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Vibe Coding: Shaping the Future of Software

A New Era of Code Vibe coding is a new method of using natural language prompts and AI tools to generate code. I have seen firsthand that this change Discover how vibe coding is reshaping software development. Learn about its benefits, challenges, and what it means for developers in the AI era.
Author
Vishwastam Shukla
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July 2, 2025
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3 min read

A New Era of Code

Vibe coding is a new method of using natural language prompts and AI tools to generate code. I have seen firsthand that this change makes software more accessible to everyone. In the past, being able to produce functional code was a strong advantage for developers. Today, when code is produced quickly through AI, the true value lies in designing, refining, and optimizing systems. Our role now goes beyond writing code; we must also ensure that our systems remain efficient and reliable.

From Machine Language to Natural Language

I recall the early days when every line of code was written manually. We progressed from machine language to high-level programming, and now we are beginning to interact with our tools using natural language. This development does not only increase speed but also changes how we approach problem solving. Product managers can now create working demos in hours instead of weeks, and founders have a clearer way of pitching their ideas with functional prototypes. It is important for us to rethink our role as developers and focus on architecture and system design rather than simply on typing c

The Promise and the Pitfalls

I have experienced both sides of vibe coding. In cases where the goal was to build a quick prototype or a simple internal tool, AI-generated code provided impressive results. Teams have been able to test new ideas and validate concepts much faster. However, when it comes to more complex systems that require careful planning and attention to detail, the output from AI can be problematic. I have seen situations where AI produces large volumes of code that become difficult to manage without significant human intervention.

AI-powered coding tools like GitHub Copilot and AWS’s Q Developer have demonstrated significant productivity gains. For instance, at the National Australia Bank, it’s reported that half of the production code is generated by Q Developer, allowing developers to focus on higher-level problem-solving . Similarly, platforms like Lovable enable non-coders to build viable tech businesses using natural language prompts, contributing to a shift where AI-generated code reduces the need for large engineering teams. However, there are challenges. AI-generated code can sometimes be verbose or lack the architectural discipline required for complex systems. While AI can rapidly produce prototypes or simple utilities, building large-scale systems still necessitates experienced engineers to refine and optimize the code.​

The Economic Impact

The democratization of code generation is altering the economic landscape of software development. As AI tools become more prevalent, the value of average coding skills may diminish, potentially affecting salaries for entry-level positions. Conversely, developers who excel in system design, architecture, and optimization are likely to see increased demand and compensation.​
Seizing the Opportunity

Vibe coding is most beneficial in areas such as rapid prototyping and building simple applications or internal tools. It frees up valuable time that we can then invest in higher-level tasks such as system architecture, security, and user experience. When used in the right context, AI becomes a helpful partner that accelerates the development process without replacing the need for skilled engineers.

This is revolutionizing our craft, much like the shift from machine language to assembly to high-level languages did in the past. AI can churn out code at lightning speed, but remember, “Any fool can write code that a computer can understand. Good programmers write code that humans can understand.” Use AI for rapid prototyping, but it’s your expertise that transforms raw output into robust, scalable software. By honing our skills in design and architecture, we ensure our work remains impactful and enduring. Let’s continue to learn, adapt, and build software that stands the test of time.​

Ready to streamline your recruitment process? Get a free demo to explore cutting-edge solutions and resources for your hiring needs.

How Candidates Use Technology to Cheat in Online Technical Assessments

Discover common technologies used by candidates for cheating in online assessments. Explore effective prevention methods like proctoring, AI monitoring, and smart test formats.
Author
Nischal V Chadaga
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July 2, 2025
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3 min read

Impact of Online Assessments in Technical Hiring


In a digitally-native hiring landscape, online assessments have proven to be both a boon and a bane for recruiters and employers.

The ease and efficiency of virtual interviews, take home programming tests and remote coding challenges is transformative. Around 82% of companies use pre-employment assessments as reliable indicators of a candidate's skills and potential.

Online skill assessment tests have been proven to streamline technical hiring and enable recruiters to significantly reduce the time and cost to identify and hire top talent.

In the realm of online assessments, remote assessments have transformed the hiring landscape, boosting the speed and efficiency of screening and evaluating talent. On the flip side, candidates have learned how to use creative methods and AI tools to cheat in tests.

As it turns out, technology that makes hiring easier for recruiters and managers - is also their Achilles' heel.

Cheating in Online Assessments is a High Stakes Problem



With the proliferation of AI in recruitment, the conversation around cheating has come to the forefront, putting recruiters and hiring managers in a bit of a flux.



According to research, nearly 30 to 50 percent of candidates cheat in online assessments for entry level jobs. Even 10% of senior candidates have been reportedly caught cheating.

The problem becomes twofold - if finding the right talent can be a competitive advantage, the consequences of hiring the wrong one can be equally damaging and counter-productive.

As per Forbes, a wrong hire can cost a company around 30% of an employee's salary - not to mention, loss of precious productive hours and morale disruption.

The question that arises is - "Can organizations continue to leverage AI-driven tools for online assessments without compromising on the integrity of their hiring process? "

This article will discuss the common methods candidates use to outsmart online assessments. We will also dive deep into actionable steps that you can take to prevent cheating while delivering a positive candidate experience.

Common Cheating Tactics and How You Can Combat Them


  1. Using ChatGPT and other AI tools to write code

    Copy-pasting code using AI-based platforms and online code generators is one of common cheat codes in candidates' books. For tackling technical assessments, candidates conveniently use readily available tools like ChatGPT and GitHub. Using these tools, candidates can easily generate solutions to solve common programming challenges such as:
    • Debugging code
    • Optimizing existing code
    • Writing problem-specific code from scratch
    Ways to prevent it
    • Enable full-screen mode
    • Disable copy-and-paste functionality
    • Restrict tab switching outside of code editors
    • Use AI to detect code that has been copied and pasted
  2. Enlist external help to complete the assessment


    Candidates often seek out someone else to take the assessment on their behalf. In many cases, they also use screen sharing and remote collaboration tools for real-time assistance.

    In extreme cases, some candidates might have an off-camera individual present in the same environment for help.

    Ways to prevent it
    • Verify a candidate using video authentication
    • Restrict test access from specific IP addresses
    • Use online proctoring by taking snapshots of the candidate periodically
    • Use a 360 degree environment scan to ensure no unauthorized individual is present
  3. Using multiple devices at the same time


    Candidates attempting to cheat often rely on secondary devices such as a computer, tablet, notebook or a mobile phone hidden from the line of sight of their webcam.

    By using multiple devices, candidates can look up information, search for solutions or simply augment their answers.

    Ways to prevent it
    • Track mouse exit count to detect irregularities
    • Detect when a new device or peripheral is connected
    • Use network monitoring and scanning to detect any smart devices in proximity
    • Conduct a virtual whiteboard interview to monitor movements and gestures
  4. Using remote desktop software and virtual machines


    Tech-savvy candidates go to great lengths to cheat. Using virtual machines, candidates can search for answers using a secondary OS while their primary OS is being monitored.

    Remote desktop software is another cheating technique which lets candidates give access to a third-person, allowing them to control their device.

    With remote desktops, candidates can screen share the test window and use external help.

    Ways to prevent it
    • Restrict access to virtual machines
    • AI-based proctoring for identifying malicious keystrokes
    • Use smart browsers to block candidates from using VMs

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Talent Acquisition Strategies For Rehiring Former Employees

Discover effective talent acquisition strategies for rehiring former employees. Learn how to attract, evaluate, and retain top boomerang talent to strengthen your workforce.
Author
Nischal V Chadaga
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July 2, 2025
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3 min read
Former employees who return to work with the same organisation are essential assets. In talent acquisition, such employees are also termed as ‘Boomerang employees’. Former employees are valuable because they require the least training and onboarding because of their familiarity with the organization’s policies. Rehiring former employees by offering them more perks is a mark of a successful hiring process. This article will elaborate on the talent acquisition strategies for rehiring former employees, supported by a few real-life examples and best practices.

Why Should Organizations Consider Rehiring?

One of the best ways of ensuring quality hire with a low candidate turnover is to deploy employee retention programs like rehiring female professionals who wish to return to work after a career break. This gives former employees a chance to prove their expertise while ensuring them the organization’s faith in their skills and abilities. Besides, seeing former employees return to their old organizations encourages newly appointed employees to be more productive and contribute to the overall success of the organization they are working for. A few other benefits of rehiring old employees are listed below.

Reduced Hiring Costs

Hiring new talent incurs a few additional costs. For example, tasks such as sourcing resumes of potential candidates, reaching out to them, conducting interviews and screenings costs money to the HR department. Hiring former employees cuts down these costs and aids a seamless transition process for them.

Faster Onboarding

Since boomerang employees are well acquainted with the company’s onboarding process, they don’t have to undergo the entire exercise. A quick, one-day session informing them of any recent changes in the company’s work policies is sufficient to onboard them.

