Outline

Overview

The unit enables teacher education students who have an enthusiasm for and expertise in mathematics to undertake more extensive preparation and satisfy NESA-accreditation requirements for a primary teacher with a specialisation in mathematics. It is designed to strengthen teaching strategies for challenging aspects in K to 8 Number and Algebra, and Geometry and Measurement. Emphasis is placed on evidence-based approaches to engaging all students in learning. The unit aims to explore the roles of a mathematics specialist through lesson-study and peer-mentoring. Connections between theory, research and practice are exemplified through teaching rehearsals, lesson study and/or school visits.

Unit details and rules

Academic unit	Education
Credit points	6
Prerequisites ?	36 credit points of 3000-level EDUP-coded units
Corequisites ?	None
Prohibitions ?	None
Assumed knowledge ?	2 units of mathematics at HSC level or equivalent
Available to study abroad and exchange students	No

Teaching staff

Coordinator	Janette Bobis, janette.bobis@sydney.edu.au
Lecturer(s)	Jennifer Way, jennifer.way@sydney.edu.au
Lecturer(s)	Janette Bobis, janette.bobis@sydney.edu.au

Assessment

The census date for this unit availability is 31 March 2025

Details
Criteria

Type	Description	Weight	Due	Length
Presentation	Workshop design and presentation. Workshop presentation plus written summary and reflective statement.	40%	Multiple weeks	15 minutes (1500wd equiv) + 500wd
Outcomes assessed:
Assignment	Critical reflection on professional learning experience Reflection on in-class lesson study and peer mentoring task	15%	Week 05 Due date: 28 Mar 2025 at 23:59	500wd
Outcomes assessed:
Assignment	Extended lesson sequence Sequence of lesson plan outlines and justification	45%	Week 09 Due date: 02 May 2025 at 23:59	2000wd
Outcomes assessed:
= group assignment ? = AI allowed ?

Assessment summary

Assessment Task 1: Critical reflection on professional learning experiences

Individual students will critically reflect on their own emerging lesson analysis and peer-mentoring skills, relation to and principles of lesson-study and peer-mentoring. The basis for the reflection will be the in-class learning experiences in Week 3. University endorsed AI tools may be used to assist with this assignment, including, ‘Microsoft Copilot’ (formerly Bing Chat) at https://copilot.microsoft.com; ChatGPT And other mass-market internet browser-based generative AI tools, like Bard and MidJourney. See other endorsed tools here https://intranet.sydney.edu.au/strategy-governance/gen-ai/endorsed-tools.html

Assessment Task 2: Extended lesson sequence.

Individual students will prepare an overview of a sequence of ten lessons on selected topic from the Number & Algebra or Measurement and Space strands of the syllabus and provide a rationale for the sequence. University endorsed AI tools may be used to assist with this assignment, including, ‘Microsoft Copilot’ (formerly Bing Chat) at https://copilot.microsoft.com; ChatGPT And other mass-market internet browser-based generative AI tools, like Bard and MidJourney. See other endorsed tools here https://intranet.sydney.edu.au/strategy-governance/gen-ai/endorsed-tools.html

Assessment Task 3: Workshop design and presentation

Groups of students will design and implement a 15-minute professional learning session for their peers, focusing on an educational issue, policy, content topic or teaching strategy. Students will both seek and give feedback to their colleagues. The written component consists of a preparation summary and a brief reflective statement incorporating the feedback received. This component is submitted in Week 12 for all groups. University endorsed AI tools may be used to assist with this assignment, including, ‘Microsoft Copilot’ (formerly Bing Chat) at https://copilot.microsoft.com; ChatGPT And other mass-market internet browser-based generative AI tools, like Bard and MidJourney. See other endorsed tools here https://intranet.sydney.edu.au/strategy-governance/gen-ai/endorsed-tools.html

