Back to search

Agent Based Modelling for Archaeologists

2021-2-IE01-KA220-VET-0000490542021Cooperation partnerships in vocational education and trainingfinalized
Countries: IE|DK|NL · Grant: €109,830
Cultural heritageCreating new, innovative or joint curricula or coursesDigital skills and competences

Objectives

To address the aim of this project, addressing skill shortages due to a lack of vocational training opportunities, the primary objective of the project was to create Open (Open Access and Open Source) Educational Resources (OERs) for training in Agent Based Modelling (ABM) for Archaeologists They would be hands-on practical exercises, taking learners through the process of creating the digital models, and modular so they can be independent or incorporated into other teaching tools like learning management systems This was to be supported by the secondary objectives of creating support materials to encourage use of the OERs, including competency matrices so users can track and demonstrate their skills and 'how-to' guides to help trainers incorporate OERs into their training delivery The overall outcome is be the creation of a full educational environment for ABM in archaeology, providing the ability for learners to be trained, for them to track and prove their competencies; and for trainers anywhere, from employers to educational institutes, to be able incorporate the open training resources into their training provisions to reach more learners

Background

Agent-based modelling (ABM) is a class of computational models for simulating complex interactions which emphasises how actions by individuals combine to produce global patterns. ABM is a valuable digital tool with a wide range of uses, for archaeologists as well as for their clients in other sectors like construction and agriculture. It is used to create predictive models which estimate the location of archaeological resources that will be encountered during development work by other industries, such as construction or mining, thus allowing the estimation of costs and/or to develop strategies of mitigation, providing immense benefit to the archaeological, construction and minerals sectors. Predictive models significantly reduce development costs while protecting irreplaceable heritage resources. However, even though this digital vocational skill is in high demand by archaeologists, there are significant problems with the limited levels of delivery of vocational training for this skill in the sector. The project set out to create portable, re-usable specialist e-learning materials to address this need.

Project partners (4)