Retention of Knowledge

As a former employee, rehired executives have knowledge of the previous workflows and insights from working on former projects. This can be valuable in optimizing a current project. They bring immense knowledge and experience with them which can be instrumental in driving new projects to success.Starbucks is a prime example of a company that has successfully leveraged boomerang employees. Howard Schultz, the company's CEO, left in 2000 but returned in 2008 during a critical time for the firm. His leadership was instrumental in revitalizing the brand amid financial challenges.

Best Practices for Rehiring Former Employees

Implementing best practices is the safest way to go about any operation. Hiring former employees can be a daunting task especially if it involves someone who was fired previously. It is important to draft certain policies around rehiring former employees. Here are a few of them that can help you to get started.

1. Create a Clear Rehire Policy

While considering rehiring a former employee, it is essential to go through data indicating the reason why they had to leave in the first place. Any offer being offered must supersede their previous offer while marking clear boundaries to maintain work ethics. Offer a fair compensation that justifies their skills and abilities which can be major contributors to the success of the organization. A well-defined policy not only streamlines the rehiring process but also promotes fairness within the organization.

2. Conduct Thorough Exit Interviews

Exit interviews provide valuable insights into why employees leave and can help maintain relationships for potential future rehires. Key aspects to cover include:
  • Reasons for departure.
  • Conditions under which they might consider returning.
  • Feedback on organizational practices.
Keeping lines of communication open during these discussions can foster goodwill and encourage former employees to consider returning when the time is right.

3. Maintain Connections with Alumni

Creating and maintaining an alumni association must be an integral part of HR strategies. This exercise ensures that the HR department can find former employees in times of dire need and indicates to former employees how the organization is vested in their lives even after they have left them. This gesture fosters a feeling of goodwill and gratitude among former hires. Alumni networks and social media groups help former employees stay in touch with each other, thus improving their interpersonal communication.Research indicates that about 15% of rehired employees return because they maintained connections with their former employers.

4. Assess Current Needs Before Reaching Out

Before reaching out to former employees, assess all viable options and list out the reasons why rehiring is inevitable. Consider:
  • Changes in job responsibilities since their departure.
  • Skills or experiences gained by other team members during their absence.
It is essential to understand how the presence of a boomerang employee can be instrumental in solving professional crises before contacting them. It is also important to consider their present circumstances.

5. Initiate an Honest Conversation

When you get in touch with a former employee, it is important to understand their perspective on the job being offered. Make them feel heard and empathize with any difficult situations they may have had to face during their time in the organization. Understand why they would consider rejoining the company. These steps indicate that you truly care about them and fosters a certain level of trust between them and the organization which can motivate them to rejoin with a positive attitude.

6. Implement a Reboarding Program

When a former employee rejoins, HR departments must ensure a robust reboarding exercise is conducted to update them about any changes within the organization regarding the work policies and culture changes, training them about any new tools or systems that were deployed during their absence and allowing them time to reconnect with old team members or acquaint with new ones.

7. Make Them Feel Welcome

Creating a welcoming environment is essential for helping returning employees adjust smoothly. Consider:
  • Organizing team lunches or social events during their first week.
  • Assigning a mentor or buddy from their previous team to help them reacclimate.
  • Providing resources that facilitate learning about any organizational changes.
A positive onboarding experience reinforces their decision to return and fosters loyalty.

Real-Life Examples of Successful Rehiring

Several companies have successfully implemented these strategies:

IBM: The tech giant has embraced boomerang hiring by actively reaching out to former employees who possess critical skills in emerging technologies. IBM has found that these individuals often bring fresh perspectives that contribute significantly to innovation7.

Zappos: Known for its strong company culture, Zappos maintains an alumni network that keeps former employees engaged with the brand. This connection has led to numerous successful rehiring instances, enhancing both morale and productivity within teams6.

Conclusion

Rehiring former employees can provide organizations with unique advantages, including reduced costs, quicker onboarding, and retained knowledge. By implementing strategic practices—such as creating clear policies, maintaining connections, assessing current needs, and fostering welcoming environments—companies can effectively tap into this valuable talent pool.

As organizations continue navigating an ever-changing workforce landscape, embracing boomerang employees may be key to building resilient teams equipped for future challenges. By recognizing the potential benefits and following best practices outlined above, businesses can create a robust strategy for rehiring that enhances both employee satisfaction and organizational performance.
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Building your own Lisp Parser Part II

You might remember the Lisp parser we created in the article (Building Your Own Lisp Parser Part I), which is a pre-requisite for this post. You will now see how the buffered input class (UngettableInput in the previous post) can be improved.

The Problems

Although the UngettableInput class works for our Lisp parser, it is highly specific and could break when used in other programs. In this section, I will talk about the problems with the UngettableInput class.1. There's no method for emptying the input buffer.

Implementing a method to empty the buffer was trivial but we didn't need it in the Lisp parser we created earlier so we left it out. We will accomplish this in this post as an ideal input class should provide one.

2. Getting input of a particular kind is not possible.UngettableInput knows only character and word; getting a number via UngettableInput is not possible. As a result, if the user types (+1 2), our program won't work. The reason is there's no space between “(“ and “+” or “1” and “)”.

The Solutions:

This section lists possible solutions to the problems presented above. The code comes in the next section.1. There's no method for emptying the buffer

The solution is really simple; assign an empty string to the buffer. But in the code section, you will notice a different implementation.

Although both work, a good programmer should think out of the box. What happens to the previous buffer content if we just assign an empty string to the buffer? We just lose it. What if the programmer would need it? The solution to this particular problem is simple but it takes a good programmer to even recognize that there is a problem. We have taken this into account in this post and implemented a method to empty the buffer while also returning the previous content.

2. Getting input of a particular kind is not possibleIn other words, there's only getc (for a single character) and getword (group of characters without any whitespace in between). We should implement a method to get an integer and a float at least. You can later try to write methods to parse for other numeric types.

The Code

Try figuring out how to solve these problems before looking at the following BufferedInput class. You could even write some pseudocode.https://gist.github.com/HackerEarthBlog/ed8269f4f12c02c398910e3b54808fb3

Explanation

The code itself is simple, but there is at least one edge case we have taken care of in an ugly way (See the Homework section). The method-by-method explanation follows.getc()

There isn't any change in the logic but we have used a helper method fill_buffer(). fill_buffer() reads more character from stdin if the buffer is empty.

getword()

getword() repeatedly gets a single character and appends it to “w” unless the character returned by getc() is whitespace. Note that the while loop should break only after encountering atleast one character.

In other words, getwords() gets a continuous group of characters delimited by whitespace.

getint()

getint() first skips whitespace. Then a character is read, which serves as the sign (+ or -). In case the sign is not one of + and -, we unget it.

Then we get the first digit of the number. The reason for doing this is that we want to make sure that the word following is a valid number.

Once confirmed, we read characters continuously and append it to num as long as the digit read is a valid digit (in the range 0 to 9). The read num, which is currently a str of digits, is converted to int using the built-in in function.

getfloat()getfloat() works in three steps corresponding to the integer before the decimal point, the decimal point itself, and the digits after the decimal point. All these are concatenated and converted to float using the built-in function.Note that our implementation of getfloat accurately handles x.y, x., x.Please look at the rest of the code and if at any point some part of it is not understandable please let us know in the comments below.

Homework

Now our code is general enough to be called a general purpose buffered input library! Or is it not? No, it's not. There are obvious flaws. Fortunately, they are easy to fix and will be homework for the reader.Our class works only with stdin. Modify it to handle files as well.Sometimes we need to check what the next character in the buffer is, and then unget it depending on what we are trying to do. A better idea is to have a peek method which returns the next character in the buffer without actually reading it.Modify getfloat to handle numbers of the form .x (such as .5, .1, etc.)

Challenge

The getint and getfloat methods get digits and strings, append them, and generate a number which is returned. This is fine but it is slow. As a challenge, implement a version of getint and getfloat such that they generate the number as the user types in the expression. The answer will change as more characters come in. That will be way cooler.!!!

Getting started with Virtual Reality

“There are two kinds of people in this world: Those who think VR will change the world. And, those who haven’t tried VR."

I read this quote somewhere not so long ago. And even while conservatively looking at the scope and scale of the technology, one can easily say that the Virtual Reality experience is exciting to say the least, whether you use a $10 Google Cardboard or a more expensive Oculus Rift or HTC Vive.

Every advancement in computing allows new form factors to emerge which allows us to use the power of computation to create new applications and experiences never seen or felt before. And Virtual Reality is one new form factor which stretches the boundaries of creativity for developers and storytellers.

Within some time any existing game developer can quickly start building applications for VR and for those who haven’t tried their hand on game development or come from non-technical background can learn to develop for VR in no time as well.

What does one need to know to start building for VR?

