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DigitalRecent competencesstudies conducted with university students show that attitudes towards artificial intelligence (AI) can vary significantly based on demographic variables such as gender, age, education level, and field of teachersstudy. areThis recognized as a prerequisite for a successful teaching process. The initial teacher educationstudy aims to ensureunderstand the developmentattitudes of competencesstudents necessaryat forthe entryUniversity of Shkoder, regarding artificial intelligence (AI) and to identify the possible variables that influence these attitudes. The research employs a descriptive research design, according to the profession,quantitative approach. A sample of 170 university students, including teacher144 digitalfemales competence,and which26 ismales, consideredwas selected using non-probability sampling due to convenience. The AI attitude scale (AIAS-4) developed by Grassini in 2023, administered online, was used for data collection. The results indicated that female students display a more positive attitude towards AI compared to their male colleagues. Moreover, our research has proven a significant difference in attitudes towards AI among university students specializing in different branches, with Social Work students showing a significantly positive attitude towards AI compared to other branches. The findings of this study suggested that there are no statistically significant differences regarding AI attitudes among students of different age groups. Furthermore, we examined the fundamental competenceinfluence of alleducational teacherslevel today.on AI attitudes and found no significant difference in attitudes at different educational levels among university students.
TheIn European Commission has developedconclusion, the European Framework for Teachers' Digital Competences (DigCompEdu, 2017) which includes and describes 22 digital competences specific to teachers in six areas: professional engagement, digital resources, and materials, learning and teaching, monitoring and evaluation, empowering students, enabling development and directing students' digital competences.
The complexity of social processes and the accelerated development of knowledge impose the need for constant professional development and continuous learning, which is necessary so that teachers can follow and implement innovations in their performance curricula, as well as in their daily work with students.
In order to enable the continuum in the development of digital competences following initial teacher education, the ContinueUP project created a model for harmonizing the learning outcomes of digital competence in the area of professional engagement,study at the levelUniversity of initialShkoder teacherreveals that female students hold a more positive attitude towards AI compared to males. Social Work students show notably positive views. Age and educational levels do not significantly impact AI attitudes among university students. To promote diversity, AI education should be tailored to different fields of study, and itsongoing further development at professional development programs. The competence development modelresearch is basedcrucial onfor theunderstanding developmentevolving ofattitudes digitaltowards competences at the levels recognized in DigCompEd and ensures a continuum in the development of the digital competence of teachers. The model is applicable in an international context and meets the needs of teachers across Europe.AI.
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