B-School Selection Criteria Influencers
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This caselet enables an understanding of the application of descriptive and inferential statistics for data analysis. The caselet revolves around identifying the factors that influence the students to pursue management education and in particular those that encourage them to choose a particular top rated B-School. The caselet is structured on the data collected from the 233 respondents who had enrolled for a PGDM program in a premier B-School and the same was utilized to demonstrate methods and suitability of finding few descriptive statistical measures and use of statistical test to find the impact of gender on factors that influence in selection of a B-School.
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Site selection, site planning, site divelepment
Site selection is crucial for earthquake-resistant design. At the macro level, sites should be evaluated based on their tectonic plate position and seismic zone. Potentially hazardous sites at the micro level include steep unstable slopes, landslide-prone areas, river banks, and faults. When planning sites, buildings should be set back from steep slopes and not located on filled soil without special foundations. Forests and individual trees can help mitigate landslides but buildings should not be too close to avoid falling risks. Overall, the safest sites avoid known hazards and have sufficient space between structures.
EducationalFacilities and Mapping
The document outlines several key principles for effective educational facilities and school mapping. It discusses the importance of developing functional facilities based on a comprehensive community plan. The planning process should maximize collaboration, establish a proactive management program, and design schools as neighborhood centers that provide accessible services. School mapping is also described as a dynamic process to optimally plan school distribution, size, and resources based on factors like demographics, environment, and policies. The expected results include prioritizing repair, expansion, and resource allocation needs.
Site Planning
Introduction to Site Planning. These slides should be able to provide urban planners a simple guide to factors and issues to consider in planning a a site. These slides were prepared for urban design class for masters students in Makerere University Kampala ( Uganda)
School plant
The document discusses the importance of proper school infrastructure and facilities. It notes that in the past, schools lacked dedicated buildings and had to use makeshift structures like mosques and temples. Over time, improvements were made with regular maintenance of buildings and additions of libraries, laboratories, and other amenities. However, some schools still lacked basic facilities. The document outlines factors to consider for school planning like adequate space, ventilation, lighting, classroom size requirements, and accessibility. It also discusses different approaches to schooling including open-air schools that focus on education rather than buildings.
School site development plan.ppt
The document discusses school site development planning and zoning. It defines school site development as the graphic representation of the current infrastructure and program on a school site. The principles of site development include orienting buildings along an east-west axis for cross-ventilation and solar orientation. Functional zones are created by grouping related buildings and activities. A site development plan shows existing structures, proposed additions, and circulation elements to anticipate future facility needs.
Site planning
This document provides an overview of site planning and site analysis. It defines site planning as allocating functions on a piece of land to efficiently utilize resources. The purpose of site planning is to fit design programs and sites harmoniously while considering natural, socio-economic, and technological factors. Site analysis involves researching and inventorying various elements of a site, such as location, neighborhood context, subsurface features, natural and manmade surface features, circulation, utilities, sensory factors, climate, and aesthetics. This information is then analyzed to achieve a successful site design that incorporates relevant site characteristics.
Architectural Professional Practice - Site الممارسة المهنية المعمارية - الموقع
Architectural Professional Practice - Site الممارسة المهنية المعمارية - الموقع
تحليل الموقع للمشروعات المعمارية
Site planning
Climate change is attributed directly or indirectly to human activities that alter the composition of the atmosphere. Vulnerable human settlements include housing, infrastructure, health services, and more. Site planning for settlements in hot-arid zones should emphasize compactness, shade, air circulation, and proximity to water to minimize sun exposure and heat gain. Landscaping can help control microclimate variables like temperature, wind, and humidity through elements like trees, walls, and water bodies.
Site analysis presentation
The document summarizes the landscape and biological attributes of the Taylor's University Lakeside Campus site. It describes the types of plants and trees found on the 27 acre site, including trees like Hopea Odorata, Samanea Saman, and Eugenia Oleina. It also lists various flowering shrubs, groundcovers, and foliage plants. Birds like sparrows are also present. The landscape helps create an attractive environment and positive impression of the university.
Site planning kevin lynch
The document discusses site planning and analysis of natural factors for site selection. It describes analyzing a site's geology, geomorphology, hydrology, vegetation, wildlife and climate. Key aspects of the natural analysis include examining a site's topography and slopes through tools like contour maps and slope maps. These maps are used to understand drainage, soil composition and erosion potential to determine suitable land uses and site design.
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Architectural Professional Practice - Site الممارسة المهنية المعمارية - الموقع
Architectural Professional Practice - Site الممارسة المهنية المعمارية - الموقع
Similar to B-School Selection Criteria Influencers
EBUS5423 Data Analytics and Reporting Bl
Distance Learning, Online Teaching [19+ Years]
• Possess substantial strengths in distance learning, adult education, teaching with technology, student and faculty relations, higher education, and curriculum development.
