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ISYS3401: Information Technology Evaluation (2019 - Semester 1)

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Unit: ISYS3401: Information Technology Evaluation (6 CP)
Mode: Normal-Day
On Offer: Yes
Level: Senior
Faculty/School: School of Computer Science
Unit Coordinator/s: A/Prof Poon, Simon
Session options: Semester 1
Versions for this Unit:
Campus: Camperdown/Darlington
Pre-Requisites: (INFO2110 OR ISYS2110) AND (INFO2120 OR ISYS2120) AND (ISYS2140 OR ISYS2160).
Brief Handbook Description: Information Systems (IS) professionals in today's organisations are required to play important roles in technology implementation and assessment. Your success in this field will be aided by your being able to plan, implement and execute of an study in evaluating technology in individual and organisational contexts. Practical research and analytical skills are some of the most important assets you will need in your IT career. This unit of study will cover important concepts and skills in practical research for assess technology impacts from both technology and user perspective It will also provide hand-on experience of using statistical software and other tools to perform some of the quantitative analysis.
Assumed Knowledge: MATH1005 OR MATH1905.
Lecturer/s: A/Prof Poon, Simon
Tutor/s: Iris Yang Xiaoyu (email: xyan0700@uni.sydney.edu.au)
Timetable: ISYS3401 Timetable
Time Commitment:
# Activity Name Hours per Week Sessions per Week Weeks per Semester
1 Lecture 2.00 1 13
2 Tutorial 1.00 1 13
3 Independent Study 9.00 13
T&L Activities: Tutorial: Lab based tutorial, students are practicing data analysis skills using Excel and other tools for statistical analysis of data

Independent Study: Students are required to read the text book, to do take home quizzes and additional homework

Learning outcomes are the key abilities and knowledge that will be assessed in this unit. They are listed according to the course goal supported by each. See Assessment Tab for details how each outcome is assessed.

(4) Design (Level 3)
1. understand experiment design and various ways of analyzing experiment data
2. be able to build relationships between variables and use them for forecasting
3. Understand basic concepts in decision modelling
(3) Problem Solving and Inventiveness (Level 3)
4. be able to build and solve various decision models
5. be able to carry out proper hypothesis testing given a data set.
(1) Maths/ Science Methods and Tools (Level 3)
6. Understand different types of data and be able to describe data using descriptive statistics
7. Understand various probability distributions
8. understand the difference between sample and population and be able to make inference from samples
Assessment Methods:
# Name Group Weight Due Week Outcomes
1 Quiz* No 15.00 Week 7 5, 6, 7, 8,
2 Group Assignment 1 Yes 10.00 Week 11 3, 4,
3 Group Assignment 2 Yes 10.00 Week 13 1, 2, 3, 4, 6,
4 Final Exam No 65.00 Exam Period 1, 2, 3, 4, 5, 6, 7, 8,
Assessment Description: * indicates an assessment task which must be repeated if a student misses it due to special consideration.

Quiz: Written test during the lecture.

Group Assignment 1: Written assignment on designing an empirical study. Late submission is subject to penalty of 20% of the mark per day.

Group Assignment 2: Written assignment on analysing an empirical study. Late submission is subject to penalty of 20% of the mark per day.

Final Exam: Written examination covering all aspects of the unit of study.

Mark moderation: There may be statistically defensible moderation when combining the marks from each component to ensure consistency of marking between markers, and alignment of final grades with unit outcomes.
Grading:
Grade Type Description
Standards Based Assessment Final grades in this unit are awarded at levels of HD for High Distinction, DI (previously D) for Distinction, CR for Credit, PS (previously P) for Pass and FA (previously F) for Fail as defined by University of Sydney Assessment Policy. Details of the Assessment Policy are available on the Policies website at http://sydney.edu.au/policies . Standards for grades in individual assessment tasks and the summative method for obtaining a final mark in the unit will be set out in a marking guide supplied by the unit coordinator.
Minimum Pass Requirement It is a policy of the School of Computer Science that in order to pass this unit, a student must achieve at least 40% in the written examination. For subjects without a final exam, the 40% minimum requirement applies to the corresponding major assessment component specified by the lecturer. A student must also achieve an overall final mark of 50 or more. Any student not meeting these requirements may be given a maximum final mark of no more than 45 regardless of their average.
Policies & Procedures: IMPORTANT: School policy relating to Academic Dishonesty and Plagiarism.

