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CRIM 495 - Internship
Credits: Three (3)
This course is designed as a culminating experience to integrate theory and practice in the context of an approved field-based experience under the supervision of the course instructor. Practicum requires completion of 135 clock hours on site along with coursework relevant to the student’s field experience.
General Education Area: Social Science
Prerequisite: PSYC-101,PSYC-101F, PSYC-202H, SOC-101, SOC-101F or SOC-202H; Minimum grade C-
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CRIM 496 - Independent Study
Credits: One (1) to Four (4)
Junior or senior level students may design and conduct an
independent study project in a field of their interest under the
direction of a faculty advisor.
General Education Area: Social Science
Prerequisite: One 200 level or higher CRIM course
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CRIM 497 - Special Studies
Credits: One (1) to Four (4)
These courses are offered periodically based on the interests of our students and faculty.
General Education Area: Social Science
Prerequisite: CRIM-102
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DSCI 200 - Foundations of Data Science
Credits: Three (3)
The course develops the core concepts and skills in statistical inference and computational techniques through working on real-world data. The course is to introduce the foundation of data science to entry-level students who have not previously taken statistics or computer science courses.
Prerequisite: MATH-117
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DSCI 201 - Math Modeling-Excel
Credits: Three (3)
Students receive basic training in Microsoft Excel. A variety of real-life math models will provide the context for developing spreadsheet proficiency, including functions and formulas, pivotal tables, statistical analysis, numerical solutions, optimization and graphical output. Other areas to be covered include database applications and basic application programming techniques.
Prerequisite: MATH-117
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DSCI 297 - Special Studies
Credits: Variable
Prerequisite: Permission of Program Director
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DSCI 301 - Math Modeling-VBA
Credits: Three (3)
The content focuses on business applications including finance, statistics, and mathematical modeling. The applications provide the context for developing programming skills, using the Visual Basic Applications language as the programming vehicle.
Prerequisite: MATH-117
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DSCI 302 - Introduction to R
Credits: Three (3)
This course covers practical issues in data analysis and graphics that includes programming in R, debugging R codes, Jupyter Notebook, cloud computing, data exploration and data visualization. Project based learning is used to help students develop effective problem solving skills and effective collaboration skills.
Prerequisite: MATH-117
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DSCI 303 - Introduction to Python
Credits: Three (3)
This course covers data types, statements, expressions, control flow, top Python core libraries (NumPy, SciPy, Pandas, Matplotlib and Seaborn) and modeling libraries (Statsmodels and Scikit-learn). Project based learning is used to help students develop effective problem solving skills and effective collaboration skills.
Prerequisite: MATH-117
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DSCI 304 - Introduction to SQL
Credits: Three (3)
This course is for students who want to enhance their SQL skills through exploring real-world examples. Topics covered include but are not limited to pattern-matching using regular expressions, analytical functions, common table expressions. Students are expected to be able to construct advanced SQL queries to retrieve desired information from the database and solve real-world problems
Cross-listed: DSCI-504
Prerequisite: MATH-117
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DSCI 307 - SAS Programming
Credits: Three (3)
This class is an introduction to the SAS programming language. Topics include reading, exporting, sorting, printing, and summarizing data; modifying and combining data sets; writing flexible code with the SAS macro facility; visualizing data; and performing descriptive and basic statistical analyses such as Chi-square tests, T-Tests, ANOVA, and regression.Project based learning is used to help students develop effective problem solving skills and effective collaboration skills.
Prerequisite: DSCI-200
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DSCI 314 - Text Mining
Credits: 3
This course covers text analytics extracting the useful information hidden in the unstructured text such as social media, emails and web pages using R/Python. Topics include corpus, transformations, metadata management, term document matrix, world cloud and topic models. Project based learnings is used to help students develop effective problem solving skills and effective collaboration skills.
Prerequisite: DSCI-303
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DSCI 318 - Statistical Design
Credits: Three (3)
This course covers principles of experiments and basic statistics using R/SAS. Topics include analysis of variance, different designs, analysis of covariance, mixed model, categorical data analysis , survey data analysis, sample size and power analysis and model comparison. Project based learning is used to help students develop effective problem solving skills and effective collaboration skills.
Prerequisite: MATH-316
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DSCI 324 - Data Visualization
This course is intended for students with introductory experience in SQL, R, and Excel. In this course students will learn how to connect SQL Server to tools like Excel, R and Tableau, and how to leverage the database engine to manipulate large amounts of data for data analysis tasks. Students will learn how to create analytical plots in Excel and R and how to follow best practices for creating report-quality graphs and presentations. Students will learn to use R Markdown so that their analysis follows the reproducible research paradigm. Finally, students will learn to build reporting and analytics dashboards in Shiny and Tableau. This course will be project based. By the end of the class, the students will have a portfolio of analytical work completed inside and outside of class.
Cross-listed: DSCI-624
Prerequisite: DSCI-302 and DSCI-304
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DSCI 393 - Cooperative Education
Credits: Variable
Cooperative Education is a structured method of combining classroom-based education with practical work experience. A cooperative education experience, commonly known as a “co-op”, provides academic credit for structured job experience. Cooperative Education is taking on new importance in helping young people to make the school-to-work transition, service learning, and experiential learning initiatives.
