Ai in Education
A.Y. 2024/2025
Learning objectives
Course objective is to acquire knowledge and develop skills useful for applying Artificial Intelligence technologies to teaching and learning activities and processes so as to achieve a qualified integration between the potential of machines and the attitudes of training experts.
Expected learning outcomes
A: Knowledge and understanding
At the end of the course, the student will:
- Know and understand the institutional, historical, and regulatory frameworks on a national and international scale that affect the adoption of Artificial Intelligence in education and teaching
- Know and understand the issues affecting the contemporary realities of education
- Know and understand the basic tools for interpreting and analyzing specific issues, in the short-, medium-, and long-term perspectives
B: Ability to apply knowledge and understanding
At the end of the study path, the students will:
- Know how to apply his or her knowledge in national and international professional settings
C: Autonomy of judgment
At the end of the course, the student will be able to:
- Make decisions and deal with complex situations through the ability to autonomously integrate their knowledge of AI in education, even when faced with partial and incomplete data and information
- Reflect on the social and ethical responsibilities related to the application of their knowledge in education and teaching
-act in accordance with a principle of responsibility and non-discrimination
D: Communication skills
At the end of the course, the student will be able to:
- Write reports and papers on issues concerning AI in education
- communicate the results of their work while respecting the principles of transparency of public action
- refer to disciplinary lexicons
E: Learning ability
At the end of the course, the student will be able to:
- Set their own methodological and content update on AI in education
- select, analyze and process the data that are the subject of their study
At the end of the course, the student will:
- Know and understand the institutional, historical, and regulatory frameworks on a national and international scale that affect the adoption of Artificial Intelligence in education and teaching
- Know and understand the issues affecting the contemporary realities of education
- Know and understand the basic tools for interpreting and analyzing specific issues, in the short-, medium-, and long-term perspectives
B: Ability to apply knowledge and understanding
At the end of the study path, the students will:
- Know how to apply his or her knowledge in national and international professional settings
C: Autonomy of judgment
At the end of the course, the student will be able to:
- Make decisions and deal with complex situations through the ability to autonomously integrate their knowledge of AI in education, even when faced with partial and incomplete data and information
- Reflect on the social and ethical responsibilities related to the application of their knowledge in education and teaching
-act in accordance with a principle of responsibility and non-discrimination
D: Communication skills
At the end of the course, the student will be able to:
- Write reports and papers on issues concerning AI in education
- communicate the results of their work while respecting the principles of transparency of public action
- refer to disciplinary lexicons
E: Learning ability
At the end of the course, the student will be able to:
- Set their own methodological and content update on AI in education
- select, analyze and process the data that are the subject of their study
Lesson period: First semester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course can be attended as a single course.
Course syllabus and organization
Single session
Responsible
Lesson period
First semester
Course syllabus
1. The culture of artificial intelligence and the contexts of education
2. a brief history of Artificial Intelligence in Education
3. Educating for Artificial Intelligence: Digital Citizenship and Data Literacy, AI literacy
4. Educating with Artificial Intelligence: systems, teaching, training
5. ethics and Design of artificial intelligence applied to education
2. a brief history of Artificial Intelligence in Education
3. Educating for Artificial Intelligence: Digital Citizenship and Data Literacy, AI literacy
4. Educating with Artificial Intelligence: systems, teaching, training
5. ethics and Design of artificial intelligence applied to education
Prerequisites for admission
No prior knowledge is needed
Teaching methods
Lectures
Debate and discussion
Group work
e-tivites
Debate and discussion
Group work
e-tivites
Teaching Resources
1. Kurni, M., Mohammed, M.S. , Srinivasa K G (2023). A beginner's guide to introduce Artificial Intelligence in teaching and learning. Springer Nature.
2. Mormando S., Gumper, C. & Devine, J. (2024). Navigating the AI revolution in our schools. Edvative Learning Corporation: Prospect Park, Pennsylvania.
3. papers and other resources published - Communicate by the end of september.
2. Mormando S., Gumper, C. & Devine, J. (2024). Navigating the AI revolution in our schools. Edvative Learning Corporation: Prospect Park, Pennsylvania.
3. papers and other resources published - Communicate by the end of september.
Assessment methods and Criteria
oral exam: The purpose of the oral exam will be to test the knowledge and skills acquired by students in light of the activities and other course topics.
Evaluation criteria:
- knowledge of the theoretical aspects of the topics discusses during the course (exposition);
- ability to exemplify concepts (understanding);
- capacity of use and apply concepts (development);
- communication skills in terms of the appropriateness of the language used to explain the competences acquired and the related problems.
Evaluation criteria:
- knowledge of the theoretical aspects of the topics discusses during the course (exposition);
- ability to exemplify concepts (understanding);
- capacity of use and apply concepts (development);
- communication skills in terms of the appropriateness of the language used to explain the competences acquired and the related problems.
M-PED/03 - METHODOLOGIES OF TEACHING AND SPECIAL EDUCATION - University credits: 6
Lessons: 48 hours
Professor:
Garavaglia Andrea
Educational website(s)
Professor(s)
Reception:
Friday from 9am to 12am on Microsoft Teams. Please read information
Online in Microsoft Teams