Learn2Analyze MOOC

Learn2Analyze MOOC

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

This MOOC supports the development of the basic competences for Educational Data Analytics of Online and Blended teaching and learning. It is ideal for:

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

Download the MOOC Syllabus here.

Enrollment

Is Now Open!

About the Course

Hello and welcome to the Learn to Analyze Educational Data and Improve your Blended and Online Teaching Massive Open Online Course (MOOC).

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 L2A MOOC and the certificate are free of charge!

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.

We’re excited to offer this new course and we do hope you will enjoy learning about analyzing Educational Data to improve your Blended and Online Teaching!

What you will learn

By completing this course you will:

  • know where to locate useful educational data in different data sources and understand their limitations;
  • know the basics for managing educational data to make them useful, understand relevant methods and be able to use relevant tools;
  • know the basics for organising, analysing, interpreting and presenting learner-generated data within their learning context, understand relevant learning analytics methods and be able to use relevant learning analytics tools;
  • know the basics for analysing and interpreting educational data to facilitate educational decision making, including course and curricula design, understand relevant teaching analytics methods and be able to use relevant teaching analytics tools;
  • understand issues related with educational data ethics and privacy.

The learning outcomes of this course cover the set of competences anticipated by the Learn2Analyse Educational Data Literacy competence framework.

Learn2Analyze Educational Data Literacy competence framework

Course Syllabus

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.

Assessment Method, Grading Policy and Certification

This course is graded as Pass or Fail, meaning you will either be given a passing score or a failing score.

In order to successfully complete this course and gain your Certificate of Achievement you must gain a mark of 60% or greater overall to all 100 quiz questions.

Your grade in the course is calculated based on your replies to 100 multiple choice questions distributed to the 6 core modules.  The Multiple Choice Questions are included at the end of Module #2 to Module #7 and aim to assess your understanding of the core concepts presented.

You may complete the Multiple Choice Questions Assessment at any time as there are no ‘due dates’. Nevertheless, we recommend that you complete them sequentially, after you have completed the relevant module.

If you successfully complete this course you will receive a Certificate of Achievement. Successful completion of the course requires:

  • completing the Multiple Choice Questions Assessment with 60% success
  • completing the Pre-course and the Post-course Surveys

The certificate is free of charge!

L2A Certificate Template

Your Instructors

Module 2: Educational Data

  • Prof Demetrios Sampson
  • Sofia Mougiakou
  • Dimitra Vinatsella

UPRC Logo

Module 3:  Learning Analytics

  • Prof Michael Giannakos
  • Dr Zacharoula Papamitsiou

NTNU Logo

Module 4: Teaching Analytics

  • Prof Dirk Ifenthaler
  • Marc Egloffstein

University of Mannheim Logo

Module 5: Educational Data Analytics with Moodle

  • Deborah Couëdelo
  • Mary Jones

Enovation Logo

Module 6:  Educational Data Analytics with eXact Suite

  • Elisabetta Parodi
  • Laura Brambilla
  • Maria La Porta

Lattanzio Logo

Module 7: Educational Data Analytics with IMC Learning Suite

  • Dr Uta Schwertel
  • Samandar Atoev
  • Dr Mareike Schmidt

IMC Logo

Course Data

Start Date
21 October 2019

End Date
14 December 2019

Pre- Requisites
None

Duration
8 weeks

Time Commitment
68 hours in total

Level
Introductory

Language
English

Certificate available
Yes

Costs
Free (course and certificate)

MOOC Syllabus
Download