The resources include a glossary of all the terms developed throughout the project, and a curated bibliography that has been used as reference literature, useful for those seeking to delve deeper into theoretical aspects.

This section collects all the terms encountered during the process and aims to unpack and clarify their meaning within the specific context of this project and the purpose they have been considered for. The following definitions have been formulated based on the literature and expert interviews to be adapted to combine design and artificial intelligence fields of theory and practice.

The glossary also works as a summary of the project, providing a first overview of the contents touched and faced during the process.

Design Phases

Understand

Investigate the context, target groups, and stakeholders through research to explore, discover and analyse needs, barriers, attitudes, and aspirations

Define

Gather insights from the research to frame key findings to outline specific design opportunities and challenges

Ideate

Generate ideas for new design solutions in response to opportunities and challenges

Prototype

Transforming ideas into a concrete solution, making samples for use, observation, and evaluation in their context

Develop

Shaping in detail the final solution after appropriate refinements and testing

Release

Communicate, distribute, publish, and make open solutions and outputs available to the target groups, stakeholders, as well as the whole society

AI Capabilities

Classify

Identifying by or dividing data into classes based on similar features

Collect

Gathering data from physical or digital environments driven by research interests

Debug

Finding and fixing errors in given data

Generate

Creating new data or content based on given instructions or parameters

Optimise

Improving data quality and performance

Rank

Organising hierarchies based on data relevance within a given context

Recognise

Detecting and identifying patterns in data based on given instruction or previous knowledge

Recommend

Suggesting content based on past behaviours, preferences, or relevance within a given context

Summarise

Selecting and disclosing relevant data with the overall meaning

Test

Evaluating the performance and functionality based on parameters

Translate

Transforming (existing) data from one domain to another preserving context meaning

Visualise

Transforming data into visual outputs useful for exploration or explanation.

Data Types

Raw Data

Data used as input to an AI system by users

Cooked Data

Data processed as output by an AI system

Elementary Data

A single data type that lacks structure or organization

Composite Data

A data type constituted by organised elementary data types.

Educational Framework

Educational Objective

Description of the expected results in terms of knowledge and skills students should acquire from an educational module.

Instructional Activities

Description of how educational objectives are accomplished, providing tasks and exercises teachers must prepare and conduct during the module to facilitate student learning.