• Significant experience as an adjunct online faculty member, Core Faculty, Dissertation Chair, Committee Member, Curriculum Developer/Author, and Faculty Development Manager.
• Create a safe, respectful, and welcoming learning environment.
• Specialize in working with new students, first generation students, and academically under-prepared students.
• Developed an exceptional record of academic excellence, end-of-course evaluations, collaboration, communication, mentoring, coaching, and professionalism.
• Computer proficient with online classroom platforms that include WebCT, eCollege, Canvas, Sakai, Moodle, Educator, Desire2Learn, Blackboard, Brightspace and others.
Dissertation Chair and Mentor [Remote, 11+ years]
• Provide high quality instruction, direction and mentorship for assigned students throughout all phases of the dissertation process.
• Provide timely and supportive mentoring throughout the student’s process of developing, researching, writing, and revising the dissertation.
• Participate in the Defense process of a student’s Prospectus and final Dissertation.
• Facilitate the successful completion of all IRB protocols.
Faculty Development [Remote, 10+ years]
• Served as a Trainer and Mentor for New Faculty Members.
• Performed faculty peer reviews and assessed classes based upon best practices and adult learning theories.
• Inspired faculty to improve their facilitation practice by leading online faculty workshops.
Curriculum Development [Remote, 12+ years]
• Authored hundreds of courses as a SME for multiple schools, including undergraduate and graduate courses.
• Strong knowledge and application of adult cognitive learning theories and instructional design methodologies.
• Develop content and assessments that met learning objectives, including discussions and assignments.
Background Includes: Various Online Schools (08/05 – Present)
Online Instructor, Doctoral Committee Member, Dissertation Chair, Faculty Development, Curriculum Development.
quantitative-research.pptx
Quantitative research focuses on collecting and analyzing numerical data using statistical and computational methods. It emphasizes objective measurements to analyze data collected from surveys, questionnaires, or pre-existing statistical data. There are three main types of quantitative research: descriptive research aims to describe characteristics of a population or phenomenon; correlational research examines relationships between variables; and experimental research tests hypotheses by manipulating variables and controlling for other factors to determine cause-and-effect relationships. Quantitative research generates results that can be generalized to wider populations and aims to classify, count, and statistically explain observed data.
Role of data analytics in educational industry
Educational institutions are collecting large amounts of data but not effectively using it. Data analytics can help institutions increase profits, reduce dropout rates, and gain competitive advantages by better understanding student performance, identifying at-risk students, and tailoring education to individual needs. Analyzing academic, financial, and operational data through data analytics allows for targeted strategies, performance management, personalized education, and improved curriculum. This helps schools achieve goals of customizing learning and personalizing instruction for each student.
Analytics in education
The document discusses how business analytics can be used in education. It defines business analytics as using quantitative techniques and data to help decision makers make more informed choices. In education, analytics allows teachers to measure student understanding in real time, identify factors that influence student success like attendance and interactions, and customize education programs for each student. Analytics can also help educational institutions understand employment trends, measure effectiveness, and get insights to stay competitive and improve student outcomes.
Predictive Analytics in Education Context
ow-a-days data volumes are growing rapidly in several domains. Many factors have contributed to this growth, including inter alia proliferation of observational devices, miniaturization of various sensors ,improved logging and tracking of systems, and improvements in the quality and capacity of both disk storage and networks .Analyzing such data provides insights that can be used to guide decision making. To be effective, analysis must be timely and cope with data scales. The scale of the data and the rates at which they arrive make manual inspection infeasible. As an educational management tool, predictive analytics can help and improve the quality of education by letting decision makers address critical issues such as enrollment management and curriculum Development. This paper presents an analytical study of this approach’s prospects for education planning. The goals of predictive analytics are to produce relevant information, actionable insight, better outcomes, and smarter decisions, and to predict future events by analyzing the volume, veracity, velocity, variety, value of large amounts of data and interactive exploration.