Assessment criteria

Results name	Mark Range	Description
High Distinction	85 -100	High distinction indicates work of an exceptional standard
Distinction	75 -84	A Distinction is a very high standard
Credit	65 - 74	A credit a good standard
Pass	50 - 64	A pass is an acceptable standard
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
Week 01	Introduction to Unit. Representation theory and the development of mathematical understanding (Pirie-Kieren model). Sequences of representations to build understanding of Number K-8, a) Multiplication: from dot arrays to dynamic digital representations of the distributive property to algorithms; b) The complexities of number lines: from counting to the number plane.	Lecture and tutorial (3 hr)
Week 02	Multiple representations & representational fluency – inclusive practices. Embodied learning. Emerging representations in early years. Measurement and Space K-8: Pedagogies for supporting spatial thinking, self-created representations and representational drawing development.	Lecture and tutorial (3 hr)
Week 03	Principles of lesson-study and peer-mentoring: Interpersonal skills, self-directed professional learning and peer mentoring strategies. Peer maths chats, lesson observation protocols. Video Lesson study 1 activity (Basis for Assessment Task 1).	Lecture and tutorial (3 hr)
Week 04	Curriculum models and teacher planning. Influences on and tensions between the official curriculum and the enacted curriculum. The role of teacher perceptions and beliefs. Translating the syllabus into a school scope and sequence plan, and alternative approaches to syllabus ‘dot points’. (Discussion of Assessment Task 2)	Lecture and tutorial (3 hr)
Week 05	Motivation and engagement, productive struggle and growth mindset Open-ended tasks and inquiry approaches – working mathematically, scaffolding and questions. Rehearsal experience and/or Lesson study 2	Lecture and tutorial (3 hr)
Week 06	Promoting student creativity, reasoning and classroom dialogue – interaction patterns. Number Talks & Talk Moves, vertical whiteboarding for problem-solving. Rehearsal experience and/or Lesson study 3	Lecture and tutorial (3 hr)
Week 07	Designing and leading professional learning workshops and issue-based meetings – rationales and approaches. Techniques for leading whole-staff discussion, debate and decision-making on issues such as homework, student grouping, reporting to parents (Jig Saw, SWOT). Approaches to workshop content and/or pedagogy (pre-survey, task-based, discussion of reading, demonstration, expert presentation etc.) (Discussion of Assessment Task 3)	Lecture and tutorial (3 hr)
Week 08	Teaching for, about and through problem solving. Types of problems and types of strategies. Contextualising problems within other disciplines. Language barriers in written problems. Structures for creating your own problems. Lesson designs for individual and collaborative problem solving - Consideration of accessibility and inclusiveness.	Lecture and tutorial (3 hr)
Week 09	Task design for learning and assessment – analyse levels of task design (e.g. Task analysis guide by Stein et al., 1998) & student responses (e.g. SOLO taxonomy). Exploring closed and open task design. Assessing student responses and work samples.	Lecture and tutorial (3 hr)
Week 10	Learning portfolios, feedback loops and communicating with families Technologies to support personalised communication. Rehearsing feedback strategies.	Lecture and tutorial (3 hr)
Week 11	Professional learning: Student presentations for Assessment Task 3.	Lecture and tutorial (3 hr)
Week 12	Professional learning: Student presentations for Assessment Task 3. Reflective practice in mathematics education – models and strategies. Revisiting lesson observation and reflective practice. Reflecting on personal learning. Setting professional goals. Articulating a ‘philosophy’ for mathematics teaching.	Lecture and tutorial (3 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

Professional Learning & Mentoring

Bobis, J., Kaur, B., Cartwright, K., & Darragh, L. (2020). Practicing teachers’ professional learning and development in mathematics education. In J. Way, C. Attard, J. Anderson, J. Bobis, H. McMaster, K. Cartwright (Eds.), Research in Mathematics Education in Australasia: 2016-2019 (pp. 117-146), Singapore: Springer.

Le Cornu, R. (2005). Peer mentoring: engaging pre‐service teachers in mentoring one another. Mentoring & Tutoring: Partnership in Learning, 13 (3), 355-366. DOI: 10.1080/13611260500105592

A comprehensive list of readings for this unit can be accessed from the Library and additional links available in 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. Demonstrate advanced development of specialised mathematical content knowledge and pedagogy in challenging aspects of the Number and Algebra, and Measurement and Space strands.
LO2. Synthesise current research, curriculum and policy documents to inform effective and inclusive practices for enhancing motivation and engagement of all students, particularly in mathematical problem solving and investigations.
LO3. Demonstrate confidence in task design and competency in the selection and effective use of robust mathematical representations in both physical and digital forms.
LO4. Demonstrate advanced knowledge and skills in planning for the teaching and assessment of key concepts in Number and Algebra, and Measurement and Space at classroom and school levels.
LO5. Demonstrate advanced development of professional confidence, interpersonal communication, identifying professional learning needs and discipline-specific curriculum leadership skills.

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 is a new unit of study for 2025. Everything is new.

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

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

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

EDUP4101: Leading Mathematics Learning A

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

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