HEA530 Course Introduction
is a taught postgraduate course, which gives students the opportunity to explore the role of data in decision making in higher education. Students will apply their learning through research projects and then present their findings at an end-of-semester conference. Topics covered include statistical inference, data analysis, and multiple regression, with particular emphasis on how to interpret results. The course is designed for students who have an interest in using statistics or data analysis for decision-making in higher education.
What does HEA530 cover?
HEA530 Course Description
in the undergraduate courses offered by the College of Education. (More info) Graduate Courses for Degree Graduate courses for degree may be found at www.scccd.edu/graduate/ and http://www.uncc.edu/education/degreeprograms/. Up one level: Degrees, Certificates, and Programs
English – Course Descriptions
Course Number Course Name Credit Hours Prerequisites Credits English 102 Intro to Writing 3 ENG with a grade of C- or better; or ENG 104 or
Universities Offering the HEA530 Course
: Other Colleges and Universities
HEA530 Course Outline
– Spring 2019
*All courses are offered in the evening only.
Academic Senate (AS)
College of Education and Human Development (CEHD)
Asst. Director of Communications and Strategic Planning
2000 East University Blvd.
Associate Registrar, Office of Admissions & Records (OAR)
104 SPH Building, Ken
HEA530 Course Objectives
Session: 1. Overview of Data-Driven Decision-Making in Higher Education
Curriculum Framework for the Bachelor of Science Degree in Biological Sciences University of Tennessee, Knoxville THE BACHELOR OF SCIENCE DEGREE IN BIOLOGICAL SCIENCES University of Tennessee, Knoxville The
COURSE: INTRODUCTION TO ENGINEERING STATISTICS COURSE NUMBER: 3-200-2C/6E(4) ECTS Credit Value: 3 HEA Units: 6 Prerequisites:
HEA530 Course Pre-requisites
Registration Information HEA530 is a 6-credit course and is open to all students, with preference given to full-time undergraduate students. Registration for the course is open on a rolling basis.
Registration will close when there are at least 5 students enrolled. For information about your HEA530 registration or to view the schedule for the course, please visit the course webpage. This course is an advanced elective in the Social Sciences and Humanities division, focusing on research methods and data-driven decision-making in higher
HEA530 Course Duration & Credits
Course Description In this course, students will use their problem-solving skills to design and conduct a quantitative data analysis that is appropriate to a given domain. Students will learn the importance of using appropriate research questions and use appropriate sampling procedures. For example, they will learn how to decide what statistical tests are best suited for a particular analysis, and how to justify the application of these tests. Throughout the course, students will become proficient in the use of Microsoft Excel software and more advanced statistical packages such as SPSS or
HEA530 Course Learning Outcomes
Course Learning Outcomes for HEA530 – Data-Driven Decision-Making in Higher Education (HEA530) This course will develop students’ understanding of the process of strategic decision making using data, and the role of data in decision making. Students will develop skills to read, interpret and use data to inform their own and others’ decisions. Students will have an increased ability to collect and analyse data using appropriate quantitative and qualitative methods; recognise the importance of ethics in analysing data; identify key features
HEA530 Course Assessment & Grading Criteria
Course Assessment and Grading Criteria
Course Assessment and Grading Criteria for HEA530 – Data-Driven Decision-Making in Higher Education (HEA530) Course Assessment & Grading Criteria from the Course Calendar
Course Assessment & Grading Criteria from the Course Calendar Class Presentation Outline
Class Presentation Outline Sample Project Proposal
Sample Project Proposal Sample Grade Report Form
Class Project Proposal
Sample Grade Report Form Discussion Board Questions (updated 2013)
Discussion Board Questions (updated 2013) Discussion Board
HEA530 Course Fact Sheet
Course Description This course introduces how research methods are used to assess quality, identify strengths and weaknesses, and formulate strategies for improvements in higher education. It is designed to develop critical thinking skills in the area of higher education and students’ ability to make decisions based on research evidence. As part of a program, this course will examine the following questions: What are some of the problems that our current system faces? How does a better system affect the health of our society? How do we measure the effectiveness of an
HEA530 Course Delivery Modes
Graduate Course/Level: Graduate Course Credit Hours: 3 ADMISSION REQUIREMENTS Admission to the Master of Science in Education (MSEd) program is by application. You must also meet the requirements for admittance into the graduate program, and meet prerequisites as specified by each department or college. Admission to a master’s degree program generally requires a bachelor’s degree from an accredited institution and admission to the graduate school. Students who have not completed their undergraduate education within five years prior to enrolling in
HEA530 Course Faculty Qualifications
Treasurer, University of Northern British Columbia Teaching & Learning Coordinator, University of British Columbia
Student Qualifications for HEA530 – Students will be taught by an experienced instructor with a passion for data analytics and decision-making in higher education.
