In light of the Covid-19 pandemic practical training sessions have been limited by travel bans, distancing requirements and other government restrictions, limiting the practical experience firefighters have been able to gather. For that very reason, training providers including RelyOn Nutec have invested in alternative methods to ensure that critical competences are kept up to date at all times.
For years, e-learning has been a go-to tool for companies and organisations that need an efficient way to educate or update competences for their workforce. However, traditional e-learning is in itself not harvesting the true power of learning on a digital platform. It assumes that all learners have the same level of knowledge and understanding and therefore the learner must follow the whole course to be successful, going through tedious time-consuming assessments.
Adaptive learning is a technology-enabled approach to learning. It combines theories of optimal learning with the capabilities of algorithms and computing power. The study material simply adapts to the learner, ensuring that time is spent on the subjects that need the most attention. This significantly boosts the efficiency of the learning process as well as learners’ motivation. In essence someone who already has knowledge on the subject will go through the training much quicker compared to a conventional e-learning format. Conversely a learner who has very little knowledge will be taken on a different and longer path to gain competence on that subject. This process ensures that every learner will achieve 100% proficiency on the topic at the end of the course while at the same time, the process reveals blind spots, perhaps unknown for the learner, that can be addressed either on the job or in connection with practical training.
How does this work?
RelyOn Nutec has entered into a partnership with Area9 Lyceum to bring adaptive learning technology to the energy sector. Area9 Lyceum’s platform Rhapsode is considered the most advanced learning platform in the world. Its transformative, personalised, high-impact learning experience is built on 25 years of research and has proven its value particularly across the healthcare and workforce education sectors. It relies on well-established concepts in educational psychology and cognitive science – augmented by usage and data points from real learners using the platform. The aim is to cut training time, increase knowledge, confidence and skills acquisition, and boost learning retention. This increases workforce competence with an overall ambition to facilitate further reduction of serious incidents and reduce risk of errors across the energy sector protecting people, assets and the environment.
The platform uses probing questions specifically designed to test the learner’s prior knowledge. The way the learner answers the questions determines how the adaptive engine adjusts in real time to take the learner on the most efficient path to ensure mastery of the subject material. This generates a one-on-one personal experience for the learner, giving a positive, engaging and balanced interaction that is neither too easy nor too difficult for the learner, as well as instant feedback.
For example, learners may be asked what is required to create a fire. You can choose up front that you are a novice and new to the subject, an expert with a good knowledge or somewhere in between. The ‘Fire Triangle’ is a basic level of knowledge or for a more expert view point the ‘Fire Tetrahedron’ is more relevant. The system tracks your answers. Once you have selected your answer, you must confirm the answer by indicating your confidence level on your answer such as ‘I know’, ‘I think I know’, ‘I am unsure’ or ‘I have no idea’. The learner can at any time select a full interactive explanation of the lesson material before attempting to answer
the question.
The system makes the learner self-aware, creating consciousness of what they do not know rather than being unconscious of potential knowledge
which may lead to incidents. The system can be used on a regular basis; each time there will be a different path selected depending on their knowledge and the competency levels required. As such this system is not just an opportunity to improve on e-learning but can be used to safeguard competences across a company at all times. Rather than refreshing a course every two, four or five years, you will be able to track the competences at all times and react when data shows that gaps are starting to form. The learner and the employer get feedback on the competency on the subject.
and weaknesses.
The importance of acting without thinking
Automaticity is the ability to do things without occupying the mind with the low-level details required, becoming an automatic response pattern or habit. It is usually the result of learning, repetition and practice. When faced with stress, the human brain falls back on things that are ‘second nature’. Those fallbacks must generate the correct response. We do not need to achieve automaticity in every skill or piece of knowledge. However, automaticity is a requirement in areas such as core skills and safety-critical behaviour. Adaptive learning helps the learners achieve automaticity by facilitating the practice and re-practice on the specific topics that are relevant.
Actionable data insights
One of the significant strengths of the adaptive learning platform is the highly granular data collected by the system. This data provides actionable insights for learners, instructors, content developers and employers. All information regarding the learner’s performance can be analysed and visualised, helping the learner identify their strengths and where extra coaching is needed. For learners, access to their learning performance data is a huge step forward from simple, limited information like a single completion figure or even information on which questions were incorrect. With learning analytics, learners can gain insights that can guide their learning. They can see which sections they struggled with, where they struggled to self-assess their knowledge, and what content they should review to improve. Instructors can get a much broader and more granular review of their learners’ performance, not just a simple matter of questions right and wrong, such as whether learners understand their lack of knowledge, whether they are motivated and engaged, and whether certain sections are particularly problematic. Data analytics is also used to gain insights into the course content itself. It allows continuous and iterative improvements based on learners’ feedback and data usage at a very granular level. This ensures a systematic approach to the quality of the content. New topics within the subject material can be easily added to ensure that the learner remains up to date with developments.
Adaptive learning is an excellent means to keep your workforce up to date and competent in an engaging way. Over the coming months we will build and roll out a foundational programme to cover all critical competencies and skills for industrial firefighters using this approach. This will include modules such as foam application, rescue, cooling, gas dispersion and many others.
The system including the first fully developed module will be available for demonstration at the coming Intersec exhibition in Dubai, 16–18 January 2022.
For more information, go to www.relyonnutec.com
Steve Watkins
