MED 900 Correlational Studies online safety sake.pptx

This study compared the teaching attitudes of government and private secondary school teachers in India. 200 teachers were surveyed using the Teaching Attitude Scale. The results showed that government secondary school teachers had significantly higher attitudes towards teaching compared to private secondary school teachers. When comparing attitudes by gender within each school type, government male teachers had higher attitudes than females, while private female teachers had higher attitudes than males. The study aimed to understand differences in teaching attitudes that could impact the quality of education.

1) The document reviews research on defining and characterizing effective teaching. It examines challenges in defining effectiveness, perspectives on effectiveness, and characteristics of effective teaching practices. 2) Effective teachers are clear about instructional goals, knowledgeable about content and teaching strategies, and monitor student understanding through feedback. They address both lower-level and higher-level cognitive objectives. 3) Characteristics of effective schools include consistency across the school, a culture of professional development and evaluation, and prioritizing literacy and individual student needs.

This document discusses challenges in defining and studying effective teaching. It provides various definitions of effective teaching from the literature, ranging from a focus on observable teacher behaviors and student outcomes to broader definitions encompassing teacher characteristics and duties beyond instruction. Five challenges are identified: defining effectiveness, considering different perspectives, characterizing effective practices, measuring teaching quality, and developing theoretical models. The review examines issues like the goals of education that determine definitions of effectiveness and difficulties in isolating teacher impacts on diverse student outcomes.

This document discusses establishing positive teacher-student relationships. It includes a group project overview on the topic, with members listed. It then covers research showing teacher-student relationships impact student behavior, motivation and achievement. Methods for communicating care and support are outlined, like praise, listening, expectations and feedback. A survey was conducted and references literature on the importance of these relationships.

Thesis Paper by Melloso, Cristy; Cuenca, Malou; Argallon, Jenifer And Reubal, Aprilon; BEED IV-1 Students at CUP

In this interactive talk, the presenter introduces a study of learner engagement in university EFL contexts in Japan that is being undertaken as part of a doctoral program at the University of Reading in the U.K. Intuitively, as teachers, we can recognize engagement or disengagement in our own learners when we see it. However, it is not clear where this recognition comes from, or whether or not our perceptions align with learner realities. After presenting an outline of the research project and preliminary findings, the presenter will ask participants to collectively work on a list of instructional practices that promote engagement in university EFL classes.

The document discusses performance standards, developmental standards, and the standards-based movement in education. It proposes strengthening performance standards to better assist student learning through collaboration between teachers. It also examines how the standards-based movement has negatively affected schools by limiting flexibility and prioritizing standardized testing over real learning. The response supports transforming schools through providing counselor support, teacher training, community partnerships, and addressing teacher retention issues. It predicts successful transformations will provide more teacher support and structure as well as opportunities for teacher collaboration and input.

This summary analyzes an article about educational negligence. The article discusses how negligence in education can negatively impact students' school lives and future ambitions. It addresses the issue of educational negligence in three main points: 1) Educational negligence can take many forms from poor teaching standards to ignoring student needs and attendance issues. It seriously impacts students. 2) A study in South Korea found that neglecting culturally diverse students was linked to relationship issues, dropout rates increasing over time. Neglect harmed peer and teacher relationships for these students. 3) To address educational negligence, teachers must ensure all students complete assignments by attending all lessons to fully cover required material. Parents and teachers must work together to meet students' needs for

The document summarizes a study on learner engagement in university English language classes in Japan. It discusses different types of engagement and introduces research questions on what instructional practices, teacher characteristics, and contextual features influence engagement. Preliminary findings suggest things like difficulty level, locus of control, group work, teacher talk and questioning style can impact engagement. The presentation aims to get audience input on practices that promote engagement and implications for competence, autonomy and relatedness.

This document is a project proposal submitted by Yasmina Akhter to IGNOU for her MAE degree. The proposal outlines her study on the adjustment level of primary school teachers in Anantnag, Jammu and Kashmir. The objectives of her study are to examine the social, home, rural, urban and overall dimensions of adjustment for male and female primary teachers. She will analyze factors impacting job satisfaction among primary teachers and how teacher adjustment may affect student learning. The literature review discusses previous research that found a relationship between teacher adjustment, attitude, personality and job satisfaction. The proposal outlines the need to study factors influencing primary teacher satisfaction and adjustment in the local context.

1) The dynamic model of educational effectiveness provides a framework for conducting theory-driven evaluations of educational reforms and policies. It considers factors at the classroom, school, and system levels and how they influence student achievement. 2) Evaluations using this model examine the direct and indirect impact of reforms on student outcomes and the functioning of effectiveness factors. They also take into account the multilevel nature of education. 3) The dynamic model's measurement framework dimensions of frequency, focus, stage, quality, and differentiation can be used to analyze reform characteristics and implementation across different levels. This provides a comprehensive approach for understanding how and why reforms are more or less effective.

This document summarizes research on how school leadership influences instructional quality. It reviews studies published since 2000 using various methodologies: 1) Quantitative studies using surveys found that principals perceive they have more influence over instruction and supervision when teachers are involved in decision-making, showing the benefits of shared leadership. 2) Qualitative case studies provided examples of conditions that support shared leadership patterns, such as principals fostering teacher engagement and innovation. 3) Network analysis examined how formal and informal interactions align, finding strong collaborative relationships oriented toward improvement are necessary for quality teaching.

