This word has appeared in 255 articles on NYTimes.com in the past year. Can you use it in a sentence?
How Data Helps Build Succession Plans and Future Leadership Pipelines
Every organisation faces one truth, no matter how big or small the industry: people move on. Leaders resign, managers retire, and high performers are rewarded with promotions. If the organisation isn’t ready, this can cause catastrophic disruption and long-term negative impact to culture, reputation and productivity.
This is why succession planning isn’t just a “nice to have” – it’s a necessity. However, succession planning is only as strong and viable as the data supporting it.
In many businesses, succession planning is informal and heavily biased. Loyalty, tenure, and internal relationships are too often pivotal in choosing successors, while not necessarily qualifying a person as ready to step up or the correct choice of candidate. In today’s talent ecosystem, companies have more reliable ways of choosing leaders, and it is time for them to start using them.
They need to check their bias at the door.
They need to use psychometric data.
The Risk of Traditional Methods
Traditional succession methods often begin by asking who is next in line. However, it is important to consider a person’s skillset, potential and development needs before making these decisions.
Common mistakes include:
- Promoting people based on how long they have been in a company, instead of on how able or experienced they are.
- Promoting top performers at the job, who are individual contributors, into leadership roles with no management experience or aptitude.
- Allowing internal politics and relationships to sway decision-making.
- Blindness to the right competencies, traits, and skills in less vocal or visible performers,
- Hiring externally without consideration of the cultural impact on the organisation
Using Data to Determine Future Leaders
Planning succession should begin with a clear view of talent at your disposal. By using data-driven assessments, you can audit your current talent and skills holdings as you would stocktake your business’s storehouse.
Using this method, evaluate an employee’s skills, knowledge and growth areas across various departments in the workplace. From here, shortlisting candidates and adding context will enable smarter decision-making about who is really ready to lead, and who may need support.
Having the right tools will help you:
- Identify potential within your company
- Clearly see the high performers and high-potential candidates
- Curate and implement development plans specific to future leadership roles
- Be prepared for any sudden changes in leadership
Data collected will reveal much more than what a person has done; it assists in helping companies identify what they can do. This is crucial for building a pipeline of leaders who will be ready in the future.
Building Leadership Through Learning
Once a potential leader is identified, it becomes simpler to begin the process of training the person for the responsibilities that lie ahead.
However, one key thing to note is that training must always be targeted at their specific development areas and tailored to their learning needs. Leadership programmes that are generic or one-off workshops won’t deliver the anticipated results. Future leaders need developmental plans that will address them at their current level and take them to where they need to be for future roles.
With psychometric assessment data, HR and L&D teams will ensure that learning is done in accordance with the specific requirements of a leadership role in their unique organisation. This in turn ensures that every candidate who may be a possible fit for a future role is receiving adequate, focused development in line with the company’s growth trajectory.
And because this data is measurable, companies can track the readiness of their top performers over time, which will help them make better decisions about succession.
Don’t Overlook Communication: It’s a Vital Element
In every role, one key element that is essential in leadership is communication. With the rise of remote work and multicultural teams, it is even more important that leaders know how to communicate effectively. English is the common business language in many organisations and is vital for leaders to be able to lead meetings, draft reports, and collaborate with people externally to ensure the success of their business.
Alison’s English language test within the Psychometric Assessment Suite is a vital tool in this regard. It assists employers:
- To ensure communication standards are met
- Identify future leaders who may need extra assistance with language development
- Help prevent misunderstandings that may arise from improper communication
Even when a future leader is promoted from within the company, it is important that it is not assumed that the person is language-ready. Completing a simple test will identify leaders who are not only able to communicate effectively, but also uncover the path to get them where they need to be.
Removing the Barriers to Accessing Skills Data
Even though there are many benefits, HR and L&D teams still seem to lack access to good skills-based data. They rely heavily on feedback from managers, performance reviews that may be biased, and check-ins that don’t present a full picture.
This leads to leadership gaps, poor skills development planning, and hiring errors that prove to be rather costly.
At Alison, we believe that this shouldn’t be the case, so we’ve built an accessible way for organisations to access the data that can not only overhaul their workforce planning, but also their business’s ability to deliver future growth.
