Outline

Overview

This unit of study furthers competence in all aspects of the language, with a particular focus on advanced reading and writing skills. It deals with different aspects of Italian contemporary society through a variety of text types and levels of formality, encouraging cross-cultural appreciation and discussion.

Unit details and rules

Academic unit	Italian Studies
Credit points	6
Prerequisites ?	ITLN2612 or HSC Continuers mark of 80 or higher, or HSC Extension, or IB Italian
Corequisites ?	None
Prohibitions ?	ITLN3631 or ITLN3201 or ITLN3301
Assumed knowledge ?	None
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	Antonia Rubino, antonia.rubino@sydney.edu.au
Lecturer(s)	Antonia Rubino, antonia.rubino@sydney.edu.au
Lecturer(s)	Anna Marini, anna.marini@sydney.edu.au

Assessment

The census date for this unit availability is 31 March 2025

Details
Criteria

Type	Description	Weight	Due	Length
Participation	Seminar participation On Canvas	10%	Ongoing	Throughout semester
Outcomes assessed:
Small continuous assessment	Writing Task 1 This is a writing task on one of the topics studied and discussed as part of the syllabus.	5%	Week -05	350 words
Outcomes assessed:
Small test	In-class test This test will consist of a passage followed by various comprehension activities of different formats, some exercises of grammar and vocabulary, and a short writing task.	15%	Week 08	900 wds
Outcomes assessed:
Small continuous assessment	Writing Task 2 This is a writing task on one of the topics studied and discussed as part of the syllabus.	5%	Week 10	350 words
Outcomes assessed:
Small test	Reading & Writing test This test will consist of one reading passage with comprehension activities in different formats, all in Italian; and one short written composition in Italian.	20%	Week 12	1000 words
Outcomes assessed:
Small test	Listening test This test consists of an audio and questions in different formats to be answered (in Italian).	10%	Week 12	550 words
Outcomes assessed:
Presentation	Speaking test The Speaking Test will be a conversation between the student and the tutor. It will be based on the topics studied during the Semester. Practice questions will be provided beforehand. More detailed information about the test will be posted in Canvas.	15%	Week 13	550 words
Outcomes assessed:
Small test	Grammar test This test consists of a series of grammar exercises of different formats, based on grammatical structures and vocabulary studied throughout the semester.	20%	Week 13	800 words
Outcomes assessed:

Assessment summary

Detailed information for each assessment can be found on Canvas.

Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2014 (Schedule 1).

As a general guide, a High distinction indicates work of an exceptional standard, a Distinction a very high standard, a credit a good standard, and a pass an acceptable standard.

Result name	Mark range	Description
High distinction	85 - 100
Distinction	75 - 84
Credit	65 - 74
Pass	50 - 64
Fail	0 - 49	When you don’t meet the learning outcomes of the unit to a satisfactory standard.

For more information see guide to grades.

Use of generative artificial intelligence (AI) and automated writing tools

Except for supervised exams or in-semester tests, you may use generative AI and automated writing tools in assessments unless expressly prohibited by your unit coordinator.

For exams and in-semester tests, the use of AI and automated writing tools is not allowed unless expressly permitted in the assessment instructions.

The icons in the assessment table above indicate whether AI is allowed – whether full AI, or only some AI (the latter is referred to as “AI restricted”). If no icon is shown, AI use is not permitted at all for the task. Refer to Canvas for full instructions on assessment tasks for this unit.

Your final submission must be your own, original work. You must acknowledge any use of automated writing tools or generative AI, and any material generated that you include in your final submission must be properly referenced. You may be required to submit generative AI inputs and outputs that you used during your assessment process, or drafts of your original work. Inappropriate use of generative AI is considered a breach of the Academic Integrity Policy and penalties may apply.

The Current Students website provides information on artificial intelligence in assessments. For help on how to correctly acknowledge the use of AI, please refer to the  AI in Education Canvas site.

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

Deduction of 5% of the maximum mark for each calendar day after the due date.
After ten calendar days late, a mark of zero will be awarded.

Academic integrity

The Current Student website provides information on academic integrity and the resources available to all students. The University expects students and staff to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

We use similarity detection software to detect potential instances of plagiarism or other forms of academic integrity breach. If such matches indicate evidence of plagiarism or other forms of academic integrity breaches, your teacher is required to report your work for further investigation.

