scholarly journals Active Learning, Students Who Are Academically At-Risk, and Institutional Classification

2021 ◽  
Vol 4 (1) ◽  
pp. 26-36
Keyword(s):  
At Risk ◽  
Active Learning ◽  
Doctoral Degree ◽  
Learning Activities ◽  
Traditional Learning ◽  
Chi Square ◽  
Data Set ◽  
Academic Level ◽  
Course Grades ◽  
Academically At Risk

In this study, self-reported survey results from the National Survey of Student Engagement (NSSE) 2017 and 2018 are examined to understand the extent to which students who were academically at-risk and academically prepared engaged in active learning versus traditional learning methods across bachelor’s, master’s, and doctoral degree-granting institutions. The NSSE Report Builder Public (2018) was utilized to create a data set from first year student responses selecting for teaching methodologies, Carnegie Institutional Categories, and student academic level as determined by course grades. Researchers used chi-square analyses to establish associations between the variables; all chi-square results were statistically significant except for one; there was no association found between students who were academically at-risk and coursework that emphasized evaluative learning activities. Next, researchers analyzed the frequencies of types of learning activities reported by students. Students who were were academically at-risk reported lower frequencies of using active learning techniques and tended to engage in study for fewer hours across all institution types. From this analysis, suggestions for improving the instruction for students who are academically at-risk include increased use of active learning teaching strategies for the various types of degree-granting institutions.

Comparing biology majors from large lecture classes with TA-facilitated laboratories to those from small lecture classes with faculty-facilitated laboratories

2005 ◽  
Vol 29 (2) ◽  
pp. 112-117 ◽  
Author(s):  
Barbara E. Goodman ◽  
Karen L. Koster ◽  
Patrick L. Redinius
Keyword(s):  
Active Learning ◽  
Student Learning ◽  
Faculty Perceptions ◽  
Learning Activities ◽  
Control Group ◽  
Course Grades ◽  
Lecture Material ◽  
Large Lecture ◽  
Teaching Faculty

The teaching faculty for this course sought to address their own concerns about the quality of student learning in an impersonal large lecture biology class for majors, the difficulties in getting to know each student by name, and difficulties in soliciting answers and reactions from the students during the lecture. Questions addressed by this study were, Do active-learning activities in a small and personal lecture setting enhance student learning more than active-learning activities in large impersonal lectures? and Are students more satisfied with an educational experience in a small and personal lecture setting? Based on faculty perceptions of how they best relate to their students, the prediction was that the students in the experimental group with small lecture classes and increased direct contact with the teaching faculty would learn physiological principles better than the students in the control group in the large impersonal lecture portion of the course. One of the laboratory sections of this large enrollment biology course was randomly selected to be taught with separate small lectures by the teaching faculty. In addition, the teaching faculty participated in the laboratory with these students during their experiments correlated with the lecture material. The students in both groups were compared by pre- and posttests of physiological principles, final course grades, and class satisfaction surveys.

Bridging the gap between perioperative pelvic floor training and urologic surgeries with risk of incontinence by digital technologies: a survey. (Preprint)

2020 ◽  
Author(s):  
Jan Niclas Mumm ◽  
Lucas Bohn ◽  
Lennert Eismann ◽  
Alexander Buchner ◽  
Theresa Vilsmaier ◽  
...  
Keyword(s):  
At Risk ◽  
Pelvic Floor ◽  
Digital Technologies ◽  
Preventive Treatment ◽  
Final Analysis ◽  
Chi Square ◽  
Group Iii ◽  
Pelvic Floor Training ◽  
Group I ◽  
Group Ii