Alison is Changing Workforce Planning
Succession planning isn’t a guessing game. It should be well thought out, intentional and strategic. It should also, and most importantly, be a data-informed process that develops your team and secures the future of your organisation. It’s a toolkit that every business should take advantage of. It helps build the next generation of leaders in a fair and just way.
Many businesses don’t have access to this level of insight, but with Alison’s LMS+, you can reduce the risk of hiring mistakes.
This tool will help you uncover hidden potential and develop a leadership pipeline that’s built to last.
Find out how you can get started today with psychometric assessments in Alison’s LMS+, and take the first step toward a brighter, results-driven future.
Word of the Day: ebullient
This word has appeared in 102 articles on NYTimes.com in the past year. Can you use it in a sentence?
Synthesis plus content plus granular data – It’s all there for your learning
My name is Craig, and I’m working in a job that requires me to learn about Microsoft Word because I’ll use it often.
You know some things but not everything.
You might be interested in using AI, like Copilot, with Word or learning to use macros or VBA in Excel.
You can learn to create labels if the course includes that; great!
You should be able to jump directly to those sections without following a linear path.
Consider a scenario where executive assistants need to learn Outlook 365.
Some might be interested in creating email signatures, while others might focus on using AI tools for accuracy.
Tracking their interactions with the course content helps identify these preferences. For instance, if a learner is interested in creating email signatures, you can provide additional resources or exercises related to this topic, tailoring future training to their specific needs.
In essence, the ability to navigate freely within a course and the insights gained from tracking these interactions are far more valuable than simply knowing whether someone completed the course. It’s about the quality of the data, not just the quantity.
It’s about understanding and addressing each learner’s specific needs and interests.
I see a collective, so over the collective, let’s say it’s 30 people, and I see 27 of them going into whatever tool you have to streamline things.
There could be a table of contents within that tool, and now I’m drilling further down. OK, they’ve clicked into the tool, but where are they going in the tool?
Let’s say that’s the mini-module, and it’s 10 minutes long.
Even if it’s a video, some systems can benchmark and tell you, “OK, this person went here this many times,” or “This person went over here this many times.”
That gives you the insight you won’t get just by starting a course or doing a comprehension exam, because the comprehension exam covers everything, right?
It covers everything.
If I’m focused on returning to my label example, maybe there’s a question or not.
Then, I’m winging it based on my knowledge, which may or may not correlate. The idea that the assessment throughout the course will be relevant to someone may not be accurate.
Again, how good is it if I jump only to labels and you don’t include your assessment?
Does Retention deliver comprehension?
This gets back to retention. I can have a high retention rate on the day I take that quiz, but in two weeks, after I’ve got a bunch of stuff to do at work, my retention may go back to zero.
I often see this idea where vendors pitch their systems, saying, “You know, Company A and Company B, they all talk about how they’ve seen an increase in retention or comprehension.” And ergo, this is why the system is fantastic.
Ergo, this is why people take the content, go through it, and comprehend it.
Now, if it’s assigned learning, of course, they have to complete it.
So, wouldn’t you expect comprehension or what you think is retention? But if I can bounce around and don’t have to complete it, is that a good or bad thing?
That’s a good thing. It’s giving me relevant information, and I’m more interested in that aspect.
Let’s say you have a heat map.
Two of these five people have increased their response rate and leads from prospects to legitimate leads or demos over the last two quarters.
The sales director with L&D says, “Hey, look, by taking this content, they increased their leads; therefore, comprehension and retention occurred.”
How do you identify productivity? You can show a number in sales, but is it directly related? Let’s say that’s the data you’re presenting.
But what if you allow the person to bounce around?
You see, of these five people, three of them repeatedly hit something in follow-up and communication.
That should tell you this is the next piece of content you should create.
If you do it over six months, you want data showing points over time.
Initially, if I look at everybody, I can get an idea of what piece of content they go to first.
That tells me they have an interest there versus all the other modules.
Then you can create a table of contents and see where the items are going in that table of contents.
You want the granular data
I’m surprised how many people in L&D and training seem to ignore that granular data and look at the big picture.
The big picture doesn’t tell me much.
You’ve got to get into that granular data.
One of the most significant problems with today’s learning systems is that they have moved away from canned reports.
