Using Learning Analytics to Explore Responses from Student Conversations with Chatbot for Education

Chatbot simulates humans' conversations through computer programs using natural language. They are developed for various reasons and purposes, such as virtual characters and entertainers or as an interactive game component. Nowadays, Chatbots for education are using widely to enable students to engage with learning content constantly. In this study, students use Chatbot to query the Web Programming learning contents such as code description, coding and problem-solving. However, the successful responses of Chatbot to student queries is unknown. The lecturers also do not know the desired learning content of students who use the Chatbot. Thus, the purposes of this study are to explore the probability of a student getting successful responses in each conversation and to identify the students desired learning content. The learning analytics method is used to analyse the learning data of Chat-bot. The data analysis performed is descriptive analysis and binomial probability testing. The finding of the studies showed that the value of successful responses of Chatbot is high. The most desired learning content by the students is related to three categories of Web Programming contents, which is the hypertext Preprocessor (PHP), database & structured query language (SQL) and hypertext markup language (HTML). The Chatbot is updated based on proposed actions to provide more successful responses.

Case Fatality in COVID-19; a District Perspective

Objectives: To determine the case fatality rate of COVID-19 by evaluating the data of Patients died due to COVID-19. Materials and Methods: A total of 243 patients with PCR done from the government designated Public health research laboratory of Khyber Medical University were included in a cross sectional comparative study. Chi-square test, risk analysis, probability testing and survival analysis using Kaplan Meir test was done on data sheet prepared in SPPS version 25 in accordance with the objectives of the study. Results: Out of total 243 patients, 165 (67.90%) were negative by PCR testing and 78 (32.09%) were COVID-19 positive. The Mean age with SD was 36+17 years. Out of total 178 (73.3%) were males and 65 (26.7%) were females. 34 (13.99%) had age more than 55 years, where 4/5 (80%) of the deaths were recorded. The relationship of an increase in age with rate of mortality was statistically significant (p=0.001). The over all probability of death in our population in age more than 55 years is 24 times higher (OR=24,95CI: 2.6-221.24) with relative risk of 1.1 (rr=1.11, 95CI:1-1.24). Mortality rate was 6.41%. A significant correlation of mortality with case positivity (p=0.003) with relative risk of 1.06 (rr=1.06, 95CI: 1.008-1.13). Three out of 5 of the COVID-19 positive deceased had cardiac diseases and 2/5 had respiratory disease/viral pneumonia. Using Kaplan Meir test, the survival graphs of COVID positive vs COVID negative cases had similar pattern that shows the mortality rate in the positive cases was not solely due to COVID-19, but has aggravated the pre-existing illness to cause death. Conclusion: The mortality rate was 6.41%, more in age>55 years (80%) and almost all the deceased had chronic co-morbid conditions like CAD, CCF and COPD at time of presentation. COVID-19 is not the sole killer, it contributes killing in immune-deficient patients.

Dual Image-Based Dictionary Encoded Data Hiding in Spatial Domain

In the modern digital era, the privacy of personal communication is a serious concern to all netizens. A better way to preserve privacy could be to hide the secret message inside some innocent looking digital object such as image, audio, video, etc., which is known as steganography. A new steganographic scheme using a reference image along with the cover image has been proposed in this article. It enhances the robustness and security by increasing the obscurity of the hidden message. It also employs an additional dictionary-based encoding module to increase the hiding capacity as well as security. Experiments show that bit changes in the reference image are very few and undetectable to human perception, it also evades common statistical tests. Evaluation of standard quality parameters such as MSE, PSNR, UIQI, SSIM along with chi-squared statistics based embedding probability testing has been performed. When dictionary-based encoding is applied it further improves the quality parameters.

Introducing Modern Leraning Tools for Developing English Language Among School Students

The examination manages "A STUDY ON BRAND BUILDING THROUGH INTERNET. The primary goal of this investigation is to think about how Equitas Small Finance Bank are marking their administration through Internet. The Brand building has transformed into a significant factor for advertising. This examination focuses on the significant of these measurements (Brand Visibility, Brand Loyalty, Brand Image). The size of the example is 110 and the examining procedure utilized is Stratified inspecting (Probability testing), through the poll technique. Both the wellsprings of information accumulation viz. essential and auxiliary have been utilized in this report

Inappropriate testing for the diagnosis of coronary artery disease

In the last three decades also in our country it has been a huge growth of the use of non invasive testing for diagnosis of CAD. Therefore, appropriateness of prescription in diagnostic testing is crucial. Clinical evaluation is mandatory before a diagnostic test, including the evaluation of pre-test probability of the disease based on symptoms, age, sex and cardiovascular risk factors. The main benefit of testing is in patients with an intermediate pre-test probability. Testing for diagnosis of CAD is rarely appropriate in asymptomatic subjects, except for ECG exercise test in intermediate and high risk individuals, while stress or anatomic imaging is preferable in higher risk individuals. Coronary calcium score should not be used as screening test in asymptomatic subjects, except for excluding CAD in those with low pre-test probability. As far as diabetic patients is concerned, available evidence indicates an unfavorable risk-benefit ratio of extensive CAD screening, except in the presence of high clinical suspicion.