The Stack:Developing for VR is not much different from game development. Apart from the fact that some additional hardware and software dependencies are required, the basic tools for development do not vary much.Most VR, and even AR, applications require a gaming engine for development, such as Unity3d or Unreal Engine:While these are new tools to learn for developers who do not have much experience in game development, the learning curve is relatively steep for you to start getting comfortable and start building your first application for VR. Many free resources are now also available online to learn.*Quick Tip: Start with Unity3d as it is less complex and a lot of open source knowledge base and resources are available easily.You will also require an appropriate SDK (Software Development Kit) depending on what device you want to build for:Hardware:Although there is a necessary hardware dependency for a VR application, you don’t necessarily need to purchase an expensive device straightaway. When you’re just getting started, a cheaper Google Cardboard can do the job just fine, but it restricts your movement to just 3 DOF (Degrees of Freedom) as opposed to a 6 DOF HTC Vive or Oculus Rift, which allows an immersive room-scale experience.3 DOF means that although you will be able to see in X, Y, Z directions by the motion of your head mounted display (HMD) in the Virtual environment, you wouldn’t be able to move or touch anything. However,, 6 DOF allows for a room-scale experience. While a 6 DOF looks good on the face of it, there are downsides as well. Room-scale VR requires high computation performance with a high-end graphic card and RAM that you probably won’t get from your standard laptops and will require a desktop computer with optimal performance and also at least 6ft × 6ft free space as opposed to 3 DOF that requires just a standard smart phone with an inbuilt gyro (which is inbuilt in most modern smart phones that cost about ₹15,000 or more).Some common devices available in the market today are

Tutorials and Courses:

It can sound a little intimidating in the beginning but actually learning to develop for VR is not all that hard. Once you get a hang of the game engine, one can quickly catch on and there are multiple avenues to explore if you want to learn how to create your VR application:YouTube Tutorials

Here are a few channels that provide good “Getting Started” tutorials for VR:

NurFACEGAMES

MatthewHallberg

Fuseman

Online CoursesA lot of MOOC (massive open online course) courses have come out in the last few months, making it easier to learn and some of them are even free!Most of these courses are short (typically 2–4 weeks). Here are a few of them:
  1. Introduction to Virtual Reality | Udacity (Free)
  2. VR Scenes and Objects | Udacity (Free)
  3. VR Software Development | Udacity (Free)
  4. https://www.coursera.org/learn/augmented-reality/home (Free)
  5. Make Mobile VR Games in Unity with C# for Google Cardboard ($95, there are some discounts available reducing the price to $20–$40)
  6. Cinematic VR Crash Course - Produce Virtual Reality Films (Free)
  7. VR Developer Nanodegree | Udacity (₹9,800/month)

Additional Resources:

And these should be enough to get you started.But if you get stuck, here are some cool applications to follow if you are looking for some inspiration or just want to explore the diversity of the content being generated for VR:SUPERHOT VR

Within

Discovery VR

Job Simulator: the 2050 Archives

Roller Coaster VR attraction - Android Apps on Google Play

Cardboard - Android Apps on Google Play

Google Earth VR

Tilt Brush by Google

Jaunt - Cinematic Virtual Reality - 360° VR video

Pee World VR

To be updated with the space, there are a few media platforms that cover Mixed Reality (VR/AR) exclusively, such as

VR News, Events, and Talent | UploadVR

Road to VR - Virtual Reality News

Inside VR & AR

http://vrtalk.com/forum/

So get started and make some exciting applications.

Register at the UnitedByHCl hackathon
Happy Mixing Reality!!

Happy mixing reality!!

Author:
Pratham Sehgal
Mixed Reality Enthusiast
Previously CoFounder - Trustio Acquired by Slicepay (Exclusive: Student micro-financing startup SlicePay acquires P2P lender Trustio)

How to solve nondeterministic polynomial (NP) challenge problems in programming contests

In this article, we talk about what Challenge problems are and how to solve them. I find them the most attractive questions in a long contest.However, students new to competitive programming often avoid them because they seem weird at first. Let’s try and change that perception.

What are Challenge problems?

A challenge problem in a programming contest uses NP (Nondeterministic Polynomial) problems to test a candidate.

With no perfect answer, candidates are tested on how good they are at finding approximate solutions.

This is why the evaluation is score based.The top scorer is given a score of 100, while the others are given relative scores.Usually, problem statements are simple and allow candidates to find interesting nuances while solving.Because of the generality of the problem, candidates can choose numerous approaches to optimize their score.These include Number Theory, Graphs, Data Science, etc...Some problems require prior knowledge of algorithms, but the best challenge problems are those which have simple explanations and lots of scope for improvement.Such problems allow beginners to try and test their approximate solutions while making sure that the experienced players are tested too.

How do we solve this:

Watch this brilliant video by MIT professor Patrick Wilson, who solves a problem (at 42:30) and amazing trick he puts into it

To summarize the procedure for the problem discussed by the professor, here are the steps -

  1. Definition
    Does the problem reduce to Knapsack? Subset sum? Something else?
  2. Representation
    Should the main data structure be an array, a list or a tree?
  3. Approach
    Dynamic Programming? Graph Algorithm? etc...
  4. Algorithm
    DFS / Sorting / Edit Distance --> Simulated Annealing / Genetic Algorithm
  5. Experiment
A key point is that drawing and discussing ideas are far more important than jumping into code. The other super important thing is you can't follow this process in just one shot.

It has to be repeated, with each iteration improving your solution.



First, you need a base solution. Choose a simple, clear-cut algorithm (like the first three mentioned above in point 4).

This is the foundation, setting a minimum guarantee to your score.

Invest your time in this, because a weak base solution will directly result in a poor score.

You now need to tweak the best solution you have, updating if you get something better than the current best.

Hill climbing, Simulated Annealing, or any Evolutionary Algorithm will help you here.

Most of your time after this will be spent improving the parameters of the algorithm and improving the time complexity.

The time required to solve them

They can’t be solved in half a day, to be practical. Unless you are looking for an okay score and minimum effort, be prepared to invest significantly.Also, beware of the law of diminishing returns. In general, the more time you invest in these problems, the smaller the improvements you will see.

The first few hours will give you interesting solutions => perhaps a score of 75–85; the next few days might take you to 95–100. And staying there takes tons of effort.

The primary reason why these problems are difficult is that we have to customize and optimize our solutions every time.

You can create a general framework for Simulated Annealing to help in the coding phase. However, the “representation” part will change every time.

Up to which 't' point do I keep optimizing

Until you feel that there is very little progress being made. To be practical, the other problems will give you many more points for the same amount of effort.

When you hit problems beyond your league, come back to improving on the challenge problem solution.

Remember that the people at the top have access to the same resources as you do. There is no reason why they should get a better score than you.

When should I start with this problem

This problem will stay at the back of your mind throughout the contest. So, it is better to start a little late.

More often than not, the problems within our league are solved within the first 80% of the contest’s duration.

The challenge problem can be started then.

Final tips and tricks:
  1. Do not jump into meta-heuristics (Genetic Algorithms, Simulated Annealing) without creating a strong base solution.
  2. When optimizing, try to keep the code clean for later.
  3. Your nested loops need the most attention because that’s where you get the maximum gains.
  4. Greed is good. Keep your heuristics simple and easy to change.
  5. If some idea feels too complicated, it is. Save it for the next contest, after reading a little more and being confident about it.
Practice your learning at one of the challenges at HackerEarth Challenges

Can the Asus Tinker Board take the pie away from Raspberry Pi ?

To satisfy our voracious appetite for economical, easily-programmable, and open source hardware to bring our imagination to life, technology giants such as Broadcom, Intel, Texas Instruments, Samsung, and Qualcomm have come up with their own single- board computers. But none of them were successful in replacing Raspberry Pi.

Recently, Asus, the Taiwanese chip major, recently launched its own single-board computer “Tinker Board.”

Tinker Board

Raspberry Pi vs. Tinker Board - A battle of super boards

Raspberry Pi 3 comes with 64-bit ARM Cortex-A57 based Broadcom BCM2837 quad-core processor at 1.2GHz, whereas Tinker Board comes with a slightly powerful processor, a 32-bit ARM Cortex-A17 based Rockchip RK3288 quad-core at 1.8GHz.

The GPU of Tinker Board is more powerful than Broadcom VideoCore IV GPU used in Raspberry Pi 3. The Tinker Board comes with Rockchip RK3288's ARM Mali-T764 graphics core with full H.264 4K video decode capability, whereas Raspberry Pi 3 has a standard HD output.

The Asus Tinker Board supports 192K/24-bit audio sample rates, whereas the Raspberry Pi 3 is just able to handle 48K/16-bit.

The Tinker Board has 2 GB LPDDR3 RAM which is twice that of Raspberry Pi 3. The board from Asus comes with an integrated full-speed Gigabit Ethernet port, which is a significant boost over the Raspberry Pi's 100Mb LAN. Similar to Raspberry Pi 3 Model B, integrated connectivity options such as 802.11b/g/n WiFi and Bluetooth 4 are available on Tinker Board.

Like you see in Raspberry Pi 3, Tinker Board also has the following features:
  • Built-in WiFi
  • 4 USB ports
  • 1 HDMI 2.0
  • 1 MicroSD card slot
  • 40 GPIO pins
  • A 3.5mm audio jack
  • 1 Micro USB for power
The Asus Tinker Board supports Debian Linux and KODI (formerly called XBMC or Xbox Media Center) with its slick media streaming interface.