The objective of this course is to provide students with the knowledge, skills and techniques required to manage and analyse data using the most appropriate statistical analysis software. The course will cover:
Data from any research undertaken in higher education (quantitative
HEA530 Course Syllabus
Correlations are provided for this course. Information about how to interpret the correlation is available in “Hea530 – Syllabus”.
Overview of course requirements for HEA530
The course will be assessed through the submission of a 3,000-word report.
You must submit your assignment by midday on the last day of classes.
Credit hours: 3.0
Enrollment status: This is an on-campus enrollment-only course.
Suggested HEA530 Course Resources/Books
– Data-Driven Decision-Making in Higher Education (HEA530) BOOK INFORMATION: Publisher: Cengage Learning, 2013 ISBN-10: 1305779486 ISBN-13: 9781305779484 This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book. About The Book: There are many ways to become a good decision-maker, but how do you make sound decisions based
HEA530 Course Practicum Journal
Practicum experience in a data-driven decision-making process.
1. Create a hypothetical, real-world problem based on an organization’s mission statement and identified stakeholders.
2. Present the problem to faculty members within the institution in a PowerPoint presentation (4-6 slides) that includes a summary of the problem, rationale for the decision, identified stakeholders’ perspectives, and recommendations for future action(s). Presentations must be made by team members.
3. Create a final report
Suggested HEA530 Course Resources (Websites, Books, Journal Articles, etc.)
New York University Tandon School of Engineering, https://tandon.nyu.edu/
HEA530 Course Project Proposal
in the School of Information Technology, University of Florida Data-Driven Decision-Making in Higher Education (HEA530) in the School of Information Technology, University of Florida [Proposal]
Submitted to: Mr. William Clingman
Faculty: Dr. Yiping Zhang
Date Submitted: February 28, 2013
Deadline for Proposal Submission: April 15, 2013.
Any questions may be directed to the Chair of the Proposal Review Committee at firstname.lastname@example.org
HEA530 Course Practicum
Faculty: Dr. Alexandra Womack
This course is an introduction to data-driven decision-making in higher education. Students will have the opportunity to learn how to use statistics and predictive analytics in a variety of decision-making contexts such as student recruitment, financial aid, enrollment management, and program planning and assessment. The course focuses on the use of applied statistics and mathematical modeling techniques for problem-solving at the institution level, including but not limited to decision making related to recruitment strategies, enrollment projections, cohort
Related HEA530 Courses
– Spring 2017. This page is for those students seeking an exemption to this requirement or who need extra time to complete the degree. The requirements are as follows: Students may have up to six (6) credits of residency course work completed by spring 2015 and one (1) credit of residency course work completed after that date.
Students must have a cumulative grade point average of 2.0 or higher in all courses for which they seek residence, including all core courses.
Nov. 21, 2017 at 11:00 am
This course is designed to help students understand how to collect and interpret data that will be used in the analysis of various problems in higher education. This course will teach you about different types of data analysis, how to manipulate these data sets, and the skills required for writing reports and making decisions based on the results of your analysis.
Your instructor may assign projects or readings that use real-world data
Top 100 AI-Generated Questions
– AI Lab. This includes questions for lab exercises, test or quiz questions, and exams for this course. The purpose of the data-driven decision-making in higher education course is to prepare students to use machine learning models (e.g., neural networks) in order to make decisions on a range of topics in higher education. In 2004, 24 states had laws that classified “exploitation” as a crime and defined it as follows: Any person who knowingly or intentionally uses another person’s image
What Should Students Expect to Be Tested from HEA530 Midterm Exam
at Midway University
This is a sample of HEA530 Midterm Exam for HEA530 – Data-Driven Decision-Making in Higher Education (HEA530) at Midway University. We are the best provider of Midterm Exam for HEA530 – Data-Driven Decision-Making in Higher Education (HEA530) in all over United States. Our expertise lies in providing you with a real exam environment so that you can experience the true feel of what it is like to take
How to Prepare for HEA530 Midterm Exam
at East Carolina University
The online version of this course is a self-study course that you can do from anywhere in the world.
