Students

COMP7860 – Computing Methods for Research

2024 – Session 2, In person-scheduled-weekday, North Ryde

General Information

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Unit convenor and teaching staff Unit convenor and teaching staff Lecturer, Convenor
Dr Rolf Schwitter
rolf.schwitter@mq.edu.au
4 Research Park Drive, level 3, office 359
By appointment.
Lecturer
Diego Molla-Aliod
diego.molla-aliod@mq.edu.au
4 Research Park Drive, level 3, office 360
By appointment.
Credit points Credit points
10
Prerequisites Prerequisites
Admission to MRes
Corequisites Corequisites
Co-badged status Co-badged status
COMP8240
Unit description Unit description
This unit deals with the effective use of computing devices and tools for research purposes. It aims at equipping research students with relevant computing skills that can greatly improve their research productivity. It introduces a range of tools covering data processing and analysis (eg, data mining), coding (eg, scripting, web-based programming, control version system), modelling techniques, communication media, document preparation systems (eg, LaTeX), computer-based presentation tools, bibliography management, and human-computer interfaces, among other topics.

Important Academic Dates

Information about important academic dates including deadlines for withdrawing from units are available at https://www.mq.edu.au/study/calendar-of-dates

Learning Outcomes

On successful completion of this unit, you will be able to:

  • ULO1: Define and manage a project involving empirical research.
  • ULO2: Apply a knowledge of programming and/or use of appropriate applications (for e.g. data gathering, curation, cleaning or analysis) in the context of practical work relevant to an empirical research project.
  • ULO3: Articulate clearly a coherent argument in written and oral form to a variety of audiences.
  • ULO4: Apply a knowledge of the principles of ethical conduct of research, including an examination of the role of open access to data and publications.
  • ULO5: Demonstrate best practice in document preparation and management in research.

General Assessment Information

Late Assessment Submission Penalty 

Unless a Special Consideration request has been submitted and approved, a 5% penalty (of the total possible mark of the task) will be applied for each day a written report or presentation assessment is not submitted, up until the 7th day (including weekends). After the 7th day, a grade of ‘0’ will be awarded even if the assessment is submitted. The submission time for all uploaded assessments is 11:55 pm. A 1-hour grace period will be provided to students who experience a technical concern. For any late submission of time-sensitive tasks, such as scheduled tests/exams, performance assessments/presentations, and/or scheduled practical assessments/labs, please apply for Special Consideration. For example, if the assignment is worth 8 marks (of the entire unit) and your submission is late by 19 hours (or 23 hours 59 minutes 59 seconds), 0.4 marks (5% of 8 marks) will be deducted. If your submission is late by 24 hours (or 47 hours 59 minutes 59 seconds), 0.8 marks (10% of 8 marks) will be deducted, and so on. 

Assessments where Late Submissions will be accepted 

In this unit, late submissions will be accepted as follows: 

  • Practical Assignments – YES, Standard Late Penalty applies 
  • Final Report – YES, Standard Late Penalty applies 
  • Presentations to be delivered during class time – NO, unless Special Consideration is granted 
  • Exam - NO, unless Special Consideration is granted 

Special Consideration 

The Special Consideration Policy aims to support students who have been impacted by short-term circumstances or events that are serious, unavoidable and significantly disruptive, and which may affect their performance in assessment. If you experience circumstances or events that affect your ability to complete the assessments in this unit on time, please inform the convenor and submit a Special Consideration request through ask.mq.edu.au. 

Assessment Tasks

Name Weighting Hurdle Due
Practical Assignments 30% No First week break and Week 12: Friday 23:55
Project Proposal Presentation 5% No Week 6: Monday 12:00-14:00
Project Update Presentation 5% No Week 10: Monday 12:00-14:00
Final Presentation 5% No Week 13: Monday 12:00-14:00
Final Report 55% No Week 13: Friday 23:55

Practical Assignments

Assessment Type 1: Practice-based task
Indicative Time on Task 2: 30 hours
Due: First week break and Week 12: Friday 23:55
Weighting: 30%

 

There will be some small practical assignments during the semester, linked to the lecture material and weekly practical exercises.