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DSCI 397 - Special Studies
Credits: Variable
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DSCI 408 - Machine Learning
Credits: Three (3)
This is an introductory course intended primarily for students majoring or minoring in Applied Statistics, Data Science or Actuarial Science. This course may also be useful for those using predictive modeling techniques in business, economics or research applications. The main focus of this course is to understand the basic operations and applications of what we currently call machine learning. This course will cover material from several sources. A few main topics that will be covered include: how machine learning differs from traditional programming techniques, data manipulation and analysis, some basic coding skills and an introduction to some of the tools available for data scientists. Specific application techniques will include the following (as time permits): data acquisition, classification, regression, overfitting, supervised and unsupervised training, normalization, distance metrics, k-means clustering, error calculation, optimization training, tree-based algorithms (including random forests), frequent item sets and recommender systems, sentiment analysis, neural networks, genetic algorithms, visualizations, and deep learning (including an introduction to convolutional neural networks and generative adversarial networks).
Prerequisite: DSCI-302 or DSCI-303
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DSCI 409 - Forecasting Principles
Credits: 3
This course is designed to provide a practical overview of forecasting practices and methodologies. The course will follow more of a “cookbook” approach rather than classical academic course. This course can benefit a wide range of audience from actuarial and data science students to “accidental” data analysts who trained in the sciences, business, or engineering and then found themselves confronted with data for which they have no formal analytic training. In this course, different type of sequential information (such as financial or sales data) will be analyzed and several mathematical models that might be used to describe the processes which generate these types of data will be demonstrated. The end goal is to develop a set of skills to build a forecast model that provides intelligence about what might be expected in the future.
Prerequisite: DSCI-302
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DSCI 412 - Predictive Modeling
Credits: Three (3)
This course prepares students with the fundamental statistical learning and real world business problems. Topics include generalized linear model, tree based models, clustering methods and principal components analysis. It provides students key steps and considerations in building predictive model, selecting a best model and effectively communicating the model results. Project based learning is used to help students develop effective problem solving skills and effective collaboration skills.
Prerequisite: DSCI-302 or DSCI-303
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DSCI 417 - Big Data Analytics
Credits: Three (3)
This course targets data scientists and engineers. It covers programming with RDDS, Tuning and debugging Spark, Spark SQL, Spark steaming and machine learning with MLlib. It provides students the tools to quickly tackle big data analysis problems on one machine or hundreds. Project based learning is used to help students develop effective problem solving skills and effective collaboration skills.
Prerequisite: DSCI-303
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DSCI 419 - Deep Learning
Credits: Three (3)
This course is an introduction to deep learning with the development and application of advanced neural networks. It covers convolutional neural networks, recurrent neural networks, generative adversarial networks, Hopfield networks and Boltzmann machines. Project based learning is used to help students develop effective problem solving skills and effective collaboration skills.
Prerequisite: DSCI-408
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DSCI 501 - Math Modeling
Credits: Three (3)
The course covers Microsoft Excel skills and Visual Basic Applications. A variety of real-life problems will provide the context for developing spreadsheet proficiency, including functions and formulas, pivot tables, data tables, and charts. Other areas to be covered related to data include importing and exporting data, data protection, filtering data, examples of data management, and handling the outputs from other valuation software
Note: This course is for graduate students only.
Cross-listed: DSCI-301
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DSCI 502 - R Programming
Credits: Three (3)
This course covers practical issues in data analysis and graphics that includes programming in R, debugging R codes, Jupyter Notebook, cloud computing, data exploration and data visualization. Project based learning is used to help students develop effective problem solving skills and effective collaboration skills.
Note: This course is for graduate students only.
Cross-listed: DSCI-302
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DSCI 503 - Python
Credits: Three (3)
This course covers data types, statements, expressions, control flow, top Python core libraries (NumPy, SciPy, Pandas, Matplotlib and Seaborn) and modeling libraries (Statsmodels and Scikit-learn). Project based learning is used to help students develop effective problem solving skills and effective collaboration skills.
Note: This course is for graduate students only.
Cross-listed: DSCI-303
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DSCI 504 - SQL
Credits: Three (3)
This course is for students who want to enhance their SQL skills through exploring real-world examples. Topics covered include but are not limited to pattern-matching using regular expressions, analytical functions, common table expressions. Students are expected to be able to construct advanced SQL queries to retrieve desired information from the database and solve real-world problems.
Note: This course is for graduate students only.
Cross-listed: DSCI-304
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DSCI 507 - SAS Programming
Credits: Three (3)
This class is an introduction to the SAS programming language. Topics include reading, exporting, sorting, printing, and summarizing data; modifying and combining data sets; writing flexible code with the SAS macro facility; visualizing data; and performing descriptive and basic statistical analyses such as Chi-square tests, T-Tests, ANOVA, and regression. Project based learning is used to help students develop effective problem solving skills and effective collaboration skills.
Note: This course is for graduate students only.
