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Course profile

Theory & Practice in Science (SCIE1000)

Study period
Sem 2 2024
Location
St Lucia
Attendance mode
In Person

Course overview

Study period
Semester 2, 2024 (22/07/2024 - 18/11/2024)
Study level
Undergraduate
Location
St Lucia
Attendance mode
In Person
Units
2
Administrative campus
St Lucia
Coordinating unit
Mathematics & Physics School

This foundation course in science introduces students to the broad range of mathematical, analytical, conceptual and computational tools employed by scientists to develop, analyse and interpret models of scientific processes. To emphasize the importance and generality of these tools, a number of key contemporary topics in science will be studied, including climate change, population dynamics, drugs and pharmacokinetics, and epidemics. The course will demonstrate how and why mathematical models underpin modern science, and students will learn how to develop and analyse such models. The course also introduces computer programming (using the language Python) as a vital tool in modern scientific modelling. Students will be introduced to some fundamental philosophical issues in science, gaining an appreciation of some of the assumptions that underlie science and the supposed scientific method, reinforcing the importance of critical thinking, creativity and quantitative scientific skills.

Science is increasingly interdisciplinary, requiring a breadth of understanding, an appreciation of some of the key challenges in different disciplines, and the ability to apply mathematical, quantitative and computing skills. SCIE1000 will help you to develop these abilities, thus giving you the general skills and knowledge you will need to study and practise science successfully.

All the material covered in SCIE1000 will be in the context of some of the big issues in science today, ranging from climate change and species diversity to epidemics and catastrophes. We will cover areas such as the philosophy of science and what scientific thinking means, how to model complex scientific phenomena, how mathematics is used as a formal language to develop models that describe such phenomena, and how to use computer programming to analyse the models.

SCIE1000 is taken by all science students at UQ. It is one of the few courses (STAT1201 is the other) in which students from all branches of science will come together, letting you see some of the breadth and rich diversity of science.ᅠWe believe strongly that SCIE1000 will be very useful, interesting, challenging and fun!

In the School of Mathematics and Physics we are committed to creating an inclusive and empowering learning environment for all students. We value and respect the diverse range of experiences our students bring to their education, and we believe that this diversity is crucial for fostering a rich culture of knowledge sharing and meaningful exploration. We hold both students and staff accountable for actively contributing to the establishment of a respectful and supportive learning environment.

Bullying, harassment, and discrimination in any form are strictly against our principles and against UQ Policy, and will not be tolerated. We have developed a suite of resources to assist you in recognising, reporting, and addressing such behaviour. If you have any concerns about your experience in this course, we encourage you to tell a member of the course teaching team, or alternatively contact an SMP Inclusivity Champion (see Blackboard for contact details). Our Inclusivity Champions are here to listen, to understand your concerns, and to explore potential actions that can be taken to resolve them. Your well-being and a positive learning atmosphere are of utmost importance to us.

Course requirements

Assumed background

Any student accepted into any science-based course at UQ will have the necessary background to take SCIE1000. Specifically, the assumed background is:

  • Years 11 and 12 English from the Queensland Secondary Education system (or equivalent).
  • Years 11 and 12 Mathematical Methods (previously called Maths B) from the Queensland Secondary Education system (or equivalent, such as the UQ course MATH1040).
  • General science sophistication, equivalent to having studied a branch of science in Years 11 and 12.

Note that we do not assume you have completed Specialist Mathematics (previously called Maths C), Physics, Chemistry or Biology: all you need is English, Mathematical Methods (previously calledᅠMaths B), and any one science.

Incompatible

You can't enrol in this course if you've already completed the following:

SCIE1100

Course contact

Course staff

Lecturer

Tutor

Ms Saskia Van Ryt
Ms Sabrina Morrison
Mr Ryan White
Mr Sam Davis
Ms Sara Thomas
Mr John Saxon
Mr Dylan Ramke
Ms Katherine Harris
Mr Seb Porras
Mr Will Chung
Mr Tianyu Xiao
Mr Ryan Gray
Mr Lleyton Lao

Timetable

The timetable for this course is available on the UQ Public Timetable.

Additional timetable information

There is one 2 hour workshop and one 2 hour practical per week. There is also an optional contact lecture for Python programming, called "Contact" in MyTimetable,ᅠwhich you are strongly encouraged to attend if you are new to computer programming or would like more computer programming support.

