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Full-Text Articles in Online and Distance Education
Technology-Supported Distance Learning For Basic Education In The Philippines, Raymund Sison, Auxencia A. Limjap, Frederick Torralballa Talaue, Ryan Samuel Dimaunahan, Kristine Hernandez, Alen Mateo Munoz, Angelica San Buenaventura
Technology-Supported Distance Learning For Basic Education In The Philippines, Raymund Sison, Auxencia A. Limjap, Frederick Torralballa Talaue, Ryan Samuel Dimaunahan, Kristine Hernandez, Alen Mateo Munoz, Angelica San Buenaventura
Angelo King Institute for Economic and Business Studies (AKI)
Distance learning (DL) is a teaching-learning modality in which teaching occurs at a different place from learning (Moore & Diehl, 2018). Technology-supported distance learning (TDL) is DL in which learning contents—whether documents, videos, or games—are disseminated via the Internet, broadcast signals, or storage devices like USB drives and can be accessed by a learner any time after they have been received. These three kinds of TDL are called online DL (ODL), DL via datacasting (DLD), and electronic DL (EDL), respectively. Reproduction of learning materials is much faster and cheaper using TDL than traditional, paper-based DL.
Digital Capital And Belonging In Universities: Quantifying Social Inequalities In The Philippines, Wilfred Luis Clamor, Czarina Saloma-Akpedonu
Digital Capital And Belonging In Universities: Quantifying Social Inequalities In The Philippines, Wilfred Luis Clamor, Czarina Saloma-Akpedonu
Sociology & Anthropology Department Faculty Publications
This study examines social inequalities in Philippine universities that were exacerbated during the COVID-19 pandemic. A quantitative approach using a national sample of 677 university students was utilized to measure the mediating role of digital capital on social inequalities associated with belonging to academic spaces. For the purpose of determining direct and indirect impacts, structural equation modeling (SEM) was employed. Sociodemographic (i.e., gender, age, type of residence, and family income) and educational (i.e., type of university, year in the university, and excellence criterion) characteristics were the direct predictors that were examined as exogenous variables for both digital capital and belonging. …