Development of Evidence-Based Scenario with High Fidelity Simulation to Improve Nursing Care of Chest Pain Patients

Cardiovascular disease remains the leading cause of mortality in the United States, and a primary educational objective is to develop professional competency among nurses to ensure the provision of safe and effective care to the cardiac patient. Benner\u27s theory of novice-to-expert led to the development of an evidence-based scenario for the care of the patient with chest pain using risk-free high-fidelity simulation environments that focused on assessment, history taking, and communication, while evaluating improvements in the competency of nurses providing care to chest pain patients. Thirty-six nurses volunteered in the study. Feedback from nurse educators, which led to modifications to the scenario, preceptor evaluation of participants during simulation, and post simulation feedback of participants, were analyzed using an inductive and exploratory theme analysis. Participants reported they learned meaningful information but felt somewhat confused regarding the correct course of action when multiple events occurred simultaneously. Preceptors\u27 feedback identified participant failure to meet stated scenario expectations. Quantitative analysis of data, using one sample t test, compared the pre- and post-test scores measuring participant knowledge on assessment, history taking, and communication. Although knowledge scores increased, the difference was not clinically significant based on the negative feedback from both preceptor and participants. Accurate appraisal of nurses\u27 competency in assessment, history-taking, and communication skills is needed prior to exposure to simulation. Simulation scenarios may be more clinically significant when tailored to an individual participant\u27s competency levels

The wheat-meal-fermentation time test

Call number: LD2668 .T4 1963 M37Master of Scienc

Utilizing Social Media in Improving Creative Writing Skills of Grade 7 Students in English

The study identified the performance of Grade 7 students enrolled in Umingan Central National High School across their academic performance in English under creative writing skill. In gathering the profile of the students and their performance in identifying morphological and syntactical errors, descriptive and correlational research designs with the use of rubrics and standard deviation were used in the treatment of data. In answering the relationship between the students’ profile variables and their performance in identifying morphological and syntactical errors, Pearson R and Spearman Rho were used. It disclosed that most of the students achieved an overall rating of “good” in identifying morphological errors while “fair” in identifying syntactical errors. There was a significant relationship between the students’ academic performance in English and their performance in identifying syntactical errors. Further, the computed significance value 0.00 which was less than the level of alpha 0.05, the r value reflected a moderately positive correlation between English grade and controlled group. The experimental group was found out to have no significant relationship to the ability to identify performance of students in creative writing skill

Pitfalls of Teachers on Modular Distance Learning: Basis for a Proposed Action Plan

The study was conducted to determine the pitfalls encountered by grade five teachers during modular teaching and learning. Specifically, it aimed to find out the pitfalls encountered by teachers along with students’ comprehension, students’ academic behavior, monitoring of students’ education, and physical interaction with the learners. The personal profile of teachers, out of the total respondents (56), most of the teachers are female-dominated. Most of them belong to the age bracket of 34 to 45 and most of the teachers are married. Most of the teachers had attended post-graduate studies. Most respondents are still young in the service, holding Teacher 2 and Teacher 3 positions, and attending local, national, and regional training. On the level of pitfalls encountered by teachers in modular teaching and learning, most respondents experienced a slight gravity level in the four aspects. The computed average weighted mean along comprehension is 2.50, along academic behavior is 2.54, along monitoring of students’ performance is 2.58, and along physical interaction is 2.79. All have an equivalent value of moderately grave. There is a specific profile of teachers that is significantly related. Age is significantly associated with monitoring students’ learning. The computed r value is .270, while the calculated significance level is 0.04. Training attended by the teachers is significantly related to some aspects of students’ comprehension, (computed sig. value is 0.04 and physical interaction is .02), which is lower than the .05 level of significance. The grade five teachers who served as respondents are mostly female dominated; they are in their early forties and married. Most of them are attending post-graduate studies and have attended relevant training. Second, the level of teachers’ pitfalls is mostly moderately grave. In addition, age is significantly related to monitoring, training is significantly associated substantially with physical interaction and comprehension

PREPARATION, CHARACTERIZATION AND APPLICATION OF RICE HULL- DERIVED ZEOLITES IN WATER TREATMENT

ABSTRAC

Quantum State Tomography using Quantum Machine Learning

Quantum State Tomography (QST) is a fundamental technique in Quantum Information Processing (QIP) for reconstructing unknown quantum states. However, the conventional QST methods are limited by the number of measurements required, which makes them impractical for large-scale quantum systems. To overcome this challenge, we propose the integration of Quantum Machine Learning (QML) techniques to enhance the efficiency of QST. In this paper, we conduct a comprehensive investigation into various approaches for QST, encompassing both classical and quantum methodologies; We also implement different QML approaches for QST and demonstrate their effectiveness on various simulated and experimental quantum systems, including multi-qubit networks. Our results show that our QML-based QST approach can achieve high fidelity (98%) with significantly fewer measurements than conventional methods, making it a promising tool for practical QIP applications.Comment: 18 pages, 19 figure