HPSC3888: Semester 2, 2023

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Units HPSC3888 Semester 2 2023 [Normal day]

Unit outline_

HPSC3888: HPSC Interdisciplinary Project

Semester 2, 2023 [Normal day] - Camperdown/Darlington, Sydney

Overview

Our ever-changing world requires knowledge that extends across multiple disciplines. The ability to identify and explore interdisciplinary links is a crucial skill for emerging professionals and researchers alike. This unit presents the opportunity to bring together the concepts and skills you have learnt in your discipline and apply them to a real-world problem. You will work on a project which involves evaluating theories in HPS based on knowledge drawn from collaborators in another discipline, for instance by taking a recent scientific controversy or theoretical innovation as a case study. For example, you might test a proposal about the theoretical basis of neuroscience by comparing it to a predictive coding model of brain function, or test assumptions about how scientific models work by studying specific models in climatology or ecology. In this unit, you will continue to understand and explore disciplinary knowledge, while also meeting and collaborating with students from across the University through project-based learning; identifying and solving problems, collecting and analysing data and communicating your findings to a diverse audience. All of these skills are highly valued by employers. This unit will foster the ability to work in interdisciplinary teams, and this is essential for both professional and research pathways in the future.

Unit details and rules

Academic unit	History and Philosophy of Science Academic Operations
Credit points	6
Prerequisites ?	12 credit points of HPSC2XXX
Corequisites ?	None
Prohibitions ?	None
Assumed knowledge ?	Students should have demonstrated the ability to explain topics and concepts in HPS at an intermediate level
Available to study abroad and exchange students	No

Teaching staff

Coordinator	Maureen O'Malley, maureen.omalley@sydney.edu.au
Demonstrator(s)	Rebecca Mann, rebecca.c.mann@sydney.edu.au

Type	Description	Weight	Due	Length
Assignment	Definition of Question Reflective Essay	20%	Week 05 Due date: 01 Sep 2023 at 23:59	Details on Canvas
Outcomes assessed:
Assignment	Mid-term essay Individual written essay	30%	Week 06 Due date: 08 Sep 2023 at 23:59	Detailed information on canvas
Outcomes assessed:
Presentation	Project Presentation Project presentation (oral, in class)	20%	Week 11 Due date: 16 Oct 2023 at 14:00	Detailed info on Canvas. In class.
Outcomes assessed:
Assignment	Written Group Report Written Group Report	30%	Week 12 Due date: 26 Oct 2023 at 23:59	Details on Canvas
Outcomes assessed:
= group assignment ?

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.

For more information see guide to grades.

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.

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

You may only use generative AI and automated writing tools in assessment tasks if you are permitted to by your unit coordinator. If you do use these tools, you must acknowledge this in your work, either in a footnote or an acknowledgement section. The assessment instructions or unit outline will give guidance of the types of tools that are permitted and how the tools should be used.

Your final submitted work must be your own, original work. You must acknowledge any use of generative AI tools that have been used in the assessment, and any material that forms part of your submission must be appropriately referenced. For guidance on how to acknowledge the use of AI, please refer to the AI in Education Canvas site.

The unapproved use of these tools or unacknowledged use will be considered a breach of the Academic Integrity Policy and penalties may apply.

Studiosity is permitted unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission as detailed on the Learning Hub’s Canvas page.

Outside assessment tasks, generative AI tools may be used to support your learning. The AI in Education Canvas site contains a number of productive ways that students are using AI to improve their learning.

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.

Weekly schedule

WK	Topic	Learning activity
Week 01	Working with a team to solve a problem	Workshop (2 hr)
Week 01	Interdisciplinary lecture: survival	Lecture (2 hr)
Week 02	Team charter; intro to group projects	Workshop (2 hr)
Week 02	From science to policy	Lecture (2 hr)
Week 03	Development of research question	Workshop (2 hr)
Week 03	Survival of the fittest (HPS perspective)	Lecture (2 hr)
Week 04	Project work: Writing workshop; Intro to definition of question assessment; literature search	Workshop (2 hr)
Week 04	Adapt or die (HPS perspective)	Lecture (2 hr)
Week 05	Project work	Workshop (2 hr)
Week 05	Winners and losers: invasive species (HPS perspective)	Lecture (2 hr)
Week 06	Interdisciplinary workshop on project content	Workshop (2 hr)
Week 06	De-extinction and rewilding (HPS perspective)	Lecture (2 hr)
Week 07	Project work	Workshop (2 hr)
Week 07	Humans in a changing world (HPS perspective)	Lecture (2 hr)
Week 08	Interdisciplinary workshop: project	Workshop (2 hr)
Week 08	Mid-semester short paper: discussion, preparation and feedback	Lecture (2 hr)
Week 10	Project work	Workshop (2 hr)
Week 10	Project advice and feedback: individualized sessions	Studio (2 hr)
Week 11	Project presentations	Workshop (2 hr)
Week 11	Interdisciplinary workshop: presentations	Workshop (2 hr)
Week 12	Interdisciplinary workshop: project	Workshop (2 hr)
Week 12	Project advice and feedback individualized sessions	Studio (2 hr)
Week 13	Reflecting on group contributions	Studio (2 hr)
Week 13	Reflecting on group contributions	Studio (2 hr)

Attendance and class requirements

See Canvas; additional details provided in class.

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

All readings and other material will be made 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. Apply disciplinary knowledge to solve problems in an interdisciplinary context.
LO2. Find, define and delimit authentic problems in order to address them
LO3. Create an investigation strategy, explore solutions, discuss approaches and predict outcomes.
LO4. Analyse data using modern information technology and digital skills.
LO5. Demonstrate integrity, confidence, personal resilience and the capacity to manage challenges, both individually and in diverse teams
LO6. Collaborate with diverse groups and across cultural and disciplinary boundaries to develop solutions(s) to the project problems.
LO7. Communicate project outcomes effectively to a broad audience.

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.

New interdisciplinary strategies; HPS demonstrator added; new topics; careful attention to group composition

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

Assessment summary

Assessment criteria

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

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

Disclaimer

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