Canned reports or reports that have been pre-set up or defined by the vendor.
It may be the most popular reports or whatever they’ve offered back in the day.
This could get granular, and if you wanted something that the system doesn’t provide even today, you can contact the vendor and say, “Look, I need this specific report because they have that data. I need this specific report.”
It’s going to cost, so it isn’t free, but it may be relevant to you that the system doesn’t offer, but you want to stay with it.
If you’re looking at systems, ad hoc is OK; everybody does that. Do they offer canned reports, which would save you a lot of time?
If you have a table of contents and running time, and this is relevant to you, which it should be, and how many times, and you can’t do it in their ad hoc and they don’t have a canned report, you should be able to tell the vendor, “I want this report, and I want a custom report.”
A vendor should say yes if they have the data.
Now, if they say no, we do not offer custom reports (and realize they are fee-based to produce), then I’d seriously consider walking away—if you want those or that report.
Synthesis and Data- Where has it gone?
Content is all about synthesis, and we’ve moved away from that.
Systems have moved away from that, too.
If I can do that with my table of contents and add scenarios, why can’t I see the data around this scenario?
The scenario gives you a synthesis, applying what I’ve learned. I want to see that person come back often. You use it today and build on it tomorrow, focusing on skills and knowledge gaps you won’t get in a seminar. That’s why people stare into space until something interesting comes up.
It’s the same here. If you’re interested, you’ll learn and retain it. If you’re not, or you’re forced, you won’t retain it. You go in once, get knocked for not completing it, or enter several places. You need that granular data. Systems have mostly moved away from that.
Content and Objectives – It plays a role by having someone build up that synthesis
Let’s talk about creating a course. People use AI for content creation.
These tools put out massive descriptions, and then you have to go back into the prompt and say, “Reduce this to 25 words” or “Lose 10 words.” It should be right and to the point.
That’s what this description is.
You have objectives. Never say, “You will learn,” because that’s false. I may not learn it. It should be, “You should be able to…”
When you say, “You will,” I remember an example someone told me early on. Let’s say you’re playing golf and put in there, “You will learn how to get a hole-in-one.” If you don’t get a hole-in-one, then what?
I’ll learn it and get a hole-in-one. But if I never get a hole-in-one, is it my mistake or yours?
It’s not the Safety Dance, it’s Safety Training and Return to Build Synthesis
Think about safety training. “You will learn how to use a forklift.”
You’ll show me how, but how do you know I’ve learned it? Is it when it rolls over my feet? Safety training is highly relevant, and you need that granular data.
Did I start up the forklift and do this with it?
You may make it required, but you still want to know where they’re going, not just A-Z in five minutes. They’re not retaining that. You want them to go back more and more. If you’re saying, “Here’s how to use a forklift,” you want a table of contents. You want them to return even if you force them to complete it.
If they go in once, you assume they can drive a forklift. You’d know that from a general survey: “Do you know how to drive a forklift?” Yes or no. If no, and that’s the forklift you’re using, you can go back.
If they look at it for 30 seconds and move on, but they don’t know it, you can address that through their manager.
That’s relevant, not just completing the course and leaving.
It’s not your fault
Let’s say it’s not assigned, so people can go wherever they want.
Then you start noticing that people are just going in and leaving, and nobody’s coming back. That’s a huge issue.
The person overseeing L&D, training, HR, marketing, or sales often says, “Well, the problem isn’t me.
I can’t get these people back in, so it’s the system’s fault.” Or, “You bought third-party content, and nobody’s taking it, so it’s the system’s fault.”
Some systems include content they build and throw in regardless of quality.
They give it to you, and your learners take it, but don’t stick around or take all the courses.
Instead of looking at the content and thinking, “Maybe the content we got isn’t up to speed,” they complain to you and say it’s the system’s fault. Then, the company leaves and goes to another system.
How about this idea?
If I have third-party content that I’ve purchased and put into a system, typically, I get a bundle.
I would never get one course; vendors don’t like to do that. If I’ve got it in there, pick the ones you want, but look at them first. Don’t just say, “OK, I want this bundle,” and never pay attention.