Undoubtedly Asus Tinker Board has better specs than Raspberry Pi 3. But Tinker Board loses when it comes to pricing. Raspberry Pi 3 is priced at $35, whereas Tinker Board is priced at $68.

But how do the benchmark metrics look?

The benchmark scores of CPU/Memory- Tinker Board Vs Raspberry Pi

The benchmark scores of storage- Tinker Board Vs Raspberry Pi

Undoubtedly, the Asus Tinker Board wins in specs and performance metrics, but does that mean Raspberry Pi 3 is going lose ground to Tinker Board? I don’t think so because it's not just specs that made Raspberry Pi a revolutionary product, but it is more than that:

Support by the Raspberry Pi team: Active support by the Raspberry Pi foundation has created a sufficient knowledge base which builds enough trust among the developers to consider it for their DIY projects.

Vast user base: Raspberry Pi has a very engaged and innovative user base of makers or DIY enthusiasts because of which there is always a new project / hack every day.

Availability: Raspberry Pi has widespread and continued availability of supporting hardware.

In the early days of Raspberry Pi, the creators thought that they would be able to sell 10,000 units in its lifetime. But the Raspberry Pi foundation has sold more than a million units.

I don't see the adoption of Raspberry Pi dipping any time soon, do you?

Top 13 (free) must read machine leaning books for beginners

Getting learners to read textbooks and use other teaching aids effectively can be tricky. Especially, when the books are just too dreary.

In this post, we’ve compiled great e-resources for you digital natives looking to explore the exciting world of Machine Learning and Neural Networks. But before you dive into the deep end, you need to make sure you’ve got the fundamentals down pat.

It doesn’t matter what catches your fancy, machine learning, artificial intelligence, or deep learning; you need to know the basics of math and stats—linear algebra, calculus, optimization, probability—to get ahead.

Top machine learning books to read for beginners

  1. Matrix Computations

    This 2013 edition by Golub and Van Loan, published by The Johns Hopkins University Press, teaches you about matrix analysis, linear systems, eigenvalues, discrete Poisson solvers, least squares, parallel LU, pseudospectra, Singular Value Decomposition, and much more.

    This book is an indispensable tool for engineers and computational scientists. It has great reviews on Amazon, especially by users looking for problems, discussions, codes, solutions, and references in numerical linear algebra.

    Free Book:Download here

  2. A Probabilistic Theory of Pattern Recognition

    Written by Devroye, Lugosi, and Györfi, this an excellent book for graduate students and researchers. The book covers various probabilistic techniques including nearest neighbour rules, feature extraction, Vapnik-Chervonenkis theory, distance measures, parametric classification, and kernel rules.

    Amazon reviewers laud it for its nearly 500 problems and exercises.

    Wikipedia says “The terms pattern recognition, machine learning, data mining and knowledge discovery in databases are hard to separate, as they largely overlap in their scope.”

    No wonder, machine learning enthusiasts swear by this comprehensive, theoretical book on “nonparametric, distribution-free methodology in Pattern Recognition.”

    Free Book:Download here

  3. Advanced Engineering Mathematics

    Erwin Kreyszig’s book beautifully covers the basics of applied math in a comprehensive and simplistic manner for engineers, computer scientists, mathematicians, and physicists.

    It teaches you Fourier analysis, vector analysis, linear algebra, optimization, graphs, complex analysis, and differential and partial differential equations.

    It has up-to-date and effective problem sets that ensure you understand the concepts clearly.

  4. Probability and Statistics Cookbook

    A collection of math and stats reference material from the University of California (Berkeley) and other sources put together by Matthias Vallentin, this cookbook is a must-have for learners.

    There are no elaborate explanations but concise representations of key concepts. You can view it on GitHub, or download a PDF file using the link below.

    Free Book:Download here

  5. An Introduction to Statistical Learning (with applications in R)

    This book written by Gareth James, Daniela Witten, Trevor Hastie, and Robert Tibshirani is meant for non-math students.

    For data scientists, this is a valuable addition because of its R labs.

    The TOC includes linear regression, classification, resampling methods, linear model and regularization, tree-based methods, shrinkage approaches, clustering, support vector machines, and unsupervised learning.

    With interesting real-world examples and attractive graphics, this is a great text for statistical tools and techniques.

    Free Book:Download here

  6. Probabilistic Programming and Bayesian Methods for Hackers

    Cameron Davidson-Pilon describes Bayesian methods and probabilistic programming from math and computation perspectives.

    The book discusses modeling Bayesian problems using Python’s PyMC, loss functions, the Law of Large Numbers, Markov Chain Monte Carlo, priors, and so lots more.

    The content is open sourced. The print version has updated examples, EOC questions, and improved and extra sections.

    Free Book:Download here

  7. The Elements of Statistical Learning

    Authors Trevor Hastie, Robert Tibshirani, and Jerome Friedman (all three are Stanford professors) discuss supervised learning, linear methods of regression and classification, kernel smoothing methods, regularization, model selection and assessment, additive trees, SVM, neural networks, random forests, nearest neighbors, unsupervised learning, ensemble methods, and more.

    This book covers a broad range of topics is particularly useful for researchers interested in data mining and machine learning.

    You need to know linear algebra and some stats before you can appreciate the text.

    This is what one of the reviewers said about the book on Amazon: The Elements of Statistical Learning is a comprehensive mathematical treatment of machine learning from a statistical perspective.

    Free Book:Download here

  8. Bayesian Reasoning and Machine Learning

    David Barber’s books is a comprehensive piece of writing on graphical models and machine learning.

    Meant for final-year undergraduate and graduate students, this text has ample guidelines, examples,and exercises. The author also offers a MATLAB toolbox and a related website.

    It covers inference in probabilistic models including belief networks, inference in trees,the junction tree algorithm, decision trees; learning in probabilistic models including Naive Bayes, hidden variables and missing data, supervised and unsupervised linear dimension reduction, Gaussian processes, and linear models; dynamic models including discrete- and continuous-state model Markov models, and distribution computation; and approximate inference.

    Free Book:Download here

  9. Information Theory, Inference, and Learning Algorithms

    David MacKay exciting book discusses key concepts that form the core of machine learning, data mining, pattern recognition, bioinformatics, and cryptography.

    Amazon reviewers find the illustrations, depth, and “esoteric” approach remarkable.

    It is a great book on information theory and inference, which covers topics such as data compression, noisy-channel coding, probabilities, neural networks, and sparse graph codes.

    Free Book:Download here

  10. Deep Learning

    This what Elon Musk, co-founder of Tesla Motors, has to say about this definitive text written by Ian Goodfellow, Yoshua Bengio, and Aaron Courville: “Written by three experts in the field, Deep Learning is the only comprehensive book on the subject.”

    The authors talk about applied math and machine learning basics, deep networks and modern practices, and deep learning research.

    For engineers interested in neural networks, this could well be their bible.

    The book is highly recommended for people in academia, providing the required mathematical background to fully appreciate deep learning in its current state.

    Free Book:Download here

  11. Neural Networks and Deep Learning

    Michael Nielsen’s free online book is a comprehensive text on the core concepts of deep learning and artificial neural networks.

    The book has great interactive elements, but it does not provide solutions for the exercises. Laid out like a narrative, Nielsen holds onto core math and code to explain the key ideas.

    He talks about back propagation, hyper parameter optimization, activation functions, neural networks as functional approximates, regularization, a little about convolution neural networks, etc.

    The author includes valuable links to ongoing research and influential research papers and related tutorials.

    Free Book:Download here

  12. Supervised Sequence Labelling with Recurrent Neural Networks

    Alex Graves discusses how to classify and transcribe sequential data, which is important in part-of-speech tagging, gesture, handwriting, and speech recognition, and protein secondary structure prediction.

    He talks about the role of recurrent neural networks in sequence labeling.

    Long short-term memory, a comparison of network architectures, hidden Markov model hybrids, connectionist temporal classification, multidimensional networks, and hierarchical sub sampling networks are other chapters in this book.

    Free Book:Download here

  13. Reinforcement Learning: An Introduction

    Richard S. Sutton and Andrew G. Barto’s pioneering book onreinforcement learning covers the intellectual background, applications, algorithms, and the future of this exciting field. These University of Massachusetts Professors describe this artificial intelligence concept with clarity and simplicity.

    This book includes interesting topics such as Markov decision processes, Monte Carlo methods, dynamic programming, temporal-difference learning, eligibility traces, and artificial neural networks.

    Free Book:Download here

Summary

What’s better than getting educational resources that are free and authored by pioneers in the field?

Can’t think of a downside really…Especially for struggling students, these ebooks are a boon.

They don’t need to wait for the books to turn up at the library or swap with others;grab them and start learning!

So, what’s stopping you from picking up one of these excellent books and fashioning a successful career in data science, AI, or machine learning?