BACKGROUND Pelvic floor training (PFT) is the gold standard for conservative treatment of male stress urinary incontinence. OBJECTIVE To evaluate patients´ perspective at risk of incontinence on PFT and application of digital technologies for PFT. METHODS Patients undergoing transurethral surgery of the prostate (group I), radical prostatectomy (group II) or treatment at a specialized incontinence outpatient clinic (group III) were surveyed anonymously. Chi-Square test and Kruskal-Wallis-analysis were used for statistical analysis. RESULTS 180 patients were included in the final analysis. In group I (n=35) no patient underwent PFT prior to transurethral surgery. 23.5% of patients in group II (n=51) and 95.7% of patients in group III (n=94) performed PFT. 11.4% in group I, 80.4% in group II and 91.5% in group III have been advised to perform PFT by their urologist. Regarding the information level on PFT, patients from group I (median 1, range 0-5) are less satisfied than patients from group II (median 3, 0-9) or group III (median 5, range 0-10, p<0.001). 88.6% of patients from group I are willing to perform PFT as preventive treatment or to avoid incontinence surgery, 100% from group II and 68.4% from group III (p<0.001). The likelihood to use digital PFT is higher in group I (median: 9, range 0-10) and II (median: 9, range 0-10) than in group III (median: 4, range 0-10, p<0.001). CONCLUSIONS Patients at risk of incontinence currently have limited access to PFT, although they are willing to perform PFT. Digital PFT is highly accepted by patients preoperatively and might be a valuable tool to increase PFT participation.

scholarly journals Text Mining of Hazard and Operability Analysis Reports Based on Active Learning

Processes ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 1178
Author(s):  
Zhenhua Wang ◽  
Beike Zhang ◽  
Dong Gao
Keyword(s):  
Active Learning ◽  
Named Entity Recognition ◽  
Entity Recognition ◽  
Chemical System ◽  
Chemical Safety ◽  
High Quality ◽  
Data Set ◽  
Final Model ◽  
Named Entity ◽  
Sampling Algorithms

In the field of chemical safety, a named entity recognition (NER) model based on deep learning can mine valuable information from hazard and operability analysis (HAZOP) text, which can guide experts to carry out a new round of HAZOP analysis, help practitioners optimize the hidden dangers in the system, and be of great significance to improve the safety of the whole chemical system. However, due to the standardization and professionalism of chemical safety analysis text, it is difficult to improve the performance of traditional models. To solve this problem, in this study, an improved method based on active learning is proposed, and three novel sampling algorithms are designed, Variation of Token Entropy (VTE), HAZOP Confusion Entropy (HCE) and Amplification of Least Confidence (ALC), which improve the ability of the model to understand HAZOP text. In this method, a part of data is used to establish the initial model. The sampling algorithm is then used to select high-quality samples from the data set. Finally, these high-quality samples are used to retrain the whole model to obtain the final model. The experimental results show that the performance of the VTE, HCE, and ALC algorithms are better than that of random sampling algorithms. In addition, compared with other methods, the performance of the traditional model is improved effectively by the method proposed in this paper, which proves that the method is reliable and advanced.

Attitude towards online classes among school and college going students during lockdown due to COVID-19 pandemic

2021 ◽  
Vol 8 (7) ◽  
pp. 3446
Author(s):  
Saurav Kumar ◽  
Shiv Prakash ◽  
Mona Srivastava
Keyword(s):  
Family Income ◽  
Cross Sectional Study ◽  
Categorical Variables ◽  
Online Classes ◽  
Online Questionnaire ◽  
Chi Square ◽  
Cross Sectional ◽  
Academic Level ◽  
College Going ◽  
Significant Difference

Background: The aim of the study was to assess the attitude of the school and college-going students towards online classes. Methods: An online cross-sectional study was conducted on 228 school and college-going students fulfilling inclusion and exclusion criteria selected through purposive sampling methods. A semi-structured online questionnaire consisting of a socio-demographic questionnaire and Attitude towards online classes (ATOC) questionnaire was prepared by the researcher using Google form. The link of the questionnaire was sent to all the selected respondents through WhatsApp messages and emails. The data was analyzed using the IBM SPSS version 20 software. The reliability of the attitude questionnaire was assessed using Cronbach’s alpha test. The association between categorical variables was assessed using Chi-square tests. The comparison between variables was assessed using the students independent t-test.Results: More than half of the respondents (51.32%) were found with a positive attitude towards online classes. There was a significant association found between attitude towards online classes and socio-demographic variables such as age (p<0.05), academic level (p<0.05), and family income (p<0.01). The respondents who attended online classes (p<0.05), have technical knowledge (p<0.01), and got supported by their parents in the study (p<0.05) were found significantly high positive attitudes towards online classes. There was a significant difference found in the attitude of the respondents who faced psychological disturbances such as a decline in attention-concentration (p<0.05), irritation-anger (p<0.01), and tension (p<0.05) due to online classes.Conclusions: Although, online classes are more beneficial for the students and teachers in their academic activities during the lockdown period due to the COVID-19 pandemic but it can’t take place of traditional face-to-face classes. 