All classes will be conducted on campus. Consult your personal timetable for times and locations. Students are expected to attend these sessions in person unless they have a valid reason for being unable to attend (such as illness).

Important: if you are ill, then do not attend any classes in person. Alternative arrangements can be organised – consult Blackboard for details.

Please refer to Blackboard for information regarding alternate arrangements for the public holidays this semester.

Aims and outcomes

SCIE1000 aims to:

  • introduce students to the interdisciplinary nature of modern science;
  • instil an appreciation of the quantitative skills required for the practice of modern science, regardless of discipline; 
  • improve students’ mathematical and computer programming skills in the context of scientific problems and issues;
  • demonstrate the importance of formulating and applying quantitative models of various phenomena in science; 
  • introduce students to philosophical issues in science, including core activities which comprise science and some fundamental aspects of scientific reasoning;
  • improve students’ skills in scientific communication and quantitative reasoning;
  • involve students in analysis of some “big picture” issues in science; and
  • engage students in the UQ “science community”.


Learning outcomes

After successfully completing this course you should be able to:

LO1.

Recognise the interdisciplinary nature of modern science, including some of the similarities and differences across a range of discipline areas.

LO2.

Explain the importance of modelling in science by demonstrating the skills required to produce and analyse such models.

LO3.

Apply fundamental mathematical techniques that are important to problems across a range of scientific discipline areas.

LO4.

Explain key introductory concepts in computer science, design and write simple computer programs in the language Python, and interpret the output of these programs.

LO5.

Describe and discuss some philosophical accounts of scientific reasoning.

LO6.

Communicate responses to quantitative and science-based problems in a correct, logical and scientifically appropriate style.

LO7.

Describe and discuss some of the current key issues in science, including relevant social and ethical issues.

Assessment

Assessment summary

Category Assessment task Weight Due date
Participation/ Student contribution Practical exercises 10%

Week 1 - Week 13

Due each week at the time of your practical.

Essay/ Critique Philosophy assignment 15%

30/08/2024 1:00 pm

Computer Code, Project Python & communication assignment 15%

15/10/2024 1:00 pm

Examination Final Exam
  • Hurdle
60%

End of Semester Exam Period

2/11/2024 - 16/11/2024

A hurdle is an assessment requirement that must be satisfied in order to receive a specific grade for the course. Check the assessment details for more information about hurdle requirements.

Assessment details

Practical exercises

Mode
Activity/ Performance
Category
Participation/ Student contribution
Weight
10%
Due date

Week 1 - Week 13

Due each week at the time of your practical.

Task description

You must attend your practicals in-person. For each practical, you will be provided with a task sheet containing relevant tasks, many of which are in the style of SCIE1000 exam questions. Some tasks will involve writing Python code. You will be encouraged to engage in discussion with your fellow classmates during practicals.

If you are unwell then DO NOT attend your in-person practical. Please email scie1000supertutor@uq.edu.au to arrange to attend a different practical that week. 

Submission guidelines

Deferral or extension

You cannot defer or apply for an extension for this assessment.

Practicals are graded based on participation so there are no extensions.

If you are too unwell to attend any practical please note that you can miss up to two assessed practicals without penalty. If you are unable to attend more than two assessed practicals please email the course coordinators on scie1000staff@uq.edu.au to explain your circumstances and request a re-weighting of your remaining practicals. You should include appropriate documented evidence with your request (e.g. a medical certificate). You can receive at most 3 exemptions per semester. Students unable to complete sufficient practicals during the semester should consider withdrawing and re-enrolling in a forthcoming semester.

Late submission

You will receive a mark of 0 if this assessment is submitted late.

Philosophy assignment

Mode
Written
Category
Essay/ Critique
Weight
15%
Due date

30/08/2024 1:00 pm

Task description

This assignment will assess the degree to which students have reached the learning objectives in the philosophy component of SCIE1000, by requiring them to write an essay discussing aspects of the scientific method.

Submission guidelines

All assignments must be submitted electronically through Blackboard by the due date and time.

Deferral or extension

You may be able to apply for an extension.

The maximum extension allowed is 14 days. Extensions are given in multiples of 24 hours.

Feedback will be released to students for this assessment item approximately 14 days after the assessment is due and as such, an extension after 14 days will not be possible.

See ADDITIONAL ASSESSMENT INFORMATION for the extension information relating to this assessment item.

Late submission

A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.

