# Developing an Institutional AI Digital Assistant in an Age of Industry 5.0
## 2 Literature Review: Industry 5.0 and Education 5.0
### Technology Acceptance Model and AI Digital Assistant  
As reported in [PERSON] and [PERSON] [20], there is a suggestion that the low adoption and use of digital technology by employees represents a major barrier to successful IT deployment. The Technology Acceptance Model (TAM) [19] and the follow-up Unified Theory of Acceptance and Use of Technology (UTAUT) by [PERSON] et al. [40] have been extensively used and validated. For example, in a recent meta-analysis by [PERSON], [PERSON], [PERSON], and [PERSON] [39] that reported from 1149 studies containing a total of 25,619 effect sizes from 737,112 users, it found that UTAUT was a robust predictor of how people intent to use technology. In its most basic form, TAM indicates that learners' intentions to use a technology (in this case: i-AIDA) are primarily determined by two key perceptions: (1) Perceived Usefulness (PU) of i-AIDA (e.g., allowing the learner to better understand key learning materials, perform better on assessments, stimulate motivation); and (2) Perceived  
Figure 2: Overview of studies of how i-AIDA was developed over time, and the beta study in January 2025.  
Ease of Use (PEU) of i-AIDA (e.g., how the functionality of i-AIDA is easy to understand and engage with, how easy it is to engage with).  
At the OU, we face a somewhat similar challenge. How to bring the benefits of Generative AI to our 200 K students, many of whom come from disadvantaged backgrounds, have low self-esteem generally, and low digital technology skills? To this effect, we have recently adopted TAM as advocated in [20,39] to help us increase adoption rates. From previous work [41,42], we are aware that the use of AI-based digital technologies in teaching delivery can increase retention rates, which is especially important for our students.  
Beyond how students were engaging with the various design features of i-AIDA, how easy (or not) they were to use and how useful they might be for their studies, we were particularly interested in looking at the prompts that students used when interacting with the assistant. Prompts are expressions of thinking and often represent questions [15,43]. From classroom research, we know that analyzing the thoughts and questions of students can, for example, help to diagnose students' understanding, stimulate further inquiry into the topic, and provoke critical reflections on educational practice [44]. Similarly, the analysis of learner prompts has the potential to provide insights into the thought process of learners to diagnose their understanding, interests, and needs. Furthermore, it may inform the development of assistants that specialize in responding to common themes expressed in the prompts. Therefore, our main questions were:  
1. After engaging with a beta-version of an institutional AI digital assistant (i-AIDA) what are the main perceptions of participants, and do they change their perceptions?
2. What design features encourage engagement with i-AIDA, and which design features in particular are useful to support distance learning students in the context of Education 5.0?
3. What ideas did students express in their prompts when engaging with i-AIDA?