 
On successful completion you will be able to:
  • Apply a knowledge of programming and/or use of appropriate applications (for e.g. data gathering, curation, cleaning or analysis) in the context of practical work relevant to an empirical research project.
  • Demonstrate best practice in document preparation and management in research.

Project Proposal Presentation

Assessment Type 1: Presentation
Indicative Time on Task 2: 10 hours
Due: Week 6: Monday 12:00-14:00
Weighting: 5%

 

Part of the assessment for the unit will be built around a single project you will devise. This initial presentation is to pitch the idea to the audience (lecturers and students): explain the data you'll be using, give any relevant background, and outline a plan for tackling the project. The workload for the task includes the time spent on the project needed for the presentation, as well as the presentation itself.

 
On successful completion you will be able to:
  • Define and manage a project involving empirical research.
  • Articulate clearly a coherent argument in written and oral form to a variety of audiences.

Project Update Presentation

Assessment Type 1: Presentation
Indicative Time on Task 2: 10 hours
Due: Week 10: Monday 12:00-14:00
Weighting: 5%

 

This presentation will give an update on the state of the project. The workload for the task includes the time spent on the project needed for the presentation, as well as the presentation itself.

 
On successful completion you will be able to:
  • Define and manage a project involving empirical research.
  • Articulate clearly a coherent argument in written and oral form to a variety of audiences.

Final Presentation

Assessment Type 1: Presentation
Indicative Time on Task 2: 10 hours
Due: Week 13: Monday 12:00-14:00
Weighting: 5%

 

This presentation will describe to an audience the results of your project. Feedback from the presentation can be incorporated into the final report. The workload for the task includes the time spent on the project needed for the presentation, as well as the presentation itself.

 
On successful completion you will be able to:
  • Define and manage a project involving empirical research.
  • Apply a knowledge of programming and/or use of appropriate applications (for e.g. data gathering, curation, cleaning or analysis) in the context of practical work relevant to an empirical research project.
  • Articulate clearly a coherent argument in written and oral form to a variety of audiences.

Final Report

Assessment Type 1: Report
Indicative Time on Task 2: 25 hours
Due: Week 13: Friday 23:55
Weighting: 55%

 

This report will describe the completed project as a whole: what the goals were, what data was used, how it was processed, and what the results were relative to the goals. It may also include any related programs written as part of the project, etc. The workload for the task includes the time spent on the project needed for the report, as well as the report itself.

 
On successful completion you will be able to:
  • Define and manage a project involving empirical research.
  • Apply a knowledge of programming and/or use of appropriate applications (for e.g. data gathering, curation, cleaning or analysis) in the context of practical work relevant to an empirical research project.
  • Articulate clearly a coherent argument in written and oral form to a variety of audiences.
  • Apply a knowledge of the principles of ethical conduct of research, including an examination of the role of open access to data and publications.
  • Demonstrate best practice in document preparation and management in research.

1 If you need help with your assignment, please contact:

  • the academic teaching staff in your unit for guidance in understanding or completing this type of assessment
  • the Writing Centre for academic skills support.

2 Indicative time-on-task is an estimate of the time required for completion of the assessment task and is subject to individual variation

Delivery and Resources

CLASSES

Each week consists of a formally designated two hours of lecture and one hour practical session, although the lecture session may involve some practical aspects as well. For details of days, times and rooms, consult the University timetables webpage (http://www.timetables.mq.edu.au).  It will be co-taught with COMP8240. Lectures start in Week1 and practicals in Week2.

REQUIRED AND RECOMMENDED TEXTS AND/OR MATERIALS

There is no set text for the unit.  We will be providing pointers to reading material over the course of the unit.

The unit has some parallels with the freely available Software Carpentry course.  We'll be using those resources as supplementary ones for the unit.

UNIT WEBPAGE AND TECHNOLOGY USED AND REQUIRED

Web Home Page

The unit will make extensive use of the iLearn course management system, including for delivery of class materials, discussion boards, submission of work and access to marks and feedback. Students should check the iLearn site (https://ilearn.mq.edu.au) regularly for unit updates.

