University of Technology Sydney

65313 Forensic Intelligence

Warning: The information on this page is indicative. The subject outline for a particular session, location and mode of offering is the authoritative source of all information about the subject for that offering. Required texts, recommended texts and references in particular are likely to change. Students will be provided with a subject outline once they enrol in the subject.

Subject handbook information prior to 2023 is available in the Archives.

UTS: Science: Mathematical and Physical Sciences
Credit points: 6 cp
Result type: Grade and marks

Requisite(s): 65316 Criminalistics

Description

The subject builds upon the discipline knowledge and skills developed in 65242 Principles of Forensic Science and 65316 Criminalistics. Over the years, forensic science has primarily positioned itself as a service provider for the criminal justice system. Unfortunately, this focus on the criminal justice system has limited its capacity to provide knowledge about crime and deviant activities. This subject introduces this added value of forensic science. The role of the trace in forensic science, intellectual reasoning and generic processes to apply forensic intelligence in practice is presented. Through a set of complementary lectures, computer labs and independent online learning activities, the students gain theoretical and practical knowledge about the use of a variety of forensic traces in an intelligence perspective. Students develop their critical thinking and inquiry-based skills as they extract a profile from a trace or a case, compare this profile to others, highlight links or trends in the data and finally communicate their findings in a presentation and a short report.

Subject learning objectives (SLOs)

Upon successful completion of this subject students should be able to:

1. Integrate information from collective forensic analyses through intelligence frameworks.
2. Discuss the extended use of forensic traces to provide knowledge about crime and deviant activities.
3. Analyse information conveyed by traces.
4. Extract a profile from a trace or a case and compare it to other traces or cases.
5. Use general software (Excel) and specialist software (I2 Analyst’s Notebook) to analyse and visualise forensic case data.
6. Synthesise and communicate results (links and trends) through written and verbal reporting formats.

Course intended learning outcomes (CILOs)

This subject also contributes specifically to the development of following course intended learning outcomes:

  • Synthesise: Integrate information from individual and collective forensic analyses into investigative, evaluative, or intelligence frameworks. (1.3)
  • Analyse: Critically analyse and evaluate data, experimental results, and academic literature. (2.2)
  • Synthesise: Discuss the impact and role of forensic science in addressing current and future challenges faced by law enforcement, the legal system, security, and the wider community. (3.3)
  • Analyse: Combine various methods to record and communicate observations and evaluation of traces throughout all stages of an investigation. (5.2)

Contribution to the development of graduate attributes

Graduate Attribute 1.0 - Disciplinary knowledge

An understanding of the nature, practice and application of forensic intelligence is fostered through lecture material and is enhanced through critical discussion with experts in the field during guest lectures. Upon completion of this subject, students should be able to understand the role and function of forensic science in the wide security framework, and society at large. In particular, through the computer labs, students will learn how to extract relevant information from traces or cases, compare this information to other traces/cases, highlight links or trends and integrate them into an intelligence framework. These are essential skills for all forensic science students as it underpins a number of careers. Students will have the opportunity to demonstrate the application of their knowledge and practical skills in all assessment items and feedback will be provided during the computer lab sessions and online activities to assist student development.

Graduate Attribute 2.0 – Research, inquiry, and critical thinking

During the computer labs, students will learn how to clean and analyse data. They will investigate data coming from mock cases and learn how to extract relevant information from these cases and produce an intelligence product. In order to achieve this, the students will need to develop hypotheses, review existing knowledge and develop new understandings of crime phenomenon through the processes of research, inquiry and critical thinking. The development of inquiry-based learning is embedded in all tasks during the computer lab. Feedback will be provided to students formally (on assessment tasks 1 and 2) as well as informally during the computer labs.

Graduate Attribute 3.0 – Professional, ethical, and social responsibility

Students will refine their professional, collaborative and independent learning skills through the computer lab sessions where they will work on real cases (old cases) mimicking case work encountered in practice. Students will have access to software (Excel and Analyst’s Notebook) currently used in practice. Students will have an opportunity to refine generic skills such as time management, problem-solving and personal organisation, and they will also work collaboratively in their computer labs. The development of these professional skills will be monitored via feedback on assessable items and verbal feedback during classes.

Graduate Attribute 5.0 – Communication

Students will refine their communication skills both informally and via formal assessment. Students will strengthen their ability to convey the results of their analysis (i.e. links between cases/traces and trends) through visual aids (i.e. charts) and a report. Students will develop these skills in the computer labs and be assessed on this throughout the computer labs and through assessment tasks 1 and 2. Students will receive feedback on their development during the computer labs and through a chart/report benchmarking exercise using SparkPlus.

Teaching and learning strategies

Students will attend a series of lectures and computer labs, complemented by interactive online independent learning activities. Feedback on student’s progress will be available during the lectures, computer labs and online activities.

Lectures and classroom engagement

There will be 2 hours of lectures each week. It is recommended that you attend all lectures to develop a complete understanding of the content. The lectures provide the students with the theoretical knowledge required to understand the extended use of traces in an intelligence perspective. During the lectures, there will be opportunities for students to engage with the lecture content through scenario-based questions and reasoning tasks (through the use of Socrative) as well as classroom discussion. These activities will provide an enhanced study experience, where the students will be able to actively participate in the learning process. It is a valuable tool in learning about forensic intelligence as the questions give you the chance to practice key concepts which will appear on the final examination.