Radial Basis Function Network

step 6: Determine centers of the neurons using KMeans.
K_cent= 8

km= KMeans(n_clusters= K_cent, max_iter= 100)

km.fit(X_train)

cent= km.cluster_centers_
step 7: Determine the value of [latex]\sigma[/latex]
max=0 

for i in range(K_cent):

for j in range(K_cent):

d= numpy.linalg.norm(cent[i]-cent[j])

if(d> max):

max= d

d= max



sigma= d/math.sqrt(2*K_cent)
step 8: Set up matrix G.
shape= X_train.shape

row= shape[0]

column= K_cent

G= numpy.empty((row,column), dtype= float)

for i in range(row):

for j in range(column):

dist= numpy.linalg.norm(X_train[i]-cent[j])

G[i][j]= math.exp(-math.pow(dist,2)/math.pow(2*sigma,2))
step 9: Find weight matrix W to train the network.
GTG= numpy.dot(G.T,G)

GTG_inv= numpy.linalg.inv(GTG)

fac= numpy.dot(GTG_inv,G.T)

W= numpy.dot(fac,Y_train)
step 10: Set up matrix G for the test set.
row= X_test.shape[0]

column= K_cent

G_test= numpy.empty((row,column), dtype= float)

for i in range(row):

for j in range(column):

dist= numpy.linalg.norm(X_test[i]-cent[j])

G_test[i][j]= math.exp(-math.pow(dist,2)/math.pow(2*sigma,2))

step 11: Analyze the accuracy of prediction on test set
prediction= numpy.dot(G_test,W)

prediction= 0.5*(numpy.sign(prediction-0.5)+1)



score= accuracy_score(prediction,Y_test)

print score.mean()

With an RBF network, a prediction with an accuracy of 88% is achieved and so is the cause with MLP. However, the computational cost of training an MLP is much higher as compared to RBF; hence, here it's better to use RBF network instead of MLP.
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AI In Recruitment: The Good, The Bad, The Ugly

Artificial Intelligence (AI) has permeated virtually every industry, transforming operations and interactions. The tech recruitment sector is no exception, and AI’s influence shapes the hiring processes in revolutionary ways. From leveraging AI-powered chatbots for preliminary candidate screenings to deploying machine learning algorithms for efficient resume parsing, AI leaves an indelible mark on tech hiring practices.

Yet, amidst these promising advancements, we must acknowledge the other side of the coin: AI’s potential malpractices, including the likelihood of cheating on assessments, issues around data privacy, and the risk of bias against minority groups.

The dark side of AI in tech recruitment

Negative impact of AI

The introduction of AI in recruitment, while presenting significant opportunities, also brings with it certain drawbacks and vulnerabilities. Sophisticated technologies could enable candidates to cheat on assessments, misrepresent abilities and potential hiring mistakes. This could lead to hiring candidates with falsifying skills or qualifications, which can cause a series of negative effects like:

  • Reduced work quality: The work output might be sub-par if a candidate doesn’t genuinely possess the abilities they claimed to have.
  • Team disruptions: Other team members may have to pick up the slack, leading to resentment and decreased morale.
  • Rehiring costs: You might have to let go of such hires, resulting in additional costs for replacement.

Data privacy is another critical concern

Your company could be left exposed to significant risks if your AI recruiting software is not robust enough to protect sensitive employee information. The implications for an organization with insufficient data security could be severe such as:

  • Reputational damage: Breaches of sensitive employee data can damage your company’s reputation, making it harder to attract clients and talented employees in the future.
  • Legal consequences: Depending on the jurisdiction, you could face legal penalties, including hefty fines, for failing to protect sensitive data adequately.
  • Loss of trust: A data breach could undermine employee trust in your organization, leading to decreased morale and productivity.
  • Financial costs: Besides potential legal penalties, companies could also face direct financial losses from a data breach, including the costs of investigation, recovery, and measures to prevent future breaches.
  • Operational disruption: Depending on the extent of the breach, normal business operations could be disrupted, causing additional financial losses and damage to the organization’s reputation.

Let’s talk about the potential for bias in AI recruiting software

Perhaps the most critical issue of all is the potential for unconscious bias. The potential for bias in AI recruiting software stems from the fact that these systems learn from the data they are trained on. If the training data contains biases – for example, if it reflects a history of preferentially hiring individuals of a certain age, gender, or ethnicity – the AI system can learn and replicate these biases.

Even with unbiased data, if the AI’s algorithms are not designed to account for bias, they can inadvertently create it. For instance, a hiring algorithm that prioritizes candidates with more years of experience may inadvertently discriminate against younger candidates or those who have taken career breaks, such as for child-rearing or health reasons.

This replication and possible amplification of human prejudices can result in discriminatory hiring practices. If your organization’s AI-enabled hiring system is found to be biased, you could face legal action, fines, and penalties. Diversity is proven to enhance creativity, problem-solving, and decision-making. In contrast, bias in hiring can lead to a homogenous workforce, so its absence would likely result in a less innovative and less competitive organization.

Also read: What We Learnt From Target’s Diversity And Inclusion Strategy

When used correctly, AI in recruitment can take your hiring to the next level

How to use AI during hiring freeze

How do you evaluate the appropriateness of using AI in hiring for your organization? Here are some strategies for navigating the AI revolution in HR. These steps include building support for AI adoption, identifying HR functions that can be integrated with AI, avoiding potential pitfalls of AI use in HR, collaborating with IT leaders, and so on.

Despite certain challenges, AI can significantly enhance tech recruitment processes when used effectively. AI-based recruitment tools can automate many manual recruiting tasks, such as resume screening and interview scheduling, freeing up time for recruiters to focus on more complex tasks. Furthermore, AI can improve the candidate’s experience by providing quick responses and personalized communications. The outcome is a more efficient, candidate-friendly process, which could lead to higher-quality hires.

Let’s look at several transformational possibilities chatbots can bring to human capital management for candidates and hiring teams. This includes automation and simplifying various tasks across domains such as recruiting, onboarding, core HR, absence management, benefits, performance management, and employee self-service resulting in the following:

For recruiters:

  • Improved efficiency and productivity: Chatbots can handle routine tasks like responding to common inquiries or arranging interviews. Thereby, providing you with more time to concentrate on tasks of strategic importance.
  • Enhanced candidate experience: With their ability to provide immediate responses, chatbots can make the application process more engaging and user-friendly.
  • Data and insights: Chatbots can collect and analyze data from your interactions with candidates. And provide valuable insights into candidate preferences and behavior.
  • Improved compliance: By consistently following predefined rules and guidelines, chatbots can help ensure that hiring processes are fair and compliant with relevant laws and regulations.
  • Cost saving: By automating routine tasks for recruiters, chatbots can help reduce the labor costs associated with hiring.

Also read: 5 Steps To Create A Remote-First Candidate Experience In Recruitment

How FaceCode Can Help Improve Your Candidate Experience | AI in recruitment

For candidates:

Additionally, candidates can leverage these AI-powered chatbots in a dialog flow manner to carry out various tasks. These tasks include the following:

  • Personalized greetings: By using a candidate’s name and other personal information, chatbots can create a friendly, personalized experience.
  • Job search: They can help candidates search for jobs based on specific criteria.
  • Create a candidate profile: These AI-powered chatbots can guide candidates through the process of creating a profile. Thus, making it easier for them to apply for jobs.
  • Upload resume: Chatbots can instruct candidates on uploading their resume, eliminating potential confusion.
  • Apply for a job: They can streamline the application process, making it easier and faster for candidates to apply for jobs.
  • Check application status: Chatbots can provide real-time updates on a candidate’s application status.
  • Schedule interviews: They can match candidate and interviewer availability to schedule interviews, simplifying the process.

For hiring managers:

These can also be utilized by your tech hiring teams for various purposes, such as:

  • Create requisition: Chatbots can guide hiring managers through the process of creating a job requisition.
  • Create offers: They can assist in generating job offers, ensuring all necessary information is included.
  • Access requisition and offers: Using chatbots can provide hiring managers with easy access to job requisitions and offers.
  • Check on onboarding tasks: Chatbots can help track onboarding tasks, ensuring nothing is missed.

Other AI recruiting technologies can also enhance the hiring process for candidates and hiring teams in the following ways:

For candidates:

  1. Tailor-made resumes and cover letters using generative AI: Generative AI can help candidates create custom resumes and cover letters, increasing their chances of standing out.
  2. Simplifying the application process: AI-powered recruiting tools can simplify the application process, allowing candidates to apply for jobs with just a few clicks.
  3. Provide similar job recommendations: AI can analyze candidates’ skills, experiences, and preferences to recommend similar jobs they might be interested in.

For recruiters:

  • Find the best candidate: AI algorithms can analyze large amounts of data to help you identify the candidates most likely to succeed in a given role.
  • Extract key skills from candidate job applications: Save a significant amount of time and effort by using AI-based recruiting software to quickly analyze job applications to identify key skills, thereby, speeding up the screening process.
  • Take feedback from rejected candidates & share similar job recommendations: AI can collect feedback from rejected candidates for you to improve future hiring processes and recommend other suitable roles to the candidate.

These enhancements not only streamline the hiring process but also improve the quality of hires, reduce hiring biases, and improve the experience for everyone involved. The use of AI in hiring can indeed take it to the next level.

