Outline

Overview

This compulsory unit of study is the third and final unit in primary mathematics education. It is designed to build on the content and ideas introduced in Mathematics Education 1 and 2, with emphasis on Number and Algebra Strand in Stages 2 and 3 of the NSW Mathematics Syllabus for the Australian Curriculum. The unit will explore how children's mathematical thinking strategies develop via research-based frameworks and assessment-based planning for teaching.

Unit details and rules

Academic unit	Education
Credit points	4
Prerequisites ?	138 credit points including EDUP3004 and EDUP3006 and EDUP3007 and (EDUP3009 or EDUP3010) and EDUP3034
Corequisites ?	None
Prohibitions ?	None
Assumed knowledge ?	None
Available to study abroad and exchange students	No

Teaching staff

Coordinator	Jennifer Way, jennifer.way@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
Practical skill	Assignment 1a Writing a diagnostic interview Assessment-based planning part A of a 3-part assignment	5%	Week 03 Due date: 22 Aug 2025 at 23:59	200 words	AI allowed
Outcomes assessed:
Written work	Assignment 1b Student profile Assessment-based planning part B of a 3-part assignment. See Canvas.	45%	Week 06 Due date: 12 Sep 2025 at 23:59	1250 words	AI allowed
Outcomes assessed:
Written work	Assignment 1c Unit of work design Assessment-based planning part C of a 3-part assignment. See Canvas.	20%	Week 08 Due date: 26 Sep 2025 at 23:59	800 words	AI allowed
Outcomes assessed:
Written work	Conducting a statistical investigation Digital media report/presentation of statistical investigation	30%	Week 12 Due date: 27 Oct 2025 at 23:59	750 words equivalent	AI allowed
Outcomes assessed:
= hurdle task ? = group assignment ?

Assessment summary

Assessment-based planning: This is a three-part assignment requiring students to develop and demonstrate their ability to design and implement a task-based assessment (diagnostic) interview protocol for stage 2/3 fractions, then plan appropriate learning experiences to cater for the differing needs of a class.
Conducting a Statistical Investigation: In pairs, plan an investigation and prepare digital media report for presentation in-class.

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	Exceptional
Distinction	75 - 84	Very high
Credit	65 - 74	Good
Pass	50 - 64	Acceptable
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)

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.

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	1. Unit introduction; 2. Representations in mathematics; 3. Issues in fractions learning; 4. Assignment 1 briefing	Lecture (1 hr)
Week 01	1. Multiple representations of fractions concepts and processes; 2. Whole class lessons using technology	Tutorial (1 hr)
Week 02	1. Fractions framework – development of proportional thinking; 2. Task-based interviews	Lecture (1 hr)
Week 02	1. Designing diagnostic tasks for fractions concepts and skills; 2. Feedback on assessment	Tutorial (1 hr)
Week 03	1. Multiplicative thinking and proportional reasoning; 2. Equivalence and operations with fractions	Lecture (1 hr)
Week 03	1. Supporting transition to mental strategies and symbolic notation; 2. Calculators for fractions; 3. Anticipating misconceptions and misunderstandings	Tutorial (1 hr)
Week 04	Place value with whole numbers and decimal fractions	Lecture (1 hr)
Week 04	Tasks and resources to promote understanding of decimal fractions;	Tutorial (1 hr)
Week 05	Multiplicative thinking and proportional reasoning.	Lecture (1 hr)
Week 05	Advancing strategies for multiplication & division. Exploring connections between fractions, percentages, ratios and rates	Tutorial (1 hr)
Week 06	Choosing teaching approaches to fit mathematics content and student learning needs. Consideration of learning theories in the design of lessons and tasks	Lecture (1 hr)
Week 06	Designing lesson sequences using knowledge of student learning and content to set goals, and choosing effective teaching practices that support all students. (Group meetings)	Tutorial (1 hr)
Week 07	Developing student’s algebraic thinking. Developing a growth mindset.	Lecture (1 hr)
Week 07	Teaching algebra through selecting appropriate mathematical investigations and planning questions and scaffolding to promote mathematical thinking and generalisation.	Tutorial (1 hr)
Week 08	Key concepts and skills in working with data K-6. Syllabus and learning progression for data Assignment 2 briefing.	Lecture (1 hr)
Week 08	Data-based inquiry and supporting student reasoning. Displaying and interpreting data	Tutorial (1 hr)
Week 09	The role of mathematics in STEM education, Numeracy, KLA integration and evidence-based reasoning.	Lecture (1 hr)
Week 09	Contexts for learning and applying mathematics and mathematical thinking	Tutorial (1 hr)
Week 10	Probabilistic thinking and types of probability. ‘Big ideas’ of expectation, variation and randomness. Chance in the syllabus.	Lecture (1 hr)
Week 10	Supporting the development of descriptive interpretation of chance events and the beginning of quantification of probability. Using digital tools to explore probability.	Tutorial (1 hr)
Week 11	Large-scale numeracy assessments and what can and cannot be learnt from them.	Lecture (1 hr)
Week 11	Reflecting on major transitions in mathematics learning through examining student work samples.	Tutorial (1 hr)
Week 12	1. Continued professional learning; 2. Programming mathematics	Lecture (1 hr)
Week 12	Data investigation examples and application of digital technologies. Assignment 2 presentations	Tutorial (1 hr)