You are required to submit assessable items on time. If you fail to meet the submission deadline for any assessment item then the listed penalty will be deducted per day for up to 7 calendar days, at which point any submission will not receive any marks unless an extension has been approved. Each 24-hour block is recorded from the time the submission is due.

Python & communication assignment

Mode
Product/ Artefact/ Multimedia, Written
Category
Computer Code, Project
Weight
15%
Due date

15/10/2024 1:00 pm

Task description

This assignment will assess the degree to which students have reached the learning objectives in the Python and scientific communication components of SCIE1000.  Students will develop and demonstrate their skills in writing a Python program, and also demonstrate their ability to communicate science in a way which is appropriate for a prescribed target audience.  The assignment will be given within a specific scientifc context, and students will use scientific information and mathematical models within their Python program.

Submission guidelines

All assignments must be submitted electronically through Blackboard by the due date and time. Plagiarism detection software will be used to check the originality of your code and other written material.

Deferral or extension

You may be able to apply for an extension.

The maximum extension allowed is 14 days. Extensions are given in multiples of 24 hours.

Feedback will be released to students for this assessment item approximately 14 days after the assessment is due and as such, an extension after 14 days will not be possible.

See ADDITIONAL ASSESSMENT INFORMATION for the extension information relating to this assessment item.

Late submission

A penalty of 1 grade for each 24 hour period from time submission is due will apply for up to 7 days. After 7 days you will receive a mark of 0.

For the Python & Communication Assignment (which has a maximum mark of 14), there will be a penalty of 2 marks for every day or part thereof.

You are required to submit assessable items on time. If you fail to meet the submission deadline for any assessment item then the listed penalty will be deducted per day for up to 7 calendar days, at which point any submission will not receive any marks unless an extension has been approved. Each 24-hour block is recorded from the time the submission is due.

Final Exam

  • Hurdle
Mode
Written
Category
Examination
Weight
60%
Due date

End of Semester Exam Period

2/11/2024 - 16/11/2024

Task description

The Final is cumulative, covering the entire course, and will focus on conceptual questions and problem-solving. It will not require you to write computer programs, but may require you to read, modify and interpret computer programs. There will be a formula sheet provided (this is available on Blackboard, under Learning Resources). There will be a reference page provided, explaining what you need to know about the scientific context of the questions - see past final examinations as examples (available on Blackboard, under Learning Resources).

Hurdle requirements

See ADDITIONAL COURSE GRADING INFORMATION for the hurdle/s relating to this assessment item.

Exam details

Planning time 10 minutes
Duration 120 minutes
Calculator options

(In person) Casio FX82 series only or UQ approved and labelled calculator

Open/closed book Closed Book examination - specified written materials permitted
Materials

One A4 sheet of handwritten notes, double sided, is permitted

Exam platform Paper based
Invigilation

Invigilated in person

Submission guidelines

Deferral or extension

You may be able to defer this exam.

See ADDITIONAL ASSESSMENT INFORMATION for the deferred examination information relating to this assessment item.

Course grading

Full criteria for each grade is available in the Assessment Procedure.

Grade Cut off Percent Description
1 (Low Fail) -

Absence of evidence of achievement of course learning outcomes.

Course grade description: Students will receive this grade if their final mark is less than 20%.

2 (Fail) -

Minimal evidence of achievement of course learning outcomes.

Course grade description: Students will receive this grade if their final mark is at least 20% and less than 45%.

3 (Marginal Fail) -

Demonstrated evidence of developing achievement of course learning outcomes

Course grade description: Students will receive this grade if EITHER of the following occurs: (a) their final mark is at least 45% and less than 50% OR (b) their final mark is at least 50% BUT they do not receive at least 40% of the marks on the Final Exam.

4 (Pass) -

Demonstrated evidence of functional achievement of course learning outcomes.

Course grade description: Students will receive this grade if their final mark is at least 50% and less than 65% AND they receive at least 40% on the Final Exam.

5 (Credit) -

Demonstrated evidence of proficient achievement of course learning outcomes.

Course grade description: Students will receive this grade if their final mark is at least 65% and less than 75% AND they receive at least 40% on the Final Exam.

6 (Distinction) -

Demonstrated evidence of advanced achievement of course learning outcomes.

Course grade description: Students will receive this grade if their final mark is at least 75% and less than 85% AND they receive at least 40% on the Final Exam.

7 (High Distinction) -

Demonstrated evidence of exceptional achievement of course learning outcomes.

