AINV13004 - Learning From Failure

General Information

Unit Synopsis

This unit will provide students the opportunity to critically evaluate the potential for learning from failure to inform future mitigation of a specific accident type. Students are enabled to develop skills to inform key stakeholders through the creation of a communication plan so that the learning from accidents reaches the appropriate stakeholder audience.

Details

Level Undergraduate
Unit Level 3
Credit Points 6
Student Contribution Band SCA Band 2
Fraction of Full-Time Student Load 0.125
Pre-requisites or Co-requisites

Prereq: AINV13001 Accident Analysis and AINV12003 Accident Forensics and AINV12002 Accident Phenomenolgy and Coreq: AINV13002 Human Factors Investigation.

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 3 - 2024

There are no availabilities for this unit on or after Term 3 - 2024

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

This information will not be available until 8 weeks before term.
To see assessment details from an earlier availability, please search via a previous term.

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 2 - 2022 : The overall satisfaction for students in the last offering of this course was 100.00% (`Agree` and `Strongly Agree` responses), based on a 41.67% 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: Feedback during tutorials
Feedback
Some students are challenged by learning the new skill of manipulating large quantities of data
Recommendation
Continue to provide additional resources to support students in learning how to manipulate large quantities of data. These activities will guide students through the steps of their assessment tasks and reflect authentic work-based activities.
Action Taken
Resources were provided to students to assist in their activities required for this unit.
Source: Feedback during tutorials
Feedback
Students need to develop the skills of identifying and evaluating the source, integrity and quality of large data sets
Recommendation
Continue to provide activity-based tutorials that support students through the skills of identifying and evaluating the source, integrity and quality of large data sets. These activities will guide students through the steps of their assessment tasks and reflect authentic work-based activities.
Action Taken
Tutorials were offered as a group, however these were not supported by students. One on one sessions were provided to any student who wished to go through material.
Source: SUTE Comments
Feedback
Students commented on the lecturer and how well they had been supported in this final unit during the term. All gave glowing comments on the management of the teach out of units by Kevin Perry.
Recommendation
There are no recommendations as this was the final teaching of this unit.
Action Taken
In Progress
Unit learning Outcomes
This information will not be available until 8 weeks before term.
To see Learning Outcomes from an earlier availability, please search via a previous term.