Introduction to Artificial Intelligence 4100-1SWdSZI

The "Introduction to Artificial Intelligence" course aims to equip future foreign language teachers with the competencies necessary for the conscious and critical use of AI technology in an educational context. In light of the rapid development of digital tools, the course focuses on understanding both the technical and socio-ethical aspects of artificial intelligence, with particular emphasis on its applications in language didactics.

The program combines theoretical perspectives with practical skills for designing lessons utilizing AI. Students will familiarize themselves with the mechanisms of machine learning systems, language models, and generative tools, while also analyzing their impact on the teaching-learning process. The course addresses key issues such as: personalization of educational content, automation of language assessment, ethics of using student data, copyright issues, and the problem of algorithmic bias.

An important element is fostering a sense of professional responsibility in the era of digital transformation. Discussions and case studies will serve to develop skills in critically evaluating ready-made AI solutions and designing one's own lesson scenarios while respecting principles of equity, transparency, and student well-being. The course prepares students not only to use existing tools but also to actively participate in the debate about the future of education in the AI era.

The subject is interdisciplinary, drawing from the fields of pedagogy, glottodidactics, sociology of technology, ethics, and law. Through a combination of lectures, case study analyses, and workshops, students will acquire a comprehensive foundation for further independent development in a dynamically changing technological landscape.

Sample Topics:
Basic Concepts of AI: What is AI? Machine learning, natural language processing (NLP), generative models (e.g., LLMs - Large Language Models).

AI in Foreign Language Didactics: Practical applications: personalizing learning paths, automating the assessment of written and oral work, AI-powered tools for creating interactive exercises and teaching materials.

Ethics of AI: Algorithmic bias and fairness, transparency ("explainable AI"), data privacy and protection of student information, teacher and institutional accountability.

Copyright and Intellectual Property: Legal aspects of using AI-generated content, licensing of digital materials, copyright law in the context of content creation by AI.

AI and the Teacher-Student Relationship: Opportunities and threats. The changing role of the teacher: from knowledge transmitter to guide and facilitator in the use of technology. Impact on student autonomy and critical thinking.

The Future of AI in Education: Scenarios, trends, and recommendations for the responsible implementation of AI in schools.

Course coordinators

Małgorzata Al-Khatib

Type of course

obligatory courses

Mode

Classroom

Prerequisites (description)

Course Rationale and Foundational Principles The curriculum for the "Introduction to Artificial Intelligence" course is based on the following foundational principles, which define its pedagogical objectives and educational philosophy. Prioritization of Critical Technological Awareness. The paramount objective of this course is to cultivate critical technological awareness and the analytical capacity to evaluate new technologies, rather than merely providing technical proficiency in the use of specific, transient applications. The course is predicated on the assumption that the core competency of a modern educator is a sophisticated understanding of the operational mechanisms of AI, its potential, its limitations, and its impact on the cognitive and social processes of learners. Positioning AI as an Augmentative Tool for the Educator. Artificial Intelligence is conceptualized as an assistive and augmentative tool for the educator, rather than a substitute. According to this premise, the role of AI is to automate routine tasks and personalize the learning process, thereby enabling the educator to concentrate on the essential, interpersonal dimensions of teaching, such as building relationships, fostering critical thought, and supporting socio-emotional development. The Integrality of Ethical and Legal Perspectives. The course operates on the principle that ethical and legal reflection is an integral and inseparable component of the analysis of any technological subject matter. Issues such as the protection of intellectual property, student data privacy, algorithmic transparency, and bias are treated as fundamental to the responsible implementation of AI in educational practice. The Interdisciplinary Nature of Knowledge. It is assumed that a comprehensive understanding of the phenomenon of Artificial Intelligence necessitates an interdisciplinary approach. Consequently, the curriculum integrates perspectives from pedagogy, language didactics (glottodidactics), communication studies, law, ethics, and sociology to provide students with a holistic understanding of AI's impact on society and education. A Balanced Approach to Opportunities and Risks. The course program aims to cultivate an objective and balanced perspective on Artificial Intelligence, avoiding the extremes of both uncritical techno-optimism and prohibitive technological pessimism. The student is prepared to identify and leverage the benefits offered by AI while concurrently developing the ability to recognize and mitigate potential risks. Practical Relevance within the Professional Context. All theoretical content presented in the course is intrinsically linked to its practical application within the foreign language teaching profession. The objective is to equip students with the knowledge and tools that enable the deliberate design and evaluation of didactic processes utilizing AI, in a manner that fosters cognitive development and intellectual autonomy among learners.