Course grade description: Students will receive this grade if their final mark is at least 85% AND they receive at least 40% on the Final Exam.

Additional course grading information

Hurdle:

You cannot earn above a 3 unless you earn at least 40% on the Final Exam.

Supplementary assessment

Supplementary assessment is available for this course.

Should you fail a course with a grade of 3, you may be eligible for supplementary assessment. Refer to my.UQ for information on supplementary assessment and how to apply. 

Supplementary assessment provides an additional opportunity to demonstrate you have achieved all the required learning outcomes for a course.  

If you apply and are granted supplementary assessment, the type of supplementary assessment set will consider which learning outcome(s) have not been met.  

Supplementary assessment in this course will be a 2-hour examination similar in style to the end-of-semester examination. To receive a passing grade of 3S4, you must obtain a mark of 50% or more on the supplementary assessment. 

Additional assessment information

Artificial Intelligence

The assessment tasks in this course evaluate students’ abilities, skills and knowledge without the aid of Artificial Intelligence (AI). Students are advised that the use of AI technologies to develop responses is strictly prohibited and may constitute misconduct under the Student Code of Conduct.

Applications for Extensions to Assessment Due Dates

Extension requests are submitted online via my.UQ – applying for an extension. Extension requests received in any other way will not be approved. Additional details associated with extension requests, including acceptable and unacceptable reasons, may be found at my.UQ.

Please note:

  • Requests for an extension to an assessment due date must be submitted through your my.UQ portal and you must provide documentation of your circumstances, as soon as it becomes evident that an extension is needed. Your application must be submitted on or before the assessment item's due date and time.
  • Applications for extension can take time to be processed so you should continue to work on your assessment item while awaiting a decision. We recommend that you submit any completed work by the due date, and this will be marked if your application is not approved. Should your application be approved, then you will be able to resubmit by the agreed revised due date.
  • If an extension is approved, you will be notified via your my.UQ portal and the new date and time for submission provided. It is important that you check the revised date as it may differ from the date that you requested.
  • If the basis of the application is a medical condition, applications should be accompanied by a medical certificate dated prior to the assignment due date. If you are unable to provide documentation to support your application by the due date and time you must still submit your application on time and attach a written statement (Word document) outlining why you cannot provide the documentation. You must then upload the documentation to the portal within 24 hours.
  • If an extension is being sought on the basis of exceptional circumstances, it must be accompanied by supporting documentation (eg. Statutory declaration).
  • For extensions based on a SAP you may be granted a maximum of 7 days (if no earlier maximum date applies). See the Extension or Deferral availability section of each assessment for details. Your SAP is all that is required as documentation to support your application. However, additional extension requests for the assessment item will require the submission of additional supporting documentation e.g., a medical certificate. All extension requests must be received by the assessment due date and time.
  • Students may be asked to submit evidence of work completed to date. Lack of adequate progress on your assessment item may result in an extension being denied.
  • If you have been ill or unable to attend class for more than 14 days, you are advised to carefully consider whether you are capable of successfully completing your courses this semester. You might be eligible to withdraw without academic penalty - seek advice from the Faculty that administers your program.
  • There are no provisions for exemption from an assessment item within UQ rules. If you are unable to submit an assessment piece then, under special circumstances, you may be granted an exemption, but may be required to submit alternative assessment to ensure all learning outcomes are met.

Applications to defer an exam

In certain circumstances you can apply to take a deferred examination for in-semester and end-of-semester exams. You'll need to demonstrate through supporting documentation how unavoidable circumstances prevented you from sitting your exam. If you can’t, you can apply for a one-off discretionary deferred exam.

Deferred Exam requests are submitted online via mySi-net. Requests received in any other way will not be approved. Additional details associated with deferred examinations, including acceptable and unacceptable reasons may be found at my.UQ.

Please note:

  • Applications can be submitted no later than 5 calendar days after the date of the original exam.
  • There are no provisions to defer a deferred exam. You need to be available to sit your deferred examination.
  • Your deferred examination request(s) must have a status of "submitted" in mySI-net to be assessed.
  • All applications for deferred in-semester examinations are assessed by the relevant school. Applications for deferred end-of-semester examinations are assessed by the Academic Services Division.
  • You’ll receive an email to your student email account when the status of your application is updated.
  • If you have a medical condition, mental health condition or disability and require alternative arrangements for your deferred exam you’ll need to complete the online alternative exam arrangements through my.UQ. This is in addition to your deferred examinations request. You need to submit this request on the same day as your request for a deferred exam or
  • supplementary assessment. Contact Student Services if you need assistance completing your alternative exam arrangements request.


