Using Data Science approaches to build Automated Job-role specific Skills Assessment to close the unemployment gap and handle applications surge post COVID-19 lockdown.

使用数据科学方法构建针对特定工作角色的自动化技能评估，以缩小失业差距并应对 COVID-19 封锁后申请激增的情况。

• 批准号: 59291
• 金额: $ 9.2万
• 依托单位: KNOWLEDGE OFFICER LTD
• 依托单位国家: 英国
• 项目类别: Feasibility Studies
• 财政年份: 2020
• 资助国家: 英国
• 起止时间: 2020 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=59291
• 关键词: Using; Data; Science; approaches; build

Knowledge Officer create personalised, dynamic e-learning paths to digital content for professionals based on their own career goals, to help them land jobs in tech-related roles. Our approach to career-oriented learning is based on real market-signals. At the core is skills and job titles taxonomy which provides a consistent way of helping users learn more about the skills they need and the value of those skills. We want our platform to reflect the exact and current market needs related to skills and requirements of the job roles of the highest demand. Based on this valuable data, our technology then recommends a personalised learning path, as unique to each learner as their own DNA, and also recommends job applications relevant to the career goal that they are after. Knowledge Officer aim to create the shortest and most efficient path to employment and career progression. Our e-learning platform technology builds a personalised learning path, helping the user to learn with a purpose to achieve their career goals. Understanding the true capabilities of people as they are going through learning through ongoing assessment is really essential to measure the impact of the learning experience. Pairing that with recommendations for jobs that one can apply to based on the specific job needs and one's capability is truly innovative.Our solution will measure the proficiency at the individual skill level grade and compare that with the skills needed for a certain job post of a given job role to measure the match score and the probability of someone's success on the job. Our scoring system will get smarter with more people going through assessments, applying to jobs, getting accepted/rejected and then measuring the duration they stay on the job as a true measure of the quality of the recommendation.This project will conduct challenging research to extend our technology so that given a job post, we will be able to generate an adaptive assessment on the fly based on the skills required of the post and generate a match/fit score after a job candidate finishes the assessment.A three month project extension will allow for more extensive testing activities to increase the impact and speed to market by further collaboration with potential partners, giving access to technical, design and business expertise. Beta testing with early adopters will ensure the product will have the maximum impact at launch.

Knowledge Officer根据专业人士的职业目标，为他们创建个性化、动态的电子学习路径，以获取数字内容，帮助他们在技术相关岗位上找到工作。我们以职业为导向的学习方法是基于真实的市场信号。核心是技能和职位分类，它提供了一种一致的方式来帮助用户更多地了解他们需要的技能和这些技能的价值。我们希望我们的平台能够准确反映当前市场对相关技能和工作角色要求的最高要求。基于这些有价值的数据，我们的技术会推荐个性化的学习路径，就像每个学习者的DNA一样独特，还会推荐与他们追求的职业目标相关的工作申请。知识官旨在为就业和职业发展创造最短、最有效的途径。我们的电子学习平台技术建立了个性化的学习路径，帮助用户有目的地学习，以实现他们的职业目标。了解人们在学习过程中的真实能力通过持续的评估对衡量学习体验的影响至关重要。将其与基于特定工作需求和个人能力的工作推荐相结合，这才是真正的创新。我们的解决方案将测量个人技能水平等级的熟练程度，并将其与给定工作角色的特定工作岗位所需的技能进行比较，以测量匹配分数和某人在工作中成功的概率。随着越来越多的人通过评估、申请工作、被接受/被拒绝，然后衡量他们在工作上的持续时间，我们的评分系统将变得更加智能，这是对推荐质量的真实衡量。该项目将进行具有挑战性的研究，以扩展我们的技术，使我们能够根据职位所需的技能动态生成适应性评估，并在求职者完成评估后生成匹配/适合分数。为期三个月的项目延期将允许开展更广泛的测试活动，通过与潜在合作伙伴的进一步合作，获得技术、设计和业务专业知识，从而提高影响和上市速度。与早期用户进行Beta测试将确保产品在发布时产生最大的影响。