LAWS13019 - Legal Automation

General Information

Unit Synopsis

This unit is designed for students who want to develop knowledge and skills in the automation of the practice of law. This unit incorporates theory, research and the practical application of legal project management, process improvement and innovation frameworks, expert systems, document and process automation, data analytics, machine learning and blockchain. Students will examine software systems that empower consumers including lawyerless internet-based systems that vend interactive documents and intelligent legal assistance. Intelligent systems designed for lawyers to produce inexpensive transactional outcomes will be considered. The challenges, threats, opportunities and ethical considerations associated with these developments will be explored. Consideration will also be given as to how governments, pro bono and community legal centres may directly benefit from automation. Through engagement with legal knowledge engineering, students will develop a legal App. No programming experience or other technical knowledge is required.

Details

Level Undergraduate
Unit Level 3
Credit Points 6
Student Contribution Band SCA Band 4
Fraction of Full-Time Student Load 0.125
Pre-requisites or Co-requisites

Co-requisites: LAWS11057 and LAWS11059, or LAWS11030

Important note: Students enrolled in a subsequent unit who failed their pre-requisite unit, should drop the subsequent unit before the census date or within 10 working days of Fail grade notification. Students who do not drop the unit in this timeframe cannot later drop the unit without academic and financial liability. See details in the Assessment Policy and Procedure (Higher Education Coursework).

Class Timetable View Unit Timetable
Residential School No Residential School

Unit Availabilities from Term 2 - 2025

Term 1 - 2026 Profile
Online

Attendance Requirements

All on-campus students are expected to attend scheduled classes - in some units, these classes are identified as a mandatory (pass/fail) component and attendance is compulsory. International students, on a student visa, must maintain a full time study load and meet both attendance and academic progress requirements in each study period (satisfactory attendance for International students is defined as maintaining at least an 80% attendance record).

Assessment Overview

Recommended Student Time Commitment

Each 6-credit Undergraduate unit at CQUniversity requires an overall time commitment of an average of 12.5 hours of study per week, making a total of 150 hours for the unit.

Assessment Tasks

Assessment Task Weighting
1. Practical Assessment 80%
2. Group Work 20%

This is a graded unit: your overall grade will be calculated from the marks or grades for each assessment task, based on the relative weightings shown in the table above. You must obtain an overall mark for the unit of at least 50%, or an overall grade of ‘pass’ in order to pass the unit. If any ‘pass/fail’ tasks are shown in the table above they must also be completed successfully (‘pass’ grade). You must also meet any minimum mark requirements specified for a particular assessment task, as detailed in the ‘assessment task’ section (note that in some instances, the minimum mark for a task may be greater than 50%).

Consult the University's Grades and Results Policy for more details of interim results and final grades

Past Exams

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Previous Feedback

Term 1 - 2025 : The overall satisfaction for students in the last offering of this course was 75.00% (`Agree` and `Strongly Agree` responses), based on a 47.06% response rate.

Feedback, Recommendations and Responses

Every unit is reviewed for enhancement each year. At the most recent review, the following staff and student feedback items were identified and recommendations were made.

