Work Readiness Scale (WRS): An online assessment for work readiness in career education

The School of Psychology at Deakin University, in collaboration with DeakinTALENT and the FreelancingHUB, under the leadership of Professor Dineli Mather, Pro Vice-Chancellor (Graduate Employment) has been undertaking a Work Readiness Scale (WRS) project. This project establishes an online assessment of the work readiness of an individual, that is integrated into career education and work integrated learning initiatives. The individual completes an online questionnaire and receives a comprehensive summary report, providing advice and assistance on career development, tailored for the individual on the basis of their responses. The project team had the work readiness survey and metrics but required a means of rapid, automated analysis to generate and send the tailored reports.

Dr Andrew Goh, an eResearch Analyst (eRA) at Deakin University, was instrumental in the design and implementation of the automation process. Using his experience in designing project workflows and technical Python and Unix skills, he was able to solve the challenge, resulting in the automated preparation and delivery of thousands of summary reports for individuals who had completed the questionnaires.

The survey questionnaire was designed on the Qualtrics platform, utilising the expertise of Dr Jerry Lai, another Intersect eRA based at Deakin University. The responses from the completed questionnaire are automatically  analysed by a Python script written by Andrew to download the data, process the responses, and generate the summary reports in PDF format. The analysis undertaken by the script takes into account the individual responses in order to generate customised evaluations for inclusion in the reports. Another Python script was developed to handle the process of distributing the reports to the respective respondents. All the scripts and reports are stored securely in the Deakin University research data storage (RDS) server and a Unix cron job was configured on  the server to trigger regular examination of the platform for new responses requiring analysis and report generation, ensuring there is no manual task involved in the entire assessment.

The survey questionnaire was designed on the Qualtrics platform, utilising the expertise of Dr Jerry Lai, another Intersect eRA based at Deakin University. The responses from the completed questionnaire are automatically analysed by a Python script written by Andrew to download the data, process the responses, and generate the summary reports in PDF format. The analysis undertaken by the script takes into account the individual responses in order to generate customised evaluations for inclusion in the reports. Another Python script was developed to handle the process of distributing the reports to the respective respondents. All the scripts and reports are stored securely in the Deakin University research data storage (RDS) server and a Unix cron job was configured on  the server to trigger regular examination of the platform for new responses requiring analysis and report generation, ensuring there is no manual task involved in the entire assessment.

This project had been implemented for Deakin University students to evaluate their work readiness level. So far, thousands of students in the Autumn and Spring sessions have been participating in the survey. The majority of respondents were from the Faculty of Health and some had just completed the internship program under Deakin FreelancingHub. In 2022, the WRS team plans to introduce this WRS survey into career education, where it is thought that there will be more students taking the survey. Without the automation, it is impossible to meet the high demand of the WRS reports. With the automation, thousands of reports can be generated in a day and respondents can receive the summary reports within half an hour of completing the survey.

The WRS team is planning to improve user experience and engage a wider community by creating a website for anyone who is interested in the WRS survey to register and enrol in the survey. Andrew will be involved in this enhancement to ensure effective interaction between the automated scripts and the project website.