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Unit outline_

ELEC9610: E-Business Analysis and Design

Semester 1, 2021 [Normal day] - Remote

This unit examines the essential pre-production stages of designing successful internet websites and services. It focuses on the aspects of analysis, project specification, design, and prototype that lead up to the actual build of a website or application. Topics include, B2C, B2B and B2E systems, business models, methodologies, modeling with use cases / UML and WebML, the Project Proposal and Project Specification Document, Information Architecture and User-Centred Design, legal issues, and standards-based web development. Students build a simple use-case based e-business website prototype with web standards. A final presentation of the analysis, design and prototype are presented in a role play environment where students try to win funding from a venture capitalist. An understanding of these pre-production fundamentals is critical for future IT and Software Engineering Consultants, Project Managers, Analysts and CTOs.

Unit details and rules

Academic unit School of Electrical and Computer Engineering
Credit points 6
Prerequisites
? 
None
Corequisites
? 
None
Prohibitions
? 
ELEC5743 OR EBUS3003
Assumed knowledge
? 

Basic knowledge of Database Management Systems

Available to study abroad and exchange students

No

Teaching staff

Coordinator Phee Yeoh, phee.yeoh@sydney.edu.au
Type Description Weight Due Length
Final exam (Record+) Type B final exam Final exam
Final exam covering all aspects of the unit of study.
40% Formal exam period 1 hour
Outcomes assessed: LO1 LO4 LO5 LO7 LO8
Assignment group assignment Proposal
Project Proposal to be submitted in Canvas
30% Week 08 Approximately 5000 words
Outcomes assessed: LO1 LO7 LO6 LO5 LO3 LO2
Presentation group assignment Presentation
Presentation: Online video of group presentation to be submitted in Canvas
15% Week 13 15 minutes
Outcomes assessed: LO4 LO8
Assignment group assignment Website prototype
Final prototype: Demo website to be submitted in Canvas
15% Week 13 Demo of website core functionalities
Outcomes assessed: LO2 LO3 LO5 LO9
group assignment = group assignment ?
Type B final exam = Type B final exam ?

Assessment summary

All assessments should be submitted online in 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.

Result name

Mark range

Description

High distinction

85 - 100

 

Distinction

75 - 84

 

Credit

65 - 74

 

Pass

50 - 64

 

Fail

0 - 49

When you don’t meet the learning outcomes of the unit to a satisfactory 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.

This unit has an exception to the standard University policy or supplementary information has been provided by the unit coordinator. This information is displayed below:

Standard late penalties apply.

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.

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.

WK Topic Learning activity Learning outcomes
Multiple weeks Individual and group work outside of scheduled classes Independent study (80 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9
Week 01 1. Course overview; 2. Information databases Lecture (2 hr) LO1 LO3 LO4
Week 02 1. Project management; 2. Formal software engineering RUP; 3. Project specification document Lecture and tutorial (5 hr) LO1 LO2 LO3 LO5
Week 03 1. Modelling functionality; 2. Use case scenarios Lecture and tutorial (5 hr) LO1 LO2 LO3 LO5 LO7
Week 04 1. Elements and categories of e-commerce; 2. Business to business systems Lecture and tutorial (5 hr) LO2 LO3 LO5 LO6
Week 05 1. E-marketplaces; 2. Online revenue models Lecture and tutorial (5 hr) LO2 LO5 LO6 LO7 LO8
Week 06 1. Business to employee systems; 2. Knowledge management; 3. Website usability Lecture and tutorial (5 hr) LO2 LO5 LO6 LO7 LO8
Week 07 Modelling applications with WebML Lecture and tutorial (5 hr) LO2 LO5 LO6 LO7 LO9
Week 08 E-commerce software for small and large businesses Lecture and tutorial (5 hr) LO2 LO3 LO6 LO7 LO8
Week 09 E-commerce security Lecture and tutorial (5 hr) LO1 LO2 LO3 LO4 LO7
Week 10 E-commerce: legal and ethical issues Lecture and tutorial (5 hr) LO1 LO2 LO3 LO4
Week 11 1. Business to customer systems; 2. Customer relationship management Lecture and tutorial (5 hr) LO2 LO3 LO7 LO8 LO9
Week 12 1. Social networking; 2. Mobile commerce Lecture and tutorial (5 hr) LO2 LO4 LO5 LO7 LO8
Week 13 Unit review Lecture and tutorial (5 hr) LO1 LO4 LO7 LO8 LO9

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 for this unit can be accessed through the Library eReserve, available on Canvas.

  • Gary P. Schneider, Electronic Commerce (12). CENGAGE, 2016. 9781305867819

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.

At the completion of this unit, you should be able to:

  • LO1. demonstrate an understanding of the roles of all the stakeholders in an e-commerce development project by clarifying individual responsibilities and deliverables towards the team effort
  • LO2. work in a group, manage or be managed by a leader in roles that optimise the contribution of all members, while showing initiative and receptiveness so as to jointly achieve engineering project goals with the scope of the projects
  • LO3. develop milestones and implement project management techniques to manage the workload in a group for specific engineering projects
  • LO4. demonstrate an understanding of professional practice in terms of social, ethical and economical responsibilities with respect to successful web projects
  • LO5. demonstrate proficiency in undertaking inquiry and knowledge development for a particular engineering problem by identifying information needs and evaluating a vast number of documents in varied formats to draw meaningful conclusions
  • LO6. write proposals in a clear and well constructed engineering format to convey stakeholder specific information at a degree of thoroughness commensurate to the requirement and task at hand
  • LO7. demonstrable understanding of 'use-case scenarios' as specific tools used in improving the usability of e-business sites to the extent of the work presented
  • LO8. demonstrate an understanding of current issues and developments in content management systems, e-commerce and knowledge management systems
  • LO9. demonstrate an understanding of a web modelling language such as WebML, including the underlying principles and techniques, to the extent of the material presented in the course.

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
GQ1 GQ2 GQ3 GQ4 GQ5 GQ6 GQ7 GQ8 GQ9

This section outlines changes made to this unit following staff and student reviews.

Streamlined assignments to better align with tutorials.

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.