Developing a student support system through learning analytics for undergraduates at the University of the Philippines Open University

Using learning analytics, this study aimed to determine the characteristics of successful learners and the factors that affect program completion at the undergraduate level. By developing a learning analytics tool based on existing information about students in The Associate in Arts (AA) programme, researchers aimed to predict the probability of student completion of the AA program. A Distance Education (DE) Readiness Module was designed to provide applicants with a preview of what it is like to be an online DE student. Even as enrollment in DE programs continues to increase student attrition is a major concern for institutions offering DE.UK Government’s Department for International DevelopmentInternational Development Research Centr

Online learning in chemistry: Design, development, accessibility, and evaluation

Online learning has played an integral role in delivering large-cohort chemistry courses in undergraduate degree programs. This study includes describing how a first-year chemistry course transitioned from traditional face-to-face teaching to blended learning using the Resource-Based Learning framework (Hannafin & Hill, 2007; Reyes et al., 2022a). Using this framework, different types of online learning resources were curated to deliver chemistry content. A variety of learning activities were also developed to enhance these resources guided by Laurillard’s Conversational Framework (Laurillard, 2002). Considering that accessibility is a critical aspect to improve students’ learning experience, the Universal Design for Learning (UDL) framework was integrated into the learning design of first-year chemistry (Rose & Meyer, 2002; Reyes et al., 2022b). The perceived utility of online learning resources enhanced with UDL-based features was evaluated through students’ responses to surveys, interviews, and focus groups. Furthermore, learning analytics using temporal, sequence, and process mining analytical techniques were employed on students’ trace data to evaluate course learning design and to understand students’ engagement with learning resources and activities included in the course. Results of this study show the importance of careful development and implementation of learning design of the online learning component of chemistry courses, to enhance the students’ learning experiences. REFERENCES Hannafin, M. J., & Hill, J. (2007). Resource-based learning. In M. Spector, M. D. Merrill, J. van Merrienboer, & M. P. Driscoll (Eds.), Handbook of research on educational communications and technology. Erlbaum. Laurillard, D. (2002). Rethinking university teaching: A conversational framework for the effective use of learning technologies (2nd ed.). RoutledgeFalmer. Reyes, C.T., Kyne, S. H., Lawrie, G. A., & Thompson, C. D. (2022a). Implementing blended first-year chemistry in a developing country using online resources. Online Learning, 26(1), 174–202. https://doi.org/10.24059/olj.v26i1.2508 Reyes, C.T., Lawrie, G. A., Thompson, C. D., & Kyne, S. H. (2022b). “Every little thing that could possibly be provided helps”: analysis of online first-year chemistry resources using the universal design for learning framework. Chemistry Education Research and Practice. https://doi.org/10.1039/d1rp00171j Rose D. H. & Meyer A. (2002). Teaching every student in the digital age: Universal Design for Learning. Alexandria, VA: ASCD

A study on the performance of the Philippine stock market in terms of market return and stock volume from years 1994-2005: A comparison of the periods before, during and after the Asian financial crisis

The study measures the performance of the Philippine Stock Market using market return and stock volume of the Philippine Composite Index (PSEi) from the years 1994-2005. Using the Two-Way Analysis of Variance (ANOVA), the results showed that there are significant differences in the performance of the Philippine stock market, which suggests that the Asian Financial Crisis affected the stock market performance. The Regression Analysis showed the variables affecting market return and stock volume. The results showed that the Dollar-peso exchange rate and Dow Jones Industrial Average (DJIA) affect the market return. The same variables affect the stock volume with the addition of the Philippine T-bill rate