In assessing a piece of submitted work, the School of Computer Science may reproduce it entirely, may provide a copy to another member of faculty, and/or to an external plagiarism checking service or in-house computer program and may also maintain a copy of the assignment for future checking purposes and/or allow an external service to do so.

Other policies

See the policies page of the faculty website at http://sydney.edu.au/engineering/student-policies/ for information regarding university policies and local provisions and procedures within the Faculty of Engineering and Information Technologies.
Prescribed Text/s: Note: Students are expected to have a personal copy of all books listed.

Note that the "Weeks" referred to in this Schedule are those of the official university semester calendar https://web.timetable.usyd.edu.au/calendar.jsp

Week Description
Week 1 Introduction to the Topic: IT Evaluation
Week 2 Quantitative Approaches for Evaluation Studies
Week 3 Empirical Approaches for Evaluation Studies(1)
Week 4 Empirical Approaches for Evaluation Studies(2)
Week 5 Interpretation and Reporting in Practice
Week 6 Research Methods of Evaluation Studies
Week 7 Assessment Due: Quiz*
Week 8 Planning and Design for User Evaluation
Week 9 Measurement Models and Constructs
Week 10 Reliability & Validity
Week 11 Structure Equation Modelling
Assessment Due: Group Assignment 1
Week 12 Special Topic: Qualitative Comparative Analysis
Week 13 Special Topic: Economic Evaluation Study of IT
Assessment Due: Group Assignment 2
STUVAC (Week 14) This week is left free for independent study.
Exam Period Assessment Due: Final Exam

Course Relations

The following is a list of courses which have added this Unit to their structure.