Computer Labs

This subject is practice-oriented since students will spend most of their time on exercises based on real cases. They will learn how to process data and cases to extract relevant features to be used in an intelligence perspective. A series of independent online activities before or after the computer labs will complement the computer lab activities. These online activities will include short questions on UTS Canvas, benchmarking activities and readings. Guidelines will be provided to the students on UTS Canvas. Students will be working individually and collaboratively during the computer labs. Active participation will be required as students will submit short reports/charts or give a presentation related to the activity conducted during the computer lab. Verbal and written feedback on progress and activities will be given during and after the computer lab activities (e.g. feedback as part of online activities, benchmarking, feedback on particular computer lab activities, etc.). Students will work both individually and as part of a team. They are thus expected to exercise considerable collaboration skills as well as independence, to ensure maximum learning benefit from the computer labs and their group. These two skills are highly sought by employers.

From week 2 to 7, students will work collaboratively on small tasks to familiarise themselves with the software (Excel and Analyst’s Notebook). These two software are used by law enforcement agencies, intelligence analysts and government agencies. As a consequence, being able to use them will increase the students’ chance of employability. In addition and most importantly, students will develop their critical thinking and inquiry-based skills as they will have to extract relevant features from cases, analyse the information and the links observed as well as communicate the results to audiences other than the Court.

From week 8 to week 10, students will work individually on real cases. They will extract a profile from a particular case, present that profile to their peers using Analyst’s Notebook and detect links between cases. During that time, students will be given two short reports to read. They will evaluate and critique these two reports by benchmarking them against a detailed marking rubric. They will use SparkPlus to provide written comments on the two reports. By grading these reports, students will become familiar with the assessment criteria that will be applied to their own intelligence report (Assessment Task 2).

During week 11 and 12, students will work collaboratively to compare their methods and come to a consensus regarding the best method. It will allow them to reflect on their methodology, encounter the strengths, weaknesses, benefits and problems associated with working as a member of a team.

Content (topics)

  • The trace and its use in forensic science
  • From trace to intelligence
  • How to use and organise forensic information
  • Forensic intelligence
  • Forensic intelligence research
  • Guest lectures from practitioners
  • Use of excel – data cleaning and visualisation
  • Use of Analyst’s Notebook – Series analysis and communication of in intelligence product

Assessment

Assessment task 1: Computer lab exercises

Intent:

This assessment task contributes to the development of the following graduate attributes:

1.0 Disciplinary knowledge

2.0 Research, inquiry, and critical thinking

3.0 Professional, ethical, and social responsibility

5.0 Communication

Objective(s):

This assessment task addresses subject learning objective(s):

3, 4, 5 and 6

This assessment task contributes to the development of course intended learning outcome(s):

1.3, 2.2, 3.3 and 5.2

Type: Exercises
Groupwork: Group, group assessed
Weight: 25%
Criteria:

Assessment will be based on the student’s technical, problem-solving and communication skills. Full marking criteria will be uploaded on UTS Canvas.

In week 5, one member of the group will hand in their excel file or word document with their answers. Assessment will be based on:

  1. Correct use of excel formula to clean the data and extract relevant information
  2. Correct visualisation to represent the trend
  3. Correct interpretation of the results
  4. Quality of visualisation

In week 7, one member of the group will hand in their chart in a powerpoint presentation with the correct answer. Assessment will be based on:

  1. Correct choice of entities and links
  2. Clarity of the chart
  3. Distinction between facts and hypotheses
  4. Correct answer to the problem
  5. Suitable representation (minimal line crossings, links should be at a perpendicular angle (when possible), colour should only be used if required)

Assessment task 2: Series analysis

Intent:

This assessment task contributes to the development of the following graduate attributes:

1.0 Disciplinary knowledge

2.0 Research, inquiry, and critical thinking

3.0 Professional, ethical, and social responsibility

5.0 Communication

Objective(s):

This assessment task addresses subject learning objective(s):

1, 2, 3, 4, 5 and 6

This assessment task contributes to the development of course intended learning outcome(s):

1.3, 2.2, 3.3 and 5.2

Type: Report
Groupwork: Individual
Weight: 45%
Length:

Part 1: week 8 to 12

Part 2: 2-3 pages

Criteria:

Full marking criteria will be uploaded on UTS Canvas.

Part 1: assessment will be based on:

  1. active involvement (attendance, completion of pre- and post-computer laboratory engaged learning activities and submission of results at the end of each workshop) during computer labs in week 8 to 12
  2. completion of pre and post-computer lab engaged learning activities (when required)

Part 2: assessment will be based on:

  1. Explanation of the methodology
  2. Ability to reason in light of the data provided
  3. Logical structure and organisation
  4. Explanation of the findings (number of cases in the series, number of people involved and anything significant that could provide any potential leads)
  5. Clarity of writing and use of appropriate language
  6. Communication of the intelligence product. In particular, the quality of the chart (minimal line crossings, links should be at a perpendicular angle (when possible))

Assessment task 3: Multiple choice and short answer quizzes

Intent:

This assessment task contributes to the development of the following graduate attributes:

1.0 Disciplinary knowledge

2.0 Research, inquiry, and critical thinking

Objective(s):

This assessment task addresses subject learning objective(s):

1, 2, 3 and 4

This assessment task contributes to the development of course intended learning outcome(s):

1.3 and 2.2

Type: Quiz/test
Groupwork: Individual
Weight: 30%
Length:

Each short answer questions will have a specific word limit, which will be given within the quiz.

Criteria:

Students will be assessed on:

  1. evidence of understanding of key concepts in forensic intelligence
  2. evidence of problem solving skills through the correctness of their response
  3. their ability to extract a profile from a trace/case
  4. their ability to discuss charts

Minimum requirements

Students are expected to attend all computer labs. Attendance is critical to achieve the subject learning outcomes for this subject.

Required texts

All readings and materials will be made available to students. There is no specific textbook.