Massive Intravascular Hemolysis From Clostridium perfringens Septicemia

2013 ◽  
Vol 29 (6) ◽  
pp. 327-333 ◽  
Author(s):  
Tracey G. Simon ◽  
Joanna Bradley ◽  
Adisa Jones ◽  
Gerardo Carino
Keyword(s):  
Clostridium Perfringens ◽  
Patient Survival ◽  
Case Reports ◽  
English Literature ◽  
Case Series ◽  
Surgical Removal ◽  
Chi Square ◽  
Data Set ◽  
Male Mortality ◽  
Time To Death

We describe the case of a patient with hemolysis-associated Clostridium perfringens septicemia and review all similar cases published in the literature since 1990, with specific focus on the relationship between treatment strategy and survival. We searched PubMed for all published cases of C. perfringens-associated hemolysis, using the medical subject terms “clostridia,” “clostridial sepsis,” and/or “hemolysis.” All case reports, case series, review articles, and other relevant references published in the English literature since 1990 were included in this study. There were no exclusion criteria. Each case was examined with respect to presenting features of illness, antibiotic regimen, time-to-antibiotic therapy, additional interventions, complications, and patient survival. These variables were entered into a data set and then systematically analyzed with the aid of a statistician, using serial t tests and chi-square analyses. Since 1990, 50 patients of C. perfringens septicemia with hemolysis have been reported. Median age was 61 years (range 31-84), and 58% were male. Mortality was 74%, with a median time to death of 9.7 hours (range 0-96 hours). Of the patients, 35 (70%) were treated medically, while 15 (30%) received antibiotics and surgery. Surgical intervention was associated with significantly improved survival (risk ratio [RR] 0.23, 95% confidence interval [CI] 0.10, 0.53) as was the use of a combination of penicillin and clindamycin (RR of death 0.46, 95% CI 0.25, 0.83). Four patients utilizing hyperbaric oxygen therapy (HBOT) have been reported, and all patients survived. In cases of clostridial sepsis with hemolysis, strong predictors of survival include early initiation of appropriate antibiotics as well as surgical removal of infected foci. The HBOT may also be associated with survival. The disease often progresses rapidly to death, so rapid recognition is critical for the patient survival.

scholarly journals Analysis of Gender Differences in Internet Use of Children: Evidence from Turkey

2016 ◽  
Vol 8 (1) ◽  
pp. 199
Author(s):  
Ömer Alkan
Keyword(s):  
Mobile Phone ◽  
Information Technologies ◽  
Internet Use ◽  
Educational Status ◽  
Probit Regression ◽  
Chi Square ◽  
Data Set ◽  
Printed Media ◽  
Female Children ◽  
Chi Square Analysis

<p>In this study, factors in Internet use of female and male children in Turkey were determined with probit regression model by using micro data set in Household Information Technologies Usage Research of 2013 carried out by Turkish Statistical Institute. Dependent variable of the study is two category variable, namely Internet use and non-use of female and male children. Independent variables are socio-economic and demographic variables. According to chi-square analysis, there is a relation between Internet use of female and male children and socio-economic and demographic characteristics. According to probit regression analysis results, for female children, region, educational status, having computer or mobile phone on their own, frequency of watching TV, watching movie, series; floor show, music, game show; watching educational programs such as documentaries, culture, art, reading newspaper and journal in printed media, using mobile phone and frequency of using computer are variables effective in Internet use. Region, rural-urban difference, age, being literate, educational status, having mobile phone or game console on their own, watching entertainment, music, competition programs, reading newspaper and journal in printed media, using mobile phone and, frequency of using computer are variables effective in Internet use among male children. Frequency of using computer is the most effective variable in Internet use and it is more effective among female children compared to male children.</p>

scholarly journals Return Based Risk Measures for Non-Normally Distributed Returns: An Alternative Modelling Approach

