Conference Program

Artificial intelligence is making rapid progress in all sectors of society as well as in the field of education by becoming a major educational technology (Carvalho et al., 2022). Artificial intelligence in education has four main areas of application:

1. profiling and prediction,

2.assessment and evaluation,

3. adaptive systems and personalization, and

4. intelligent tutoringsystems (Zawacki-Richter et al., 2019).

Since attitudes and personality are relevant to the adoption of new technology (Park & Woo, 2022) the present study aims to investigate teachers' attitudes toward the use of AI in education concerning their perceived knowledge of AI (self-reports on
course attendance and usefulness), some individual characteristics assessed through the Big Five Inventory (Fossati et al., 2011), and a self-efficacy scale related to the ability to recognize the originality of a paper done by a student and to recognize a paper done by an AI. The questionnaire consists of 74 items of which 3 with open-ended questions, the other items are multiple choices. The questionnaire was administered online and addressed only to secondary school teachers (first and second grade). The research tool used to administrate the survey is Qualtrics and the data were analyzed using Mixed-method methodology to identify quantitative-descriptive and qualitative-anecdotal information related mainly to the frequency of words recorded in the open-ended questions. In total of 58 replies were collected. Although the sample is random and not representative of the entire country, the data allow for a meaningful analysis of teachers’ attitudes, at present, on AI. Especially the multidisciplinary approach, pedagogical and psychological, gives the study an original setting.

Since the public advent of ChatGPT in November 2022, there was immediate discussion about the impact that Artificial Intelligence would have in the educational context. Most of the scenarios featured AI in the role of Tutor (positive scenario) or actual substitute for the traditional teachers (dystopian scenario). However, little has been discussed about the gradual implementations of AI in the academic context and how these “almost invisible” implementations can benefit students. In this sense, a possible application, consists in the improvement of the compensatory tools indicated for BES and DSA students who - through the implementation of AI - could further improve the students' personal study experience thanks to their high level of personalization.

Among these new technologies, we can add Reasy, an all-round study support application based on scientific research from the European Vrailexia project on dyslexia and created by Tech4All, a university spin-off of the University of Tusciain Viterbo. Powered by generative AI, the application allows the student total customization of texts, the creation of summaries, concept maps, as well as the text to speech function. But how can we evaluate the impact that these new compensatory tools have on DSA students? In previous introductory research, we focused on the immediate cognitive results, quantitatively evaluating whether the student had immediate improvements in understanding the text using the compensatory tool. We soon realized that this method of analysis was not valid as a cognitive analysis includes too many subjective variables, including time: each student learns at his own pace. If we want to draw a parallel, it's like the metaphor of eyeglasses: putting on glasses allows the patient with blurry vision to focus on the world around him, allowing him to see better. This does not create an immediate cognitive improvement but a psychological and emotional situation that will allow him to improve over time. Likewise - from the study - the Reasy application seems to put the subject at ease with the written text, giving him the possibility of entering a more "proactive" mental state towards the text. Starting from these assumptions we decided to evaluate the efficiency of the compensatory tool based on a qualitative and quantitative analysis on the constructs of "emotional perception" and "self-efficacy" of the dyslexic student in a context in which he is asked to read without and with compensatory tool. To do this, a sample of DSA high school and university students with certified dyslexia was used and the survey was conducted with the GEW (Geneva Emotion Wheel) instrument, which is a theoretically derived and empirically tested instrument to measure emotional reactions to objects, events, and situations.