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Unit outline_

ISYS3401: Information Technology Evaluation

Semester 1, 2024 [Normal day] - Camperdown/Darlington, Sydney

Information Systems (IS) professionals in today's organisations are required to play leadership roles in change and development. Your success in this field will be aided by your being able to carry out research-based investigations using suitable methods and mastery over data collection and analysis to assist in managing projects and in decision making. Practical research skills are some of the most important assets you will need in your career. This unit of study will cover important concepts and skills in practical research for solving and managing important problems. This will also provide you with the skills to undertake the capstone project in the IS project unit of study offered in Semester 2 or other projects. It will also provide hand-on experience of using Microsoft Excel and other tools to perform some of the quantitative analysis.

Unit details and rules

Academic unit Computer Science
Credit points 6
Prerequisites
? 
(INFO2110 OR ISYS2110) AND (INFO2120 OR ISYS2120) AND (ISYS2140 OR ISYS2160)
Corequisites
? 
None
Prohibitions
? 
None
Assumed knowledge
? 

MATH1005 or MATH1905 or MATH1062 or DATA1001 or DATA1901

Available to study abroad and exchange students

Yes

Teaching staff

Coordinator Simon Poon, simon.poon@sydney.edu.au
Demonstrator(s) Ruihua Guo, ruihua.guo@sydney.edu.au
Lecturer(s) Simon Poon, simon.poon@sydney.edu.au
The census date for this unit availability is 2 April 2024
Type Description Weight Due Length
Short release assignment Final exam
Questions and case-studies based on contents covered in the unit.
40% Formal exam period Take-home short release assignment
Outcomes assessed: LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9 LO1
Assignment Assignment 1
Appraisal of Evaluation Study & Plan for User Evaluation
30% Mid-semester break
Due date: 31 Mar 2024 at 23:59
3 weeks
Outcomes assessed: LO1 LO7 LO6 LO5 LO4 LO3 LO2
Assignment Assignment 2
Empirical Evaluation Study: Measuring Technology Acceptance/Adoption
30% Week 13
Due date: 20 May 2024 at 23:59
3 weeks
Outcomes assessed: LO1 LO2 LO3 LO5 LO8 LO9

Assessment summary

Assignment 1: Appraisal of Evaluation Study & Plan for User Evaluation

Assignment 2: Empirical Analysis & Assessment of Evaluation Result

Take-Home Final Exam: Short Release

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:

Deduction of 5% of 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.

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.

Support for students

The Support for Students Policy 2023 reflects the University’s commitment to supporting students in their academic journey and making the University safe for students. It is important that you read and understand this policy so that you are familiar with the range of support services available to you and understand how to engage with them.

The University uses email as its primary source of communication with students who need support under the Support for Students Policy 2023. Make sure you check your University email regularly and respond to any communications received from the University.

Learning resources and detailed information about weekly assessment and learning activities can be accessed via Canvas. It is essential that you visit your unit of study Canvas site to ensure you are up to date with all of your tasks.

If you are having difficulties completing your studies, or are feeling unsure about your progress, we are here to help. You can access the support services offered by the University at any time:

Support and Services (including health and wellbeing services, financial support and learning support)
Course planning and administration
Meet with an Academic Adviser

WK Topic Learning activity Learning outcomes
Week 01 Introduction to the topic: IT evaluation Lecture (2 hr) LO1 LO2 LO3
Week 02 Establishing empirical evidence 1: Quantitative Approaches Lecture (2 hr) LO5 LO8 LO9
Statistical foundations for Evaluation Studies Workshop (1 hr) LO8 LO9
Week 03 Establishing empirical evidence 2: Interpretation & Reporting Lecture (2 hr) LO5 LO8 LO9
Empirical Testing part 1: Comparative Analysis Workshop (1 hr) LO5 LO8 LO9
Week 04 Reviewing evaluation methodologies: Study Types Lecture (2 hr) LO1 LO3
Empirical Testing Part 2: measure of impacts using regression Workshop (1 hr) LO5 LO8 LO9
Week 05 Planning for Evaluation studies: Reviewing qualities of evaluation studies Lecture (2 hr) LO4 LO6
Study Types for Evaluation Workshop (1 hr) LO1 LO3
Week 06 Developing Evaluation Metrics Lecture (2 hr) LO2 LO5
Review of evidence using Case Study Workshop (1 hr) LO4 LO6
Week 07 Evaluating behavioural and physiological aspects Lecture (2 hr) LO2 LO4
Developing User Acceptability Metrics of IT Evaluation Workshop (1 hr) LO2 LO5
Week 08 Measurement Models for Evaluations Lecture (2 hr) LO2 LO5
Design of Survey Questionnaire Workshop (1 hr) LO2 LO4
Week 09 Measurement Model Validity Lecture (2 hr) LO1 LO2 LO5 LO7
Introduction of SPSS: Regression and Exploratory Factor Analysis Workshop (1 hr) LO2 LO5
Week 10 Measurement Model Reliability Lecture (2 hr) LO1 LO2 LO5 LO7
Evaluating Validity Workshop (1 hr) LO1 LO2 LO5 LO7
Week 11 Structure Equation Modelling Lecture (2 hr) LO5 LO7 LO8
Introduction to AMOS: Evaluating Reliability Workshop (1 hr) LO1 LO2 LO5 LO7
Week 12 Path Model Analysis Lecture (2 hr) LO5 LO8 LO9
Structural Equation Modelling using AMOS: Confirmatory Factor Analysis Workshop (1 hr) LO5 LO8 LO9
Week 13 Special topic: economic evaluation study for Information Technology. Revision Lecture (2 hr) LO3 LO4
Structural Equation Modelling using AMOS: Path Analysis Workshop (1 hr) LO5 LO8 LO9

Attendance and class requirements

There are no specific attendence and class requirements for this unit.

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.

  • William Albert, Thomas Tullis. (2013), Measuring the User Experience: Collecting, Analyzing, and Presenting Usability Metrics, (Can search online and Download Free via the university library)
  • Anol Bhattacherjee (2012), Social Science Research: Principles, Methods, and Practices. Global Text Project. Access: https://scholarcommons.usf.edu/oa_textbooks/3/

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. understand user experience, usability and usefulness
  • LO2. Understanding theories of Technology Acceptance, Adoption and task-technology fit
  • LO3. Understand different approaches to evaluation
  • LO4. Appreciate a variety of qualitative and quantitative methods for evaluation studies
  • LO5. develop measure measurement models for evaluations
  • LO6. understand experiment design and various ways of analyzing experiment data
  • LO7. understand survey instrument design and various ways of analyzing and survey data
  • LO8. carry out proper empirical tests with given experimental and survey data sets
  • LO9. ability to report and interpret from qualitative and quantitative findings

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.

More practical contents added to both assignments.

There is no other relevant information for this unit

Additional costs

There are no additional costs for this unit.

Site visit guidelines

There are no site visit guidelines for this unit.

Work, health and safety

There are no specific work health and safety requirements for this unit.

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.