Source: LAWS13019 Student 2024 Offering
Feedback
This is my last unit before I graduate and it was an absolute pleasure. I looked forward to attending every tutorial Tuesday and enjoyed every session. More importantly, I enjoyed completing the assessment because they were practical. Kudos to Cait for making the subject fun and easy to understand. Cait provided personalised feedback and assistance all the way through. This unit has also helped me with my career as my employer is very impressed in my ability to design and create a chatbot and I am able to further my career due to this newly acquired skill. I hope this unit will influence how other units are run to ensure better engagement from students.
Recommendation
Caitlin Schiavone is retained as the Teaching Staff for LAWS13019 Legal Automation 2025 offering.
Action Taken
Caitlin Schiavone taught LAWS13019 in 2025.
Source: LAWS13019 Student 2024 Offering
Feedback
I was skeptical about taking this unit but it has opened my mind up to something new - a new (and fun!) way of teaching and all that AI has to offer the legal profession.
Recommendation
LAWS13019 Legal Automation has been offered again in 2025.
Action Taken
LAWS13019 was taught again in term 1 2025.
Source: LAWS13019 Student 2024 Offering
Feedback
I am writing to express my deepest gratitude and appreciation for the exceptional teaching and support provided by Caitlin during my recent term in the Legal Automation unit (LAWS13019). From the moment I started in Caitlin's class, I was greeted with warmth, encouragement, and a genuine desire to see her students succeed. Her welcoming demeanor and positive energy created an environment that fostered inclusivity and engagement, making learning not only accessible but also enjoyable. Throughout the term, Caitlin demonstrated an unparalleled level of understanding and support, particularly during challenging personal circumstances I faced. Her compassion and belief in my abilities were unwavering, providing me with the encouragement and motivation needed to overcome obstacles and excel in my studies. What truly sets Caitlin apart is her innovative and effective teaching techniques. Rather than adhering to traditional lecture styles, Caitlin employed interactive methods that kept students actively involved and invested in the material. Her commitment to inclusivity ensured that every student felt valued and heard, creating a sense of belonging that enhanced the learning experience for all. I am deeply grateful for Caitlin's dedication to her students' success and well-being. Her impact extends far beyond the classroom, influencing not only academic achievements but also personal growth and confidence. I believe Caitlin's exceptional contributions deserve recognition, and I wholeheartedly recommend her for any teaching awards or accolades within your institution. Her passion for education, combined with her genuine care for her students, makes her truly deserving of such honor. Thank you for providing me with the opportunity to learn from Caitlin's expertise and guidance. I look forward to seeing her continued impact on future students and the academic community as a whole.
Recommendation
Caitlin Schiavone is retained as the Teaching Staff for LAWS13019 Legal Automation 2025 offering. Teaching Staff to develop training and other learning support materials for other staff/units, particularly, Miro.
Action Taken
Caitlin Schiavone taught LAWS13019 in 2025. Learning and Teaching materials were developed for the School of Business and Law for Miro.
Source: LAWS13019 Student 2024 Offering
Feedback
Given me hope that neurodivergent people can achieve, not only be accepted but thrive in our work.
Recommendation
Teaching Staff to engaged Learning and Teaching to provide materials on delivery methods and strategies to assist with promoting inclusivity across all CQUniversity subjects, where practicable.
Action Taken
Learning and Teaching materials have been part of presentations to the broader University to promote engagement and inclusivity practices as part of LAWS13019.
Source: LAWS13019 Student 2024 Offering
Feedback
Caitlin was my teacher for Legal Automation at CQU. Caitlin's teaching style was unlike any I have experienced. She was passionate, enthusiastic, supportive and interesting. She made herself available to students when they needed help, guidance or even just a chat! Caitlin took the time to provide personalised feedback along with assessment marks, and took a genuine interest in helping students to learn and achieve. She was invested in our learning and worked hard to keep students engaged. Her dedication to the subject and her students drove me to try harder, and this was reflected in the marks I earned.
Recommendation
Caitlin Schiavone is retained as the Teaching Staff for LAWS13019 Legal Automation 2025 offering. Teaching Staff to engaged Learning and Teaching to provide materials on delivery methods and strategies to assist with promoting inclusivity across all CQUniversity subjects, where practicable.
Action Taken
Learning and Teaching materials were refreshed for the 2025 offering to be more inclusive than the 2024 offering through multi-modal communication methods.
Source: LAWS13019 Student 2024 Offering
Feedback
Upon taking the course, I had reservations as I did not fully grasp what kind of work required to complete and participate in Legal Automation LAWS13019. As the weeks commenced, attending the tutorials and reading through the material, I became very fascinated with the world of Artificial Intelligence. It has been a topic of conversation in the technology world for a number of years, but I had very little understanding of it. Caitlin has been absolutely amazing in providing the necessary framework to capture continuous attention in the course and making it inviting, where no question is silly. She has been a pleasure to learn of and her teaching style is not-like any other law course that I have completed. I thoroughly enjoyed and looked forward to attending the tutorials to truly understand how to create a chatbot. This is an extremely credible skill to take into the workforce, especially with the growing understanding and usability of artificial intelligence. I cannot emphasise how much I’ve enjoyed Caitlin’s teaching styling and course. I would highly recommend this to other law students as we cannot shy away from artificial intelligence as it is necessary for future lawyers to learn this skill to prepare us for the future.
Recommendation
Caitlin Schiavone is retained as the Teaching Staff for LAWS13019 Legal Automation 2025 offering. LAWS13019 Legal Automation has been offered again in 2025. Continued offering to be reviewed on a rolling basis.
Action Taken
LAWS13019 was taught in 2025 with the same teaching staff. The unit will be again offered in 2026.
Source: LAWS13019 Student 2024 Offering
Feedback
