Text Clustering of COVID-19 Vaccine Tweets

The advent of the novel coronavirus disease (COVID-19) in late December 2019 led to the dramatic loss of human life worldwide and presented an unprecedented challenge to public health, education, social life, world economics, and the world of work. Equal access to safe and effective vaccines is very vital to ending the coronavirus pandemic. This research paper aims to perform text clustering on COVID-19 vaccine tweets. It investigates the optimal number of clusters prevalent in the COVID-19 vaccine corpus using deep learning techniques and machine learning algorithms. The study also investigates how using word embeddings can improve the accuracy of the proposed models by evaluating unsupervised learning methods. Machine learning clustering algorithms such as k-means and HDBSCAN, deep learning-based clustering techniques, and UMAP a dimensionality reduction algorithm were employed to perform text clustering. The results of this research showed the optimal clusters obtained by using deep learning clustering techniques and machine-learning algorithms for text clustering. HDBSCAN clustering algorithm showed better clustering results based on features learned while k-means performed better clustering based on various evaluation metrics. © 2022 IEEE.

Problems Encountered in Distance Teaching Practices Course and Solution Suggestions

This study aimed to examine the problems experienced by senior students studying at education faculties in the distance Teaching practice (DTP) course, where they participated in practice activities in formal schools due to the Covid-19 pandemic, and the suggestions for solving them. To achieve this aim, the students' opinions, who were determined with purposive sampling in the study conducted with a qualitative research design, were collected with open-ended questionnaires. The results obtained from the study are as follows: (1) The DTP process provided teacher candidates with experience in distance education, increased their technology predispositions, prevented the total interruption of education due to the pandemic, prevented the further spread of the pandemic, and ensured that trainings were conducted independently of time and place. (2) In the DTP process, communication problems between the parties (school administrators, counselors, and students), technical problems, technical impossibilities, inexperience, indifference, and inadequacy of technology use emerged as fundamental problems. (3) For the DTP process to be more effective, teaching practice courses should be fully face-to-face, or the DTP process should not only be conducted by distance education but should also be supported by face-to-face education processes. © 2021 IEEE.