The course uses learning materials created by Professor Deborah A. Josselson, Associate Dean and Professor of Higher Education, College of Education and Human Development, East Carolina University.
This course examines student success factors in higher education by focusing on the goals, priorities, and methods used to measure student success. Each section provides a brief review of recent research findings on
Midterm Exam Questions Generated from Top 100 Pages on Bing
from University of Houston.
The Top 100 pages are derived from Bing’s search results, which are based on the previous day’s search activity. The Top 100 sites have a rating between 0-10, where a higher number is better.
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Midterm Exam Questions Generated from Top 100 Pages on Google
– Lecture 2: Introduction to the Problem of Quality Data
Answer Key to Selected Questions and Problems
Click to view Answer Key for Selected Questions and Problems
1. Why is the Student-Level Model used in this course? What are some of its limitations?
This model provides a rich source of data on the characteristics of students who take each course in a given semester. However, the models limitations include:
Incomplete data: The models include only limited information about courses taken by individual students; it does not
is now available. The exam consists of 25 questions in four sections.
The passing score is 70% or higher, with a time limit of 60 minutes. This exam covers material from Chapters 1-4 of the textbook.
Deadline for submitting your exam is December 3 at midnight Eastern Standard Time (EST). You must email your exam results to email@example.com and include the Subject: HEA530 test code. Only online submissions will be accepted.
The course materials
Top 100 AI-Generated Questions
Class – Assignment 3: Search for a new world. Data-Driven Decision-Making in Higher Education (HEA530) Class – Assignment 3: Search for a new world.
New World, New Question… on Data-Driven Decision-Making in Higher Education (HEA530) Class – Assignment 3: Search for a new world. The assignment questions cover the following topics:
Project Planning and Implementation
Project Risks and Scheduling
What Should Students Expect to Be Tested from HEA530 Final Exam
. Final exam consists of 50 questions and the time limit is 120 minutes. It is important to study the following points before taking the final exam: The questions are multiple choice. You can only answer one question per question paper.
The questions are based on material covered in unit HEA530. As such, you should familiarise yourself with all materials in the units that you have studied in HEA530
You must take each question seriously as it carries a mark weight of 10% of
How to Prepare for HEA530 Final Exam
Final Exam Questions Generated from Top 100 Pages on Bing
Study Flashcards On HEA530 – Data-Driven Decision-Making in Higher Education (HEA530) at Cram.com. Quickly memorize the terms, phrases and much more. Cram.com makes it easy to get the grade you want!
Home / HEA 530 Final Exam Part 1 with Answers
HEA 530 Final Exam Part 1 with Answers – Calculus-Based Models for Data-Driven Decision Making in Higher Education (15 Questions
Final Exam Questions Generated from Top 100 Pages on Google
at the University of Nevada, Las Vegas
HEA530 Quiz: The Quiz on Google for HEA530 Data-Driven Decision-Making in Higher Education (HEA530) at the University of Nevada, Las Vegas
1. Which of the following is a
Week by Week Course Overview
HEA530 Week 1 Description
For this assignment, you will be creating an innovative tool to visualize data related to students’ academic success. We will explore the use of a variety of technology tools that provide a platform for sharing data. The assignment will allow you to integrate these various tools and develop your own visualization to demonstrate your understanding of data analytics techniques. This project requires you to work with a variety of tools, including Excel, PowerPoint, or Keynote. You may use one or more of these tools to create the visualizations and
HEA530 Week 1 Outline
1. Introduction to HEA530 Data-Driven Decision-Making in Higher Education 2. The Critical Data-Driven Decisions Making Task 3. Overview of Analyzing and Using Data in the Decision-Making Process 4. Student and Faculty Demographics: Testing, Monitoring, and Assessment 5. Program Effectiveness: Recruiting and Retention, Program Design, Quality Improvement
1 Homework – Week 1 HW#1 Research Assignment #1 Due Week 1 Assignment I have listed
HEA530 Week 1 Objectives