Cross-listed: DSCI-307
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DSCI 508 - Machine Learning
Credits: Three (3)
This is an introductory course intended primarily for students majoring or minoring in Applied Statistics, Data Science or Actuarial Science. This course may also be useful for those using predictive modeling techniques in business, economics or research applications. The main focus of this course is to understand the basic operations and applications of what we currently call machine learning. This course will cover material from several sources. A few main topics that will be covered include: how machine learning differs from traditional programming techniques, data manipulation and analysis, some basic coding skills and an introduction to some of the tools available for data scientists. Specific application techniques will include the following (as time permits): data acquisition, classification, regression, overfitting, supervised and unsupervised training, normalization, distance metrics, k-means clustering, error calculation, optimization training, tree-based algorithms (including random forests), frequent item sets and recommender systems, sentiment analysis, neural networks, genetic algorithms, visualizations, and deep learning (including an introduction to convolutional neural networks and generative adversarial networks)
Note: This course is for graduate students only.
Cross-listed: DSCI-408
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DSCI 512 - Predictive Modeling
Credits: Three (3)
This course prepares students with the fundamental statistical learning and real world business problems. Topics include generalized linear model, tree based models, clustering methods and principal components analysis. It provides students key steps and considerations in building predictive model, selecting a best model and effectively communicating the model results. Project based learning is used to help students develop effective problem solving skills and effective collaboration skills.
Note: This course is for graduate students only.
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DSCI 598 - Capstone Project
Credits: Three (3)
The Capstone Project course is for the students to apply the knowledge acquired during the Data Science program to a company project involving actual data in a realistic setting. Students will engage in the entire process of solving a real-world data science project, from collecting and processing actual data to applying suitable and appropriate analytic methods to the problem.
Note: This course is for graduate students only.
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DSCI 609 - Forecasting Principles
Credits: 3
This course is designed to provide a practical overview of forecasting practices and methodologies. The course will follow more of a “cookbook” approach rather than classical academic course. This course can benefit a wide range of audience from actuarial and data science students to “accidental” data analysts who trained in the sciences, business, or engineering and then found themselves confronted with data for which they have no formal analytic training. In this course, different type of sequential information (such as financial or sales data) will be analyzed and several mathematical models that might be used to describe the processes which generate these types of data will be demonstrated. The end goal is to develop a set of skills to build a forecast model that provides intelligence about what might be expected in the future.
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DSCI 613 - NOSQL Database
Credits: Three (3)
This course covers no-relational database on a large scale. Topics include MongoDB, Cassandra, Redis, HBase and Neo4j. Project based learnings is used to help students develop effective problem solving skills and effective collaboration skills.
Note: This course is for graduate students only.
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DSCI 614 - Text Mining
Credits: Three (3)
This course covers text analytics extracting the useful information hidden in the unstructured text such as social media, emails and web pages using R/Python. Topics include corpus, transformations, metadata management, term document matrix, world cloud and topic models. Project based learnings is used to help students develop effective problem solving skills and effective collaboration skills.
Note: This course is for graduate students only.
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DSCI 617 - Big Data Analytics
Credits: Three (3)
This course targets data scientists and engineers. It covers programming with RDDS, Tuning and debugging Spark, Spark SQL, Spark steaming and machine learning with MLlib. It provides students the tools to quickly tackle big data analysis problems on one machine or hundreds. Project based learning is used to help students develop effective problem solving skills and effective collaboration skills.
Note: This course is for graduate students only.
Cross-listed: DSCI-417
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DSCI 618 - Statistical Design
Credits: Three (3)
This course covers principles of experiments and basic statistics using R/SAS. Topics include analysis of variance, different designs, analysis of covariance, mixed model, categorical data analysis , survey data analysis, sample size and power analysis and model comparison. Project based learning is used to help students develop effective problem solving skills and effective collaboration skills.
Note: This course is for graduate students only.
Cross-listed: DSCI-318
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DSCI 619 - Deep Learning
Credits: Three (3)
This course is an introduction to deep learning with the development and application of advanced neural networks. It covers convolutional neural networks, recurrent neural networks, generative adversarial networks, Hopfield networks and Boltzmann machines. Project based learning is used to help students develop effective problem solving skills and effective collaboration skills.
Note: This course is for graduate students only.
Cross-listed: DSCI-419
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DSCI 624 - Data Visualization
Credits: Three (3)
This course is intended for students with introductory experience in SQL, R, and Excel. In this course students will learn how to connect SQL Server to tools like Excel and R and how to leverage the database engine to manipulate large amounts of data for data analysis tasks. Students will learn how to create analytical plots in Excel and R and how to follow best practices for creating report-quality graphs and presentations. Students will learn how to use tools like R Notebooks so that their analysis follows the reproducible research paradigm. Finally, students will learn to create simple web applications in R Shiny to build reporting and analytics dashboards. This course will be project based. By the end of the class, the students will have a portfolio of analytical work completed inside and outside of class.
Note: This course is for graduate students only.
Cross-listed: DSCI-324
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DSCI 625 - Blockchain
Credits: Three (3)
This course will introduce students to the workings and applications of this potentially disruptive technology. This course explores the fundamentals of the public, transparent, secure, immutable and distributed database called blockchain. Blockchains can be used to record and transfer any digital asset not just currency. Its potential impact on financial services, government, banking, contracting and identity management will be discussed. This course will be project based. By the end of the class, the students will have a portfolio of analytical work completed inside and outside of class.
Note: This course is for graduate students only.
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DSCI 697 - Thesis/Research
Credits: Three (3)
A master’s thesis is a piece of original scholarship written under the direction of a data science faculty advisor. Students need to write a data science academic paper in which a research question is developed and analyzed through original empirical and/or theoretical research, supplemented with a literature review. Students will do both a written final report and a presentation.
