PHIL1012: Semester 2, 2025

Units PHIL1012 Semester 2 2025 [Normal day]

Unit outline_

PHIL1012: Introductory Logic

Semester 2, 2025 [Normal day] - Camperdown/Darlington, Sydney

Overview

An introduction to modern logic: the investigation of the laws of truth. One essential aspect of good reasoning or argumentation is that it is valid: it cannot lead from true premises to a false conclusion. In this unit we learn how to identify and construct valid arguments, using techniques such as truth tables, models and truth trees. Apart from being a great aid to clear thinking about any subject, knowledge of logic is essential for understanding many areas not only of contemporary philosophy, but also linguistics, mathematics and computing.

Unit details and rules

Academic unit	Philosophy
Credit points	6
Prerequisites ?	None
Corequisites ?	None
Prohibitions ?	None
Assumed knowledge ?	None
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	Nicholas Smith, nicholas.smith@sydney.edu.au
Lecturer(s)	Nicholas Smith, nicholas.smith@sydney.edu.au

Assessment

The census date for this unit availability is 1 September 2025

Details
Criteria

Type	Description	Weight	Due	Length	Use of AI
Written exam ?	Exam 2 hour Final Examination (2250 word equivalent)	60%	Formal exam period	2 hours	AI prohibited
Outcomes assessed:
Practical skill	Problem Sets Problem Sets	40%	Multiple weeks	8 x 250 word equivalent	AI allowed
Outcomes assessed:
Out-of-class quiz	Quiz #earlyfeedbacktask	0%	Week 03	250 word equivalent	AI allowed
Outcomes assessed:
= hurdle task ? = early feedback task ?

Early feedback task

This unit includes an early feedback task, designed to give you feedback prior to the census date for this unit. Details are provided in the Canvas site and your result will be recorded in your Marks page. It is important that you actively engage with this task so that the University can support you to be successful in this unit.

Assessment summary

For the Quiz and the Problem Sets, questions will be posted online, and you submit your answers online. Full details concerning dates and procedures will be given on the Canvas site.

The Exam is a final examination to be held in the exam period. The date and time of the exam will be determined by the Examinations Office and communicated to you via your exam timetable.

If you fail to submit enough of the Problem Sets, or fail to sit the Exam, you will get a final grade of Absent Fail. Full details will be given on the Canvas site.

The Exam is a Hurdle Task: a passing standard must be met in this assessment in order to pass the unit as a whole, regardless of overall performance.

Assessment criteria

The Problem Sets constitute 40% of your final mark for the unit. Each problem set individually is worth 5%.

For more information see guide to grades.

Use of generative artificial intelligence (AI)

You can use generative AI tools for open assessments. Restrictions on AI use apply to secure, supervised assessments used to confirm if students have met specific learning outcomes.

Refer to the assessment table above to see if AI is allowed, for assessments in this unit and check Canvas for full instructions on assessment tasks and AI use.

If you use AI, you must always acknowledge it. Misusing AI may lead to a breach of the Academic Integrity Policy.

Visit the Current Students website for more information on AI in assessments, including details on how to acknowledge its use.

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.

This unit has an exception to the standard University policy or supplementary information has been provided by the unit coordinator. This information is displayed below:

Information on applying for Special Consideration, in case illness or misadventure prevents you submitting work on time or attending the Exam, is on the Current Students site. Work submitted late, without special consideration, will be penalised per day late in accordance with University policy. For each Problem Set, there is also a further date (usually one week after the due date) after which no submissions can be accepted at all: precise details of these dates for each Problem Set will be given on the Canvas site.

Academic integrity

The University expects students to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

Our website provides information on academic integrity and the resources available to all students. This includes advice on how to avoid common breaches of academic integrity. Ensure that you have completed the Academic Honesty Education Module (AHEM) which is mandatory for all commencing coursework students

Penalties for serious breaches can significantly impact your studies and your career after graduation. It is important that you speak with your unit coordinator if you need help with completing assessments.

Visit the Current Students website for more information on AI in assessments, including details on how to acknowledge its use.

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
Week 01	Propositions and Arguments	Lecture (2 hr)
Week 02	The Language of Propositional Logic; Semantics of Propositional Logic	Lecture (2 hr)
Week 02	Previous Week's Lecture Topics	Tutorial (1 hr)
Week 03	Uses of Truth Tables; Logical Form	Lecture (2 hr)
Week 03	Previous Week's Lecture Topics	Tutorial (1 hr)
Week 04	Connectives: Translation and Adequacy	Lecture (2 hr)
Week 04	Previous Week's Lecture Topics	Tutorial (1 hr)
Week 05	Trees for Propositional Logic	Lecture (2 hr)
Week 05	Previous Week's Lecture Topics	Tutorial (1 hr)
Week 06	The Language of Monadic Predicate Logic	Lecture (2 hr)
Week 06	Previous Week's Lecture Topics	Tutorial (1 hr)
Week 07	Semantics of Monadic Predicate Logic	Lecture (2 hr)
Week 07	Previous Week's Lecture Topics	Tutorial (1 hr)
Week 08	Trees for Monadic Predicate Logic	Lecture (2 hr)
Week 08	Previous Week's Lecture Topics	Tutorial (1 hr)
Week 09	The Language of General Predicate Logic	Lecture (2 hr)
Week 09	Previous Week's Lecture Topics	Tutorial (1 hr)
Week 10	Semantics of General Predicate Logic; Trees for General Predicate Logic	Lecture (2 hr)
Week 10	Previous Week's Lecture Topics	Tutorial (1 hr)
Week 11	The Identity Relation; General Predicate Logic with Identity; Semantics of General Predicate Logic with Identity	Lecture (2 hr)
Week 11	Previous Week's Lecture Topics	Tutorial (1 hr)
Week 12	Trees for General Predicate Logic with Identity; Numerical Quantifiers	Lecture (2 hr)
Week 12	Previous Week's Lecture Topics	Tutorial (1 hr)
Week 13	Previous Week's Lecture Topics	Tutorial (1 hr)

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

Nicholas J.J. Smith. Logic: The Laws of Truth. Princeton University Press, Princeton, 2012.

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. demonstrate understanding of the formal languages of propositional and predicate logic, and ability to translate propositions of English into those formal languages
LO2. demonstrate understanding of the semantics of classical propositional logic in terms of truth tables
LO3. demonstrate understanding of the semantics of classical predicate logic in terms of models
LO4. demonstrate understanding of, and ability to construct, tree proofs for classical propositional and predicate logic
LO5. improvement in skills of logical analysis and reasoning

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.

The content and design of this unit are reviewed each time it is taught, in light of student evaluations, peer review and informal feedback. If you have any comments or suggestions, please let us know at any time during the semester.

Additional information

Disclaimer

The University reserves the right to amend units of study or no longer offer certain units, including where there are low enrolment numbers.

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

Early feedback task

Assessment summary

Assessment criteria

Use of generative artificial intelligence (AI)

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

Weekly schedule

Weekly schedule

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Disclaimer

On this page

Useful links