Attendance and class requirements

Attendance: The Sydney School of Education and Social Work requires attendance of at least 90 percent of all seminars, workshops or lectures. Where a student is unable to attend at the required rate evidence of illness or misadventure may be required and the student may be required to undertake extra work. Students should discuss the circumstances of their absence(s) with the co-ordinator of the unit of study. Further details are provided in the School canvas site: https://canvas.sydney.edu.au/courses/13426

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 4 credit point unit, this equates to roughly 80-100 hours of student effort in total.

Required readings

All readings for this unit can be accessed on links available on Canvas.

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. use a diagnostic interview to assess a child’s level of mathematical thinking and analyse the results in relation to a research-based framework of number development
LO2. demonstrate the ability to work collaboratively with peers in the design of a sequence of learning experiences based on the outcomes of diagnostic assessments
LO3. utilise appropriate ICT to further your own knowledge in mathematics education and communicate professionally with peers
LO4. develop the ability to choose, provide and use appropriate mathematical activities that promote risk taking, foster efficient learning strategies, develop positive attitudes, promote enjoyment and provide opportunities for children to create for themselves mathematical thinking skills
LO5. demonstrate your understanding of a variety of assessment strategies, including clinical interviewing, observation and work sample analysis, and evaluate, record and report a child’s developing mathematical need
LO6. demonstrate the integration of theory and practice through the choice of activities and assessment methods
LO7. build on your own personal philosophy of how children learn mathematics based on readings, reflections and practical experiences.

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.

No changes have been made since this unit was last offered except the textbook has been removed and learning outcomes have been added to each lecture and tutorial class.

Additional information

Site visit guidelines

If you are undertaking professional experience/field education placement as part of your enrolment in this unit of study, please assess your specific needs and requirements for the safe and successful completion of an external placement within a host organisation. You will be given the opportunity to disclose any health issues that have a work health and safety significance before arranging a placement so that your safety, and the safety of others, can be properly assessed. The Professional Experience Coordinator/Field Education Manager will work to ensure that the workplace assignment to you is appropriate for your needs and requirements. If you are experiencing disability, and require reasonable adjustments to be arranged, please contact Disability Services as early as possible prior to commencing the internship. Please note, in all cases, and for the purpose of organising reasonable adjustments, only the impact and not the nature, of your disability will be disclosed to the host organisation.

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)

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

Additional information

Additional information

Site visit guidelines

Disclaimer

On this page

Useful links

EDUP4074: Mathematics Education 3

Semester 2, 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)

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

Additional information

Additional information

Site visit guidelines

Disclaimer

On this page

Useful links