May 19, 2024  
Graduate Record 2020-2021 
Graduate Record 2020-2021 [ARCHIVED RECORD]

Quantitative Analytics in Education and the Social Sciences (MEd)

Return to: Curry School of Education and Human Development: Departments/Programs  

The purpose of the proposed MEd in Quantitative Analytics is to prepare students to use rigorous data analysis to inform and improve research, management, and policy decisions in education and the social sciences. The program will provide students with a deep understanding of quantitative analytics, assessment tools and methodologies, and dynamic data reporting. Students will learn to undertake research, effectively communicate research findings and implications, and help inform data-based decisions and assessments. The program will provide students with specific coursework to harness data to address critical social and education issues across the nation. Graduates of the proposed program will be prepared to design research projects; implement surveys and studies; and collect, organize, analyze and report on data to underpin fact-based decision making. The program will prepare graduates to work as researchers and analysts in education systems and institutions, local, state and national government, testing companies, educational think tanks and start-ups, and city, state and federal departments of education, as well as to pursue doctoral study in the related academic disciplines that require quantitative analysis.

Curriculum Requirements

The Master of Education in Quantitative Analytics in Education and the Social Sciences is a 30-credit hour degree program. An independent capstone study will be required.

The curriculum is designed to provide students with prior statistics experience with a core foundation in advanced quantitative research and analysis in education and the social sciences. Students who need to acquire prerequisite statistical knowledge will complete the foundational course EDLF 5330 – Quantitative Methods and Data Analysis I or similar, before beginning the program.

The curriculum covers the core components of quantitative research design, analysis and assessment, with a focus on large sets of education and demographic data. Required courses will train students to analyze and understand large sets of data through course-based application of key analytics tools and software to real-world research problems. Throughout the core curriculum, course materials and class discussions will situate research questions and designs in an educational context, preparing students to understand and incorporate the needs of districts, schools, and educators in their analyses and recommendations. Students will be exposed to a variety of theoretical and philosophical conceptions of research designs, as well as readings and examples of various designs – e.g. cross-lagged designs, randomized control trials, and collecting survey data.  Students will learn to evaluate and apply suitable measurement, survey, and research designs, including tests and surveys. Coursework will educate students in the creation and management of large databases and prepare them to draft and interpret research reports and communicate analytics results and insights to broad audiences. The core curriculum will provide multiple opportunities for students to present their research findings in written and verbal forms, including presenting the results of their work in standard journal and popular press formats.

Restricted electives will provide students with additional breadth and depth in quantitative research and analysis, and education policy and assessment. A limited number of qualitative methods courses will be offered for students who want to incorporate these skills into their program of study. Students will select restricted electives in consultation with a faculty advisor, allowing them to pursue their interests and tailor the degree program to their personal career goals.

The required capstone will provide students with the opportunity to engage in an independent, semester-long research or internship study, through which they will integrate and apply their knowledge and skill in quantitative research design, assessment and analysis, and present their findings in a final paper.

Program Requirements

The Master of Education in Quantitative Analytics in Education and the Social Sciences is a 30-credit hour degree program.

Core Courses: 21 credit hours

  • EDLF 5310 – Data Management for Social Science Research (3 credits)
  • EDLF 7180 – Tests and Measurements (3 credits)
  • EDLF 7420 – Quantitative Methods II – General Linear Models (3 credits)
  • EDLF 8310 – Generalized Linear Models (3 credits)
  • EDLF 8360 – Multilevel Modeling in Education Research (3 credits)
  • EDLF 8361 – Structural Equation Modeling (3 credits)
  • EDLF 5993 – Independent Study (3 credits)

Restricted Electives: 9 credit hours

Students will select three (3) courses from the following prescribed list:

  • EDLF 6080 – Education Policy (3 credits)
  • EDLF 7300 – Foundations of Educational Research (3 credits)
  • EDLF 7330 – Single-Subject Research (3 credits)
  • EDLF 7402 – Program Evaluation (3 credits)
  • EDLF 7404 – Qualitative Methods (3 credits)
  • EDLF 7410 – Mixed Methods Research Design (3 credits)
  • EDLF 8311 – Design and Analysis of Field Experiments (3 credits)
  • EDLF 8315 – Causal Inference in Education Policy Research (3 credits)
  • EDLF 8380 – Special Topics in Qualitative Methods – Case Study Research (3 credits)
  • EDLF 8440 – Advanced Qualitative Analysis (3 credits)

Total: 30 credit hours

Description of Capstone Experience

For their capstone experience, students will be required to complete an independent study in their final semester. They will have the option to complete either a research project or internship, and then produce a final paper of approximately 25 pages. For a research project, the student will work closely with a faculty advisor on original research or comprehensive literature review. If conducting original research, the student must make a significant contribution to the work, though the student need not be the sole contributor (i.e., lead author). For a research internship, the student will complete a 40-hour internship with an organization in which they can obtain practical experience in data analytics, and produce a formal report documenting and reflecting on the experiences gained. The final paper will be graded and must meet a minimum of a B-. If a student does not meet the minimum grade requirement, the Program Director will meet with the student to determine a set of revisions and/or alternative academic activities to complete their project. A second grade below a B- will result in dismissal from the degree program.