Learning resources

The general objective of AI4ALL is the definition of a EU system for the data collection for AI, able to assist and simplify the process of teaching and learning evaluation, namely self-assessment of basic digital skills in continuous professional training, C-VET, assessment of learning achievements, allowing educators to build tailor-made training courses/learning paths.

To achieve its objectives, AI4All is producing key resources initially targeted at the VET ecosystem but which can be used and transferred outside the latter. 

R1

Toolkit for AI4ALL, an AI to support the basic digital skills in C-VET self-assessment and learning evaluation process.

R2

Self-Training Course on AI-assisted assessment of basic digital skills of SME’s workers and learners in C-VET paths.

References:

1. Deursen, v., & Johannes Aloysius Maria, A. (2014). Measuring digital skills : from digital skills to tangible outcomes project report. University of Twente. 

http://dx.doi.org/10.13140/2.1.2741.5044

 

2. Ghomi, M., & Redecker, C. (2019). Digital Competence of Educators (DigCompEdu): Development and Evaluation of a Self-assessment Instrument for Teachers’ Digital Competence. ResearchGate.

http://dx.doi.org/10.5220/0007679005410548

 

3. Gonzalez Calatayud, V., Prendes, P., & KaraRoig-Vilamat, R. (2021). Artificial Intelligence for Student Assessment: A Systematic Review. Applied Sciences11,5467. 

https://doi.org/10.3390/app11125467

 

4. Minn, S. (2022). AI-assisted knowledge assessment techniques for adaptive learning environments. Computers and Education: Artificial Intelligence3https://doi.org/10.1016/j.caeai.2022.100050

 

5. Roh, Y., Heo, G., & Whang, S. E. (2021). A Survey on Data Collection for Machine Learning: A Big Data – AI Integration Perspective. IEEE Transactions on Knowledge and Data Engineering33, 1328-1347.

https://doi.org/10.1109/TKDE.2019.2946162

6. Shubham, J., Radha, R., & Prathamesh, C. (2021). Evaluating Artificial Intelligence in Education for Next Generation. Journal of Physics: Conference Series1714,012039.

https://doi.org/10.1088/1742-6596/1714/1/012039

 

7. Swiecki, Z., Khosravi, H., Chen, G., Martinez-Maldonado, R., M. Lodge, J., Milligan, S., Selwyn, N., & Gašević, D. (2022). Assessment in the age of artificial intelligence. Computers and Education: Artificial Intelligence3.

https://doi.org/10.1016/j.caeai.2022.100075

 

8. Zawacki-Richter, O., Marín, V.I., & Bond, M. (2019). Systematic review of research on artificial intelligence applications in higher education – where are the educators? Int J Educ Technol High Educ16.

https://doi.org/10.1186/s41239-019-0171-0

 

9. Al Braiki, B., Harous, S., Zaki, N., & Alnajjar, F. (2020). Artificial intelligence in education and assessment methods. Bulletin of Electrical Engineering and Informatics9.

https://doi.org/10.11591/eei.v9i5.1984

This project has been funded with support from the European Commission. The author is solely responsible for this publication (communication) and the Commission accepts no responsibility for any use may be made of the information contained therein. In compliance of the new GDPR framework, please note that the Partnership will only process your personal data in the sole interest and purpose of the project and without any prejudice to your rights.

Contact us

For any inquiry, please use the facebook page or write an email to:

ai4allproject@ccitalia.pt

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