Towards predicting COVID-19 trends: Feature engineering on social media responses

During the course of this pandemic, the use of social media and virtual networks have been at an all-time high. Individuals have used social media to express their thoughts on matters related to the pandemic. It is difficult to predict current trends based on historic case data because trends are more connected to social activities which can lead to the spread of coronavirus. So, it's important for us to derive meaningful information from social media as it is widely used. Therefore, we grouped tweets by common keywords, found correlations between keywords and daily COVID-19 statistics and built predictive modeling. The features correlation analysis was very effective, so trends were predicted very well. A RMSE score of 0.0425504, MAE of 0.03295105 and RSQ of 0.5237014 in relation to daily cases. In addition, we found a RMSE score of0.07346836, MAE of 0.0491152 and RSQ 0.374529 in relation to daily deaths. © 2021 Information Systems for Crisis Response and Management, ISCRAM. All rights reserved.

"more than learning": Teaching and learning ethics within an electrical engineering undergraduate capstone course

How learning is conceptualized and negotiated within the engineering undergraduate curriculum is affected by the theory of learning implicit in the design of the curriculum. The shift to online learning due to restrictions brought about by the COVID-19 pandemic provides the opportunity to make visible aspects of the curriculum that were previously hidden. The paper presents evidence of student learning relating to ethics found in student assignments submitted in partial fulfillment of a capstone course that forms part of the undergraduate program for Electrical Engineering at the University of Cape Town. Evidence of student learning will be linked to three distinct theories of learning that are presented and contrasted as metaphors: A theory of learning that assumes transference and is acquisition-based;a theory of learning that assumes transference by means of participation within a community and a theory of learning that is activity-centered and aims to be transformative. Each of these theories will be linked to particular teaching approaches and assessment strategies. The learning theories provide a frame to examine evidence of student learning relating to ethics in a particular context. This process justifies an expanded conception of learning relating to ethics in engineering. © 2021 South African Institute of Electrical Engineers. All rights reserved.