Education analytics – reporting students growth using sgp model
Abstract Every part of the education sector is struggling to produce actionable data favorable for their growth. The primary stakeholders of this sector are unable to take effective and productive decisions as the huge amount of data collected is not being processed properly. A lot of striking data are lost in the process as there are no schemas available for extracting the intelligence from them. Various external factors affecting the student’s growth are not identified and thus the parents and teachers fail to understand the real reason behind the student’s performance. Hence to measure student's growth SGP (Students Growth Percentile) can be used. It is also necessary to keep tab on student's future marks so as to take precautionary measure in case of negative growth. Here, time series analysis and forecasting can be used. Regression is use to calculate impact of any external factors on overall performance. When all these identified external myriad data along with the academic data is captured, processed using analytical models such as R. The stakeholders will be able to understand the core reasoning behind progress rate and thus take decisions accordingly. This is the fundamental idea behind Education Analytics. Keywords - Analytics, Education Analytics, Student’s Growth Percentile, Marks Forecasting, Student’s growth
EDUCA Leveraging Analytics FINAL
This document discusses how analytics can be used to improve student success. It begins by describing a session that shows how analytics identify opportunities to improve student success. Participants will learn how to connect predictions of risk to interventions most likely to work under different conditions. The document then discusses how data is changing education and how analytics can be applied in areas like enrollment management, student services, and program design. It provides examples of how predictive analytics have been used at various institutions to improve retention, successful course completion, and graduation rates. The document emphasizes linking predictions of risk to specific interventions and measuring the impact and ROI of different interventions.
Using Data to Improve Minority-Serving Institution Success
This document discusses how Minority-Serving Institutions (MSIs) can better use data to improve student and institutional success and meet national college completion goals. It outlines that MSIs have traditionally educated underserved student populations but some are not fully utilizing data to assess areas for improvement. The document recommends that MSIs adopt interim measures to track student progress and success at multiple points along their educational pathway, such as placement upon entry, persistence in continuous enrollment, progression toward earning a credential, and ultimate completion. These interim measures can provide a more comprehensive view of student outcomes than traditional metrics like graduation rates alone.
DreamBoxWP_ActionableData_V6A (1)
This document discusses how schools can use data to personalize math instruction. It recommends that school leaders establish a clear vision for data-driven decision making and create a data-focused culture. A key part of this is designating data coaches who can help teachers analyze formative assessment data and find actionable insights. Data should also be discussed in data team meetings where teachers can collaborate on improving student learning. When done effectively through data analysis and action planning, this process can help teachers personalize instruction based on individual student needs.
bpp.pptx
This document outlines a thesis proposal on factors affecting student's academic achievement in secondary schools in Kembata Tembaro Zone, Ethiopia. The proposal includes an introduction, background, statement of the problem, objectives, research questions, scope, methodology, and financial plan. The study aims to investigate internal and external factors influencing student performance on national exams. A mixed methods approach will be used, collecting data through questionnaires, interviews, and documents. The target population includes school leaders, teachers, supervisors, and education office experts from selected districts. Data will be analyzed using descriptive and inferential statistics to understand the factors impacting academic achievement.
Big Data and Advanced Analytics For Improving Teaching Practices In 2023 | Fu...
Big Data and Advanced Analytics For Improving Teaching Practices In 2023 | Fu...Future Education Magazine
Here are 7 ways of big data and advanced analytics to improve teaching practices: 1. Data Sources in Education 2. The Role of Big Data in Education 3. Advanced Analytics in Education 4. Assessing Teaching Practices with Data 5. Enhancing Teaching Practices with DataIRJET - Recommendation of Branch of Engineering using Machine Learning
This document describes a machine learning system that recommends engineering branches to students based on their scores. It uses K-nearest neighbors and collaborative filtering techniques. The system aims to help students select an engineering branch that matches their abilities and reduces confusion. It analyzes student data like marks to make personalized recommendations. The document reviews similar existing recommendation systems and the techniques they use. The proposed system seeks to guide students towards suitable engineering fields and reduce the workload on counselors.
Assessment Selection Paper-Herman_Heritage_Goldschmidt (2011)
This document provides guidance for states and districts on developing and selecting assessments of student growth to be used in teacher evaluation systems. It outlines a validity framework consisting of 5 propositions that comprise the argument for justifying the use of student assessments to measure teacher effectiveness. Each proposition includes design and psychometric claims that must be substantiated with evidence. The document discusses the claims and potential evidence sources for each proposition, with a focus on Proposition 1 regarding learning standards. It emphasizes the importance of clear, realistic standards that reflect learning progressions and using expert reviews to evaluate design claims about standards.
Web 2.0 assessment presentation
This document discusses various types of assessments used in education including formative, summative, screening, diagnostic, progress monitoring, and outcome measures assessments. Formative assessments are ongoing and used to improve instruction, while summative assessments evaluate programs at the end of a term. Screening assessments determine if further testing is needed, and diagnostic assessments identify student strengths and weaknesses. Progress monitoring tracks student learning over time. Outcome measures assess program effectiveness. The document also describes individual student analytics and large group statistics provided by assessment results.
