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人工智能如何指导课程设计和学习选择,以帮助毕业生找到他们想要的工作

16 人参与  2021年10月15日 15:01  分类 : 科学新闻  评论
by Tomas Trescak, The Conversation Credit: Shutterstock Graduates entering an ever-more-competitive job market are often unaware of the skills and values they offer employers

The challenge is greater with emerging job roles that require certifications and both multidisciplinary skills and specialist knowledge, even for entry-level positions

We seek to empower our graduates and maximize their career prospects

New research has enabled us to harness the power of artificial intelligence for a custom-designed course planning and recommendation system for students based on the skills their desired jobs actually require

We named these curriculum delivery models JobFit and ModuLearn

JobFit: A career-driven curriculum JobFit builds on a simple premise of informing students about the skills they will gain by completing a knowledge unit

This helps students to analyze skills gained from an individual study pathway and how these relate to career prospects

Students can explore and experiment with various pathways

This "what if?" analysis is tailored to their career goals and knowledge preferences

The system monitors their study progress and proactively offers alternative pathways to maximize their acquisition of skills related to their goals

We base the skills on recognized 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

Students can see their employability rating for various job roles based on the skills they acquire

Author provided, Author provided For example, performing a basic risk assessment in an organization requires "information security" skill at the lowest level

At the highest level it enables the person to design organizational and governmental policies assuring global information security

Governments and organizations 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 would like to play in the system

A password is not required

) Western Sydney University students can use it to explore their skill compatibility with ICT job roles

The chart above shows the compatibility with general role profiles, for Bachelor of ICT students considering junior-level positions

The video below shows the possibilities of this tool

This approach has several benefits

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 how to express these in CVs and cover letters are increasingly important

This is because human resource departments are adopting automated approaches to search for and filter out candidates, using algorithmic processing and text mining

The author explains how students can match the skills they acquire with the jobs they desire

We can use SFIA to express skills in technology-related areas

However, it does not apply to other areas such as engineering, human sciences, law or medicine

We are looking at acquiring data from an external partner to analyze and process required skills from live job offers across all industries

We will then be able to inform students on the quantity, variety and compatibility of actual job offers in any industry based on their knowledge profile

This approach will also benefit curriculum designers facing the challenges of new subjects being rapidly introduced to maintain an advantage over competitors

The result is often an incoherent curriculum, particularly when it comes to meeting industry and employer needs

A lack of understanding of what skills are desired in the job market and ad-hoc additions have led to programs that do not provide clear study pathways and relevance to work roles

Our model allows curriculum designers to analyze 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 target such custom skill sets are in a stronger position when applying for work with an industry partner

The system helps guide students in choosing units of study that provide skills to match their desired jobs

ModuLearn: Promoting cross-disciplinary skills Informing students on the skills they are acquiring is only half of the job

A student must also acquire all their desired skills in a relatively short period

In undergraduate degrees, much of the course is typically pre-defined with core subjects

Students are often left with only one or two semesters to focus their knowledge on particular employers' desired skill set

It's even more of problem in shorter courses such as diplomas or certificates

It's likely too that a student's faculty or school does not offer some critical skills

Students are often reluctant to study in a different school or faculty, fearing the challenge of a new environment

To overcome these issues, we looked at ways to increase the variety and number of knowledge units with diverse skills

We found inspiration in Charles Sturt University's Engineering Topic Tree

It allows students to customize their degree by choosing from over 1,000 different topics

Topics are organized by disciplines, with well-organized prerequisites and pathways

What this topic tree lacks is the backing of technology that allows students to easily explore all their options

We built on the topic tree idea and designed skill-informed modules

These are study units usually lasting two to eight weeks

Each module clearly defines the skills required as prerequisites and the skills it delivers

Charles Sturt University’s Topic Tree offers a dizzying array of choices, but artificial intelligence can help

Credit: Charles Sturt University 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 in this way to encourage students to study across disciplines

However, managing all the possible module combinations, prerequisites and user preferences is a significant technological challenge

This called for novel research, not just 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 both curriculum designers and students

Delivery models can be adapted to different public or private financing options and educational standards, such as the Australian Qualifications Framework (AQF)

Curriculum development tends to lag behind technology development and shifting market needs

Ideally, curriculum development should be more responsive and future-focused rather than reactive

With smaller modules instead of semester-long subjects, it is possible to adapt much more quickly to ever-changing job market needs

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