Learning outcomes

(K_W11) Knows and understands fundamental concepts and principles related to the protection of industrial property and copyright in the context of generating, modifying, and using didactic materials with artificial intelligence tools. Can identify potential copyright infringements and the principles of digital content licensing.

(K_W13) Understands the fundamental social and educational dilemmas associated with the digital revolution and the development of artificial intelligence. Can critically analyze the impact of AI on the teaching profession, the learning process, and relationships within the school environment, taking into account the European context.

(K_K05) Is ready to responsibly fulfill the role of a teacher in a dynamically changing world of technology. Can make conscious and ethical didactic decisions regarding the use of AI, guided by universal norms, respect for intellectual achievements, and care for the well-being and development of the student.

Assessment criteria

**Introduction to Artificial Intelligence**

**Assessment methods and criteria**

**Programme learning outcomes assessed:** K_W11, K_W13, K_K05.

The course is assessed through a final written test and ongoing assessment activities completed during the semester. The assessment components contribute to the final result as follows:

– **final written test – 80%;**
– **ongoing assessment activities, including quizzes and polls – 20%.**

**1. Final written test (K_W11, K_W13)**
The test assesses knowledge and understanding of the course content, with particular emphasis on:

– basic concepts and principles of industrial property protection, copyright and digital content licensing in the context of artificial intelligence;
– identifying potential copyright infringements when generating, modifying and using teaching materials;
– social and educational dilemmas associated with AI development, including its impact on the teacher’s role, learning processes and relationships within the school community, with reference to the European context.

Assessment considers the accuracy of answers, understanding of concepts and relationships, and appropriate interpretation of the situations presented. Points are awarded according to the assessment criteria and scoring scheme specified for each task.

**2. Ongoing assessment activities (K_W11, K_W13, K_K05)**

Ongoing assessment activities include participation in quizzes, polls, discussions and the analysis of examples concerning the use of AI in education.

– **Quizzes (K_W11, K_W13)** – assessment considers the accuracy of answers, understanding of the topics covered and correct identification of the issues presented in the questions.

– **Polls and discussion of their results (K_W13; supporting evidence for K_K05)** – assessment considers completion of the activity and substantive contributions to the discussion of its results. Opinions expressed in polls are not marked as correct or incorrect, nor are they assessed according to whether they agree with the instructor’s views. Selecting an answer alone does not demonstrate achievement of K_K05.

– **Discussions and analysis of examples (K_W11, K_W13, K_K05)** – assessment considers the accuracy of contributions, justification of viewpoints, recognition of the consequences of proposed solutions, and consideration of pupils’ well-being, respect for intellectual work and teachers’ professional responsibility. Respectful engagement with differing arguments is also taken into account.

**3. Attendance requirements**

**One unexcused absence is permitted per semester.** Exceeding this limit results in **an NK grade and the requirement to repeat the course**, regardless of the number of points obtained. Attendance alone does not earn points.

**4. Calculation of the final grade and pass threshold**

The final result is calculated as the sum of:

– 80% of the percentage score obtained in the final written test;
– 20% of the overall percentage score obtained for ongoing assessment activities.

**The pass threshold is 60% of the combined result.** A passing grade also requires compliance with the attendance requirements.

The following grading scale applies:

– 90% to 100% – **5.0 (very good)**;
– at least 85% but below 90% – **4.5 (good plus)**;
– at least 75% but below 85% – **4.0 (good)**;
– at least 70% but below 75% – **3.5 (satisfactory plus)**;
– at least 60% but below 70% – **3.0 (satisfactory)**;
– below 60% – **2.0 (fail)**.

