Learning Analytics (LAPS)

Courses

LAPS 5310. LEARNING ANALYTICS FUNDAMENTALS. 3 Hours.

Introduction to foundational elements in the emerging field of learning analytics, including theory, philosophy, ethics, teamwork, processes, tools, and relationship with other fields.

LAPS 5320. EXPERIMENTAL DESIGN & METHODOLOGY. 3 Hours.

Statistical methods for the design and analysis of experiments in learning analytics research.

LAPS 5330. PSYCHOLOGY OF LEARNING & LEARNING SCIENCES. 3 Hours.

Exploration of knowledge construction, decision-making, and belief forming, including psychological and biological functions, and key influences on the learning process.

LAPS 5340. BIG DATA METHODS. 3 Hours.

The collection, analysis, and reporting of large-scale educational datasets, including consideration of different types of information, governing policies, and data stewardship.

LAPS 5350. PRIVACY & ETHICS IN LEARNING ANALYTICS. 3 Hours.

Ethical considerations for the collection and use of learning data, including access, ownership, contexts, obligations, storage, security, policy, transparency, and algorithms.

LAPS 5360. INTRODUCTION TO DATA ANALYSIS AND R. 3 Hours.

Fundamental elements of conducting data analysis in the R programming language, including basic operations, data structures, dataset cleaning and manipulation, and visualization.

LAPS 5370. INTRODUCTION TO STATISTICAL ANALYSIS. 3 Hours.

This course will provide students who receive probationary admission due to an inadequate mathematical background with the core principles of statistical analysis necessary to be successful in the program. Prerequisite: Completion of LAPS 5310, LAPS 5320, LAPS 5330, and LAPS 5340 or LAPS 5360.

LAPS 5375. PROBABILITY AND STATISTICAL INFERENCE. 3 Hours.

Examination of probability, distributions, estimation, and hypothesis testing in learning contexts. Prerequisite: Completion of LAPS 5310, LAPS 5320, LAPS 5330, and LAPS 5340 or LAPS 5360.

LAPS 5376. APPLIED REGRESSION ANALYSIS. 3 Hours.

A comprehensive review of different regression models that emphasizes modeling, inference, diagnostics, and application to educational datasets. Prerequisite: Completion of LAPS 5310, LAPS 5320, LAPS 5330, and LAPS 5340 or LAPS 5360.

LAPS 5377. LINEAR MODELS AND EXPERIMENTAL DESIGN. 3 Hours.

In-depth exploration of univariate and multivariate linear models to derive inferential procedures depending on appropriate learning contexts. Prerequisite: Completion of LAPS 5310, LAPS 5320, LAPS 5330, and LAPS 5340 or LAPS 5360.

LAPS 5378. MULTIDIMENSIONAL SCALING AND CLUSTERING. 3 Hours.

In-depth study of the investigation of observed similarities and dissimilarities between different objects and then grouping the objects based on those similarities. Prerequisite: Completion of LAPS 5310, LAPS 5320, LAPS 5330, and LAPS 5340 or LAPS 5360.

LAPS 5380. CAUSAL INFERENCE FOR PROGRAM EVALUATION. 3 Hours.

Using learning analytics to determine the impact of intervention outcomes and critically evaluate quantitative research pertaining to cause and effect in a learning context. This will include potential pitfalls and key factors, as well as application of both practitioner and research lenses. Prerequisite: Completion of LAPS 5310, LAPS 5320, LAPS 5330, and LAPS 5340 or LAPS 5360.

LAPS 5388. ADVANCED METHODS IN EDUCATIONAL DATA MANAGEMENT/LEARNING ANALYTICS. 3 Hours.

Sophisticated and emerging techniques for analyzing learning data, including advanced graphing and visualization techniques, modeling, process mining, and profile development. Prerequisite: Completion of LAPS 5310, LAPS 5320, LAPS 5330, and LAPS 5340 or LAPS 5360.

LAPS 5390. INSTRUCTIONAL DESIGN AND LEARNING ANALYTICS. 3 Hours.

Introduction to foundational instructional design theories, models, and strategies to design and evaluate technology that supports and helps improve learning. Prerequisite: Completion of LAPS 5310, LAPS 5320, LAPS 5330, and LAPS 5340 or LAPS 5360.

LAPS 5391. INDEPENDENT STUDY. 3 Hours.

Student and instructor agree upon topic of study and requirements for deadlines and products. Prerequisite: Completion of LAPS 5310, LAPS 5320, LAPS 5330, and LAPS 5340 or LAPS 5360.

LAPS 5392. COGNITION, COMPUTERS, AND METACOGNITION. 3 Hours.

How learning, human development, and cognition theories relate to the use of digital technology for instructional purposes. Prerequisite: Completion of LAPS 5310, LAPS 5320, LAPS 5330, and LAPS 5340 or LAPS 5360.

LAPS 5610. CAPSTONE. 6 Hours.

Application of program knowledge and skills learned in prior coursework to complete a small-scale, integrative project involving analysis of a real world, educational data set. Students will have the opportunity to apply for competitive internships that will provide small scholarships. All students will to work in diverse groups of 5 to 6 students along with a faculty mentor analyzing specific industry data to solve real-world problems. The small groups will be designed to combine students with diverse skill sets and emphasize community and collaboration. Prerequisite: Completion of coursework and approval of department.