Where is AI in recruitment headed?

AI can dramatically reshape the recruitment landscape with the following key advancements:

1. Blockchain-based background verification:

Blockchain technology, renowned for its secure, transparent, and immutable nature, can revolutionize background checks. This process which can take anywhere from between a day to several weeks today for a single recruiter to do can be completed within a few clicks resulting in:

  • Streamlined screening process: Blockchain can store, manage, and share candidates’ credentials and work histories. Thereby speeding up the verification and screening process. This approach eliminates the need for manual background checks. And leads to freeing up a good amount of time for you to focus on more important tasks.
  • Enhanced trust and transparency: With blockchain, candidates, and employers can trust the validity of the information shared due to the nature of the technology. The cryptographic protection of blockchain ensures the data is tamper-proof, and decentralization provides transparency.
  • Improved data accuracy and reliability: Since the blockchain ledger is immutable, it enhances the accuracy and reliability of the data stored. This can minimize the risks associated with false information on candidates’ resumes.
  • Faster onboarding: A swift and reliable verification process means candidates can be onboarded more quickly. Thereby, improving the candidate experience and reducing the time-to-hire.
  • Expanded talent pool: With blockchain, it’s easier and quicker to verify the credentials of candidates globally, thereby widening the potential talent pool.

2. Immersive experiences using virtual reality (VR):

VR can provide immersive experiences that enhance various aspects of the tech recruitment process:

  • Interactive job previews: VR can allow potential candidates to virtually “experience” a day i.e., life at your company. This provides a more accurate and engaging job preview than traditional job descriptions.
  • Virtual interviews and assessments: You can use VR to conduct virtual interviews or assessments. You can also evaluate candidates in a more interactive and immersive setting. This can be particularly useful for roles that require specific spatial or technical skills.
  • Virtual onboarding programs: New hires can take a virtual tour of the office, meet their colleagues, and get acquainted with their tasks, all before their first day. This can significantly enhance the onboarding experience and help new hires feel more prepared.
  • Immersive learning experiences: VR can provide realistic, immersive learning experiences for job-specific training or to enhance soft skills. These could be used during the recruitment process or for ongoing employee development.

Also read: 6 Strategies To Enhance Candidate Engagement In Tech Hiring (+ 3 Unique Examples)

AI + Recruiters: It’s all about the balance!

To summarize, AI in recruitment is a double-edged sword, carrying both promise and potential problems. The key lies in how recruiters use this technology, leveraging its benefits while vigilantly managing its risks. AI isn’t likely to replace recruiters or HR teams in the near future. Instead, you should leverage this tool to positively impact the entire hiring lifecycle.

With the right balance and careful management, AI can streamline hiring processes. It can create better candidate experiences, and ultimately lead to better recruitment decisions. Recruiters should continually experiment with and explore generative AI. To devise creative solutions, resulting in more successful hiring and the perfect fit for every open role.

Looking For A Mettl Alternative? Let’s Talk About HackerEarth

“Every hire is an investment for a company. A good hire will give you a higher ROI; if it is a bad hire, it will cost you a lot of time and money.”

Especially in tech hiring!

An effective tech recruitment process helps you attract the best talents, reduce hiring costs, and enhance company culture and reputation.

Businesses increasingly depend on technical knowledge to compete in today’s fast-paced, technologically driven world. Online platforms that provide technical recruiting solutions have popped up to assist companies in finding and employing top talent in response to this demand.

The two most well-known platforms in this field are HackerEarth and Mettl. To help businesses make wise choices for their technical employment requirements, we will compare these two platforms’ features, benefits, and limitations in this article.

This comparison of Mettl alternative, HackerEarth and Mettl itself, will offer helpful information to help you make the best decision, whether you’re a small company trying to expand your tech staff or a massive organization needing a simplified recruiting process.

HackerEarth

HackerEarth is based in San Francisco, USA, and offers enterprise software to aid companies with technical recruitment. Its services include remote video interviewing and technical skill assessments that are commonly used by organizations.

HackerEarth also provides a platform for developers to participate in coding challenges and hackathons. In addition, it provides tools for technical hiring such as coding tests, online interviews, and applicant management features. The hiring solutions provided by HackerEarth aid companies assess potential employees’ technical aptitude and select the best applicants for their specialized positions.

Mettl

Mettl, on the other hand, offers a range of assessment solutions for various industries, including IT, banking, healthcare, and retail. It provides online tests for coding, linguistic ability, and cognitive skills. The tests offered by Mettl assist employers find the best applicants for open positions and make data-driven recruiting choices. Additionally, Mettl provides solutions for personnel management and staff training and development.

Why should you go for HackerEarth over Mercer Mettl?

Here's why HackerEarth is a great Mettl Alternative!

Because HackerEarth makes technical recruiting easy and fast, you must consider HackerEarth for technical competence evaluations and remote video interviews. It goes above and beyond to provide you with a full range of functions and guarantee the effectiveness of the questions in the database. Moreover, it is user-friendly and offers fantastic testing opportunities.

The coding assessments by HackerEarth guarantee the lowest time consumption and maximum efficiency. It provides a question bank of more than 17,000 coding-related questions and automated test development so that you can choose test questions as per the job role.

As a tech recruiter, you may need a clear understanding of a candidate’s skills. With HackerEarth’s code replay capability and insight-rich reporting on a developer’s performance, you can hire the right resource for your company.

Additionally, HackerEarth provides a more in-depth examination of your recruiting process so you can continuously enhance your coding exams and develop a hiring procedure that leads the industry.

HackerEarth and Mercer Mettl are the two well-known online tech assessment platforms that provide tools for managing and performing online examinations. We will examine the major areas where HackerEarth outperforms Mettl, thereby proving to be a great alternative to Mettl, in this comparison.

Also read: What Makes HackerEarth The Tech Behind Great Tech Teams

HackerEarth Vs Mettl

Features and functionality

HackerEarth believes in upgrading itself and providing the most effortless navigation and solutions to recruiters and candidates.

HackerEarth provides various tools and capabilities to create and administer online tests, such as programming tests, multiple-choice questions, coding challenges, and more. The software also has remote proctoring, automatic evaluation, and plagiarism detection tools (like detecting the use of ChatGPT in coding assessments). On the other side, Mettl offers comparable functionality but has restricted capabilities for coding challenges and evaluations.

Test creation and administration

HackerEarth: It has a user-friendly interface that is simple to use and navigate. It makes it easy for recruiters to handle evaluations without zero technical know-how. The HackerEarth coding platform is also quite flexible and offers a variety of pre-built exams, including coding tests, aptitude tests, and domain-specific examinations. It has a rich library of 17,000+ questions across 900+ skills, which is fully accessible by the hiring team. Additionally, it allows you to create custom questions yourself or use the available question libraries.

Also read: How To Create An Automated Assessment With HackerEarth

Mettl: It can be challenging for a hiring manager to use Mettl efficiently since Mettl provides limited assessment and question libraries. Also, their team creates the test for them rather than giving access to hiring managers. This results in a higher turnaround time and reduces test customization possibilities since the request has to go back to the team, they have to make the changes, and so forth.

Reporting and analytics

HackerEarth: You may assess applicant performance and pinpoint areas for improvement with the help of HackerEarth’s full reporting and analytics tools. Its personalized dashboards, visualizations, and data exports simplify evaluating assessment results and real-time insights.

Most importantly, HackerEarth includes code quality scores in candidate performance reports, which lets you get a deeper insight into a candidate’s capabilities and make the correct hiring decision. Additionally, HackerEarth provides a health score index for each question in the library to help you add more accuracy to your assessments. The health score is based on parameters like degree of difficulty, choice of the programming language used, number of attempts over the past year, and so on.

Mettl: Mettl online assessment tool provides reporting and analytics. However, there may be only a few customization choices available. Also, Mettle does not provide code quality assurance which means hiring managers have to check the whole code manually. There is no option to leverage question-based analytics and Mettl does not include a health score index for its question library.

Adopting this platform may be challenging if you want highly customized reporting and analytics solutions.

Also read: HackerEarth Assessments + The Smart Browser: Formula For Bulletproof Tech Hiring

Security and data privacy

HackerEarth: The security and privacy of user data are top priorities at HackerEarth. The platform protects data in transit and at rest using industry-standard encryption. Additionally, all user data is kept in secure, constantly monitored data centers with stringent access controls.

Along with these security measures, HackerEarth also provides IP limitations, role-based access controls, and multi-factor authentication. These features ensure that all activity is recorded and audited and that only authorized users can access sensitive data.

HackerEarth complies with several data privacy laws, such as GDPR and CCPA. The protection of candidate data is ensured by this compliance, which also enables businesses to fulfill their legal and regulatory responsibilities.

Mettl: The security and data privacy features of Mettl might not be as strong as those of HackerEarth. The platform does not provide the same selection of security measures, such as IP limitations or multi-factor authentication. Although the business asserts that it complies with GDPR and other laws, it cannot offer the same amount of accountability and transparency as other platforms.