Note: This course is for graduate students only.
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ECON 201 - Macroeconomics
Credits: Three (3)
This course studies the overall economic activity and growth of a nation. Topics include the basic model of supply and demand, national-income accounting, the determinants of national income and employment, the meaning and measurement of inflation and unemployment, business cycles, the economics of money and banking, and the role of monetary and fiscal policies in influencing economic activity.
General Education Area: Social Science
Prerequisite: ENGL-104 OR ENGL-204H, and MATH-116 or higher; Minimum grade C-
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ECON 202 - Microeconomics
Credits: Three (3)
This course studies price theory (or the laws of supply and demand)
the market system, the economics of consumer-behavior and
firm-behavior, market structures, and government regulation of
business.
General Education Area: Social Science
Prerequisite: ENGL-104 or ENGL-204H; and MATH-116 or higher; Minimum grade C-
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ECON 470 - International Trade and Money
Credits: Three (3)
This course studies the economic principles involved in international trade and finance. It is designed to provide the student with the conceptual tools needed to analyze such international economic issues as import tariffs and quotas, import liberalization, loss of jobs to foreign countries, free-trade agreements, customs unions, monetary unions, and exchange-rate fluctuations. The general topics to be covered in this course include the pure theory of trade, the theory of trade policy (such as trade restrictions and economic integration), foreign-exchange markets and exchange rates, the international monetary system, and international economic institutions.
General Education Area: Social Science
Cross-listed: FIN-470
Prerequisite: ECON-201, and ECON-202
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ECON 497 - Spec Study in Economics
Credits: One (1) to Four (4)
General Education Area: Social Science
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ECON 620 - Business Economics
Credits: Three (3)
This course studies how economic forces can affect a business. Topics from both micro and macroeconomics are included: the basic supply and demand model, market fluctuations, elasticity of demand and revenues, production costs and profits of a firm, measures of economic performance, national output and income, inflation and unemployment, fiscal policy and the governments budget, money and monetary policy, and special topics in economic policy.
General Education Area: Social Science
Prerequisite: ACCT-509
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ECON 697 - Special Studies
Credits: One (1) to Four (4)
General Education Area: Social Science
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EDHL 735 - Advanced Research Methods
Credits: Variable: 0.0 - 3.0
This 16-week, (0-3) credit hour course provides candidates with a structured way to continue development of the Dissertation in Practice Proposal.
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EDHL 738 - Writing for Publication
Credits: 3.0
This doctoral-level writing course focuses on development of a manuscript for publication. The manuscript will be based on the student’s dissertation research. Students will identify journals for publication and revise their manuscript to meet each journal’s publishing standards.
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EDHL 750 - Reflective Leadership Practice and Inquiry
Credits: Three (3)
This course introduces students to historical and contemporary foundations of higher education with specific focus on ethical leadership and reflective practice. Students will be introduced to educational inquiry and build knowledge and skills in academic research and writing.
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EDHL 751 - The College Student Experience
Credits: Three (3)
Students will become familiar with higher education leadership from the perspective of the student experience through study of student development theory, student services, student engagement, and through application of theory to practice in student affairs.
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EDHL 752 - Leadership in Higher Education
Credits: Three (3)
This course provides a general overview of various aspects of leadership in higher education including theories, multiple frames approach, strategic planning, and various decision-making models.
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EDHL 753 - Educational Research Methods
Credits: Three (3)
Students will be able to identify educational research methodologies and methods and understand the importance of research design and paradigms.
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EDHL 754 - The Competitive Context of Higher Education
Credits: Three (3)
The context of higher education is an increasingly complex and increasingly competitive environment. This course discusses the contemporary and future roles of enrollment management, the nature and scope of institutions in higher education, and constituency engagement.
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EDHL 755 - Research Residency I
Credits: Three (3)
Students will be immersed in dissertation research and writing through workshops, presentations and critique groups.
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EDHL 756 - The Academic Community
Credits: Three (3)
In this comprehensive course students will develop strategies and leadership skills that will enable them to lead in an academic environment. Topics will include academic structure, governance, faculty tenure, emerging roles of faculty, and unions. Students will identify leadership roles in academic planning and curriculum development and will identify current and emerging issues in the academic environment in higher education.
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EDHL 757 - Organizational Leadership In Higher Education
Credits: Three (3)
Understanding the context of higher education prepares future leaders to confront most any issue if they have a grasp of organizational theory in higher education, power, conflict and crisis management, and organizational behavior.
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EDHL 758 - Understanding Data and Analysis
Credits: Three (3)
This course focuses on understanding the analysis of qualitative and quantitative data. Students will have the opportunity to learn different forms of analysis but can concentrate on the most appropriate type for their own study. Writing results and conclusions for a research study will also be discussed.
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EDHL 759 - Strategic Change and Innovation
Credits: Three (3)
Higher education is constantly evolving and changing. Future leaders must be prepared to understand, manage and implement change. This course focuses on change models, barriers and resistance to change, innovation and the future of higher education. Students will be exposed to the concept of design thinking as a tool for innovation in higher education.
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EDHL 760 - Research Residency II
Credits: Three (3)
The second residency includes presentations and workshops for advanced research and writing.
