Published April 28, 2021 | Version v1
Project deliverable Open

Deliverable 4.2: Analysis of User Requirements, Needs and Visionary User Cases for ARETE



The deliverable D4.2 reports user needs and requirements from the ARETE target groups – primary and secondary school students and teachers. The methods employed were online surveys and interviews. The teacher and secondary school surveys share a similar structure. They start with demographic questions, followed by a set of questions on general AR usage to gather data on the overall perceptions and needs for deploying AR for teaching/learning. The last set of questions is to gather contextualised data by referring to a specific AR app that teachers/students have recently used, thereby eliciting their requirements for developing future AR apps for teaching/learning. For the primary school survey, the questions are mainly on experiences of using AR in general as well as for learning at school.

Despite our repeated attempts to disseminate the surveys through different channels, the response rates were discouragingly low. Altogether we have gathered complete survey responses from 65 teachers, 65 secondary school students and 130 primary school students. However, the numbers of visits to the three online surveys were 1746, 1157 and 1083, resulting in the completion rate of 3.7%, 5.6% and 12%, respectively. The high incompletion rates of the surveys might be attributable to the low usage of AR educational applications for real-life teaching and learning. In addition, we were able to conduct interviews with five teachers with one deciding to withdraw. Similar to the surveys, recruiting participants for the online interview proved very challenging. Furthermore, the distribution of countries where the respondents resided was skewed. While these undesirable factors affected the quality of the data, we could still gain useful insights into the needs and requirements of the participating primary and secondary students and teachers for improving the uptake of AR for education.


This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 856533.



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