This paper analyzes the impact of the COVID-19 pandemic on the student’s academic performance in the School of Engineering at Universidad Nacional de Colombia – Bogota Campus. The impact is assessed from a quantitative approach based on (i) student’s grades, (ii) student’s progress in their curriculum and (iii) dropped courses. In addition, results from a faculty survey (qualitative approach) are presented to expand some explanatory perspectives on the main academic changes during the pandemic. Results show a significant increase in the average numerical grade as well as in the probability of a course being dropped during the pandemic conditions. Furthermore, the student’s average curriculum progress per semester grew approximately 18%. A differentiated academic impact, depending on sex and family income was observed which may be included in future post-pandemic programs. The survey reflects a new faculty’s perspective on evaluation tools and methodologies.
<p>Descendant Clock Auctions have been increasingly used in power markets. Traditional approaches are focused on discovering the bidders’ best response but neglecting the bidders’ adaptation. This paper presents an algorithm based on decision theory to estimate the bidders’ behavior along the auction. The proposed model uses portfolio concepts and historical data of spot market to estimate a long term contract supply curve. This model was applied to evaluate the Colombia’s Organized Market (MOR). Demand curve parameters and round size were varied to evaluate their impact over auction outputs. Results show that demand curve has a quite small impact over bidders’ decisions and round size management is useful to avoid non-competitive bidders’ behavior. In addition, it is shown that auction’s starting prices strongly influence auction’s clearing prices. These results are extremely helpful to design market structures in power markets.</p>
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