65313 Forensic Intelligence
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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. |
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| 2. | Discuss the extended use of forensic traces to provide knowledge about crime and deviant activities. |
| 3. | Extract information from a trace or a case, compare it to other traces or cases and analyse the information |
| 4. | Use general software (Excel) and specialist software (I2 Analyst’s Notebook) to analyse and visualise forensic case data. |
| 5. | 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:
- Demonstrate a command of forensic science practice, including the detection, collection, and analysis of traces in order to exploit and integrate the results of analyses into investigative, evaluative and intelligence frameworks. (1.1)
- Apply investigative, critical thinking and problem-solving skills to forensic science problems and design experimental methods to test hypotheses and critically analyse and interpret data. (2.1)
- Practise safe, ethical, and professional conduct with consideration for the role of forensic science in addressing current and future challenges faced by law enforcement, the legal system, security, and the wider community. (3.1)
- Demonstrate skills in communicating experimental conclusions, expert opinion, and the justification of professional decisions related to forensic science processes effectively to expert, scientific, and non-expert audiences. (5.1)
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. The assessed lectures will be recorded. There will also be a series of guest lectures from industry. These lectures will not be recorded for confidentiality reasons but they will give an overview of future job opportunities and the possibility to ask questions. These lectures will not be assessed.
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.
During computer labs 1-6, 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.
During computer labs 7-9, 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).
Finally, during the last computer labs, 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. They will also develop their competencies in detecting and analysing series within large datasets using spreadsheets.
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 |
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| Objective(s): | This assessment task addresses subject learning objective(s): 1, 3, 4 and 5 This assessment task contributes to the development of course intended learning outcome(s): 1.1, 2.1, 3.1 and 5.1 |
| 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 computer lab 4, one member of the group will hand in their excel file or word document with their answers. Assessment will be based on:
In computer lab 6, one member of the group will hand in their chart in a powerpoint presentation with the correct answer. Assessment will be based on:
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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 |
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| Objective(s): | This assessment task addresses subject learning objective(s): , 1, 2, 3, 4 and 5 This assessment task contributes to the development of course intended learning outcome(s): 1.1, 2.1, 3.1 and 5.1 |
| Type: | Report |
| Groupwork: | Individual |
| Weight: | 45% |
| Length: | Part 1: week 7 to 12 Part 2: 2-3 pages |
| Criteria: | Full marking criteria will be uploaded on UTS Canvas. Part 1: assessment will be based on:
Part 2: assessment will be based on:
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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 |
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| Objective(s): | This assessment task addresses subject learning objective(s): 2, 3 and 5 This assessment task contributes to the development of course intended learning outcome(s): 1.1 and 2.1 |
| 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:
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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.