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EDHL 761 - Performance And Accountability
Credits: Three (3)
Leaders now and in the foreseeable future are held to many types of performance and accountability measures from different external and internal forces. This course discusses the role of assessment and data for decision-making, accreditation, and the basics of financial management.
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EDHL 762 - Leading in a Complex Environment
Credits: Three (3)
This course provides an overview of the key policy and legal issues in public and private higher education. Students will learn how policy, legal, and finance intersect and are integrated to solve complex problems.
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EDHL 763 - Dissertation Research And Writing
Credits: Three (3)
In this doctoral-level writing course, students focus on refinement of a manuscript for publication based on the student’s dissertation research. Students will revise and finalize their manuscript to meet their identified journal’s publishing standards.
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EDHL 764 - Portfolio and Oral Defense
Credits: Three (3)
This final course is to review and defend the comprehensive portfolio through a professional conversation and an oral presentation.
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EDHL 790 - Dissertation Proposal
Credits: Zero (0)
Each student will complete a proposal of the research study including the research idea, statement of the problem, its background and significance, a review of the literature, and a proposed methodology and research design to address the problem of practice in higher education leadership to be addressed in the study. The proposal must be approved by the end of the course and the student must receive a grade of P indicating approval of the proposal by the student’s faculty advisor/dissertation chair and program faculty members. Prerequisites: EDHL 750, 751, 753, 755
Prerequisite: EDHL 750, 751, 753 & 755
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EDHL 791 - Dissertation Defense
Credits: Zero (0)
Each student will prepare a formal presentation and orally defend the dissertation of practice. The EdD program is complete when the student’s dissertation chair, program faculty members, and program director give approval. Prerequisites: all required program coursework, EDHL 764 and EDHL 790.
Prerequisite: All required program coursework, EDHL 764 and EDHL 790
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EDL 601 - Knowing Yourself as Educational Leader
Credits: Three (3)
This course explores the nature of leadership, values-based leadership, the role of leader as change agent, and the ethics of leadership. A focus on the importance of creating a learning organization informs students of the importance of personal mastery, team learning, mental models, shared vision and systems thinking. Students explore their own leadership styles and are taught how to analyze their own organizations, compare them to current models of learning organizations and communities, and work with others to build collective vision.
Corequisite: EDL-605
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EDL 602 - Internship
Credits: Three (3)
The internship places the student in a position to integrate issues/content/skills from all coursework into a practical experience in public schools. The student works closely with a certified administrator mentor at the appropriate school level. In particular, this experience ensures that the student will have broad opportunities to use the maximum number of leadership skills learned throughout the program.
Note: The internship experience may be an intensive experience during summers or in a supervised internship during the entire calendar year.
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EDL 603 - Staff Observation and Performance-Based Evaluation
Credits: Three (3)
Sudents will learn and apply principles of staff evaluation including coaching, counseling, mutual goal setting, effective communication, data gathering, conflict resolution and listening. The candidate will examine current research on what constitutes good teaching, practice observing and conferencing with teachers, and create and practice trait-based interviewing.Participation in mentored evaluationexercises will emphasize effective dialogue and interventions, and successful interactions.
Note: Evaluation of certified teachers and support staff will be emphasized.
Prerequisite: EDL-601
Corequisite: EDL-611
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EDL 604 - Issues Seminars
Credits: Three (3)
Issues seminars are designed by the faculty and students with the express purpose of meeting defined needs, providing new information, and augmenting identified areas of further development and/or areas of deficiency based on the needs assessment of the cohort. They also can serve as continuing learning experiences for practicing administrators and program graduates in the immediate area
Prerequisite: EDL-601
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EDL 605 - Improving Student Achievement
Credits: Three (3)
This course focuses on developing skills of building level leaders to champion and facilitate the work of teacher teams to ensure the success of all students in the school. Development and analysis of curriculum goals and essential outcomes, best practices in instruction, as well as the development and appropriate use of quality assessment instruments form the framework of the course. The course will also explore national trends in curriculum, instruction and assessment, and will explore effective intervention strategies for enhancing student achievement.
Corequisite: EDL-601
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EDL 606 - Organizational Leadership in Schools
Credits: 3
This course is designed to be an overview of the theory and the practical components of leading organizations with specific emphasis on schools and school districts. Candidates will examine their own leadership skills and attributes and those associated with effective leadership. An introduction to systems thinking will allow candidates to understand that schools and school districts, as examples of all organizations, are living, dynamic entities and how that reality impacts leadership practice. Special attention will be placed on understanding change and leading change. Finally, each candidate will begin an Internship by selecting a mentor, preparing an Internship Proposal, and starting to acquire hours for that Internship.
Corequisite: EDL 658
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EDL 611 - The Principalship: Elementary, Middle School and High School
Credits: Three (3)
Primary emphasis will be placed on the idea that the school exists as a true learning community whereby the principal serves as a facilitator/servant leader in creating a climate of shared vision, decision-making, and responsibility for an organization devoted to learning for all students. Specific issues related to elementary, middle, and high school levels will be explored.Students need to integrate all aspects of the principalship so that a leader is prepared to be collaborative, reflective, inquiry- oriented, database driven, student-focused and goal-directed, not only for the school, but for the community around it. The role of the principal, in light of all previous coursework, will be explored. Students will explore curriculum, instruction, organizational development, assessment, staff development, organizational staffing and scheduling, vocational and special education, and other forces that influence the role of the educational leader in the school.
