Learn2Analyze MOOC

Learn2Analyze MOOC

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

This MOOC aims to support the development of both core and advanced competences for Educational Data Analytics of Online and Blended teaching and learning. It is ideal for:

  • e-learning professionals (such as instructional designers and e-tutors) of online and blended courses;
  • school leaders and teachers engaged in blended (using the flipped classroom model) and online (during the  COVID19 crisis and beyond) teaching and learning;
  • higher education students (undergraduates & postgraduates).

Download the MOOC Syllabus here.

Enrollment

Now Open!

About the Course

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

In the wake of the Covid-19 global pandemic, emergency remote teaching has become the new reality for school education around the world. As a result, educational data, that is the rich data footprint that students generate through their interactions in digital learning environments, has increased exponentially. This unprecedented crisis has brought to the forefront the urgent demand for Educational Data Analytics (EDA) as a key enabler to seize the opportunity, through the use of educational data generated during teaching and learning (including assessment), to better support individual learners in technology-supported remote teaching. Furthermore, online learning environments and education data-driven practice and assessment raise challenges such as ethical issues and implications, especially in terms of privacy, security of data and informed consent that should be addressed via transparent and well-defined ethical policies and codes of practices.

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

The new version incorporates:

  • gamification elements to offer enhanced engagement in several authentic learning activities;
  • self-assessed assignments based on real-life scenarios to offer deeper understanding of the educational data field; and
  • an upgraded assessment mechanism leading to two levels of Certification of Achievement on Educational Data Literacy (EDL).  Level A requires the learner to have acquired a basic set of competences for EDL and Level B requires demonstration of a higher expertise assessed through hands-on assignments based on simulated practice scenarios.

It targets:

  • e-learning professionals (such as instructional designers and e-tutors) of online and blended courses;
  • school leaders and teachers engaged in blended (using the flipped classroom model) and online (during the  COVID19 crisis and beyond) teaching and learning;
  • higher education students (undergraduates & postgraduates).

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 has been developed by an international Academia-Industry consortium within the action Learn2AnalyzeAn 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.learn2analyse.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!

This is the course for you!

No previous knowledge related to Educational Data Analytics is needed. Join us and a large community of innovative instructional designers and educators from around the globe to become the pioneers of Educational Data Analytics in your workplace.

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 (L2A-EDL-CP).

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 Length

Start Date: March 1, 2021

End Date: May 1, 2021

This course is open for nine (9) weeks and consists of eight (8) modules including six (6) core modules, one orientation and one concluding module.

The expected effort from your side to complete the basic requirements for the Certificate of Achievement is approximately one hundred (100) hours in total.

Let’s take a look at what each module will cover in the next section.

Course Syllabus

Module 1: Orientation

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

Estimated Effort to complete: 4 hours

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. 

Estimated Effort to complete: 15 hours
Estimated Effort to complete Module 2 concluding Self-Assessed Assignment: 1 hour

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.

Estimated Effort to complete: 12 hours
Estimated Effort to complete Module 3 concluding Self-Assessed Assignment: 1 hour

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.

Estimated Effort to complete: 10 hours
Estimated Effort to complete Module 4 concluding Self-Assessed Assignment: 1 hour

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.

Estimated Effort to complete: 15 hours
Estimated Effort to complete Module 5 concluding Self-Assessed Assignment: 1 hour

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.

Estimated Effort to complete: 12 hours
Estimated Effort to complete Module 6 concluding Self-Assessed Assignment: 1 hour

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.

Estimated Effort to complete: 10 hours
Estimated Effort to complete Module 7 concluding Self-Assessed Assignment: 1 hour

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.