Week 1 Assignment – Data-Driven Decision-Making in Higher Education (HEA530) This course introduces you to the context of higher education data and decision-making, as well as the many ways in which those two concepts interact in practice. We will begin with a review of the historical background of higher education data, including U.S. trends in enrollment and graduation rates, as well as trends from 1990 to 2012; examine why it is important for institutions to use data wisely and
HEA530 Week 1 Pre-requisites
I will be completing the following readings in preparation for my first class: (1) Chapter 1, “What is a Data-Driven Decision?” of Michael S. McNulty and Brian R. Carter, “Decision Making in Higher Education” (2) Chapter 3, “The Use of Data in Educational Research,” of Joseph M. Dorfman and Tami G. Dorfman, “Measuring Student Outcomes in Higher Education” (3) Chapter 4, “Data
HEA530 Week 1 Duration
Week 1 Discussion and Exam – The Future of Higher Education – The Future of Higher Education, Part II (Topic 2) Professor: Dr. Roberta L. Knowles Week 2 Discussion and Exam – Making Your Classroom, Your School, and Your Profession More Inclusive (HEA530) Week 2 Discussion and Exam – The Future of Higher Education – A Call for Social Justice & Social Innovation (Topic 3) Professor: Dr. Roberta L. Knowles Week 3
HEA530 Week 1 Learning Outcomes
Resources: A variety of resources will be available for your use, including but not limited to:
Access to student records Data across institutions (and countries) and/or countries Analysis of social media Data on perceptions and experiences of students Use of algorithms to identify problem areas in a particular institution
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3 | P a g e
4 | P a g e
5 | P a g e
6 | P a g e
7 | P a g e
HEA530 Week 1 Assessment & Grading
1. Course Summary The purpose of this course is to provide students with an understanding of data-driven decision-making in higher education. Students will learn how to analyze and interpret data for decision making, develop a foundation for teaching the student in the field of data analysis, and understand the implications of data analyses for institutional policies and practices. 2. COURSE OUTLINE Week 1: Introduction to Data-Driven Decision-Making in Higher Education (HEA530) Discussion Board #1: What are
HEA530 Week 1 Suggested Resources/Books
Assignment 1: Week 1 Discussion Question #2 – Your first and most important step in understanding the data was to find the right type of data. How did you go about finding the right data? For this assignment, you will analyze a data set using Excel. Be sure to follow the steps outlined in your course textbook and this week’s Learning Team assignment (Pages 115-118). You will also want to access eCampus for additional resources. Due by Tuesday, September 25,
HEA530 Week 1 Assignment (20 Questions)
Week 1 Homework for HEA530 – Data-Driven Decision-Making in Higher Education (HEA530) Week 1 Discussion for HEA530 – Data-Driven Decision-Making in Higher Education (HEA530) Week 2 Assignment (20 Questions) for HEA530 – Data-Driven Decision-Making in Higher Education (HEA530) Week 2 Homework for HEA530 – Data-Driven Decision-Making in Higher Education (HEA530) Week 2 Discussion
HEA530 Week 1 Assignment Question (20 Questions)
for University of Phoenix. For more classes visit www.edadmission.com
HEA530 Week 1 DQ1 HEA530 Week 1 DQ2 HEA530 Week 2 DQ1 HEA530 Week 2 DQ2 HEA530 Week 3 DQ1 HEA530 Week 3 DQ2 HEA530 Week 4 DQ1 hea630 Week 4 DQ2 hea630 Week 5 DQ1 hea630 Week
HEA530 Week 1 Discussion 1 (20 Questions)
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HEA530 Week 1 DQ 1 (20 Questions)
– Statistics & Research for Assessment (Bentley) Course in the eTextbook. Read about Data-Driven Decision-Making in Higher Education (HEA530) – Statistics & Research for Assessment (Bentley) and other Textbooks at eCampus. Get Free Shipping on textbooks over $25!In this course, students will learn how to integrate data into their decision-making processes with a focus on managerial decision-making.
Description: 1. 2 Chapter 1: Introduction and
HEA530 Week 1 Discussion 2 (20 Questions)
Discussion 2 This discussion will address the following: Evaluate the role of data and information in decision making. Demonstrate how to identify potential sources of data that can be used to make decisions. Identify potential applications of software packages for decision support in higher education.
Define an ethical issue related to data privacy for a case study provided by your instructor. From your course textbook, describe how a company could determine whether a survey is appropriate for that situation.