Web 2.0 assessment presentation
This document discusses various types of assessments used in education including formative, summative, screening, diagnostic, progress monitoring, and outcome measures assessments. Formative assessments are ongoing and used to improve instruction, while summative assessments evaluate programs at the end of a term. Screening assessments determine if further evaluation is needed, and diagnostic assessments identify student strengths and weaknesses. Progress monitoring tracks student growth over time. Outcome measures assess program effectiveness. The document also describes individual student analytics and large group statistics provided by assessment results.
Recommendation of Data Mining Technique in Higher Education Prof. Priya Thaka...
International Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity.
Teaching Statistics Without Mathematics An Innovation Approach to Public Adm...
Teaching Statistics Without Mathematics An Innovation Approach to Public Adm...Dr. Michael W. Popejoy, MBA, Ph.D., M.P.H., M.S., FRSPH
This document discusses teaching statistics to adult learners in graduate programs. It argues that statistics is often taught with too much focus on mathematical processes and not enough on interpretation of results to inform decision making. For adult learners who are mid-career professionals, interpretation is more useful than learning formulas they will not use. The document presents results of a modified statistics course for public administrators that minimized mathematics and focused on interpretation. Students reported being more satisfied and believing it would help understand statistical analysis in their work. The document recommends changing statistics curriculum and teaching methods to better serve the needs of adult learners seeking immediate application, not theory, from their education.Customer and Stakeholder Perspective using Analytical Hierarchy Process Metho...
The measurement of the higher education
performance is a complex issue and becoming
increasingly important. Currently, performance
measurements have been changed. It is no longer
evaluated from the classical financial indicators.
Instead, the customer satisfaction has been proposed
as the basis for a ‘management strategic’ within
organizational. This paper presents performance
measurement at the higher education concerning in
customers and stakeholders’ perspective using the
Analytic Hierarchy Process (AHP) method. AHP is a
quantitative method which can deal with complicated
decision-making problem for evaluation. Total of four
main criteria and 26 sub-criteria were identified as
significant to the customers and stakeholders’
perspective. This empirically finding is suggested to
be a good performance measurement for solving the
problem multi criteria and contributes strategic goal
in higher education.
Keywords— Analytic Hierarchy Process (AHP),
Performance Measurement, Customer and Stakeholders
Perspective
machine learning based predictive analytics of student academic performance i...
The document presents research on using machine learning algorithms to predict student performance in courses. It tested eight algorithms on data from Bradley University and evaluated their predictive accuracy. Based on the results, it makes recommendations on selecting and using ML algorithms for predictive analytics in STEM education. It also summarizes student feedback from surveys on using ML-based predictive analytics. The proposed system aims to address the lack of a system in Malaysia to analyze student data and monitor progress. It reviews literature on predicting student performance with machine learning techniques and identifies the most important attributes to improve student achievement and success. The system architecture requires a computer with at least 4GB RAM, 100GB disk, and the ability to run Python programs in an IDE like PyCharm.
Strategic Management Framework for Institutional Success
Presented at the GMAC Leadership Conference, "Implementing a New Strategic Framework" delves into how business schools can utilize rankings intelligence to make better resource allocation decisions, hence improving the institution's value proposition to its many stakeholders.
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Education analytics – reporting students growth using sgp model
Education analytics – reporting students growth using sgp model
Using Data to Improve Minority-Serving Institution Success
Using Data to Improve Minority-Serving Institution Success
Big Data and Advanced Analytics For Improving Teaching Practices In 2023 | Fu...
Big Data and Advanced Analytics For Improving Teaching Practices In 2023 | Fu...
IRJET - Recommendation of Branch of Engineering using Machine Learning
IRJET - Recommendation of Branch of Engineering using Machine Learning
Assessment Selection Paper-Herman_Heritage_Goldschmidt (2011)
Assessment Selection Paper-Herman_Heritage_Goldschmidt (2011)
Recommendation of Data Mining Technique in Higher Education Prof. Priya Thaka...
Recommendation of Data Mining Technique in Higher Education Prof. Priya Thaka...
Teaching Statistics Without Mathematics An Innovation Approach to Public Adm...
Teaching Statistics Without Mathematics An Innovation Approach to Public Adm...
Customer and Stakeholder Perspective using Analytical Hierarchy Process Metho...
Customer and Stakeholder Perspective using Analytical Hierarchy Process Metho...
machine learning based predictive analytics of student academic performance i...
machine learning based predictive analytics of student academic performance i...
Strategic Management Framework for Institutional Success
Strategic Management Framework for Institutional Success
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Inclusive Growth in a Mobile Way: m.Paani
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Chennai Bakers’ Sales Concerns: Measuring and Scaling Dilemmas
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Service Tax Hike: Elasticity of Demand and Incidence of Tax
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