Taxonomy of Learning Objectives which concentrates on the complexity of thinking and is an alternative approach to Bloom's taxonomy

This presentation summarizes the results of tracking education graduates from East Carolina University over five years to evaluate the effectiveness of innovations in their teacher preparation program. They partnered with an external organization to access longitudinal data and track graduates teaching in North Carolina public schools. Their evaluations found no significant differences between ECU and comparison teachers in classroom observation scores, student achievement gains, graduates' self-confidence and job satisfaction. ECU graduates had higher retention rates, with over 90% staying in teaching after five years compared to around 85% of comparison teachers. The lessons learned were to use data to drive program improvements, develop systemic innovations across areas, and continue tracking graduates over time.

The document discusses value-added assessment, which measures student growth and teacher effectiveness. It aims to provide teachers with diagnostic data to improve instruction. Value-added models require assessments that closely match curricula, can detect a range of student growth, and are reliably measured. The goal is for teachers to use data to increase all student achievement through differentiated instruction focused on individual growth. Research shows teacher effectiveness varies more between teachers than other factors and is the strongest influence on academic growth. Highly effective teachers ensure all students achieve and make excellent gains across achievement levels.

"Unlocking the black box: what's happening in 'more effective' classrooms in India?" - by Rhiannon Moore at BAICE 2018 -

H) It's anybody's guess (who knows?) The document summarizes multiple studies that call into question what exactly SETs measure. While SETs were originally intended to measure teaching quality, the research presented indicates that SETs lack construct and outcome validity and the statistics used are often inaccurate. Therefore, the conclusion is that it is unclear and unknown what specifically SETs actually measure.

The document discusses time series forecasting and visualizing time series components. It covers steps in forecasting like problem definition, gathering information, preliminary analysis, choosing models, and evaluation. Graphical analysis is important to identify trends, seasonality, outliers, and abrupt changes in a time series. Examples of time series from different domains like brick production, airline passengers and champagne sales are analyzed. Identifying characteristics from plots helps determine appropriate forecasting techniques.

This document discusses time series decomposition and its applications. It presents three case studies of decomposing quarterly revenue, monthly champagne sales, and monthly passenger volumes. Decomposition models separate a time series into trend, seasonal, and irregular components. This helps analyze which effects, such as trends vs. seasons, most influence changes over time. The case studies find that for revenue, seasonal fluctuations are less important than year-over-year trends. For champagne sales, there is essentially no trend after removing seasons. And passenger volumes have an upward trend combined with seasonal peaks in summer months.

The document discusses time series forecasting. It defines time series as a sequence of measurements on the same variable collected over time at regular intervals. Examples of time series data include monthly sales, yearly GDP, and quarterly income. Time series forecasting is important for organizations to reduce risks and optimize processes like production and manpower planning. The key challenge with time series data is that observations are not independent and ordered, with dependency between consecutive observations. The objective is to learn time series forecasting techniques.

SMOTE is a technique used to handle class imbalance problems in data. It involves over-sampling the minority class by synthesizing new minority class examples and under-sampling the majority class. This helps improve recall, or the detection of truly positive instances from the minority class, which is often prioritized over precision in class imbalance situations. K-fold cross-validation is a resampling method used to evaluate machine learning models on limited data. It involves splitting the dataset into k groups, using each group as a test set while the remaining form the training set, and averaging the results.

This document discusses factor analysis, a technique used to identify underlying dimensions or factors within a set of variables. It provides definitions of key terms like factor loadings, communality, scree plot, and factor scores. It also presents an example factor analysis using data on salespeople. The results show unrotated and rotated factor loadings, variance summarized by each factor, and issues that can arise in interpreting factor analysis outputs. Applications mentioned include using factor analysis in questionnaire design and customer profiling.

This document discusses various statistical concepts including measures of central tendency, probability, probability distributions, and inferential statistics techniques. It provides examples of how to identify the appropriate probability or distribution technique to use for a given problem, including the binomial, Poisson, and normal distributions. Key steps outlined include identifying the problem type, determining if it involves discrete or continuous data, and checking for conditions that indicate applying concepts like conditional probability or Bayes' theorem.

This document outlines the problem statement and objectives of a study to analyze loan data and identify borrower characteristics that contribute to delinquency. The objectives are to understand the major factors leading borrowers to become delinquent, as delinquency increases risk of default. The main objective is to minimize this risk by building a decision tree model using CART technique to identify risk and non-risk attributes of borrowers that result in delinquency. The tool to be used is R Studio.

This document discusses two types of frequency-based classification methods: K-Nearest Neighborhood (KNN) and Naive Bayes. KNN is a simple counting-based method that measures distances between data points to classify them, but can be ad-hoc. Naive Bayes uses Bayes' theorem to calculate conditional probabilities of class membership given attribute values in order to classify data points into classes. It makes the assumption that attributes are conditionally independent given the class.

This document provides an overview of descriptive statistics concepts. It discusses different data types, measurement scales, graphical and tabular data representations, and methods for summarizing data distributions. The agenda outlines topics including descriptive statistics graphs and tables, measures of central tendency like mean, median and mode, measures of variation such as range and standard deviation, and probability distributions. Descriptive statistics are used to organize and describe characteristics of data through quantitative methods.

This document provides an introduction and overview to learning R. It covers installing R and RStudio, basic data types and structures like vectors, matrices and data frames. It also discusses importing data, viewing and manipulating data through functions like filtering, binding and transforming. Finally, it discusses creating summary tables from data, joining datasets, and creating visualizations and plots in R using packages like ggplot2. The goal is to learn the basics of working with data in R, performing basic analysis and creating charts.