Estimated Effort to complete: 4 hours

Final Assessment

Assessment Multiple Choice Questions for Level A Certificate: 100

Estimated Effort to complete: 6 hours

Assessment Multiple Choice Questions for Level B Certificate: 100

Estimated Effort to complete: 6 hours

Gamification Elements of the course

Throughout the course

  • You can gain Experience Points (XPs) by completing activities within the MOOC. By accumulating Experience Points (XPs) you can reach higher levels in an Experience Track. There are 4 Experience Tracks: Content, Engagement, Test and Module. There is a Leaderboard, a ranking list displayed per experience track.
  • You can be awarded Badges. There are 6 Module Badges one for each module (Module #2 to Module #7) and 3 Community Badges. There is a Progress bar to display progress towards next or ultimate performance level.

Experience Tracks:

  • Content track shows your progress on course content such as text, videos, slides, documents.
  • Engagement track shows your participation in the activities of the course. Points are awarded for completing quizzes, exercises and other interactive learning objects, regardless of your result.
  • Test track shows your progress on tests. Points are awarded for successfully completing quiz tests.
  • Module track shows your progress in a module (Module #2 to Module #7). Points are awarded if you complete a learning object within respective module (Module #2 to Module #7).

Module Badges, one for each module (Module #2 to Module #7):

  • Educational Data L2A Finisher
  • Learning Analytics L2A Finisher
  • Teaching Analytics L2A Finisher
  • Moodle L2A User
  • eXact Suite L2A User
  • IMC Learning Suite L2A User

To earn each of these badges you must gain at least 75% of XP points and pass the self-assessed assignment in the respective module.

Community Badges:

  • L2A Commentator
  • L2A Moderator
  • L2A Forum Master

To earn each of these community badges you must post a certain number of posts in the discussion fora, calculated across all the modules (Commentator: At least 3 posts, Moderator: At least 10 posts, Forum Master: At least 20 posts).

Learning Activities and Self-Assessed Assignment of the course

  • There are learning activities as single question quiz tests, added after some content subtopics, related to the video watched or the topic studied.
  • At the end of each module, there is a concluding self-assessed assignment. This self-assessed assignment is a real-life scenario activity (e.g. based on a use case), using a rubric across three proficiency levels and an exemplary solution rating. The evaluation of the outcomes is done by you as self-assessment, using a rubric which includes the criteria that each response should meet and guidelines to assess yourselves.
  • These types of assignments do not contribute directly your final grade for this course in order to receive the L2A Certificate of Achievement (Level A and Level B). Nevertheless, we recommend that you complete them, so as to evaluate your understanding, as well as, to gain points and respective badges.

Final 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. 

There are two levels of the L2A Certificate of Achievement:  Level A Certificate and Level B Certificate of Achievement on Educational Data Literacy.

L2A Certificate of Achievement Level A requires developing a basic set of competences for EDL. In order to gain your Certificate of Achievement Level A you must gain a mark of 60% or greater overall to the corresponding set of level A 100 multiple choice quiz questions, aiming to assess your understanding of the core concepts presented in the 6 core modules.

L2A Certificate of Achievement Level B requires demonstration of a higher expertise assessed through hands-on assignments based on simulated practice scenarios. More specifically, for the Certificate of Achievement Level B, there is a final concluding assessment, where you are requested to undertake complex tasks, by going through several steps (e.g. by following a use case) and answer a set of 100 Multiple-Choice Questions (MCQs) which are automatic graded by the platform. In order to gain your Certificate of Achievement Level B you must gain a mark of 60% or greater overall to the corresponding set of 100 level B multiple choice quiz questions. 

Both sets of Multiple Choice Questions are included at the end of the course and you may complete the Multiple Choice Questions Assessments at any time as there are no ‘due dates’. 

If you successfully complete this course you will receive a Certificate of Achievement (Level A or Level B or both). Successful completion of the course requires:

  • completing the corresponding Multiple Choice Questions Assessment for Level A and/or Level B Certificate (with 60% success each to obtain both Levels)
  • 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

 

MOOC Data

Start Date
1 March 2021

End Date
1 May 2021

Duration
9 weeks

Pre-Requisites
None

Time Commitment
100 hours in total

Level
Introductory

Language
English

Certificate available
Yes

Costs
Free (course and certificate)

MOOC Syllabus
Download