Prerequisite: EDL-601
Corequisite: EDL-603
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EDL 612 - Understanding Groups and Organizations
Credits: Three (3)
Students are introduced to the major concepts in organizational development and organizational behavior using the school as the operant model, focusing on understanding organizations as artifacts of the larger society. The class also incorporates the study of how the interaction of individuals within an organization contributes to its overall growth and development. Students explore the fundamental concepts of human relations while developing basic skills and effective techniques in understanding and managing group dynamics. The class provides opportunities for students to engage in reflective learning activities and reading in the areas of group process, building highly effective groups, developing cooperative interdependence in groups, vision building, effective communications, listening skills, conflict management and resolution, and effective communications between school and community.
Prerequisite: EDL-601
Corequisite: EDL-613
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EDL 613 - Understanding Environments: Legal,Social, Financial and Political
Credits: Three (3)
This course is an integrated approach to examining the external environment in which schools exist. As a systems approach to studying schools and their environments are inseparable and interactive, the course offers prospective school leaders with the basic knowledge of the legal,social, financial,and political realities in which their school will operate. Emphasis in the course is upon acquiring an understanding of the legal process and its’ ramifications, the fiscal responsibilities associated with being a principal, and the effects of decisions in the school on the community’s social and political environment.
Corequisite: EDL-612
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EDL 619 - Using Inquiry
Credits: Three (3)
This course is designed to provide students with the opportunity to use the action research model to evaluate the results of educational research for use in a variety of educational settings. Students will investigate the basic nature of educational research, along with pertinent methods of data collection and analysis. Students will leave the course comfortable with the reading of research and the production of an inquiry project. The major project for this class will be to complete the first two chapters of the final Capstone Experience
Prerequisite: EDL-601
Corequisite: EDL-658
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EDL 658 - Framing Issues: Using Data in Decision-Making and Curriculum Decisions
Credits: Three (3)
Learning how to collect, interpret and act upon data is essential for today’s administrator. This course examines the concepts of data management and data analysis. Case-based study of the formulation of action plans and decision making and policy formulation using data are emphasized, attending to the leader’s role in developing curriculum and supporting instruction.
Prerequisite: EDL-601
Corequisite: EDL-619
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EDL 696 - Independent Study
Credits: One (1) to Three (3)
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EDL 699 - Capstone-EDL
Credits: Three (3) to Six (6)
The EDL Capstone provides an opportunity for students to continue to complete chapters three and four of the research project started in EDL 619. Students will have already completed the initial research work on chapters one and two. This project provides an opportunity to analyze and reflect on one specific issue or problem related to Educational Administration. The Capstone involves a significant amount of independent work with the input and supervision of the Capstone instructor.
Prerequisite: EDL-619
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EDL 710 - Developing Myself as a Leader
Credits: Three (3)
Effectively leading others requires: a well-developed personal belief system, understanding the basic principles of leadership, full knowledge of one’s leadership strengths and areas for development, and how teams are created for success.In this course, each of those requirements will be explored and analyzed through readings, self-study instruments, analysis of current leaders, study of systems thinking, and simulation.The ethics of leadership will also be examined.The candidate will create his/her own personal leadership growth plan that will tie together the remaining six semesters of the program.
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EDL 711 - Introduction to Action Research
Credits: Three (3)
Teacher leaders must be able to critically interpret the research that they read in the professional literature as well as understand what research is necessary to promote k-12 student learning in their role. The current paradigm of “scientifically based research” changes the lenses through which educational research is being viewed.At the same time meaningful inquiry, through local projects (school or district wide) can produce extremely valuable information.In this course, candidates will examine research that informs and improves individual schools. Particular emphasis will be placed upon research related to student achievement and school improvement, including “Action Research”.This introductory course is designed to be the first in a series of three courses (EDL 711, EDL 712, and EDL 721) to guide the student through the process of developing and writing the final Capstone project. Candidates will review the methods of educational research and examine research that informs and improves individual schools. Using the action research model, particular emphasis will be placed upon research related to student achievement and school improvement. The guidelines for Research on Human subjects for each candidate’s district will be studied for their implications on the ability to do research and protect students throughout the processes. Chapters 1 andamp; 2 of the Capstone will be completed this semester.
Corequisite: EDL-710
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EDL 712 - Advanced Research For Teacher Leaders
Credits: Three (3)
Teacher leaders, both at the school and district levels, must be able to analyze complex research questions and data collections.As a continuation of Introduction to Action Research, this doctoral level research course will focus upon a rigorous, in-depth study of research design and implementation.The goal of this course will be to research and compose the Methodology (chapter three) for the final Capstone project. Students will understand the Institutional Review Board (IRB) process and have filed the appropriate forms for IRB approval. Students will have all surveys and forms ready to collect data and have started the process of collecting data pertinent to evaluate one’s capstone project. Statistical analysis using appropriate software for complex research with considerations of reliability and validity will be studied, as well as the scope of conclusions from research.The candidate will conceptualize his/her own research that culminates in the capstone experience.The major project for this class will be to complete chapter three and prepare to write chapters four and five.