Questions and general queries regarding the content of this unit, its lectures or mixed classes, or its assignments should be posted to the discussion boards on the iLearn site. In particular, any questions which are of interest to all students in this unit should be posted to one of these discussion boards, so that everyone can benefit from the answers. Questions of a private nature should be directed to the unit teaching staff.

Technology Used and Required

The practical work in this unit involves programming in the Python language (http://www.python.org/) which is widely used for the sorts of scripting purposes covered in this unit. Python can be downloaded free of charge for a range of operating systems from the Python website.  

Note that as this is a master's unit, there will be some self-directed learning.  We do not expect that you will know Python before the unit starts, but will pick up the necessary elements in the first few weeks of the unit; we will give pointers to resources for learning Python, and will include snippets of Python in lecture notes where relevant to computational experiments.  We will generally (but not always) use Jupyter Notebooks for Python examples, and will use Google Colab as the environment for running them.  (Google Colab is a free environment that can used for some sorts of data analysis relevant to practical assignments and the major project.) In addition to Google Colab, we will also use GitHub and GitHub Codespaces: https://github.com/codespaces.

The unit will also use various other tools for e.g. data gathering and annotation.  

COVID INFORMATION

For the latest information on the University’s response to COVID-19, please refer to the Coronavirus infection page on the Macquarie website: https://www.mq.edu.au/about/coronavirus-faqs. Remember to check this page regularly in case the information and requirements change during semester. If there are any changes to this unit in relation to COVID, these will be communicated via iLearn. 

 

Unit Schedule

The focus of this unit is understanding the notions of open science and reproducible research.  Much work in both academia and industry is driven by the free availability of papers, code and data that allow the replication and extension of existing work.  In this unit, your major project will involve getting access to some of these resources, reproducing some existing work with the original data, and then investigating whether e.g. the replication works with new data.  To engage fully with these freely available resources, competence with a range of techniques and tools is necessary. This project will be carried out in small groups.

Below is a tentative schedule.  The weekly topics are intended to cover useful techniques and tools for carrying out your data-oriented project, and may change depending upon chosen student projects, etc.  

 

Week 1

Empirical research

Tools for empirical research: Jupyter Notebooks
Week 2

Introduction to cloud computing and virtual machines

Discussion of data-based projects
Week 3

Version control and the linux shell

Discussion of data-based projects
Week 4

Introduction to data gathering and curation
Week 5

Latex and document typesetting
Week 6

Project proposal presentations
Week 7

Data analysis in Python
Week 8

Microblogging and handling messy data
 

RECESS
Week 9

Data annotation and surveys
Week 10

Project update presentations
Week 11

Databases and information extraction
Week 12

Additional topics
Week 13

Final presentations

 

Policies and Procedures

Macquarie University policies and procedures are accessible from Policy Central (https://policies.mq.edu.au). Students should be aware of the following policies in particular with regard to Learning and Teaching:

Students seeking more policy resources can visit Student Policies (https://students.mq.edu.au/support/study/policies). It is your one-stop-shop for the key policies you need to know about throughout your undergraduate student journey.

To find other policies relating to Teaching and Learning, visit Policy Central (https://policies.mq.edu.au) and use the search tool.

Student Code of Conduct

Macquarie University students have a responsibility to be familiar with the Student Code of Conduct: https://students.mq.edu.au/admin/other-resources/student-conduct

Results

Results published on platform other than eStudent, (eg. iLearn, Coursera etc.) or released directly by your Unit Convenor, are not confirmed as they are subject to final approval by the University. Once approved, final results will be sent to your student email address and will be made available in eStudent. For more information visit connect.mq.edu.au or if you are a Global MBA student contact globalmba.support@mq.edu.au

Academic Integrity

At Macquarie, we believe academic integrity – honesty, respect, trust, responsibility, fairness and courage – is at the core of learning, teaching and research. We recognise that meeting the expectations required to complete your assessments can be challenging. So, we offer you a range of resources and services to help you reach your potential, including free online writing and maths support, academic skills development and wellbeing consultations.

Student Support

Macquarie University provides a range of support services for students. For details, visit http://students.mq.edu.au/support/

The Writing Centre

The Writing Centre provides resources to develop your English language proficiency, academic writing, and communication skills.