Discuss ways that effective human resource managers could communicate with employees using
HEA530 Week 1 DQ 2 (20 Questions)
Week 1 DQ 2 (20 Questions) for HEA530 – Data-Driven Decision-Making in Higher Education (HEA530) for $10.00 Add to cart
Discussion Forum For HEA530 Week 1 DQ 1
Please answer the following questions: • Using the readings from this week, address the following questions: a. What is a learning management system? b. How can a LMS help colleges and universities recruit better students and retain them once they
HEA530 Week 1 Quiz (20 Questions)
100% Updated! Be sure to try all the quizzes in this course. Find all of them here on the “Complete” page. Take quizzes in: Math, Science, History, English and more.
1. In higher education, students and faculty members are most likely to use an online search engine as a research tool to find information about courses offered at a university or college when:
they are looking for general information
they are looking for course descriptions
they are trying to locate course offerings that
HEA530 Week 1 MCQ’s (20 Multiple Choice Questions)
is a part of the Course HEA530. Select one (1) of the following questions to complete: 1. Please answer all questions in complete sentences and use technical terms, as applicable.
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HEA530 Week 2 Description
Week 2 Assignment: Data-Driven Decision-Making in Higher Education. For this assignment, you will use data to make decisions about a specific decision. You must select a decision that is representative of one of the primary strategic goals for your institution and/or area. This decision should be based on the findings in your Decision Maker Analysis (DMA) . Visit the website http://www.intellectia.com/ to access the dataset used for this assignment.
This document includes:
• Description of the
HEA530 Week 2 Outline
Week 2: Data-Driven Decision-Making in Higher Education (HEA530) Use the Web for your assignments and class work. Do NOT use electronic resources such as blogs, YouTube, etc. Please be advised that any unsolicited comments or materials posted on this site will be considered public record under the Family Educational Rights and Privacy Act (FERPA). Therefore, FERPA applies to the posting of any information (e.g., text, images, audio, video or data) that you
HEA530 Week 2 Objectives
Week 2 Discussion Question 1 (10 points) Week 2 Discussion Question 2 (10 points) Week 3 Objectives for HEA530 – Data-Driven Decision-Making in Higher Education (HEA530) Week 3 Discussion Question 1 (10 points) Week 3 Discussion Question 2 (10 points) Week 4 Objectives for HEA530 – Data-Driven Decision-Making in Higher Education (HEA530) Week 4 Discussion Question 1 (
HEA530 Week 2 Pre-requisites
Week 2: Week 2 (Optional) Discussion: Tolerance and Bias in Decision-Making Select a case study of a decision that you would like to understand more about. In this discussion, consider how the decision can be viewed from different perspectives. The following are examples of decision cases in which the decision maker has been biased: A community college president is considering changes to their requirements for graduation. She wants to make sure that any new requirements do not hurt the overall success of students or make the
HEA530 Week 2 Duration
Week 2 DQ 1 and DQ 2 HEA530 Week 3 Discussion 1 and DQ 3 HEA530 Week 3 Discussion 2 and DQ 4 HEA530 Week […]
Module: Health Information Systems The purpose of this assignment is to provide a brief overview of the Health Information Exchange (HIE) model. Use the technology in this module to create a report that outlines the HIE as it exists today. For the purposes of this assignment, “
HEA530 Week 2 Learning Outcomes
Week 2 Learning Outcomes for HEA530 – Data-Driven Decision-Making in Higher Education (HEA530) Week 2 Learning Outcomes for HEA530 – Data-Driven Decision-Making in Higher Education (HEA530) Week 2 Learning Outcomes for HEA530 – Data-Driven Decision-Making in Higher Education (HEA530) Week 2 Learning Outcomes for HEA530 – Data-Driven Decision-Making in Higher Education (HEA530)
HEA530 Week 2 Assessment & Grading
Week 2 Assignment Data-Driven Decision-Making in Higher Education (HEA530) by Week 2 Discussion Learning Team Information and Communication Technology in Higher Education (ITH
HEA530 Week 2 Suggested Resources/Books
Week 2 Suggested Resources/Books for HEA530 – Data-Driven Decision-Making in Higher Education (HEA530) from CHEA530 Week 1 DQs. Problem: How can you use data-driven decision-making to improve student engagement in higher education? This assignment provides an opportunity to demonstrate your ability to integrate the knowledge gained in the course and apply it to real-world issues in the field of student affairs. The Discussion Forum will provide you with the opportunity to discuss real world
HEA530 Week 2 Assignment (20 Questions)
– 6324 Week 2 Assignment (20 Questions) for HEA530 – Data-Driven Decision-Making in Higher Education (HEA530) – 6324 To purchase this material click below link http://www.homeworkbasket.com/HEA530-Data-Driven-Decisions.pdf CJA 434 Week 2 DQ 1,2 &3 CJA 434 Week 2 DQ 1,2 &3 CJA 434 Week 2 DQ
HEA530 Week 2 Assignment Question (20 Questions)
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HEA530 Week 2 Discussion 1 (20 Questions)
Final Examination (100 Questions)
WEEK 3 – Course Discussions
1. As a part of the discussion, explain why students might not utilize mobile technology in their education. How can this technology be helpful to them?
