EdX

Using Data to Provide Personalized Student Support (edX)

Using Data to Provide Personalized Student Support (edX)

Learn how data is captured in learning experiences and how it is processed and analyzed to inform student support actions. This course will benefit educational designers, learning technology managers, and academics that are interested in how to use data to guide the design and improvements of a learning experience.

Class Deals by MOOC List - Click here and see EdX's Active Discounts, Deals, and Promo Codes.

Technology has the ability to collect a large amount of data about how people participate in a learning experience. How can this data be used to increase our understanding of how learning occurs? How can data be translated into actionable knowledge? How can data help improve the overall quality of a learning experience? These are the questions that are explored during the activities in the course. You will need basic knowledge about data manipulation and statistical analysis, and you will learn how to use them to translate data into actionable knowledge to apply in a learning experience.

What you'll learn

  • How data sets are captured in learning experiences
  • What basic procedures to use to manipulate these data sets
  • The use of statistical models to predict student behavior
  • The deployment of personalized support actions for the students

Syllabus

Week 1: Computer Logs
Exploration of the type of computer logs that are produced, how the logs can be processed, and the type of information available.

Week 2: From logs to indicators
Basic procedures to transform log files into meaningful indicators that are connected with the learning environment. Explore how these transformations need to be driven by the structure of the learning design.

Week 3: Combining data sources and deploying student support actions
Apply data management techniques to create data structures by mixing multiple data sets. Translate the information and knowledge derived from the data set into student support actions.

Prerequisites
We highly recommend that you take the previous course in this series before beginning this course:
Feature Engineering for Improving Learning Environments
This course is intended for those who have a bachelor’s degree and are interested in developing learning and data science skills for employment in education, corporate, nonprofit, and military sectors. Experience with programming and statistics will be beneficial to participants.

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Foundations of Data Analysis - Part 1: Statistics Using R (edX) EdX
University of Texas at Austin,UTAustinX

Foundations of Data Analysis - Part 1: Statistics Using R (edX)

Use R to learn fundamental statistical topics such as descriptive statistics and modeling. In this first part of a two part course, we’ll walk through the basics of statistical thinking – starting with an interesting question. Then, we’ll learn the correct statistical tool to help answer our question of interest – using R and hands-on Labs. Finally, we’ll learn how to interpret our findings and develop a meaningful conclusion.

No sessions available
5-12 Weeks
Técnicas Cuantitativas y Cualitativas para la Investigación (edX) EdX
Universitat Politècnica de València,UPValenciaX

Técnicas Cuantitativas y Cualitativas para la Investigación (edX)

El curso pretende acercar al alumno al método científico y, en concreto, cómo éste se aplica al estudio y análisis de los métodos de casos. El curso que se propone es ideal para investigadores y alumnos que se encuentren cursando trabajos de fin de grado, trabajos de fin de máster o realizando tesis, así como todos aquellos del área de la administración que quieran realizar un análisis cuantitativo o cualitativo en sus estudios.

Self Paced
Self-Paced
Data Analysis Essentials (edX) EdX
Imperial College Business School,Imperial College London

Data Analysis Essentials (edX)

Discover and acquire the quantitative data analysis skills that you will typically need to succeed on an MBA program. This course will cover the fundamentals of collecting, presenting, describing and making inferences from sets of data. Want to study for an MBA but unsure of the basic data analysis still required? This online course prepares you for studying in an MBA program.

Self Paced
Self-Paced
Data Analysis: Building Your Own Business Dashboard (edX) EdX
Delft University of Technology,DelftX

Data Analysis: Building Your Own Business Dashboard (edX)

Dive in headfirst and carry out an independent data analysis. Build and design your own dashboard based on raw data to better inform business decisions. Are you ready to leave the sandbox and go for the real deal? Have you followed EX101x Data Analysis: Take It to the MAX() and EX102x Data Analysis: Visualization and Dashboard Design and are ready to carry out more robust data analysis?

No sessions available
5-12 Weeks
Understanding the World Through Data (edX) EdX
MIT,MITx

Understanding the World Through Data (edX)

Become a data explorer – learn how to leverage data and basic machine learning algorithms to understand the world. Speech recognition, drones, and self-driving cars – things that once seemed like pure science fiction – are now widely available technologies, and just a few examples of how humans have taught machines to analyze data and make decisions. In this hands-on, introductory course, you will examine all the forms in which data exists, learn tools that uncover relationships between data, and leverage basic algorithms to understand the world from a new perspective.

Mar 13th 2024
5-12 Weeks
Quantitative Biology Workshop (edX) EdX
MIT,MITx

Quantitative Biology Workshop (edX)

A workshop-style introduction to tools used in biological research. Discover how to analyze data using computational methods. Do you have an interest in biology and quantitative tools? Do you know computational methods but do not realize how they apply to biological problems? Do you know biology but do not understand how scientists really analyze complicated data? 7.QBWx: Quantitative Biology Workshop is designed to give learners exposure to the application of quantitative tools to analyze biological data at an introductory level.

Self Paced
Self-Paced
Machine Learning (edX) EdX
Columbia University,ColumbiaX

Machine Learning (edX)

Master the essentials of machine learning and algorithms to help improve learning from data without human intervention. Machine Learning is the basis for the most exciting careers in data analysis today. You’ll learn the models and methods and apply them to real world situations ranging from identifying trending news topics, to building recommendation engines, ranking sports teams and plotting the path of movie zombies.

This course is archived
5-12 Weeks
The Analytics Edge (edX) EdX
MIT,MITx

The Analytics Edge (edX)

Through inspiring examples and stories, discover the power of data and use analytics to provide an edge to your career and your life. In the last decade, the amount of data available to organizations has reached unprecedented levels. Data is transforming business, social interactions, and the future of our society. In this course, you will learn how to use data and analytics to give an edge to your career and your life.

This course is archived
13-24 Weeks
Platform-Based Analytics (edX) EdX
Indiana University,IUx

Platform-Based Analytics (edX)

Gain hands-on experience extracting, preparing, exploring, and analyzing data statistically and visually using features and tools native to Microsoft Excel. In an ever-growing digital world, the need for strong data analysis skills is at the forefront of every business function, along with the ability to accurately describe and interpret analytical findings.

Nov 7th 2023
5-12 Weeks
Observation Theory: Estimating the Unknown (edX) EdX
Delft University of Technology,DelftX

Observation Theory: Estimating the Unknown (edX)

Learn how to estimate parameters from observational data for real-world engineering applications and assess the quality of the results. Are you an engineer, scientist or technician? Are you dealing with measurements or big data, but are you unsure about how to proceed? This is the course that teaches you how to find the best estimates of the unknown parameters from noisy observations. You will also learn how to assess the quality of your results.

Self Paced
Self-Paced