Don’t rely on the vendor to say, “This is amazing third-party content.” That’s your job. Your job is to go in there and say, “Yeah, this is good,” or “Man, this is boring; I want something else.”
Even if it’s coming through a system and the system oversees it, the third-party content provider should say, “OK, let’s find good quality that works for you and your employees, customers, members, or whoever.” You want people to come back to take the content.
I’ve seen people say, “Oh, the learners hate my content and don’t go back into it.” Have you ever wondered why that is? Have you ever looked at it and said, “I need to go back in and look at this. Does it make sense? Can they understand what we’re trying to achieve?”
Do I have a table of contents? Does it provide enough engagement and interactivity beyond watching a video? Does it get my learners to think deeply, taking that information and applying it in real-life scenarios? AI can’t do deep thinking yet.
Is the content relevant to them? If it isn’t, and you can honestly say this doesn’t work, create new content.
Many systems come with templates, and third-party offering tools have templates, too. You can purchase content today, sometimes given as part of the system depending on the content provider, that enables you to edit the content and add your verbiage. The problem is, it’s just text.
You want relevant examples. You may do a little interactive thing. Some providers have it, and you can inquire about it without breaking the bank to get it.
I always say to people, if you want people to come back and take your content repeatedly, ask yourself, would you like to take this content? If your answer is no—being honest, mind you—then you should review and enhance it.
The Total Hours – How Relevant is that for your Synthesis and Data?
I do not like where it says, “This cumulative 25 hours that people or learners have gone through the system.”
Plenty of people focus on the relevance of completion and the number of hours, but you have to drill that down.
Synthesis with the content and data around the content, which goes granular, is the king.
Bottom Line
By reading this post, you should be able to
- Identify why synthesis is relevant to your learner.
- Explore how synthesis is practical using real-life scenario-based learning.
- Recognize that custom reports that present granular data relevant to your learning story are more important than total hours in a course.
- Understand that it isn’t the content’s fault for failure; it may be yours.
- Develop a strategy that ties synthesis to the content. This strategy can benefit your audience via canned reports or selective custom reports.
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Digest #180: Marking Rubrics in Education
Cover image by Tara Winstead from Pexels
By Carolina Kuepper-Tetzel
Marking rubrics for assessments can be a powerful tool to set marking expectations and criteria for an assessment and support students in understanding the feedback they receive. Rubrics are most effective if introduced to students from the start and integrated in activities focused on the assessment. I have been using rubrics for my marking for many years. I feel that they also help to keep marking more consistent when several markers are involved in marking the same assessment. For this digest, I have collated some resources that can facilitate the implementation of rubrics in your teaching.
1. Creating Effective Rubrics by Centre for Teaching and Learning, University of Alberta, Canada
In this short video, a short overview of rubrics is given. What are they? What should they entail? When and how to share them with students? And the research-informed benefits of using rubrics.
2. Assessment Rubrics by The University of Edinburgh, UK
In this resource different examples of holistic versus analytical rubrics are given with a particular focus on reflective assessments. Reflection pieces can be challenging to mark because of their emphasis on personal experiences. However, in this resource clear objective criteria are suggested that can facilitate the marking process.
3. Rubrics at the School of Psychology and Neuroscience by Carolina Kuepper-Tetzel, Courtney Taylor Browne Luka, & Rebecca Lai, University of Glasgow, UK
Concrete rubric templates for different assessments used in Psychology are provided in this resource. You will find rubrics for research reports (quantitative and qualitative), case studies, and essays. A self-assessment activity for students is linked for one of the research report rubrics. In addition, there are step-by-step instructions on how to use gen AI to co-create a rubric from scratch. In the final section of this resource there are instructions on how to implement rubrics into TurnItIn or Moodle.
“This Is a True Revolution”: Why Professor Daniel Acuna Believes Now is the Time to Learn AI
Daniel Acuna has always wanted to talk to computers. Long before large language models, before Python and GPUs, he was a curious student in Chile trying to build a chatbot, without formally knowing how to program. “I thought I could interact with the computer,” he says. “And somehow, I got it to respond to a few prompts. It gave me butterflies. It sounds cliché, but I’ve always wanted to talk to computers.”
