ENGSCI 263 : Engineering Science Design I

Engineering

2025 Semester Two (1255) (15 POINTS)

Course Prescription

Introduction to concepts of model design for engineering problems, including model formulation, solution procedures, validation, and shortcomings, with examples from topics in computational mechanics, operations research and data science. Further development of problem-solving skills, group project work, and group communication skills. The use of computational models to support design-focused decision making while considering ethical, societal, cultural, and environmental factors.

Course Overview

The purpose of this course is to show you how to apply Engineering Science skills and philosophy in a practical setting.  You will design and use computer models in both computational mechanics and operations research contexts. However, a greater emphasis is placed on the practical skills that complement these models, e.g., identifying stakeholders interested in a problem, verification and validation of your work, group work and communication, and the role of models in a wider context that includes ethical, societal, legal and cultural factors.

This course will consist of two projects with associated assessments: 
  • Optimisation and Data Science: this is an optimisation project on a moderately-realistic scale, requiring descriptive, predictive and prescriptive analytics, and making recommendations to a client taking into account wider systems perspectives.
  • Computational Mechanics: this will require you building a model and making recommendations in the context of a resource consent application.

Course Requirements

Prerequisite: ENGGEN 115 and ENGSCI 233 Corequisite: ENGSCI 211 or 213

Capabilities Developed in this Course

Capability 2: Sustainability
Capability 4: Critical Thinking
Capability 5: Solution Seeking
Capability 6: Communication
Capability 7: Collaboration

Learning Outcomes

By the end of this course, students will be able to:
  1. Implement a computer modelling study, including model development, verification, calibration, prediction, inference, scenario modelling and uncertainty analysis. (Capability 4.1, 4.2 and 5.1)
  2. Participate in group design activities through the effective use of communication skills, including peer review, report writing, code documentation and oral presentation. (Capability 6.1 and 7.1)
  3. Discuss the findings of a computer model in a wider context of stakeholder interests whose priorities may involve societal, financial, environmental, legal, ethical or cultural factors. (Capability 2.1, 4.1 and 4.2)
  4. Plan a computer modelling study, including identification of key stakeholders, an analysis of existing data and research literature, and concept peer review. (Capability 4.1, 4.2, 6.1 and 7.1)

Assessments

Assessment Type Percentage Classification
Final Exam 30% Individual Examination
Projects 55% Group & Individual Coursework
Test 15% Individual Coursework
Assessment Type Learning Outcome Addressed
1 2 3 4
Final Exam
Projects
Test

A passing mark is 50% or higher, according to University policy.

The test and exam are in-person and completed on paper. Students must sit the final exam to pass the course. Otherwise, a DNS (did not sit) result will be returned.

Late Policy: Late submissions will be dealt with under the course policy published on Canvas. Late assignments will be penalised at 4% of the marks available per hour, and this is automatically applied by Canvas.

Workload Expectations

This course is a standard 15 point course and students are expected to spend 10 hours per week involved in each 15 point course that they are enrolled in.

For each week in this course, you can expect 2 hours of lectures, a 2 hour computer lab, and 6 hours of individual assignment and / or group project work.

Delivery Mode

Campus Experience

Attendance is expected at scheduled activities including labs to complete components of the course.
Lectures will be available as recordings. Other learning activities including labs will not be available as recordings.
The course will not include live online events.
The activities for the course are scheduled as a standard weekly timetable.

In-person attendance at the test and exam is required.

Learning Resources

Course materials are made available in a learning and collaboration tool called Canvas which also includes reading lists and lecture recordings (where available).

Please remember that the recording of any class on a personal device requires the permission of the instructor.

Health & Safety

Students must ensure they are familiar with their Health and Safety responsibilities, as described in the university's Health and Safety policy.

Student Feedback

At the end of every semester students will be invited to give feedback on the course and teaching through a tool called SET or Qualtrics. The lecturers and course co-ordinators will consider all feedback and respond with summaries and actions.

Your feedback helps teachers to improve the course and its delivery for future students.

Class Representatives in each class can take feedback to the department and faculty staff-student consultative committees.

