Learn to Analyze Educational Data and Improve your Blended and Online Teaching

This MOOC aims to support the development of the basic competences for Educational Data Analytics of Online and Blended teaching and learning.

It targets:

• instructional designers and e-tutors of online and blended courses, as well as,
• school teachers of blended learning courses (using the flipped classroom model).

It combines

• theoretical knowledge on core issues related to collecting, analysing, interpreting and using educational data, including ethics and privacy, with
• practical experience of applying educational data analytics in three different e-learning platforms, namely, Moodle, the eXact Suite and the IMC Learning Suite.

The MOOC is developed by an international Academia-Industry consortium within the action Learn2Analyze — An Academia-Industry Knowledge Alliance for enhancing Online Training Professionals’ (Instructional Designers and e-Trainers) Competences in Educational Data Analytics which is co-funded by the European Commission through the Erasmus+ Program of the European Union (Cooperation for innovation and the exchange of good practices – Knowledge Alliances, Agreement n. 2017-2733 / 001-001, Project No 588067-EPP-1-2017-1-EL-EPPKA2-KA). The European Commission’s support for the production of this publication does not constitute an endorsement of the contents, which reflects the views only of the authors, and the Commission will not be held responsible for any use which may be made of the information contained therein. More information about the project is available at www.learn2analyze.eu.

Module 1: Orientation

This module offers the opportunity to become familiar with the MOOC platform, the course structure and the course policies.

Module 2: Educational Data

This module will introduce the concept of educational data as a key success factor for online and blended teaching and learning, present the Learn2Analyze framework for educational data literacy competences and discuss the fundamentals of educational data collection and management, including issues related with ethics and privacy.

By successfully completing this module you will:

• Learn how educational data can support successful online and blended courses
• Understand the importance of data-driven decision making to continuously improve the online and blended teaching and learning
• Recognise the value of Educational Data Literacy to make data-informed reflections on the design and delivery of instruction
• Know the different types of Educational Data in Online and Blended courses
• Know the different Educational Data Sources related to core elements of e-learning environments
• Know and Understand the most common quality issues of raw educational data
• Understand data cleaning methods for educational datasets
• Understand the advantages of enhancing educational data through data description
• Understand the need for data curation in educational data management
• Be able to identify storage issues for preserving educational data
• Understand the importance of informed consent as a key Ethical Principle of Educational Data
• Understand the significance of educational data protection policies

Module 3 – Learning Analytics

This module will introduce the basics of methods and tools for analysing and interpreting online learners’ data to facilitate their personalised support. It will focus on organising, analysing, presenting and interpreting learner-generated data within their learning context, as well as on ethical concerns and policies for protecting learner-generated data from mistreatment and misuse.

By successfully completing this module you will:

• Know what the common measurements of learner data and their contexts are, and understand the processes needed to collect both learner and context data in online and/or blended learning settings
• Be able to identify and describe the limitations and quality measures on collecting learners’ data in online and/or blended learning settings
• Know methods for learners’ data analysis and modelling as part of learning analytics methods
• Know and understand learner-generated data presentation methods
• Know and understand learners’ data properties in learning analytics
• Be able to identify and discriminate statistics commonly used for the interpretation of educational data in learning analytics
• Be able to elaborate on the insights from learners’ data analysis
• Know and understand the methods that can be used to protect individuals’ data privacy, confidentiality, integrity and security in learning analytics

Module 4 – Teaching Analytics

This module will introduce the basics of methods and tools for analysing and interpreting educational data for facilitating educational decision making, including course and curricula design.

By successfully completing this module you will:

• Know how to identify data sources within the educational design process
• Be able to explain key concepts of data quality for data collected in the educational design process
• Be able to design automated and semi-automated interventions based on educational data
• Know and understand how to revise course tasks and contents based on educational data
• Be able to construct adequate criteria and indicators for evaluating the impact of a data-driven intervention in educational design of online and blended courses
• Be able demonstrate awareness of data privacy and distinguish between different levels of data protection in educational design of online and blended courses
• Be able to explain the differences between the concepts of authorship, ownership, data access, renegotiation, and data-sharing in education design

Module 5 – Educational Data Analytics with Moodle

This module will present tools for educational data analytics in Moodle and focus on the use of these tools to support school teachers in the design and delivery of their online and blended learning courses.

By successfully completing this module you will:

• Know how to obtain, access and gather the appropriate educational data in Moodle
• Be able to apply informed consent within Moodle
• Be able to apply educational data privacy and distinguish between different levels of data protection within Moodle
• Demonstrate an understanding of key data analysis and modelling methods and how they are applied to teaching and learning in Moodle
• Understand how to communicate your interpretation of the educational data in an intuitive accessible way within Moodle
• Be able to interpret insights from educational data analysis within Moodle
• Be able to elicit potential implications of the educational data insights from data analysis to instruction within Moodle
• Be able to use educational data analysis results to make decisions to revise instruction within Moodle

Module 6 – Educational Data Analytics with eXact Suite

This module will present tools for educational data analytics in the eXact Suite and focus on the use of these tools to help instructional designers and e-tutors of online courses in supporting online learners.

By successfully completing this module you will:

• Know how to obtain, access, and gather the appropriate educational data in eXact Suite
• Demonstrate an understanding of key educational data analysis and modelling methods and how they are applied to teaching and learning in eXact Suite
• Understand how to communicate your interpretation of the educational data in an intuitive and accessible way within eXact Suite
• Be able to interpret insights from educational data analysis within eXact Suite
• Be able to elicit potential implications of the educational data insights from data analysis to instruction within eXact Suite
• Be able to use educational data analysis results to make decisions to revise instruction within eXact Suite

Module 7 – Educational Data Analytics with IMC Learning Suite

This module will present tools for educational data analytics in the IMC Learning Suite. The focus is on how the tools can support instructional designers of online courses in reflecting on their educational design and re-design the courses. The module also shows how the tools can help e-tutors to support online learners.

This module will present tools for educational data analytics in the IMC Learning Suite and focus on the use of these tools to help instructional designers of online course in reflecting on their educational design and re-design them.

By successfully completing this module you will:

• Know how to obtain, access and gather the appropriate educational data in the IMC Learning Suite
• Understand how to apply data processing and handling methods (i.e., configuring and filtering reports, choosing the relevant data) in the IMC Learning Suite
• Be able to use data presentation tools of the IMC Learning Suite
• Be able to interpret insights from educational data analysis within the IMC Learning Suite
• Be able to elicit potential implications of the educational data insights from data analysis to instruction within the IMC Learning Suite
• Be able to use educational data analysis results to make decisions to revise instruction within the IMC Learning Suite
• Be able to apply educational data privacy and distinguish between different levels of data protection within the IMC Learning Suite

Module 8 – Concluding the MOOC

This concluding module will allow participants to finalise their assignments, discuss their overall MOOC learning experience with their peers, and reflect on their learning experience by submitting the course feedback survey.