That passion, along with years of academic and scientific training, has carried Acuna across disciplines and continents, and today he’s a faculty member in the University of Colorado Boulder’s new online Master of Science in Artificial Intelligence. From studying computer science as an undergrad to earning a PhD in the same field at the University of Minnesota and completing a postdoc in neuroscience, Acuna has spent his career trying to understand how humans and machines learn. His verdict: AI is no passing trend.
“I’ve been a witness to major AI advancements over the last 20 years,” he says. “But what’s happening right now is a true revolution. AI is becoming the base layer of our society, affecting life, work, and education, and we need to be prepared for that. We can’t escape it. We need to become a part of it.”
A Mission to Expand Access, With or Without Prior AI Experience
The CU Boulder online MS in Artificial Intelligence was designed with that revolution in mind. Acuna admits he was skeptical at first—“I was against the idea that people could get the same degree online as on campus”—but his views quickly changed.
“This technology is going to impact every field,” he says. “Restricting access to only people who live in Boulder, who can block a large chunk of their lives to study in a traditional program, is not enough. We need to be teaching people everywhere.”
The online format allows students from all walks of life and corners of the globe to gain advanced AI skills, and apply them to fields like healthcare, finance, education, and science. It also welcomes students without prior experience in machine learning.
“If you like numbers and quantitative work, this is a great course,” Acuna says. “You don’t need a background in AI or machine learning. We’ll assume you’re starting with the basics.”
When asked to define “the basics,” Acuna continued, “Critical thinking, curiosity, math–you cannot avoid math, linear algebra, calculus, and probability.” he chuckled. “It also helps to know how to think about ML, how to make a machine learn without explicitly telling it what to do, and you need to understand the importance of data and how to evaluate the performance of a machine once it learns.”
Teaching AI with Purpose and a Realistic Viewpoint
Acuna teaches CU Boulder’s Machine Learning Specialization, a foundational pathway in the MS in AI program, as well as the MS in Data Science and MS in Computer Science. His course is one of a few that make up the performance-based admissions that the MS in AI degree offers.
In his classes, students engage in a mix of traditional assessments, collaborative discussions, and hands-on projects. In his emphasis on understanding the fundamentals, he also noted the value of learning how to apply them across fields. Students are even encouraged to use AI tools in their assignments, just as they would in real-world scenarios.
“It’s going to be a fun course. People will learn a lot, and they’ll actually be able to apply it to their own fields and lives.”
But Acuna doesn’t sugarcoat the challenges of AI. He’s a realist about the rapid pace of change, the hype cycles, and the ethical complexity of the field.
“Things come and go in this field. I was very skeptical of neural networks at first. But the tools we have now—large language models, multi-modal AI—they’ve revolutionized what’s possible.”
Looking Ahead: AI in Education and Beyond
In the next 10 to 20 years, Acuna predicts, AI won’t just be a tool we use in niche areas—it will become a partner in how we learn.
“Very soon, we’re going to be using AI to help teach us. In my field of science, we will use it as an assistant or even a colleague. Human agents working alongside AI agents. It’s hard to stop this progress. There will be challenges, but we need to deal with them, speak up, and help shape this future.”
That’s exactly what he hopes students in the online MS in AI will do. His advice for anyone considering the program? Be open to failing, and keep learning through it.
“You’ll make mistakes. But then the next week, you won’t make them again. And that means something good is happening.”
Daniel Acuna’s passion for teaching was only met by his clear passion for learning, something he notes will be ongoing in the field of AI. His mission? Bring this knowledge of AI to as many people as possible while continuously learning to think about the future.
“Science is one of the most advanced things we do as humans, and we’re in a major technology shift. I hope to give a little bit of that perspective to my students.”
The Machine Learning Specialization provides an opportunity for learners to gain credits towards three online Master’s degrees from CU Boulder. These degrees include The Master of Science in Artificial Intelligence, The Master of Science in Data Science, and The Master of Science in Computer Science. The Specialization can also be applied as an elective credit to the Master of Science in Electrical Engineering and the Master of Engineering in Engineering Management. To learn more about these programs, performance-based admissions, and credit for prior learning, visit https://www.coursera.org/collections/boulder.
Using Assessments To Understand Skill Gaps and Anticipate Future Training Needs
Industries throughout the world are rapidly evolving and being reshaped by technology. Building skilled teams in today’s environment of remote work and globalisation presents unprecedented challenges.
