OLET5620: Intensive September, 2022

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Units OLET5620 Intensive September 2022 [Block mode]

Unit of study_

OLET5620: Good Science, Bad Science

Intensive September, 2022 [Block mode] - Remote

Overview

Scientific research should be reproducible. A reproducible study is one for which the methods are described in enough detail for others to follow, the analyses of the data are straightforward to re-run, and conducting the study again (where possible) yields results that support the claim of the original report. In areas of science where reproducibility has been evaluated, such as cancer biology and experimental psychology, replication success rates have generally been lower than 50%, and in clinical medicine, published outcomes show substantial biases. Bad and irreproducible research is rife. In this unit, examples are drawn from biology, health science, social science, education, and engineering. You will learn the principles of reproducible science. Building on your basic knowledge of statistics, you will understand the practices and statistical issues that lead to irreproducible science, such as poor statistical power and questionable research practices. You will also become familiar with practices that foster robust results, practices that are increasingly embraced or even required by journals and research funders. You will apply this knowledge to your own research or some other work that you choose.

Unit details and rules

Unit code	OLET5620
Academic unit	Psychology Academic Operations
Credit points	2
Prohibitions ?	None
Prerequisites ?	None
Corequisites ?	None
Assumed knowledge ?	None
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	Alex Holcombe, alex.holcombe@sydney.edu.au

Type	Description	Weight	Due	Length
Online task	Quiz 1 Canvas quiz	5%	Week 01 Closing date: 02 Oct 2022	Unlimited
Outcomes assessed:
Online task	Quiz 2 Canvas quiz	10%	Week 02 Closing date: 02 Oct 2022	Unlimited
Outcomes assessed:
Online task	Quiz 3 Canvas quiz	10%	Week 03 Closing date: 02 Oct 2022	Unlimited
Outcomes assessed:
Online task	Quiz 4 Canvas quiz	10%	Week 04 Closing date: 02 Oct 2022	30 minutes
Outcomes assessed:
Online task	MCQ writing and explanation Compose and evaluate MCQs with written explanations	20%	Week 04 Due date: 16 Sep 2022 at 23:59 Closing date: 14 Oct 2022	500 words
Outcomes assessed:
Online task	Quiz 5 Canvas quiz	5%	Week 05 Closing date: 02 Oct 2022	30 minutes
Outcomes assessed:
Assignment	Research essay Plan for reproducibility	40%	Week 06 Due date: 30 Sep 2022 at 23:59 Closing date: 28 Oct 2022	600 words
Outcomes assessed:

Assessment summary

Note that the MCQ assessment has two phases. 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 sydney.edu.au/students/guide-to-grades.

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.

You may only use artificial intelligence and writing assistance tools in assessment tasks if you are permitted to by your unit coordinator, and if you do use them, you must also acknowledge this in your work, either in a footnote or an acknowledgement section.

Studiosity is permitted for postgraduate units unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission.

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
Ongoing	Overview of reproducibility and outline of the unit	Independent study (6 hr)
	Computational reproducibility: example and success rate	Independent study (6 hr)
	Empirical reproducibility: basics	Independent study (6 hr)
	Empirical reproducibility: Variability, imprecision, and statistical power	Independent study (6 hr)
	Empirical reproducibility: Sources of bias and questionable research practices	Independent study (6 hr)
	Improving reproducibility	Independent study (6 hr)
Week 03	Scientific values	Workshop (2 hr)
Week 05	Reproducibility	Workshop (2 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 2 credit point unit, this equates to roughly 40-50 hours of student effort in total.

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 advanced knowledge of the principles of scientific reproducibility to data sets.
LO2. Critically analyse how reproducibility principles apply to a different field, and in the case of many, your own field.
LO3. Evaluate research practices from published papers for reproducibility issues.
LO4. Recognise common statistical issues that threaten the robustness of results.
LO5. Communicate effectively to specialist and/or non-specialist audiences on topics related to reproducibility issues, demonstrating responsibility and accountability.
LO6. Evaluate reproducibility issues in your own or another research project, and plan and transmit solutions to address them.

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.

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

Study commitment

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Disclaimer

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