy. The 20 variables with the highest impact in the model were identified and interpreted using the socioecological perspective of development and learning. These variables included students’ home-related resources and socioeconomic constraints, learning motivation and mindsets, reading classroom experiences with teachers, reading self-beliefs, attitudes and experiences, and social experiences in the school environment. The results were discussed with reference to the need for a system perspective to address poor proficiency that requires interconnected interventions that go beyond the students’ reading classroom

Competitive effects for the adsorption of copper, cadmium and lead ions using modified activated carbon from bambo

Modified activated carbon from bamboo was used as a low-cost potential adsorbent to remove cadmium, copper and lead in single, bimetal and trimetal aqueous solutions. Using the initial concentration of 40 ppm, the analysis was conducted to determine the effect of pH (2.5, 3.0, and 5.5), contact time (60, 90, 120 min) and adsorbent dosage (20, 40, 60 mg/50 mL of solution). Results showed that for single metal aqueous solution, the % adsorption for Cu, Cd, and Pb were 89.0%, 87.4%, and 99.5% respectively. For bimetal aqueous solution the % adsorption of CuCd, CuPb, CdCu, CdPb, PbCu,and PbCd were 90.6%, 98.9%, 55.1%, 80.7%, 99.6%, and 96.05%, respectively. While for trimetal aqueous solutions, % adsorption of Cu, Cd, and Pb were 87.4%, 73.0%, and 98.4%, respectively. The % removal uptake followed the order Pb > Cu> Cd gave insights into competition effects among the three solutes during the adsorption process. Using Box–Behnken Design, the effect pH of the aqueous solution is an important controlling parameter in which the % adsorption increased as the pH level is increased while other parameters were insignificant

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data