Even though both HackerEarth and Mettl include security and data privacy measures, the Mettle alternative, HackerEarth’s platform is made to be more thorough, open, and legal. By doing this, businesses can better guarantee candidate data’s security and ability to fulfill legal and regulatory requirements.

Pricing and support

HackerEarth: To meet the demands of businesses of all sizes, HackerEarth offers a variety of customizable pricing options. The platform provides yearly and multi-year contracts in addition to a pay-as-you-go basis. You can select the price plan that best suits their demands regarding employment and budget.

HackerEarth offers chat customer support around the clock. The platform also provides a thorough knowledge base and documentation to assist users in getting started and troubleshooting problems.

Mettl: The lack of price information on Mettl’s website might make it challenging for businesses to decide whether the platform fits their budget. The organization also does not have a pay-as-you-go option, which might be problematic.

Mettl offers phone and emails customer assistance. However, the business website lacks information on support availability or response times. This lack of transparency may be an issue if you need prompt and efficient help.

User experience

HackerEarth: The interface on HackerEarth is designed to be simple for both recruiters and job seekers. As a result of the platform’s numerous adjustable choices for test creation and administration, you may design exams specifically suited to a job role. Additionally, the platform provides a selection of question types and test templates, making it simple to build and take exams effectively.

In terms of the candidate experience, HackerEarth provides a user-friendly interface that makes navigating the testing procedure straightforward and intuitive for applicants. As a result of the platform’s real-time feedback and scoring, applicants may feel more motivated and engaged during the testing process. The platform also provides several customization choices, like branding and message, which may assist recruiters in giving prospects a more exciting and tailored experience.

Mettl: The platform is intended to have a steeper learning curve than others and be more technical. It makes it challenging to rapidly and effectively construct exams and can be difficult for applicants unfamiliar with the platform due to its complex interface.

Additionally, Mettl does not provide real-time feedback or scoring, which might deter applicants from participating and being motivated by the testing process.

Also read: 6 Strategies To Enhance Candidate Engagement In Tech Hiring (+ 3 Unique Examples)

User reviews and feedback

According to G2, HackerEarth and Mettl have 4.4 reviews out of 5. Users have also applauded HackerEarth’s customer service. Many agree that the staff members are friendly and quick to respond to any problems or queries. Overall, customer evaluations and feedback for HackerEarth point to the platform as simple to use. Both recruiters and applicants find it efficient.

Mettl has received mixed reviews from users, with some praising the platform for its features and functionality and others expressing frustration with its complex and technical interface.

Free ebook to help you choose between Mettl and Mettle alternative, HackerEarth

May the best “brand” win!

Recruiting and selecting the ideal candidate demands a significant investment of time, attention, and effort.

This is where tech recruiting platforms like HackerEarth and Mettl have got you covered. They help streamline the whole process.Both HackerEarth and Mettl provide a wide variety of advanced features and capabilities for tech hiring.

We think HackerEarth is the superior choice. Especially, when contrasting the two platforms in terms of their salient characteristics and functioning. But, we may be biased!

So don’t take our word for it. Sign up for a free trial and check out HackerEarth’s offerings for yourself!

HackerEarth Assessments + The Smart Browser: Formula For Bulletproof Tech Hiring

Let’s face it—cheating on tests is quite common. While technology has made a lot of things easier in tech recruiting, it has also left the field wide open to malpractice. A 2020 report by ICAI shows that 32% of undergraduate students have cheated in some form on an online test.

It’s human nature to want to bend the rules a little bit. Which begs the question, how do you stay on top of cheating, plagiarism, and other forms of malpractice during the assessment process?

How do you ensure that take-home assessments and remote interviews stay authentic and credible? By relying on enhanced virtual supervision, of course!

HackerEarth Assessments has always been one step ahead when it comes to remote proctoring which is able to capture the nuances of candidate plagiarism. The recent advancements in technology (think generative AI) needed more robust proctoring features, so we went ahead and built The HackerEarth Smart Browser to ensure our assessments remain as foolproof as ever.

Presenting to you, the latest HackerEarth proctoring fix - The Smart Browser

Our Smart Browser is the chocolatey version of a plain donut when compared to a regular web browser. It is extra effective and comes packed with additional remote proctoring capabilities to increase the quality of your screening assessments.

The chances of a candidate cheating on a HackerEarth technical assessment are virtually zero with the latest features! Spilling all our secrets to show you why -

1. Sealed-off testing environment makes proctoring simpler

Sealed-off testing environment makes proctoring simpler

To get started with using the Smart Browser, enable the Smart Browser setting as shown above. This setting is available under the test proctoring section on the test overview page.

As you can see, several other proctoring settings such as disabling copy-paste, restricting candidates to full-screen mode, and logout on leaving the test interface are selected automatically.Now, every candidate you invite to take the assessment will only be able to do so through the Smart Browser. Candidates are prompted to download the Smart Browser from the link shared in the test invite mail.When the candidate needs to click on the ‘start test’ button on the launch test screen, it opens in the Smart Browser. The browser also prompts the candidate to switch to full-screen mode. Now, all candidates need to do is sign in and attempt the test, as usual.
Also read: 6 Ways Candidates Try To Outsmart A Remote Proctored Assessment

2. Eagle-eyed online test monitoring leaves no room for error

Eagle-eyed online test monitoring with the smart browser leaves no room for errorOur AI-enabled Smart Browser takes frequent snapshots via the webcam, throughout the assessment. Consequently, it is impossible to copy-paste code or impersonate a candidate.The browser prevents the following candidate actions and facilitates thorough monitoring of the assessment:
  • Screensharing the test window
  • Keeping other applications open during the test
  • Resizing the test window
  • Taking screenshots of the test window
  • Recording the test window
  • Using malicious keystrokes
  • Viewing OS notifications
  • Running the test window within a virtual machine
  • Operating browser developer tools
Any candidate actions attempting to switch tabs with the intent to copy-paste or use a generative AI like ChatGPT are shown a warning and captured in the candidate report.HackerEarth’s latest proctoring fixes bulletproof our assessment platform, making it one of the most reliable and accurate sources of candidate hiring in the market today.
Also read: 4 Ways HackerEarth Flags The Use Of ChatGPT In Tech Hiring Assessments

Experience reliable assessments with the Smart Browser!

There you have it - our newest offering that preserves the integrity of coding assessments and enables skill-first hiring, all in one go. Recruiters and hiring managers, this is one feature that you can easily rely on and can be sure that every candidate’s test score is a result of their ability alone.Curious to try out the Smart Browser? Well, don’t take our word for it. Head over here to check it out for yourself!

We also love hearing from our customers so don’t hesitate to leave us any feedback you might have.

Until then, happy hiring!
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What is Headhunting In Recruitment?: Types & How Does It Work?

In today’s fast-paced world, recruiting talent has become increasingly complicated. Technological advancements, high workforce expectations and a highly competitive market have pushed recruitment agencies to adopt innovative strategies for recruiting various types of talent. This article aims to explore one such recruitment strategy – headhunting.

What is Headhunting in recruitment?

In headhunting, companies or recruitment agencies identify, engage and hire highly skilled professionals to fill top positions in the respective companies. It is different from the traditional process in which candidates looking for job opportunities approach companies or recruitment agencies. In headhunting, executive headhunters, as recruiters are referred to, approach prospective candidates with the hiring company’s requirements and wait for them to respond. Executive headhunters generally look for passive candidates, those who work at crucial positions and are not on the lookout for new work opportunities. Besides, executive headhunters focus on filling critical, senior-level positions indispensable to companies. Depending on the nature of the operation, headhunting has three types. They are described later in this article. Before we move on to understand the types of headhunting, here is how the traditional recruitment process and headhunting are different.

How do headhunting and traditional recruitment differ from each other?

Headhunting is a type of recruitment process in which top-level managers and executives in similar positions are hired. Since these professionals are not on the lookout for jobs, headhunters have to thoroughly understand the hiring companies’ requirements and study the work profiles of potential candidates before creating a list.

In the traditional approach, there is a long list of candidates applying for jobs online and offline. Candidates approach recruiters for jobs. Apart from this primary difference, there are other factors that define the difference between these two schools of recruitment.

AspectHeadhuntingTraditional RecruitmentCandidate TypePrimarily passive candidateActive job seekersApproachFocused on specific high-level rolesBroader; includes various levelsScopeproactive outreachReactive: candidates applyCostGenerally more expensive due to expertise requiredTypically lower costsControlManaged by headhuntersManaged internally by HR teams

All the above parameters will help you to understand how headhunting differs from traditional recruitment methods, better.

Types of headhunting in recruitment

Direct headhunting: In direct recruitment, hiring teams reach out to potential candidates through personal communication. Companies conduct direct headhunting in-house, without outsourcing the process to hiring recruitment agencies. Very few businesses conduct this type of recruitment for top jobs as it involves extensive screening across networks outside the company’s expanse.