2021 ◽  
Vol 14 (11) ◽  
pp. 540
Author(s):  
Eyden Samunderu ◽  
Yvonne T. Murahwa
Keyword(s):  
At Risk ◽  
Normal Distribution ◽  
Hedge Funds ◽  
Value At Risk ◽  
Financial Risk ◽  
Risk Measures ◽  
Risk Measure ◽  
Extensive Literature ◽  
Data Set ◽  
Normally Distributed

Developments in the world of finance have led the authors to assess the adequacy of using the normal distribution assumptions alone in measuring risk. Cushioning against risk has always created a plethora of complexities and challenges; hence, this paper attempts to analyse statistical properties of various risk measures in a not normal distribution and provide a financial blueprint on how to manage risk. It is assumed that using old assumptions of normality alone in a distribution is not as accurate, which has led to the use of models that do not give accurate risk measures. Our empirical design of study firstly examined an overview of the use of returns in measuring risk and an assessment of the current financial environment. As an alternative to conventional measures, our paper employs a mosaic of risk techniques in order to ascertain the fact that there is no one universal risk measure. The next step involved looking at the current risk proxy measures adopted, such as the Gaussian-based, value at risk (VaR) measure. Furthermore, the authors analysed multiple alternative approaches that do not take into account the normality assumption, such as other variations of VaR, as well as econometric models that can be used in risk measurement and forecasting. Value at risk (VaR) is a widely used measure of financial risk, which provides a way of quantifying and managing the risk of a portfolio. Arguably, VaR represents the most important tool for evaluating market risk as one of the several threats to the global financial system. Upon carrying out an extensive literature review, a data set was applied which was composed of three main asset classes: bonds, equities and hedge funds. The first part was to determine to what extent returns are not normally distributed. After testing the hypothesis, it was found that the majority of returns are not normally distributed but instead exhibit skewness and kurtosis greater or less than three. The study then applied various VaR methods to measure risk in order to determine the most efficient ones. Different timelines were used to carry out stressed value at risks, and it was seen that during periods of crisis, the volatility of asset returns was higher. The other steps that followed examined the relationship of the variables, correlation tests and time series analysis conducted and led to the forecasting of the returns. It was noted that these methods could not be used in isolation. We adopted the use of a mosaic of all the methods from the VaR measures, which included studying the behaviour and relation of assets with each other. Furthermore, we also examined the environment as a whole, then applied forecasting models to accurately value returns; this gave a much more accurate and relevant risk measure as compared to the initial assumption of normality.

scholarly journals Book Review: The One-Shot Library Instruction Survival Guide

2015 ◽  
Vol 55 (1) ◽  
pp. 68
Author(s):  
Calantha Tillotson
Keyword(s):  
Information Literacy ◽  
Time Management ◽  
Management Strategies ◽  
Learning Activities ◽  
Traditional Learning ◽  
Library Instruction ◽  
Challenges And Opportunities ◽  
The One ◽  
Traditional Learning Environments

Based on their combined thirty years of experience in information literacy instruction, Heidi Buchanan and Beth McDonough speak honestly of the challenges and opportunities associated with one-shot library sessions and provide readers with practical, creative, and inspirational resources. The authors begin each chapter with an attention-grabbing title, such as “They never told me this in library school” and “There is not enough of me to go around!” After capturing the readers’ attention, they proceed to continually captivate readers which covering relevant topics, such as how to effectively collaborate with departmental instructors, how to create a meaningful session despite severe time constraints, how to utilize active learning activities to engage students, how to instruct in non-traditional learning environments, how to successfully assess instruction sessions, and how to efficiently follow time management strategies.

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