Timeroom: Spring 2023

Displaying 1 - 7 of 7 Results for: Subject = NSIA

NSIA 720 (M1) - Intelligence Analysis

Intelligence Analysis

Online Course Delivery Method: Online (no campus visits), EUNH
Credits: 4.0
Term: Spring 2023 - E-term III (01/17/2023 - 03/10/2023)
Grade Mode: Letter Grading
Class Size:   6  
CRN: 55106
In this class we define intelligence and focus on analysis. We identify intelligence organizations relationships with policymakers and the types of intelligence products they produce. Students will learn to identify and create intelligence requirements and the related variables and collection targets. We will explore analytical approaches and develop critical thinking skills. In this class we will define data, the causes of intelligence failures, and identify creativity in intelligence analysis.
Section Comments: Note early start date. Cross listed with NSIA 820
Instructor Approval Required. Contact Instructor for permission then register through Webcat.
Instructors: John Borek
Start Date End Date Days Time Location
1/17/2023 3/10/2023 Hours Arranged ONLINE

NSIA 820 (M1) - Intelligence Analysis

Intelligence Analysis

Online Course Delivery Method: Online (no campus visits), EUNH
Credits: 3.0
Term: Spring 2023 - E-term III (01/17/2023 - 03/10/2023)
Grade Mode: Letter Grading
Class Size:   14  
CRN: 55103
In this class we define intelligence and focus on analysis. We identify intelligence organizations relationships with policymakers and the types of intelligence products they produce. Students will learn to identify and create intelligence requirements and the related variables and collection targets. We will explore analytical approaches and develop critical thinking skills. In this class we will define data, the causes of intelligence failures, and identify creativity in intelligence analysis.
Section Comments: Cross listed with NSIA 720
Registration Approval Required. Contact Instructor or Academic Department for permission then register through Webcat.
Only listed majors in section: NAT SEC INT ANL
Instructors: John Borek
Start Date End Date Days Time Location
1/17/2023 3/10/2023 Hours Arranged ONLINE

NSIA 830 (M1) - National Security Research Design and Methods

NATSEC Research Methods

Online Course Delivery Method: Online (no campus visits), EUNH
Credits: 3.0
Term: Spring 2023 - E-term III (01/17/2023 - 03/10/2023)
Grade Mode: Letter Grading
Class Size:   20  
CRN: 55104
In this class students explore the differences between academic research and intelligence analysis. We will explore research design and how to select a research approach based on intelligence requirements. You will learn about the ethical conduct of social science research. Building on the framework of intelligence requirements you will learn how to define a research problem and develop related research questions, hypothesis, and design research using appropriate methods.
Registration Approval Required. Contact Instructor or Academic Department for permission then register through Webcat.
Only listed majors in section: NAT SEC INT ANL
Instructors: Bridget Nolan
Start Date End Date Days Time Location
1/17/2023 3/10/2023 Hours Arranged ONLINE

NSIA 840 (M1) - National Security Qualitative Research Design and Analysis

NATSEC Qualitative Research

Online Course Delivery Method: Online (no campus visits), EUNH
Credits: 3.0
Term: Spring 2023 - E-term IV (03/20/2023 - 05/11/2023)
Grade Mode: Letter Grading
Class Size:   20  
CRN: 55107
Qualitative research refers to meanings, concepts, definitions, characteristics, metaphors, symbols, and descriptions of phenomena for study in the natural world. In this class we make linkages to existing research theories and intelligence methodologies. We introduce case study research and design issues.
Only listed majors in section: NAT SEC INT ANL
Instructors: Bridget Nolan
Start Date End Date Days Time Location
3/20/2023 5/11/2023 Hours Arranged ONLINE

NSIA 860 (M1) - Survey Design and Analysis

Survey Design and Analysis

Online Course Delivery Method: Online (no campus visits), EUNH
Credits: 3.0
Term: Spring 2023 - E-term IV (03/20/2023 - 05/11/2023)
Grade Mode: Letter Grading
Class Size:   20  
CRN: 55108
In this course students will learn about surveys research. Questions such as ?What is a survey?? and ?Why conduct surveys?? will be posed and answered. Students will learn about ethical issues in survey design and methods. Additional topics include survey error, sampling, nonresponse issues, survey data collection strategies, and survey question design and errors.
Only listed majors in section: NAT SEC INT ANL
Instructors: Tracy Keirns
Start Date End Date Days Time Location
3/20/2023 5/11/2023 Hours Arranged ONLINE

NSIA 870 (M1) - National Security Quantitative Research Design and Analysis I

NATSEC Quantitative Research I

Online Course Delivery Method: Online (no campus visits), EUNH
Credits: 3.0
Term: Spring 2023 - E-term III (01/17/2023 - 03/10/2023)
Grade Mode: Letter Grading
Class Size:   20  
CRN: 55105
Quantitative Design and Analysis I introduces students to data and data analysis. The course provides an overview of statistical learning. Students will learn approaches for stating and refining research questions. We will employ the epicycles of analysis approach to conduct exploratory data analysis. Students will learn how to describe data and use appropriate counting techniques. Basic data visualization will be employed using R.
Registration Approval Required. Contact Instructor or Academic Department for permission then register through Webcat.
Only listed majors in section: NAT SEC INT ANL
Instructors: Katharine Cunningham
Start Date End Date Days Time Location
1/17/2023 3/10/2023 Hours Arranged ONLINE

NSIA 890 (M1) - National Security Quantitative Research Design and Analysis II

NATSEC Quantitative Res II

Online Course Delivery Method: Online (no campus visits), EUNH
Credits: 3.0
Term: Spring 2023 - E-term IV (03/20/2023 - 05/11/2023)
Grade Mode: Letter Grading
Class Size:   20  
CRN: 55109
In this course students will develop a data science tool kit they may use to investigate research questions. The methodological approaches students will be exposed to include linear regression, classification, resampling methods, linear model selection, tree-based methods, unsupervised learning, and network analysis. Ethical approaches to the use of data science are reviewed in this class.
Only listed majors in section: NAT SEC INT ANL
Instructors: Katharine Cunningham
Start Date End Date Days Time Location
3/20/2023 5/11/2023 Hours Arranged ONLINE