I have been studying my Bachelor of Laws over the past 3 ½ years at CQU and I am in my final weeks. Admittedly, I was rather dismissive of the Legal Automation subject when it first appeared as an elective and having had heard past student experiences it was not one that interested me in the slightest. I enrolled in my last semester as I literally had no other subjects left to choose from in order to graduate. To my surprise, this course was not dry as I was led to believe but rather engaging and not at all what had been described to me from past student experiences. Caitlin had me hook line and sinker from the first moment. Injecting humor into a course such as this also deserves commendation as I really don't know how she did it! I would often find my kids looking over my learning materials and lectures intrigued by what was on the screen. Her down to earth approach to the course and meeting students where they were at was second to none. Above all her integrity throughout the last semester was refreshing. Caitlin would always follow through with what she had promised. It has been my experience only a handful of lecturers are as responsive to students as Caitlin has been and that was a huge achievement given we were all a bit of a needy bunch as we navigated this new learning style. It is difficult to remain this engaged in my last semester but through her own passion and infectious enthusiasm, Caitlin has made my final weeks at University enjoyable (I really did just say that). The subject itself has such real world applications and I have found myself offering up my services with those that are in business to create something for them.
Recommendation
Caitlin Schiavone is retained as the Teaching Staff for LAWS13019 Legal Automation 2025 offering. LAWS13019 Legal Automation has been offered again in 2025. Continued offering to be reviewed on a rolling basis.
Action Taken
LAWS13019 was taught in 2025 with the same teaching staff. The unit will be again offered in 2026.
Source: LAWS13019 Student 2024 Offering
Feedback
I am currently entering my last term for my law degree at Central Queensland University. I am a mature aged student with other qualifications from Charles Sturt University which were achieved during my service with the Australian Federal Police. Ms Schiavone has just completed teaching the unit Legal Automation. I found Ms Schiavone to be an enthusiastic, professional, diligent and caring tutor. She displays these qualities with a passion for the area of law she teaches. It is rare to find such a combination of these attributes, however they were present each and every week. The subject detail was very different to other areas of law. It required the students to interact with each other and computer based programs to achieve the desired outcomes. Ms Schiavone navigated the students with a dedicated and engaging persona that was contagious to the cohort. The final assignment saw legal issues answered with real solutions based on legal automation platforms. The platforms in 'Josef ' were incredibly complex and very well done by all students. This is a reflection on how Ms Schiavone dedicated her time during and outside university timetables. She was quick to respond to questions and eager to ensure students were both involved and confident in their progress throughout the semester. Ms Schiavone is a credit to Central Queensland University and the tertiary teaching fraternity as a whole.
Recommendation
LAWS13019 Legal Automation has been offered again in 2025.
Action Taken
LAWS13019 Legal Automation was offered in 2025 and will be offered again in 2026.
Source: Students request: Clarification of assessment requirements in response to assessment feedback
Feedback
Clarify ‘assessment requirements’
Recommendation
The Unit Coordinator will review marking rubrics prior to the next offering to ensure clarity, fairness, and consistent performance differentiation.
Action Taken
In Progress
Source: Reviewer comment
Feedback
Unit coordinator to specify plan for promotion and visibility of LAWS13019
Recommendation
It is proposed that the unit should be promoted more broadly within the School of Business and Law. This can occur through presentation at the next School of Business and Law meeting which should aim to raise awareness of the availability of LAWS13019 as an elective unit and for other Unit Coordinators to recommend/endorse same to their students, if possible.
Action Taken
In Progress
Source: Reviewer Comments
Feedback
Clarify how LAWS13019 is linked to professional employment outcomes
Recommendation
It is also proposed that for the next 2026 offering, LAWS13019 learning outcomes should explicitly map to the Bachelor of Laws degree structure. This could include mapping between LAWS13019 assessment tasks to key legal industry skills being made visible in the Week 1 orientation session for new students. This will help students recognise the relevance of artificial intelligence in the legal profession to their degree and employability.
Action Taken
In Progress
Source: End of term feedback from students: Requested clearer explanations of unit learning outcomes
Feedback
Clarify key ‘take-aways’ in Unit Profile for LAWS13019
Recommendation
The unit profile will be refreshed prior to the 2026 offering to highlight key take-aways from the LAWS13019 unit, such as hands-on building and operation of artificial intelligence tools, automation, legal tech, and the ability to critically evaluate the risks in using artificial intelligence products within contemporary legal practice.
Action Taken
In Progress
Source: Reviewer Comments
Feedback
Add competitor relevance note
Recommendation
Unit Profile to include statement that comparable units exist elsewhere in other Australian University offerings and that retaining LAWS13019 sustains CQU competitiveness. It should be noted on the unit profile that this unit provides greater breadth and depth into the use of artificial intelligence within the Australian Legal Profession, notably by offering a build-your-own AI solution assessment structure.
Action Taken
In Progress
Source: Student feedback
Feedback
Clearer explanation of assessment rubrics
Recommendation
Removed complex rubric descriptors and referenced proposed coordinated review process. It is proposed that rubric and assessment alignment should be reviewed by the Unit Coordinator and their direct supervisor. This should occur prior to the next offering to ensure continued rigor and transparency for the unit.
Action Taken
In Progress
Unit learning Outcomes

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

  1. Apply process improvement and innovation frameworks to the delivery of legal work
  2. Identify aspects of legal work and new forms of service delivery that can be automated
  3. Classify what ethical and regulatory issues are presented by lawyering using intelligent machines
  4. Construct a software application using teamwork that can model legal knowledge and reasoning to perform useful legal work for non lawyers as a form of social innovation.

This is not an accredited unit.

Alignment of Assessment Tasks to Learning Outcomes
Assessment Tasks Learning Outcomes
1 2 3 4
1 - Practical Assessment • • • •
2 - Group Work •
Alignment of Graduate Attributes to Learning Outcomes
• Introductory Level
• Intermediate Level
• Graduate Level
Graduate Attributes Learning Outcomes
1 2 3 4
1 - Communication • • • •
2 - Problem Solving •
3 - Critical Thinking • • •
4 - Information Literacy •
5 - Team Work •
6 - Information Technology Competence •
8 - Ethical practice •
9 - Social Innovation •
Alignment of Assessment Tasks to Graduate Attributes
• Introductory Level
• Intermediate Level
• Graduate Level
Assessment Tasks Graduate Attributes
1 2 3 4 5 6 7 8 9 10