# Artificial Intelligence for Student Assessment:
## 5 Discussion and Conclusions  
AI is today one of the main technologies being applied in all fields and at all levels. However, in education its use is not widespread, probably due to a lack of knowledge on the part of users [4], but it is set out to become one of the main tools to be used. As already mentioned, the main uses of AI applied to education are related to tutoring and assessment [40], although we also find other examples of use such as personalization [22, 41, 46] or quality assessment [20, 37, 39]. In this systematic review we have focused on analyzing the use of AI applied to student assessment based on the collection of articles published in the two main current databases: Web of Sciences and Scopus. To answer the first research objective, we can summarize that there are 454 works on AI and education in the last ten years, but after using our inclusion and exclusion criteria, we find out that only 22 studies are mainly focused on student assessment. The majority of them have been published in the last five years, and in the USA. One of the main conclusions drawn from the analysis is that, despite the differences between human and artificial intelligence [7, 8], this systematic research shows us the potential to facilitate and improve education, both face to face, blended or in virtual environments. Despite this, and notwithstanding all the great technological progress that AI has made in recent years, it is clear from the studies analyzed that pedagogical models are not usually conceived in the studies carried out. The authors who describe their work focus more on analyzing the resource itself, explaining the algorithm and the platform used, but do not emphasize the pedagogical underpinning behind the use of certain activities. Only one study [18] makes clear the use of the pedagogical model behind the choice of activities that AI will then evaluate. Three other studies [21, 38, 39] also hint at their pedagogical rationale, which is mainly based on collaboration. This is closely related to the fact that practically all the authors involved are linked to STEM or health science degrees, disciplines in which pedagogy is not very much considered. So, our answer to the research objective 2 is that the approach to AI is mainly technical, the educational approach is a secondary element in the majority of the works. Another of the main conclusions to be drawn from the analysis of the papers is the answer of our research objective three. We found that most of them focus on formative assessment, either implicitly or explicitly mentioning it. It is striking that three of the papers that do not use AI for formative assessment are linked to the assessment of English [27, 44, 50]. As for the papers that focus on formative assessment, it is clear that the idea of using AI for this task lies in the help that this technology can provide to teachers when they have a large number of students [41], or based on the idea that learning improves the more immediate the feedback given to students [21]. In some cases, this formative assessment is carried out through the automatic marking of students' work. Almost half of the works analyzed clearly describe how the AI system used automatically assesses and grades students, and how this event is used for feedback. On other occasions, the AI system used only grades the students at the end of the task, as is the case in the work of [PERSON] et al. [27]. It is also clear that most of the works that mention this automatic grading are from 2019 and 2020. The fact that virtual teaching has been developed worldwide during the 2020s may have led to a breakthrough in the development of this type of technology. Finally, it is worth noting as a conclusion of the articles analyzed how in those that make a comparison between the use of AI in one group with another that does not use it, the former obtains better results. In the same way, [PERSON] et al. [42] show how their AI system is suitable for student evaluation and grading, as it is similar to teacher evaluation.