Course Year(s) Offered
Bachelor of Advanced Computing (Information Systems Major) 2018, 2019, 2020
Bachelor of Computer Science and Technology 2015, 2016, 2017
Bachelor of Computer Science and Technology (Advanced) 2015, 2016, 2017
Bachelor of Computer Science and Technology (Information Systems) 2014 and earlier 2010, 2011, 2012, 2013, 2014
Bachelor of Computer Science and Technology (Information Systems)(Advanced) 2014 and earlier 2013, 2014
Bachelor of Computer Science & Tech. Mid-Year 2016, 2017
Bachelor of Information Technology 2015, 2016, 2017
Bachelor of Information Technology/Bachelor of Arts 2015, 2016, 2017
Bachelor of Information Technology/Bachelor of Commerce 2017, 2015, 2016
Bachelor of Information Technology/Bachelor of Medical Science 2015, 2016, 2017
Bachelor of Information Technology/Bachelor of Science 2015, 2016, 2017
Bachelor of Information Technology (Information Systems) 2014 and earlier 2010, 2011, 2012, 2013, 2014
Information Technology (Information Systems)/Arts 2012, 2013, 2014
Information Technology (Information Systems) / Commerce 2012, 2013, 2014
Information Technology (Information Systems) / Medical Science 2012, 2013, 2014
Information Technology (Information Systems) / Science 2012, 2013, 2014
Information Technology (Information Systems) / Law 2012, 2013, 2014
Bachelor of Information Technology/Bachelor of Laws 2015, 2016, 2017
Bachelor of Advanced Computing/Bachelor of Commerce 2018, 2019, 2020
Bachelor of Advanced Computing/Bachelor of Science 2018, 2019, 2020
Bachelor of Advanced Computing/Bachelor of Science (Health) 2018, 2019, 2020
Bachelor of Advanced Computing/Bachelor of Science (Medical Science) 2018, 2019, 2020
Bachelor of Advanced Computing (Computational Data Science) 2018, 2019, 2020
Bachelor of Advanced Computing (Computer Science Major) 2018, 2019, 2020
Bachelor of Advanced Computing (Software Development) 2018, 2019, 2020
Bachelor of Computer Science and Technology (Computer Science) 2014 and earlier 2009, 2010, 2011, 2012, 2013, 2014
Bachelor of Computer Science and Technology (Computer Science)(Advanced) 2014 and earlier 2013, 2014
Aeronautical Engineering / Science 2011, 2012, 2013, 2014
Aeronautical Engineering (Space) / Science 2011, 2012, 2013, 2014
Biomedical Engineering / Science 2013, 2014
Chemical & Biomolecular Engineering / Science 2011, 2012, 2013, 2014
Civil Engineering / Science 2011, 2012, 2013, 2014
Electrical Engineering (Bioelectronics) / Science 2011, 2012
Electrical Engineering / Science 2011, 2012, 2013, 2014
Electrical Engineering (Computer) / Science 2014
Electrical Engineering (Power) / Science 2011, 2012, 2013, 2014
Electrical Engineering (Telecommunications) / Science 2011, 2012, 2013, 2014
Aeronautical / Science 2015, 2016, 2017
Aeronautical (Space) / Science 2015
Biomedical Mid-Year 2016, 2017, 2018, 2019, 2020
Biomedical 2016, 2017, 2018, 2019, 2020
Biomedical /Science 2015, 2016, 2017
Chemical & Biomolecular / Science 2015
Civil / Science 2015
Electrical / Science 2015
Electrical (Computer) / Science 2015
Electrical (Power) / Science 2015
Electrical (Telecommunications) / Science 2015
Mechanical / Science 2015, 2016, 2017
Mechanical (Space) / Science 2015
Mechatronic / Science 2015, 2016, 2017
Mechatronic (Space) / Science 2015
Mechanical Engineering (Biomedical) / Science 2011, 2012
Mechanical Engineering / Science 2011, 2012, 2013, 2014
Mechanical Engineering (Space) / Science 2011, 2012, 2013, 2014
Mechatronic Engineering / Science 2011, 2012, 2013, 2014
Mechatronic Engineering (Space) / Science 2011, 2012, 2013, 2014
Project Engineering and Management (Civil) / Science 2011
Software Engineering / Science 2011, 2012, 2013, 2014
Bachelor of Information Technology (Computer Science) 2014 and earlier 2009, 2010, 2011, 2012, 2013, 2014
Information Technology (Computer Science)/Arts 2012
Information Technology (Computer Science) / Science 2012
Flexible First Year (Stream A) / Science 2012

Course Goals

This unit contributes to the achievement of the following course goals:

Attribute Practiced Assessed
(6) Communication and Inquiry/ Research (Level 3) No 0%
(7) Project and Team Skills (Level 3) No 0%
(8) Professional Effectiveness and Ethical Conduct (Level 3) No 0%
(5) Interdisciplinary, Inclusiveness, Influence (Level 3) No 0%
(4) Design (Level 3) No 35.38%
(2) Engineering/ IT Specialisation (Level 3) No 0%
(3) Problem Solving and Inventiveness (Level 3) No 27%
(1) Maths/ Science Methods and Tools (Level 3) No 37.63%

These goals are selected from Engineering & IT Graduate Outcomes Table 2018 which defines overall goals for courses where this unit is primarily offered. See Engineering & IT Graduate Outcomes Table 2018 for details of the attributes and levels to be developed in the course as a whole. Percentage figures alongside each course goal provide a rough indication of their relative weighting in assessment for this unit. Note that not all goals are necessarily part of assessment. Some may be more about practice activity. See Learning outcomes for details of what is assessed in relation to each goal and Assessment for details of how the outcome is assessed. See Attributes for details of practice provided for each goal.