Prerequisite: EDL-711
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EDL 713 - Practicum in Teacher Leadership
Credits: Three (3)
Under the direction of a mentor, chosen in tandem with the candidate’s school district and the Maryville advisor, the candidate will begin an in depth and extended practical experience with the area of teacher leadership as the focus. The experience should consist of a minimum of 300 hours to be completed over the course of the EdD program. The practicum must include on-site experiences across a range of district and school level curriculum, instruction, assessment and professional development work to develop expertise in the field of teacher leadership. Examples of appropriate experiences include observations and/or leadership of the curriculum development process, observation and analysis of current pedagogical strategies, analysis of student achievement data to determine building and district level professional development needs etc. The final product will in part be the development of a significant professional development experience to be made available free of charge, either in the candidates district or as an institute held at Maryville University, for teachers in the St Louis Region.
Prerequisite: EDL-710
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EDL 714 - Understanding Systems Thinking and the Change Process
Credits: Three (3)
This course focuses on the comprehensive development of the Teacher Leader Standards and Program Theme Two: developing leaders who are change agents, and who are capable of both initiating positive change and sustaining change through sound organizational skills and an orientation toward collaborative decision making.A focus on the importance of creating a learning organization informs students of the importance of personal mastery, team learning, mental models, shared vision and systems thinking. Emphasis will be given to acquiring the knowledge, dispositions and skills enabling candidates to design and lead professional development opportunities. Readings and interviews will target the analysis and application of successful change efforts.
Prerequisite: EDL-710
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EDL 715 - Adult Learning and Professional Development
Credits: Three (3)
The course will explore the characteristics of adult learners and their unique needs. Current research and best practices in adult learning and coaching will inform the activities in this course. Candidates will focus on strategies to build a climate of trust, model best practices, observe teachers, and facilitate reflective conversations within a school building and analyze district professional development policies, plans and implementation strategies.
Prerequisite: EDL-710
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EDL 716 - Curriculum Design and Development
Credits: Three (3)
Teacher leaders must be well versed in the theories and contexts that govern curriculum development and implementation to ensure the highest quality curriculum to guide instruction. This course will explore the curriculum development process from an historical perspective to build a foundation for understanding how curriculum and instructional practices have evolved over time. The development of a guaranteed and viable curriculum, based on the Common Core Standards, that maximizes students’ achievement of performance standards will be emphasized as instructional strategies and assumptions guiding teachers’ choices in curriculum and instruction are examined. The role of assessment as integral to determining the needs and setting priorities will also be a major component of the course. Good principles of staff development will also be explored to allow the teacher leader to build a collaborative community of professionals within his or her school to review and modify the instructional programs as needed.
Prerequisite: EDL-710
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EDL 717 - Assessment Literacy and Data Analysis for Teacher Leaders
Credits: Three (3)
With accountability legislation and mandates to show consistent improvement on standardized test scores, teacher leaders must understand how to develop and implement quality balanced systems of assessment. This understanding is critical if teachers are to leverage the power of assessment not only to provide timely information regarding student achievement (i.e. assessment of learning), but also to enhance student learning (i.e. assessment for learning).Teacher leaders must also have a working knowledge of the concepts and practical tools of data analysis, the multiple measures of data and their interactions, the tools to derive data, and the knowledge of how to use that data to improve learning. Throughout the course, the candidate will concentrate on:
- Improving existing systems of assessment within his/her school/district
- Understanding the data team process and how to facilitate this process with teachers in his/her school/district
- Designing professional development opportunities to help teachers build their understanding of how to develop and use assessments
Prerequisite: EDL-710
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EDL 718 - Leading Professional Development Institutes
Credits: Three (3)
The final practicum, comprehensive reflective journal, and conversation for the Maryville University Doctorate in Teacher Leadership program will bring into play the recurring themes, elements and experiences developed over the seven-semester program of studies. The processes employed to complete the experience are as critical to the worthiness of the effort as is the final product. At its conclusion, the product should contribute to the solution or the completion of a real-world challenge and the student will have demonstrated growth as a real world teacher leader.
Prerequisite: EDL-715
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EDL 719 - Classroom Teaching and Learning Strategies
Credits: Three (3)
This course will examine current research on effective teaching strategies to enhance student learning, particularly in the PK-12 setting. Candidates will apply their learning from previous coursework, specifically EDL 716 (Curriculum Design and Development) and EDL 717 (Assessment Literacy and Data Analysis for Teacher Leaders) to design, implement, evaluate, and recommend a pedagogical approach focusing on high impact instructional strategies appropriate for implementation within an individual classroom and across schools.
Prerequisite: EDL-716 and EDL-717
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EDL 720 - Strategies For Teacher Leadership I
Credits: Two (2)
Candidates will select modules from a variety of offerings intended to give in-depth learning and experience in areas of special interest.Experts in the topics will serve as adjunct professors for these intense exposures to specific content.Reflection and application will be the key assessment features for each module.The modules are created to build upon and enhance the strategies required for the candidate to perform the leadership position being trained for and desired.Possible module topics include, but are not limited to: cognitive coaching, adult learners, teaching how to teach, RTI, Understanding by Design, learning walks, specific content instruction, character education, assessment literacy, adaptive schools, data teams, etc.