In the 2024 S2 SET Evaluations, students found the lab sessions with tutor assistance and the real-life nature of projects helpful. However, students found that aspects of the projects lacked clarity, and that the lecture content shifted rapidly with some disconnect with the labs/projects.

Based on the 2024 SET Evaluations, the following changes are planned:
  • Review of the lecture and project material to ensure the course is still correctly focused given diverse student preparations.
  • Reviewing all rubrics for project deliverables to ensure that they are meaningful. 

Academic Integrity

The University of Auckland will not tolerate cheating, or assisting others to cheat, and views cheating in coursework, tests and examinations as a serious academic offence. The work that a student submits for grading must be the student's own work, reflecting their learning. Where work from other sources is used, it must be properly acknowledged and referenced. A student's assessed work may be reviewed against electronic source material using computerised detection mechanisms. Upon reasonable request, students may be required to provide an electronic version of their work for computerised review.

The use of any generative AI tool such as ChatGPT and Copilot is allowed in this course within the boundaries described below. The use of these tools outside of these boundaries may result in the breach of the Student Academic Conduct Statute, linked below together with the guidelines on software use.
  • As a chatbot, to help in finding information and guide your learning (similar to search tools like Google or encyclopaedias like Wikipedia),
  • As a proof-reader, to help in minimising typos, grammatical errors, and other language (i.e. non technical) mistakes,
  • As an editing assistant, to help with having a more fluid, more formal, more academic, shorter/longer, style as appropriate.
The usage of these generative AI tools must be disclosed in the assignments’ deliverables. Failure to disclose may result in the breach of the Statute.
Your assignment and project work must be written by you based on your own understanding.

Class Representatives

Class representatives are students tasked with representing student issues to departments, faculties, and the wider university. If you have a complaint about this course, please contact your class rep who will know how to raise it in the right channels. See your departmental noticeboard for contact details for your class reps.

Inclusive Learning

All students are asked to discuss any impairment related requirements privately, face to face and/or in written form with the course coordinator, lecturer or tutor.

Student Disability Services also provides support for students with a wide range of impairments, both visible and invisible, to succeed and excel at the University. For more information and contact details, please visit the Student Disability Services’ website http://disability.auckland.ac.nz

Special Circumstances

If your ability to complete assessed coursework is affected by illness or other personal circumstances outside of your control, contact a member of teaching staff as soon as possible before the assessment is due.

If your personal circumstances significantly affect your performance, or preparation, for an exam or eligible written test, refer to the University’s aegrotat or compassionate consideration page https://www.auckland.ac.nz/en/students/academic-information/exams-and-final-results/during-exams/aegrotat-and-compassionate-consideration.html.

This should be done as soon as possible and no later than seven days after the affected test or exam date.

Learning Continuity

In the event of an unexpected disruption we undertake to maintain the continuity and standard of teaching and learning in all your courses throughout the year. If there are unexpected disruptions the University has contingency plans to ensure that access to your course continues and your assessment is fair, and not compromised. Some adjustments may need to be made in emergencies. You will be kept fully informed by your course co-ordinator, and if disruption occurs you should refer to the University Website for information about how to proceed.

Student Charter and Responsibilities

The Student Charter assumes and acknowledges that students are active participants in the learning process and that they have responsibilities to the institution and the international community of scholars. The University expects that students will act at all times in a way that demonstrates respect for the rights of other students and staff so that the learning environment is both safe and productive. For further information visit Student Charter https://www.auckland.ac.nz/en/students/forms-policies-and-guidelines/student-policies-and-guidelines/student-charter.html.

Disclaimer

Elements of this outline may be subject to change. The latest information about the course will be available for enrolled students in Canvas.

In this course you may be asked to submit your coursework assessments digitally. The University reserves the right to conduct scheduled tests and examinations for this course online or through the use of computers or other electronic devices. Where tests or examinations are conducted online remote invigilation arrangements may be used. The final decision on the completion mode for a test or examination, and remote invigilation arrangements where applicable, will be advised to students at least 10 days prior to the scheduled date of the assessment, or in the case of an examination when the examination timetable is published.