Many HR and Learning & Development (L&D) professionals are still making decisions about hiring, upskilling, and performance, without access to the right data to guide them.
Too often, it’s a guessing game.
Psychometric Assessments are a powerful way to change this. This data-driven approach helps HR teams to measure what knowledge, competencies and traits are actually held by current and future employees -instead of just believing what their CVs or job titles suggest.
Assessments provide the insights that are needed for teams to make smarter decisions at every stage of employee development.
Skills Gaps Aren’t Always Evident
Employers may not be able to identify skills gaps. In fact, they often only become obvious when there are performance issues like missed project deadlines, poor quality outputs, communication breakdowns, or other
performance challenges. In many organisations, it becomes difficult to consistently produce results and execute on business strategy with these shortcomings.
However, the cost is even greater if skills gaps are ignored. According to a study by the SCIKEY job site, 70% of professionals have noted that skills gaps are one of the major contributors to poor productivity. It is important to ensure that people don’t just fill roles, they need to have the right capabilities to meet each job description.
The problem is that many HR and L&D teams don’t have access to the information that would help them identify these gaps.
Guesswork is Costly
With smaller teams, it is of paramount importance that every hire can carry out their duties efficiently. One ill-prepared employee could have a significant impact on the business as a whole. Errors with hiring don’t just cost the company time and money, they also affect the culture of the business and its relationship with its clients. Unfortunately, not all companies have a training budget, and not all can leave little room for trial and error.
That’s where assessments like those within Alison’s LMS+ Psychometric Suite come in.
Assessments measure the competencies, knowledge, aptitude and traits that people have, including their effectiveness in key areas like business acumen, technical capability, digital skills, and the maturity of critical soft skills such as communication.
For example, using assessments during the recruitment process means that employers can make better decisions in the hiring stages, as they don’t just rely on intuition or what the candidate is telling them, they’re backing up these answers with validated insights. The Department of Labour in the US estimates that a bad hire can cost a company 30% of an employee’s first-year earnings. (Source: HBK)
Psychometric Assessments Are a Smarter Way to Plan Training
L&D is most effective when it is specifically targeted, as opposed to being generic or ‘one-size fits all’. Training must be relevant to each individual based on their needs, current role, future potential career trajectory, and more. This will improve training effectiveness and ultimately, the organisation’s ROI, as skills gaps are identified early and can be managed properly over a schedule that aligns with the business’s needs and the learner’s work commitments.
Assessments make this possible by:
- Evaluating the skills throughout the organisation
- Identifying specific areas for upskilling or reskilling
- Automatically matching training content to the needs of employees
- Tracking progress and improvement over time, with reassessment
In other words, psychometric assessments give leaders the data they need to make informed decisions about upskilling, reskilling, and career development, ensuring that both individual aspirations and organisational objectives are met.
This proactive, personalised, data-driven approach is what differentiates strategic L&D and HR teams.
Changing the Game
Most HR and L&D teams don’t currently have access to resources like this. They spend time piecing together training plans with incomplete data and make hiring decisions with little verification
The good news is that the strategic L&D approach is no longer exclusively for those with vast budgets to procure enterprise-level tools . With psychometric assessments integrated into Alison’s LMS+, it’s now available to all.
For those that are stretched thin or just starting to formalise their learning strategy, LMS+ eliminates hours of manual admin, guesswork, and fragmented tools.
You don’t need to be a data analyst to understand and help your people; you just need the right platform. That platform is LMS+.
Alison is Making Data-Driven, Proactive L&D Accessible to All
With Alison’s assessments and LMS+, organisations big and small will now be able to operate with the kind of intelligence that was once only available to large corporations.
Alison’s English Language Test, though simple, is a powerful tool for aligning communication standards. For companies wanting to hire remote staff from around the world, infiltrating new markets, or managing multicultural teams, English proficiency is a definite must-have with both personal growth and organisational goals. Measure. Develop. Transform—with the Alison Assessment Suite.