The Library provides online and face to face support to help you find and use relevant information resources. 

Student Services and Support

Macquarie University offers a range of Student Support Services including:

Student Enquiries

Got a question? Ask us via the Service Connect Portal, or contact Service Connect.

IT Help

For help with University computer systems and technology, visit http://www.mq.edu.au/about_us/offices_and_units/information_technology/help/. 

When using the University's IT, you must adhere to the Acceptable Use of IT Resources Policy. The policy applies to all who connect to the MQ network including students.

Changes from Previous Offering

We value student feedback to be able to continually improve the way we offer our units. As such we encourage students to provide constructive feedback via student surveys, to the teaching staff directly, or via the FSE Student Experience & Feedback link in the iLearn page. Student feedback from the previous offering of this unit was very positive overall, with students pleased with the clarity around assessment requirements and the level of support from the teaching staff. As such, no change to the delivery of the unit is planned, however, we will continue to strive to improve the level of support and the level of student engagement.

Assessment Standards

 

The unit will be graded according to the following general descriptions of the letter grades as specified by Macquarie University.  In the course of the unit, these grade descriptions will be discussed with respect to example projects.

High Distinction (HD, 85-100): provides consistent evidence of deep and critical understanding in relation to the learning outcomes. There is substantial originality and insight in identifying, generating and communicating competing arguments, perspectives or problem solving approaches; critical evaluation of problems, their solutions and their implications; creativity in application as appropriate to the discipline.

In the context of this unit, the project has a good design, and has used some data that is interesting or non-obvious, or has required some effort to obtain or use.  It involves a good analysis of the data, and fairly extensively draws on the techniques and tools presented in the unit and possibly on others discovered independently by the student.  The project is described in a report and a presentation that are well-structured and essentially free from errors; these would be of a standard that could be presented at a conference with little or no polishing.

Distinction (D, 75-84): provides evidence of integration and evaluation of critical ideas, principles and theories, distinctive insight and ability in applying relevant skills and concepts in relation to learning outcomes. There is demonstration of frequent originality in defining and analysing issues or problems and providing solutions; and the use of means of communication appropriate to the discipline and the audience.

In the context of this unit, the project has a good design, and has used some data that is interesting or non-obvious, or has required some effort to obtain or use.  It involves a good analysis of the data, and fairly extensively draws on the techniques and tools presented in the unit.  The project is described in a report and a presentation that are well-structured and mostly free from errors; these would be of a standard that could be presented at a conference with some polishing.

Credit (Cr, 65-74): provides evidence of learning that goes beyond replication of content knowledge or skills relevant to the learning outcomes. There is demonstration of substantial understanding of fundamental concepts in the field of study and the ability to apply these concepts in a variety of contexts; convincing argumentation with appropriate coherent justification; communication of ideas fluently and clearly in terms of the conventions of the discipline.

In the context of this unit, the project has a sound design, and demonstrates some thought in the choice of data.  It involves a good analysis of the data, and uses a reasonable number of the techniques and tools presented in the unit.  The project is described in a report and a presentation that are well-structured and mostly free from errors.

Pass (P, 50-64): provides sufficient evidence of the achievement of learning outcomes. There is demonstration of understanding and application of fundamental concepts of the field of study; routine argumentation with acceptable justification; communication of information and ideas adequately in terms of the conventions of the discipline. The learning attainment is considered satisfactory or adequate or competent or capable in relation to the specified outcomes.

In the context of this unit, the project has a satisfactory design and uses some easily accessible data.  It involves a successful, or nearly successful, analysis of data, and shows some familiarity with tools or techniques presented in the unit.  The project is described in a satisfactory report and presentation.

Fail (F, 0-49): does not provide evidence of attainment of learning outcomes. There is missing or partial or superficial or faulty understanding and application of the fundamental concepts in the field of study; missing, undeveloped, inappropriate or confusing argumentation; incomplete, confusing or lacking communication of ideas in ways that give little attention to the conventions of the discipline.

 

 

Unit information based on version 2024.01R of the Handbook