Work Packages

The project comprises of three phases with eight interdependent Work Packages (WP) designed to address  the project’s Research Questions (RQ) and accomplish the primary and enabling objectives.

Lead Participant

Task 1.1 – Project management and administration: managing the day-to-day operation of the project according to approved plans, monitoring of the progress, schedule and resources, managing the data according to the FAIR principles of the EU

Task 1.2 – Innovation and societal impact management strategy development: maximizing the impact of the project throughout all stages and ensuring that the required outputs are prepared and delivered to the market in a timely manner

Task 1.3 – Communication and coordination: establishing and implementing a communication plan for the project, ensuring remote communication infrastructure is in place for the secure exchange of project information, results, deliverables, etc.

Task 1.4 – Data Management Plan (DMP), quality assurance and risk management: Implementing procedures for quality management, monitoring, tracking, and controlling deviations and risks throughout the project duration to ensure effective implementation

Lead Participant

Task 2.1 – State-of-the-art review: Analyse the state-of-the-art intelligent learning technologies and provide recommendations regarding the types of AI-enabled learning interventions for i-MASTER

Task 2.2 – Vessel navigation competency mapping: Map out the overall Knowledge, Understanding & Proficiency (KUP) competences for ship navigation from basics to advanced level

Task 2.3 – Performance metrics and KPIs: Define the measurable Key Performance Indicators (KPIs) for each Knowledge, Understanding & Proficiency (KUP) item for ship navigation

Task 2.4 – Measurement methodology specification: Determine the KPI measurement methodology, frequency, and data needs

Lead Participant

Task 3.1 – Training scenarios design and ship simulation trials: Define the scope of training scenarios to be designed for the intelligent learning system for remote and on-site simulation and create the educational objectives and the corresponding performance metrics for each simulation exercise

Task 3.2 – Performance patterns and instructional strategy: Conduct research on the students’ performance patterns with the developed training scenarios, determine the appropriate tutoring or instructional strategy and identify user requirements and needs to develop learning analytics and adaptive learning functions

Task 3.3 – Architecture design of the i-MASTER learning analytics and ILS: Design the architecture for the i-MASTER learning analytics dashboard and ILS by identifying the components, data requirement, their functionalities and interconnections

Task 3.4 – Consolidate KPI and performance metrics for the learning analytics algorithm and the visualization dashboard

Lead Participant

Task 4.1 – Development of the maritime learning analytics algorithms and visualization dashboard

Task 4.2 – Creation of database systems, data integration, configuration, test environment setup

Task 4.3 – Experimental testing for remote/desktop simulation exercises to ensure that data will be processed correctly and reliable output will be produced in the desired format

Task 4.4 – Experimental testing for on-site simulation exercises with full-mission simulators and eye tracking devices

Task 4.5 – Consolidate KPI and performance metrics for the learning analytics algorithm and the visualization dashboard

Lead Participant

Task 5.1 – Software Development of the Maritime Intelligent Learning System (ILS)

Task 5.2 – Data Analysis and Construction of the Adaptive Learning Functions

Task 5.3 – Data Generation and Improvement of the ML Algorithms

Task 5.4 – Maritime ILS Testable Prototype Establishment and System Integration

Lead Participant

Task 6.1 – Prototype Assessment of the Maritime ILS for Remote / Desktop Simulations

Task 6.2 – Advancement of the Maritime ILS for On-Site Full-Mission Simulator Training

Task 6.3 – Iterative Usability Testing and System Improvement

Task 6.4 – System Functional Verification and Performance Evaluation

Lead Participant

Task 7.1 – Large-Scale Demonstration Programme

Task 7.2 – Experimental Evaluation and Improvement of the Maritime ILS Performance

Task 7.3 – Multi-Dimensional Impact Analysis of the Maritime ILS on the Domain of Maritime Simulator-Based Education and Training

Task 7.4 – Training and Assessment Package with Pedagogical Guideline Regarding the System Capabilities of the Developed AI-Assisted ILS and how it Should be Utilized by the Simulator-Instructors

Full Professor of Socioeconomics of Work (2018-03) | EURAXESS

Lead Participant


Task 8.1 – Communication, Dissemination and Exploitation Strategies for the i-MASTER Project

Task 8.2 – i-MASTER Showcase and Instructor Training Activities

Task 8.3 – EC and EU Dissemination Routes

Task 8.4 – Communication and Dissemination Activities

Task 8.5 – Exploitation and Impact-Maximization Activities