2. Explain why students would still need to learn how to properly use technology for online learning.
3. Discuss some of the benefits of using a virtual assistant or software that assists with content creation and organization on campus.
4. Discuss one way your school is or has been
HEA530 Week 2 DQ 1 (20 Questions)
(2.0, 30 points) For this assignment, you will create a presentation in which you analyze and describe the use of an information technology tool or set of tools for data analysis and reporting that is commonly used by academic or other institutional staff members who are charged with strategic decision-making and faculty oversight functions within their institutions. Be sure to include all applicable sections in your presentation, including Information Technology & Data Analysis Function (IT/DAF) Function, 13a – Student Enrollment Data,
HEA530 Week 2 Discussion 2 (20 Questions)
Week 2 Discussion 2 (20 Questions) for HEA530 – Data-Driven Decision-Making in Higher Education (HEA530) Created By: http://www.homework-desk.com
Workplace Integrity and Professional Ethics Essay
1537 words – 6 pages
1. Ethical principles and standards in the workplace are guidelines that individuals use to make decisions regarding the morality of their actions or behaviors. In today’s workplace, there is often a gray area where rules and regulations are
HEA530 Week 2 DQ 2 (20 Questions)
Textbooks: Financial Accounting, 9th Edition by R. C. Harrison, W. T. Riggins and J. I. Wetmore Week 2 Homework – Submit to Blackboard for assessment.
What do you understand by the term data-driven decision making in higher education?
Explain the importance of data in decision making?
Describe how decision making is used to build or improve an organization’s business model
HEA530 Week 2 Quiz (20 Questions)
from University of North Florida. The “I don’t get it” question is one of the most difficult to answer! This is because the assignments are designed in a way that allows us to see how each student applies academic theories to the real-world (or real-life) problem they are solving. 2, 2017 . See full list on cullabedepot. edu. Academic Advising can help you succeed at Fort Hays State University. Study Flashcards On HEA530
HEA530 Week 2 MCQ’s (20 Multiple Choice Questions)
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HEA530 Week 3 Description
Homework Help Analysis Presentation Overview • Purpose and Goal • Strategies for Creating an Effective Presentation • How to Understand the Objectives of This Assignment • Formatting and Style Guidelines • How to Post Your Presentation Materials (The Spreadsheet) Overview of the Assigned Readings: ★ ★ ★ ★ ★ Student Instructions: Note: The instructions provided in this section are for HEA530 week 3, not HEA530 week 3 assignment. To access the assignment, click on the assignment file under “Assignments” in your
HEA530 Week 3 Outline
MGMT 530 Week 1 Discussion Questions
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HEA530 Week 3 Objectives
Course Assignment for HEA530 Week 3 Data-Driven Decision-Making in Higher Education (HEA530) Week 3: Theoretical Frameworks of Research and … Read More
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HEA530 Week 3 Pre-requisites
– Course Hero
HEA530 Week 3 Pre-requisites for HEA530 – Data-Driven Decision-Making in Higher Education (HEA530) Discussion Questions
Question #1: What are the four pillars of data-driven decision-making? Which one is most important?
Answer: The four pillars of data-driven decision-making are:
The ability to see everything clearly and know what to do
The role of the leader in interpreting and communicating
The ability to see the whole picture
HEA530 Week 3 Duration
3.0 Course Learning Outcomes At the end of this course, students should be able to: (1) understand the concepts of data-driven decision-making in higher education; (2) demonstrate how Data Driven Decision Making is used in a variety of contexts within higher education; and (3) demonstrate practical application of data-driven decision making to make timely decisions in a variety of contexts within higher education. Course Requirements/Grading Standards