LMS+ includes Aptitude Tests which cover three major areas: numerical reasoning, verbal reasoning and abstract reasoning. These focus areas were designed to ensure that a person’s skills are fully evaluated: problem solving, comprehension and analytical skills. You can screen job candidates or identify high-potential employees with Alison’s reliable, data-driven insights into existing skills and those that still need to be developed.
As a business leader, it is imperative that you understand how your employees work, the strengths they possess which you can utilise, and the weaknesses you need to support them to overcome. LMS+ has integrated Workplace Personality Assessments that make it easier to understand their behavioural traits, communication styles, and what motivates them to ensure your teams are always on top of their game. Identifying personality profiles will assist HR managers and team leaders to improve worker relationships, reduce conflict and help them find out how to manage each employee.
Bridge the Gaps
You can match individuals to personalised learning paths with the help of accurate assessment data from Alison. This will assist you in bridging skills gaps, improving performance and supporting each employee at the point of their need. Progress can be tracked in real-time, and reports are also generated to help improve skills.
With Alison’s LMS+, you’ll know exactly where your team stands, where they need to go, and how to help them get there.
Ready to transform your L&D function from reactive to proactive? Set up a quick demo to see how quickly you can adopt a data-led approach to training.
Word of the Day: aspirant
This word has appeared in 15 articles on NYTimes.com in the past year. Can you use it in a sentence?
How I Went from Civil Engineering to Front-End Engineer in 5 Months
Learning to code so that you can land a job in tech can feel daunting. That’s why we’re sharing inspiring stories from Codecademy’s community — to show how people like you (yes, you!) can embark on a learning journey and end up with a totally new career. We hope these stories serve as a reminder that there’s no single path to a more fulfilling work life.
Today’s story is from Mohamed El-Sharkawy, a 27-year-old with a bachelor’s degree in civil engineering turned Front-End Engineer living in Cairo, Egypt. Read more stories from Codecademy learners here — and be sure to share your story here.
Why I chose to learn to code
“I’ve always loved technology. I started working in tech at a young age, covering various fields, including a role as an IT help desk specialist, where I encountered clients who were looking to have websites built. At the time, my company was using drag-and-drop platforms to build these websites, but I wanted to learn how to create websites from scratch using coding.
Interestingly enough, I actually got my bachelor’s degree in civil engineering. Then after college, I did a year of military service. After that, I decided to switch to coding due to the challenging nature of civil engineering jobs and the impact software engineering can have. So, I started by taking front-end and full-stack courses with Codecademy.”
Learn something new for free
How I made time to learn
“Anyone who wants to do anything will find the time. I had to manage my time daily to ensure I made time to learn — and my structured routine in the military service definitely helped me. Each day, I dedicated an hour or two for learning. The hardest part was the economic pressure to find a job quickly, paired with the added challenge of interviews.”
Discover time management tricks from other learners who landed jobs!
How I saved up money to switch careers
“I started working at a young age so I had money saved to live on, which allowed me to invest in myself during my transition from military service to learning to code.”
How long it took me to land a job
“After my military service ended, I had a friend working at Banque Misr who referred me for a role as a Front-End Engineer. I went through the interview process which included a technical interview, a project submission, and an hour-long interview. It helped throughout this process that I had previously worked with Banque Misr as an intern. Once I received the offer, I made sure to do my research and compare it with average salary and employee experiences on websites like Glassdoor. I determined I was happy with the offer and ready to get to work. On my first day, I met the Scrum Master of my team, who introduced me to the rest of the team. We spent time talking about the Angular framework that was used at the bank. In total, it took me about five months to find the job.”
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What I wish I knew before I started learning
“I wished I knew the basics of software engineering, such as data structures and algorithms, before I started learning to code. Having this foundational knowledge would have helped me significantly.”
What advice I would give to others
- Just start: Don’t wait for the perfect time or environment; it may never come.
- Find a mentor: Have a friend or someone with the same career path to ask for help when needed.
- Appreciate your efforts: Be happy with any progress you make, even if it’s small.
- Make a plan: Create a roadmap to understand what to do next and stick to it.
- Trust in yourself: At first, my family disagreed with my decision to change careers. But, you need to trust in yourself. Now, all of us are happy with the decision I made.
Word of the Day: stultify
This word has appeared in two articles on NYTimes.com in the past year. Can you use it in a sentence?