Learning support

Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a simple extension.  The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

Special consideration

If exceptional circumstances mean you can’t complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students, AI in Education includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

Support for students

The Support for Students Policy reflects the University’s commitment to supporting students in their academic journey and making the University safe for students. It is important that you read and understand this policy so that you are familiar with the range of support services available to you and understand how to engage with them.

The University uses email as its primary source of communication with students who need support under the Support for Students Policy. Make sure you check your University email regularly and respond to any communications received from the University.

Learning resources and detailed information about weekly assessment and learning activities can be accessed via Canvas. It is essential that you visit your unit of study Canvas site to ensure you are up to date with all of your tasks.

If you are having difficulties completing your studies, or are feeling unsure about your progress, we are here to help. You can access the support services offered by the University at any time:

Support and Services (including health and wellbeing services, financial support and learning support)
Course planning and administration
Meet with an Academic Adviser

Weekly schedule

WK	Topic	Learning activity	Learning outcomes
Weekly	The program and related activities are detailed in the week-by-week syllabus available in Canvas.	Tutorial (3 hr)

Attendance and class requirements

Attendance: According to the Faculty of Arts and Social Sciences Student Attendance at classes provisions, students are expected to attend a minimun of 90 per cent of timetabled activities for a unit of study, unless granted exemption by the Associate Dean or relevant delegated authority. If you are absent from 50% or more of classes, regardless of the reasons for the absence, you will be automatically referred to the end-of-semester departmental examiners’ meeting for a determination.
Students are expected to be in attendance at the correct time and place of any formal or informal examinations.
Preparation: Students should commit to spend approximately three hours’ preparation time (reading, studying, homework, etc.) for every hour of scheduled instruction.

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.

Required readings

Required textbook: Balì, Maria and Ziglio, Luciana (2015) Nuovo Espresso 3, Corso di italiano. Libro dello studente e esercizi. ALMA Edizioni, Firenze (Textbook without DVD).

You can also access this textbook in an online version.

Recommended resources:

• De Rôme, D. ‘Soluzioni. A practical grammar of contemporary Italian’, Routledge (or another equivalent good Italian grammar)

• Monolingual dictionary (Zanichelli)

Learning outcomes

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University's graduate qualities and are assessed as part of the curriculum.

Outcomes
Graduate qualities

At the completion of this unit, you should be able to:

LO1. Possess a body of linguistic and cultural knowledge appropriate to the unit of study’s European Framework of Reference (CEFR) level or equivalent (B1-B2).
LO2. Possess and continue to develop a standard of oral and written communication skills in Italian, appropriate to the unit of study’s European Framework of Reference (CEFR) level or equivalent (B1-B2)
LO3. Use appropriate media, tools and methodologies to locate, access and use information related to the language and culture studied
LO4. Understand and practise the highest standards of ethical behaviour associated with communication and interactions in Italian language and culture
LO5. Be independent learners who take responsibility for their own learning setting appropriate goals; work effectively in teams and other collaborative contexts
LO6. Use language skills and advanced digital tools to acquire an in-depth knowledge of Italian-speaking societies and cultures

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1	Depth of disciplinary expertise Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.
GQ2	Critical thinking and problem solving Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.
GQ3	Oral and written communication Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.
GQ4	Information and digital literacy Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.
GQ5	Inventiveness Generating novel ideas and solutions.
GQ6	Cultural competence Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.
GQ7	Interdisciplinary effectiveness Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.
GQ8	Integrated professional, ethical, and personal identity An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.
GQ9	Influence Engaging others in a process, idea or vision.

Outcome map

Learning outcomes	Graduate qualities
Learning outcomes

Responding to student feedback

This section outlines changes made to this unit following staff and student reviews.

This unit of study is regularly updated following previous year students’ feedback and comments. In particular, more attention has been devoted to in-class activities, group and grammar explanation. Material from the textbook has also been adapted and some topics supplemented or reduced.

Disclaimer

Important: the University of Sydney regularly reviews units of study and reserves the right to change the units of study available annually. To stay up to date on available study options, including unit of study details and availability, refer to the relevant handbook.

To help you understand common terms that we use at the University, we offer an online glossary.

Current students

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Use of generative artificial intelligence (AI) and automated writing tools

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

Weekly schedule

Weekly schedule

Attendance and class requirements

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Disclaimer

On this page

Useful links

ITLN3611: Italian 5

Semester 1, 2025 [Normal day] - Camperdown/Darlington, Sydney

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Use of generative artificial intelligence (AI) and automated writing tools

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

Weekly schedule

Weekly schedule

Attendance and class requirements

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Disclaimer

On this page

Useful links