Learning resources

You'll need the following resources to successfully complete the course. We've indicated below if you need a personal copy of the reading materials or your own item.

Library resources

Find the required and recommended resources for this course on the UQ Library website.

Additional learning resources information

Note that there is no textbook for this course.ᅠ You may wish to look up the scientific papers referenced in the workbook and you can do so from the UQ library website (https://www.library.uq.edu.au/).ᅠ Click on advanced search for detailed searching options, and make sure you are logged in with your student account.

At times we will direct you to additional material which will be available in the library or on the internet.ᅠ If you are interested in finding out extra information about any of the topics we cover, there are plenty of resources available on the internet (but remember that not everything you find there is true).

Additional Resources:

  • The workbook is a very important resource! You can find a copy on the course Blackboard page and annotated notes from this will be uploaded after each workshop.
  • The SCIE1000 Blackboard page is the primary portal for communication of announcements and documents.ᅠ You should form the habit of checking Blackboard, especially the announcements, regularly.ᅠ Make sure you check out "Course Help" and also "Learning Resourcesᅠ-> Resources for support and practice".
  • Practical tasks and their solutions are a great resource for you to practice and gain confidence on assessment-style questions.ᅠ Make a regular habit of checking practical solutions!
  • SOMSE (SCIE1000/1100 Online Modules for Support and Enrichment) isᅠavailable for youᅠhere. These modulesᅠinclude videos, simulations and quiz questions to check your understanding of the main quantitative skills we use in the course.
  • We encourage you to use the courseᅠonline discussion boardᅠsite (link provided on the course website) for general questions about the course content.
  • Extra online practice for Python can be found atᅠMyPyTutorᅠ(link provided on the course website).
  • You are encouraged to attendᅠlecturer office hoursᅠ(schedule provided on the course website), to ask questions about anything SCIE1000 related - we are always happy to have a chat!ᅠᅠ

Learning activities

The learning activities for this course are outlined below. Learn more about the learning outcomes that apply to this course.

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Learning period Activity type Topic
Multiple weeks

From Week 1 To Week 13

Workshop

Weekly workshops

One 2 hour workshop each week which will be spent working through the workbook, answering questions and discussing content.

During workshops we will discuss issues, challenge your answers, and solve problems together. During discussion times you will be asked to engage and give input into the discussions in various ways. A recording of these workshops will be available on Blackboard shortly after each class. However, we encourage you to attend live (either on campus or online) to obtain the best experience from the interactive nature of the classes. Workshops commence in Week 1.

Practical

Weekly practicals

Held as two hour sessions covering problem-solving, communication in science and Python programming.

You must attend one practical each week. Each practical runs for two hours, in a computer laboratory, and you must attend both hours. You will enrol in a practical at the start of the semester and should attend the same practical each week if possible (in the case of illness or classes falling on public holidays, alternative arrangements will be made available). The practicals are a great place to ask questions, get help and engage in peer-to-peer learning. One practical will be dedicated to the philosophy of science.  Practicals commence in Week 1.

Multiple weeks

From Week 1 To Week 8

General contact hours

Additional Python support class (Demonstration)

Optional (but highly recommended) weekly class for additional Python help.

There will be 1-hour interactive Contact sessions to cover the Python programming concepts you will be expected to learn in this course. A recording of these contacts will be made available on Blackboard shortly after the session. These Contacts are highly recommended if you are new to computer programming. We recommend attending this Contact prior to attending your workshop each week. A schedule will be provided on the course Blackboard page. Contacts commence in Week 1.

Additional learning activity information

The topics that we will cover include:

  • A general characterisation of science
  • Quantitative reasoning and communication
  • Modelling
  • Climate, species and functions
  • Waves, cycles and seasons
  • Exponential and logarithmic phenomena
  • Philosophy and scientific reasoning
  • Drugs and rates of change
  • Drugs and areas under a curve
  • Populations and differential equations
  • Systems of differential equations
  • Epidemic models and catastrophes

Computer programming and scientific discussions will feature in each topic.

Policies and procedures

University policies and procedures apply to all aspects of student life. As a UQ student, you must comply with University-wide and program-specific requirements, including the:

Learn more about UQ policies on my.UQ and the Policy and Procedure Library.