The aim of this course is to introduce, consolodate and exercise reading, speaking, reading and writing in order to facilitate student's B2 or upper-intermediate English proficiency within a relevent and emerging topic in the field.  

The main approach will center around content and language integrated learning (clil), with many of the linguistic issues emerging at the behest of the learner. 

01. vocabulary and grammar focused on MACHINE LEARNING

     01.01. Speaking exercises on the topic of Intelligent Machines

     01.02. listening practice regarding What is artificial intelligence?

     01.03. composition and writing exercises on the basics of machine learning

     01.04. Reading and discussion exercise on AI Ethics

02. language consolidation focused on GENERATIVE AI

     02.01. Listenign and discussion practice and approaches: Real or Fake?

     02.02. Conversational English with Chatbots

     02.03. English grammatical emphasis and composition for Prompt engineering & how LLMs work

     02.04. Reading & wrting practice emphasizing AI and human creativity

     02.05. Oral speaking, pronunciation and consolidation with AI enhanced presentation & research

None.

Knowledge and Understanding:

• Discussing AI Misconceptions in English: Graduates will demonstrate the ability to articulate and explain common misconceptions surrounding Artificial Intelligence (AI) and their origins using clear and accurate English.
• Understanding and Using AI Terminology in English: Graduates will demonstrate knowledge and understanding of key terminology and concepts related to Artificial Intelligence (e.g., neural networks, data sets, large language models) and be able to define and apply these terms appropriately in English discussions and written work.
• Describing AI Functionality in English: Graduates will demonstrate a comprehensive understanding of the basic principles and underlying mechanisms of how AI tools and Large Language Models function, and be able to describe these functionalities clearly and precisely in English.

Applying Knowledge and Understanding:

• Analyzing AI's Impact through English Discourse: Graduates will be able to apply their understanding of AI to analyze its impact across various fields (e.g., transportation, healthcare, creative arts) and effectively discuss potential implications and express their analysis in English.
• Applying English in Prompt Engineering: Graduates will be able to apply effective prompt engineering techniques to formulate clear, precise, and targeted queries for AI chatbots and generative tools, demonstrating proficiency in constructing sophisticated English prompts.

Making Judgements:

• Evaluating AI-Generated Content and Expressing Judgments in English: Graduates will be able to make informed judgments regarding the validity and quality of information, particularly when evaluating AI-generated content and identifying "hallucinations," and be able to express these judgments clearly and critically in English.
• Articulating Diverse Perspectives on AI in English: Graduates will be able to make reasoned judgments that acknowledge and respect diverse ethical perspectives and viewpoints concerning the use and implications of AI, and be able to articulate and debate these perspectives effectively in English.

Communication Skills:

• Engaging in English Discussions on AI: Graduates will be able to communicate effectively, fluently expressing their opinions, feelings, and insights about AI clearly and coherently in English discussions with peers and instructors.
• Summarizing Complex AI Information in English: Graduates will be able to communicate complex information concisely by accurately summarizing content from various AI-related videos and articles in well-structured English.

Learning Skills:

• Reflecting on Linguistic and AI Learning in English: Graduates will develop and apply learning skills to critically reflect on their own learning process and experiences with AI tools, fostering self-awareness and continuous improvement in their linguistic proficiency (specifically in English related to AI topics) and digital literacy.

The teaching material prepared by the lecturer in addition to recommended textbooks (such as for instance slides, lecture notes, exercises, bibliography) and communications from the lecturer specific to the course can be found inside the Moodle platform › blended.uniurb.it

We recommend contacting the CLA (University Language Centre) to enrol and attend English language courses (General English), offered free of charge at all levels.

Teaching

Socratic seminar, in class discussion and listening activities will be a central part of the learning structure, with time in class also given to reading and writing exercises to be given direct instrucot feedback.

Innovative teaching methods

Lessons scaffolded with an emphasis on peer interaction (think,pair, share). Multimedia tools are heavily incorporated for listening and textual access. Experimental AI creative enhancement and application for language learning is an emerging approach to teaching and learning which this course hopes to explore.

Attendance

Students must have a knowledge of the English language around the B1+ level or higher. Please remember the possibility of attending free English language courses at all levels at the CLA.

Study the materials that will be proposed in class, as well as the grammatical topics, using the indicated grammar text and the materials uploaded on blended. 

Attendance at this course is strongly recommended.

Course books

There is no central text of the course, but all reading materials and exercises will be available on Blended.

Assessment

The aptitude test consists of both an oral presentation and a reading comprehension with a written response.

The reading comprehension with a written response will be based on a short, unseen text, and a stimulus question to provoke a authentic response.

Only those who pass the reading/writing exam will make it to the oral presentation.

The oral presentation will be prepared by students prior to the exam, applying some of the technologies in class, but emphasizing a clear articulation, pronunciation and spontaneous production based upon interaction with the interloculator.

Disability and Specific Learning Disorders (SLD)

Students who have registered their disability certification or SLD certification with the Inclusion and Right to Study Office can request to use conceptual maps (for keywords) during exams.

To this end, it is necessary to send the maps, two weeks before the exam date, to the course instructor, who will verify their compliance with the university guidelines and may request modifications.

Teaching

Individual study based upon content and guide available on Blended

Attendance

Students must have a knowledge of the English language around the B1+ level or higher. Please remember the possibility of attending free English language courses at all levels at the CLA.

Study the materials that will be proposed in class, as well as the grammatical topics, using the grammar text and the recommended dictionaries, as well as the materials uploaded on blended. 

Course books

There is no central text of the course, but all reading materials and exercises will be available on Blended.

Assessment

The aptitude test consists of both an oral presentation and a reading comprehension with a written response.

The reading comprehension with a written response will be based on a short, unseen text, and a stimulus question to provoke a authentic response.

Only those who pass the reading/writing exam will make it to the oral presentation.

The oral presentation will be prepared by students prior to the exam, applying some of the technologies in class, but emphasizing a clear articulation, pronunciation and spontaneous production based upon interaction with the interloculator.
 

Disability and Specific Learning Disorders (SLD)

Students who have registered their disability certification or SLD certification with the Inclusion and Right to Study Office can request to use conceptual maps (for keywords) during exams.

To this end, it is necessary to send the maps, two weeks before the exam date, to the course instructor, who will verify their compliance with the university guidelines and may request modifications.