Practical placement

Bibliography

PDFs
Avaible here: https://helion.pl/users/konto/biblioteka:

1. Leliwa, Gniewosz. Sztuczna inteligencja. O czym myśli, gdy nikt nie patrzy? Wydawnictwo Helion, 2025.
2. Mach, K. Biblia AI. Sztuczna inteligencja jako Twój osobisty asystent w każdym aspekcie życia. FreeBooks.pl, 2025.
3. Michalska, Joanna. Szkoła w czasach AI. Jak przygotować dzieci na wyzwania jutra. MT Biznes, 2024.
4. Moroney, Laurence. Sztuczna inteligencja i uczenie maszynowe dla programistów. Praktyczny przewodnik po sztucznej inteligencji. Wydawnictwo Helion, 2021.
5. Rozum, Emil. ChatGPT i AI dla studentów. Poradnik, jak sztuczna inteligencja może Ci pomóc w nauce i pisaniu prac na studiach. Wydawnictwo Helion, 2024.
6. Raschka, Sebastian. Stwórz własne AI. Jak od podstaw zbudować duży model językowy. Wydawnictwo Helion, 2025.
7. Suleyman, Mustafa, and Michael Bhaskar. Nadchodząca fala. Sztuczna inteligencja, władza i najważniejszy dylemat ludzkości w XXI wieku. Translated by Jan Hunia, Wydawnictwo
Otwarte, 2024.
8. Trypuz, Robert. Prosto o AI. Jak działa i myśli sztuczna inteligencja?
Wydawnictwo Helion, 2024.Chojnowski, M., Etyka sztucznej inteligencji. Wprowadzenie (2022). Centrum Etyki Technologii Instytutu Humanites (link: https://ethicstech.eu/wp-content/uploads/2022/12/ESIW-v2.0_FINAL.pdf)
Gniewosz, L. (2024).Sztuczna inteligencja: O czym myśli, gdy nikt nie patrzy?.
Janiszewski, B. (2023).Sztuczna inteligencja: To, o czym starszym ci nie mówią.
Books:
Madejski, M. (2024).AI: jak się przygotować do rewolucji?
Michalska, J. (2024).Szkoła w czasach AI: Jak przygotować dzieci na wyzwania jutra.
Mollick, E. (2024).Współinteligencja: życie i praca ze sztuczną inteligencją. Ebury.
Przegalińska, A. i Oksanowicz, P. (2023).Sztuczna inteligencja: Nieludzka, arcyludzka. Społeczny Instytut Wydawniczy Znak.
Przegalińska, A. i Triantoro, T. (2024).Przenikanie umysłów: Potencjał twórczy współpracy z AI.
Raschka, S. (2024).stwórz własne AI: Jak od podstaw zbudować duży model językowy.
Spitzer, M. (2024).Sztuczna inteligencja: Ponad człowiekiem: AI jako ratunek i zagrożenie.
Suleyman, M. i Bhaskar, M. (2024).Nadchodząca fala: Sztuczna inteligencja, władza i konsekwencja ludzkości w XXI wieku.
Trypuz, R. (2024).Prosto o AI: Jak działa i myśli sztuczna inteligencja?.
Jak używać sztucznej inteligencji zgodnie z wytycznymi Komisji Europejskiej w zakresie etyki? Opracowanie przygotowane przez Grupę Roboczą ds. Sztucznej Inteligencji Podgrupa ds. etyki i prawa (link: https://ai.gov.pl/media/2025/05/Raport_GRAI_godna_zaufania_sztuczna_inteligencja_styczen_2025_pdf.pdf).

Notes

Term 2026Z:

The online lecture takes place every two weeks: October: 06 and 10 / November: 3 and 17 / December1 and 15 /January 12.
Link to the lecture: Temat: Wprowadzenie do Sztucznej Inteligencji 4100-1SWdSZI

Zoom: https://uw-edu-pl.zoom.us/j/93673053912?pwd=UvI8GLH6uRCVC5xalZpw0I1Twc55Mw.1

ID: 936 7305 3912
Code: 344972