Graduates entering an ever-more-competitive job market are sometimes unaware of the abilities and values they provide employers. The challenge is larger with emerging job roles that require certifications and each multidisciplinary skills and specialist knowledge, even for entry-level positions.

We seek to empower our graduates and maximise their profession prospects. New research has enabled us to harness the facility of artificial intelligence for a custom-designed course planning and advice system for college kids based on the abilities their desired jobs actually require. We named these curriculum delivery models JobFit and ModuLearn.

JobFit: a career-driven curriculum

JobFit builds on an easy premise of informing students concerning the skills they may gain by completing a knowledge unit. This helps students to analyse skills gained from a person study pathway and the way these relate to profession prospects.

Students can explore and experiment with various pathways. This “what if?” evaluation is tailored to their profession goals and knowledge preferences. The system monitors their study progress and proactively offers alternative pathways to maximise their acquisition of skills related to their goals.

We base the abilities on recognised frameworks. For science, technology and business, we use the Skills for Information Age (SFIA) framework version 8, defining 121 skills, each on seven different levels.

For example, performing a basic risk assessment in an organisation requires “information security” skill at the bottom level. At the very best level it enables the person to design organisational and governmental policies assuring global information security.

Governments and organisations in Australia, United States, United Kingdom and European Union have created datasets using SFIA skills to define desired job profiles.

Drawing on these datasets, we designed a prototypical course-planning tool. (To login, please provide your email and role you desire to to play within the system. A password isn’t required.) Western Sydney University students can use it to explore their skill compatibility with ICT job roles.

Students can see their employability rating for various job roles based on the abilities they acquire.
Author provided, Author provided

The chart above shows the compatibility with general role profiles, for Bachelor of ICT students considering junior-level positions. The video below shows the chances of this tool.

The writer explains how students can match the abilities they acquire with the roles they desire.

This approach has several advantages. First, students understand how their studies develop their skills. They can then set career-driven goals and make well-informed decisions about their study pathways.

Solid understanding of skills and knowing find out how to express these in CVs and canopy letters are increasingly necessary. This is because human resource departments are adopting automated approaches to look for and filter out candidates, using algorithmic processing and text mining.

We can use SFIA to precise skills in technology-related areas. However, it doesn’t apply to other areas comparable to engineering, human sciences, law or medicine.

We are taking a look at acquiring data from an external partner to analyse and process required skills from live job offers across all industries. We will then have the option to tell students on the amount, variety and compatibility of actual job offers in any industry based on their knowledge profile.

This approach can even profit curriculum designers facing the challenges of recent subjects being rapidly introduced to take care of a bonus over competitors. The result is usually an incoherent curriculum, particularly with regards to meeting industry and employer needs.

A lack of information of what skills are desired within the job market and ad-hoc additions have led to programs that don’t provide clear study pathways and relevance to work roles. Our model allows curriculum designers to analyse and validate their curriculum against job market needs.

Last, working with industry partners, we defined custom job profiles for the industry area of interest and locality. Students who goal such custom skill sets are in a stronger position when applying for work with an industry partner.

screen shot of the curriculum design system that students can use to ensure their skills are compatible with their desired jobs
The system helps guide students in selecting units of study that provide skills to match their desired jobs.

ModuLearn: promoting cross-disciplinary skills

Informing students on the abilities they’re acquiring is simply half of the job. A student must also acquire all their desired skills in a comparatively short period.

In undergraduate degrees, much of the course is usually pre-defined with core subjects. Students are sometimes left with just one or two semesters to focus their knowledge on particular employers’ desired skill set. It’s much more of problem in shorter courses comparable to diplomas or certificates.

It’s likely too that a student’s faculty or school doesn’t offer some critical skills. Students are sometimes reluctant to check in a special school or faculty, fearing the challenge of a brand new environment.

Charles Sturt University's Topic Tree
Charles Sturt University’s Topic Tree offers a dizzying array of decisions, but artificial intelligence may also help.
Charles Sturt University

To overcome these issues, we checked out ways to extend the range and number of data units with diverse skills. We found inspiration in Charles Sturt University’s Engineering Topic Tree. It allows students to customize their degree by selecting from over 1,000 different topics. Topics are organised by disciplines, with well-organised prerequisites and pathways.

What this topic tree lacks is the backing of technology that enables students to simply explore all their options. We built on the subject tree idea and designed skill-informed modules. These are study units normally lasting two to eight weeks. Each module clearly defines the abilities required as prerequisites and the abilities it delivers.

An intertwined network of modules delivers fundamental and applied knowledge but each module requires less of a commitment from students than semester-long subjects. We hope on this option to encourage students to check across disciplines.

However, managing all of the possible module mixtures, prerequisites and user preferences is a big technological challenge. This called for novel research, not only an application of existing AI approaches.

Working with the Artificial Intelligence Research Institute (IIIA) in Barcelona, we developed technological means to design and maintain a module-based curriculum for each curriculum designers and students. Delivery models might be adapted to different public or private financing options and academic standards, comparable to the Australian Qualifications Framework (AQF).

Curriculum development tends to lag behind technology development and shifting market needs. Ideally, curriculum development needs to be more responsive and future-focused relatively than reactive. With smaller modules as a substitute of semester-long subjects, it is feasible to adapt rather more quickly to ever-changing job market needs.

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