Fostering Student Engagement through AI-driven qualitative Quality Assurance Practices (Qual-AI-ty Engagement) aims to empower QA staff to take a more proactive role in fostering student engagement. It aims to do so by leveraging AI resources to acquire and process qualitative data, thus enhancing the efficiency and creating the culture of quality for student engagement.
There is a growing urgency for fostering student engagement with society as a sign of University Quality, due to its positive effects on every nation's active citizenship, human and economic development. However, universities have been often perceived as not taking a proactive role in engaging more with society-related issues.
Generating visibility of the positive impacts that engagement with society brings to student's perceptions of university quality, by breaking the old tradition of quality measurement and focusing on a qualitative assessment of these perceptions in order to gain more human and deeper insights that just plain numbers cannot provide.
Implementing a collaborative machine-learning-based platform able to assess, analyze, and graphically showcase student feedback about the impacts of engagement with society, and in addition, empowers universities and QA staff to successfully creating innovative student engagement strategies for increasing their societal impact.
Showcase documents in which 1) aims to map the modalities and pathways of student engagement with society to serve as a springboard for the development of other IOs and 2) aims to identify success stories on student engagement with society in Europe and beyond to serve as an impetus.
Provide comprehensive QA training aimed at raising awareness and developing the competencies of QA staff on student engagement and AI with respect to qualitative data.
Ensure a detailed qualitative quality model to measure the level of student engagement with society, based on IO1 insights, deployed through AI.
Deliver a fully digitized AI platforms to collect, analyze and present the qualitative data provided by students.
Test the IO3 model and IO4 software solutions, and make necessary readjustments to both.
Create an action plan to help universities create successful student engagement strategies and means to effectively evaluate them.
