Introduction

The Methodology is the main tool for summarising and adapting all the results and lessons learned from the project. The document summarises the workings of the Edubot adaptive methodology, the blended learning methodology, the digital support system and the lessons learned from the pilot training, and helps to use the project results. The Methodology is available as an e-book in 5 languages on the project website.

The methodology and the lessons learned from the project are used in the use of the project results.

It functions as a methodological and technical guide, describing the processes for designing, developing and delivering blended learning courses, showing how they can be delivered in an adaptive way, ensuring that all learners are presented with challenging but not frustrating tasks and receive personalised support and assistance in the learning process.

 

 

The Methodology is structured as follows:

 

  • Areas for using EDUBOT
    The first chapter functions as a methodological introduction, presenting the innovative methodology that allows progression along individual learning pathways, the LMS and CAT system; the Edubot blended methodology; the typical educational situations in which EDUBOT methodology can be most useful (e.g. exam preparation, support for differentiated instruction, etc.) and its comparative advantages over other methods.
    The subsection Adaptive learning supported by AI solutions describes how the Edubot AI assistant can facilitate adaptive learning and differentiation, such as designing AI-driven personalised learning pathways; creating clusters, etc.
  • Basic Definitions and Content Structure: basic methodological concepts such as learning units, blocks, modules, learning pathways are clarified.
  • First steps or how to get started: the sub-chapter describes how the e-learning support system works, its main functions such as registration, managing users and groups, etc.
  • The main topic of the Digital Content unit, which consists of several subchapters, is how to create valuable interactive content that can serve personalized learning paths, how to structure content modules into interdependent levels and interconnected blocks. The structure of adaptive content will be demonstrated through a practical example using an IT topic.
  • In the Tasks and learning units section, the task engines are introduced; the different types of content and how they are used; the main features of linear and adaptive content (Linear vs. adaptive pathways).
  • What types of content can be created and how can EDUBOT content be used? This section of the document describes how to use the application in a way that allows the user to quickly generate the content they want to use by following the steps indicated. Typical use cases are described, how to choose the type of content appropriate to the educational purpose; the whole workflow with the learning group is described/ the steps to use the content: registration/ creating a learning group/ inviting users/ creating new units/ creating new modules/ creating learning paths/ setting up learning paths/ playing learning paths/ viewing and evaluating results.
  • The following types of content can be presented to the user, according to the educational purpose:
    • Use test path
    • learning with linear content e.g. to teach a new subject
    • using adaptive learning pathways to identify and fill competency gaps (e.g. when preparing for an exam)
    • adaptive teaching supported by individual tutoring for blended learning: using clustering to support differentiation
  • How to use the content created in the EDUBOT project: this part of the document illustrates the main ways to use the content to make use of the results, using the test path as an example: using the learning path already existing in the system; using the learning paths created using/copying public content; using the paths and content created independently.
  • Learning Outcomes - Reporting: deals with the tools for monitoring learner performance, which are also the basis for creating clusters.
  • Creating performance clusters: as part of the methodology of personalised digital learning pathways and face-to-face tutoring, it will be presented which cases where the use of clusters is recommended, how the AI assistant supports the creation of performance-based clusters based on tracking learners' digital performance, how the blended learning methodology works, and how it combines digital learning and face-to-face tutoring. The AI assistant also plays a role in increased learner motivation by keeping learners in the "flow channel", which is supported by the Edubot framework game.
  • How to motivate students The motivational effect of gamification tools (frame game, points and rewards collection) is presented in the chapter
  • The FAQ framework presents the most frequently asked question
  • Results of the content development: the final chapter presents the 4 digital content sets created in a separate subchapter for each country, includes the availability of the digital learning materials, links to the individual pathways; and provides practical methodological suggestions for the use of the learning materials. 

 

Interactive elements of the Methodology

 

The methodological core of the Methodology is complemented by other informative and interactive elements, which include:

  • Tips: in this format, methodological suggestions and advice are provided for users
  • Video tutorials: short video content, embedded through links, will help you to use the system, showing the technical implementation of the different workflows
  • Technical links: pointing to the User Guide, they provide the necessary technical and professional background knowledge, such as the definition of basic concepts; the system of learning units, blocks, modules; how to manage and create groups, routes; how to create a superunit; how to set up the framework game, etc.

The User Guide components are:

  • 1. Teacher's User Guide: provides help for managing the teacher interface for content development (tasks, paths, creating groups, etc.)
  • 2. Student User Manual: a guide to using the student application, showing how the task-solving process works
  • Links to digital content sets: links to digital learning materials for Hungary, Slovakia, Poland and Romania and English demo content are also available