Prerequisite: EDL-710
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EDL 721 - Strategies For Teacher Leadership II - School Law
Credits: 3
Candidates will be introduced to major topics in school law including school and state, school and students, teachers and the law, desegragtion, IDEA, FERPA, and other issues impacting school operations.
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EDL 722 - Strategies For Teacher Leadership III - School Finance
Credits: 3
Candidates will be introduced to the basic financial operations of public schools at the building and district levels.
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EDL 723 - Issues in Moral Leadership
Credits: Three (3)
Teacher Leaders will examine social, political, and critical moral issues of the day through the lens of the knowledge gained in the first six semesters. A variety of protocols for professional conversation and systems thinking tools will be used to stimulate in-depth dialogue and discussion regarding current issues in education. Selected texts, current articles from newspapers, journals and other appropriate sources, as chosen by the cohort, may be used as well. The final individual product will be a re-examination of each candidate’s This I Believe statement.
Prerequisite: EDL-710
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EDL 724 - Capstone and Culminating Experience
Credits: Three (3)
This course is the culminating experience of the Ed.D. program and will bring into play the recurring elements and themes developed over the seven-semester program. The candidates will, through the use of the Teacher Leader Standards, illustrate with documentation and reflections on projects, class assignments, and materials generated in their daily job, the growth experienced throughout the program. The candidate will complete with the help of their advisor, including:
All parts of the Capstone project and have the final product approved by the Capstone instructor.
A presentation of the final Capstone to the cohort of peers
Conduct a final conversation, led by the candidate, with Maryville faculty and guests covering the growth during the program.
Complete the Comprehensive Process Reflection
Prerequisite: EDL-712
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EDL 730 - Renew/Re-Examine Yourself As An Educational Leader
Credits: Three (3)
In this course, each candidate will engage in an extensive self-examination with respect to leadership skills, styles, and dispositions to guide the candidate in developing the initial draft of a personal leadership growth plan. A series of contemporary readings about effective leadership from both inside and outside education will help define and support the three themes of our program. Candidates will begin the key program components: the portfolio, personal leadership growth plans, internship and capstone project.
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EDL 731 - Introduction to Research
Credits: Three (3)
This course is designed to be the first in a series of three courses (EDL 731, EDL 735, and EDL 744) to guide the student through the process of developing and writing the final Capstone project. Candidates will review the methods of educational research and examine research that informs and improves individual schools, organizations and universities. Using the action research model, particular emphasis will be placed upon research related to organizational, school, college or university improvement.
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EDL 732 - Skills for Data-Driven Leadership
Credits: Three (3)
This course will develop a working knowledge of the concepts and practical tools of data analysis, how to effectively derive and interpret data from multiple sources, and how to use this data to improve higher education systems and student learning. The candidate will concentrate on obtaining and interpreting relevant data to evaluate and improve higher education programs, faculty, and staff. Accreditation and accountability measures will be reviewed and analyzed. Legal issues in higher education and schooling will be explored.
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EDL 733 - Understanding Change Process
Credits: Three (3)
This course focuses on the comprehensive development of Program Theme Two: developing leaders who are change agents, and who are capable of both initiating positive change and sustaining change through sound organizational skills and an orientation toward collaborative decision making. Emphasis will be given to acquiring the knowledge, dispositions and skills to effectively lead change efforts to accomplish substantive school and university improvement. Reform models in the history, philosophy and sociology of higher education will be explored.
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EDL 734 - Curriculum, Instruction, and Assessment
Credits: Three (3)
The course will provide students with the knowledge and understanding of curriculum design, development, and change in higher education. Co-curricular and learning-centered practices will be explored. A focus on the Scholarship of Teaching and Learning will assist students in developing a focus on teaching for understanding. Candidates will engage in collaborative discussions and project development designed to foster deeper understanding of curriculum, instruction and assessment and to develop effective leadership skills to guide continuous improvement of student learning.
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EDL 735 - Advanced Research For Leaders
Credits: Two (2)
The goal of this course will be to research and compose the (Methodology) for the final Capstone project. Students will understand the Institutional Review Board (IRB) process and have filed the appropriate forms for IRB approval. Students will have all surveys and forms ready to collect data and have started the process of collecting data pertinent to evaluate one’s Capstone project. Statistical analysis using appropriate software for complex research with considerations of reliability and validity will be studied.
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EDL 737 - Student Development, Student Service, Student Retention
Credits: Three (3)
Historical overview of student development theory, student life, research and literature relating to contemporary college students and student services. In addition this course introduces students to relevant research, theory, and practice related to college student retention and persistence. Students explore cultural, institutional, and individual factors that may impact college student persistence and critically examine theories attempting to explain why students leave college. Effective retention practices, programs, and assessment procedures are also identified and examined.
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EDL 738 - Policy Making and Leadership in Higher Education
Credits: Three (3)
This course provides an overview of the missions, governance, and organizational structures of American higher education institutions. The unique system of governance in higher education is explored, including administrative roles, responsibilities, and leadership issues for administrators, faculty and staff. Institutional, system, state, and federal governing mechanisms as they relate to each other are also explored. At all levels, the effective higher education leader will understand the interplay of historical legacy, public policy, internal and external organizational and governing structures, and individual roles, and how to navigate these areas to effect sound decision making that supports academic integrity while addressing the needs of higher education as a business entity.
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