Indirect headhunting: This method involves recruiters getting in touch with their prospective candidates through indirect modes of communication such as email and phone calls. Indirect headhunting is less intrusive and allows candidates to respond at their convenience.Third-party recruitment: Companies approach external recruitment agencies or executive headhunters to recruit highly skilled professionals for top positions. This method often leverages the company’s extensive contact network and expertise in niche industries.

How does headhunting work?

Finding highly skilled professionals to fill critical positions can be tricky if there is no system for it. Expert executive headhunters employ recruitment software to conduct headhunting efficiently as it facilitates a seamless recruitment process for executive headhunters. Most software is AI-powered and expedites processes like candidate sourcing, interactions with prospective professionals and upkeep of communication history. This makes the process of executive search in recruitment a little bit easier. Apart from using software to recruit executives, here are the various stages of finding high-calibre executives through headhunting.

Identifying the role

Once there is a vacancy for a top job, one of the top executives like a CEO, director or the head of the company, reach out to the concerned personnel with their requirements. Depending on how large a company is, they may choose to headhunt with the help of an external recruiting agency or conduct it in-house. Generally, the task is assigned to external recruitment agencies specializing in headhunting. Executive headhunters possess a database of highly qualified professionals who work in crucial positions in some of the best companies. This makes them the top choice of conglomerates looking to hire some of the best talents in the industry.

Defining the job

Once an executive headhunter or a recruiting agency is finalized, companies conduct meetings to discuss the nature of the role, how the company works, the management hierarchy among other important aspects of the job. Headhunters are expected to understand these points thoroughly and establish a clear understanding of their expectations and goals.

Candidate identification and sourcing

Headhunters analyse and understand the requirements of their clients and begin creating a pool of suitable candidates from their database. The professionals are shortlisted after conducting extensive research of job profiles, number of years of industry experience, professional networks and online platforms.

Approaching candidates

Once the potential candidates have been identified and shortlisted, headhunters move on to get in touch with them discreetly through various communication channels. As such candidates are already working at top level positions at other companies, executive headhunters have to be low-key while doing so.

Assessment and Evaluation

In this next step, extensive screening and evaluation of candidates is conducted to determine their suitability for the advertised position.

Interviews and negotiations

Compensation is a major topic of discussion among recruiters and prospective candidates. A lot of deliberation and negotiation goes on between the hiring organization and the selected executives which is facilitated by the headhunters.

Finalizing the hire

Things come to a close once the suitable candidates accept the job offer. On accepting the offer letter, headhunters help finalize the hiring process to ensure a smooth transition.

The steps listed above form the blueprint for a typical headhunting process. Headhunting has been crucial in helping companies hire the right people for crucial positions that come with great responsibility. However, all systems have a set of challenges no matter how perfect their working algorithm is. Here are a few challenges that talent acquisition agencies face while headhunting.

Common challenges in headhunting

Despite its advantages, headhunting also presents certain challenges:

Cost Implications: Engaging headhunters can be more expensive than traditional recruitment methods due to their specialized skills and services.

Time-Consuming Process: While headhunting can be efficient, finding the right candidate for senior positions may still take time due to thorough evaluation processes.

Market Competition: The competition for top talent is fierce; organizations must present compelling offers to attract passive candidates away from their current roles.

Although the above mentioned factors can pose challenges in the headhunting process, there are more upsides than there are downsides to it. Here is how headhunting has helped revolutionize the recruitment of high-profile candidates.

Advantages of Headhunting

Headhunting offers several advantages over traditional recruitment methods:

Access to Passive Candidates: By targeting individuals who are not actively seeking new employment, organisations can access a broader pool of highly skilled professionals.

Confidentiality: The discreet nature of headhunting protects both candidates’ current employment situations and the hiring organisation’s strategic interests.

Customized Search: Headhunters tailor their search based on the specific needs of the organization, ensuring a better fit between candidates and company culture.

Industry Expertise: Many headhunters specialise in particular sectors, providing valuable insights into market dynamics and candidate qualifications.

Conclusion

Although headhunting can be costly and time-consuming, it is one of the most effective ways of finding good candidates for top jobs. Executive headhunters face several challenges maintaining the g discreetness while getting in touch with prospective clients. As organizations navigate increasingly competitive markets, understanding the nuances of headhunting becomes vital for effective recruitment strategies. To keep up with the technological advancements, it is better to optimise your hiring process by employing online recruitment software like HackerEarth, which enables companies to conduct multiple interviews and evaluation tests online, thus improving candidate experience. By collaborating with skilled headhunters who possess industry expertise and insights into market trends, companies can enhance their chances of securing high-caliber professionals who drive success in their respective fields.

A Comprehensive Guide to External Sources of Recruitment

The job industry is not the same as it was 30 years ago. Progresses in AI and automation have created a new work culture that demands highly skilled professionals who drive innovation and work efficiently. This has led to an increase in the number of companies reaching out to external sources of recruitment for hiring talent. Over the years, we have seen several job aggregators optimise their algorithms to suit the rising demand for talent in the market and new players entering the talent acquisition industry. This article will tell you all about how external sources of recruitment help companies scout some of the best candidates in the industry, the importance of external recruitment in organizations across the globe and how it can be leveraged to find talent effectively.

Understanding external sources of recruitment

External sources refer to recruitment agencies, online job portals, job fairs, professional associations and any other organizations that facilitate seamless recruitment. When companies employ external recruitment sources, they access a wider pool of talent which helps them find the right candidates much faster than hiring people in-house. They save both time and effort in the recruitment process.

Online job portals

Online resume aggregators like LinkedIn, Naukri, Indeed, Shine, etc. contain a large database of prospective candidates. With the advent of AI, online external sources of recruitment have optimised their algorithms to show the right jobs to the right candidates. Once companies figure out how to utilise job portals for recruitment, they can expedite their hiring process efficiently.

Social Media

Ours is a generation that thrives on social media. To boost my IG presence, I have explored various strategies, from getting paid Instagram users to optimizing post timing and engaging with my audience consistently. Platforms like FB an IG have been optimized to serve job seekers and recruiters alike. The algorithms of social media platforms like Facebook and Instagram have been optimised to serve job seekers and recruiters alike. Leveraging them to post well-placed ads for job listings is another way to implement external sources of recruitment strategies.

Employee Referrals

Referrals are another great external source of recruitment for hiring teams. Encouraging employees to refer their friends and acquaintances for vacancies enables companies to access highly skilled candidates faster.

Campus Recruitment

Hiring freshers from campus allows companies to train and harness new talent. Campus recruitment drives are a great external recruitment resource where hiring managers can expedite the hiring process by conducting screening processes in short periods.

Recruitment Agencies

Companies who are looking to fill specific positions with highly skilled and experienced candidates approach external recruitment agencies or executive headhunters to do so. These agencies are well-equipped to look for suitable candidates and they also undertake the task of identifying, screening and recruiting such people.

Job Fairs

This is a win-win situation for job seekers and hiring teams. Job fairs allow potential candidates to understand how specific companies work while allowing hiring managers to scout for potential candidates and proceed with the hiring process if possible.

Importance of External Recruitment

The role of recruitment agencies in talent acquisition is of paramount importance. They possess the necessary resources to help companies find the right candidates and facilitate a seamless hiring process through their internal system. Here is how external sources of recruitment benefit companies.

Diversity of Skill Sets

External recruitment resources are a great way for companies to hire candidates with diverse professional backgrounds. They possess industry-relevant skills which can be put to good use in this highly competitive market.

Fresh Perspectives

Candidates hired through external recruitment resources come from varied backgrounds. This helps them drive innovation and run things a little differently, thus bringing in a fresh approach to any project they undertake.

Access to Specialized Talent

Companies cannot hire anyone to fill critical roles that require highly qualified executives. This task is assigned to executive headhunters who specialize in identifying and screening high-calibre candidates with the right amount of industry experience. Huge conglomerates and companies seek special talent through external recruiters who have carved a niche for themselves.

Now that you have learnt the different ways in which leveraging external sources of recruitment benefits companies, let’s take a look at some of the best practices of external recruitment to understand how to effectively use their resources.

Best Practices for Effective External Recruitment

Identifying, reaching out to and screening the right candidates requires a robust working system. Every system works efficiently if a few best practices are implemented. For example, hiring through social media platforms requires companies to provide details about their working environment, how the job is relevant to their audience and well-positioned advertisements. The same applies to the other external sources of recruitment. Here is how you can optimise the system to ensure an effective recruitment process.

Craft Clear and Compelling Job Descriptions

Detail Responsibilities: Clearly outline the key responsibilities and expectations for the role.

Highlight Company Culture: Include information about the company’s mission, values, and growth opportunities to attract candidates who align with your organizational culture.

Leverage Multiple Recruitment Channels

Diversify Sources: Use a mix of job boards, social media platforms, recruitment agencies, and networking events to maximize reach. Relying on a single source can limit your candidate pool.

Utilize Industry-Specific Platforms: In addition to general job boards, consider niche job sites that cater to specific industries or skill sets

Streamline the Application Process

Simplify Applications: Ensure that the application process is user-friendly. Lengthy or complicated forms can deter potential candidates from applying.

Mobile Optimization: Many candidates use mobile devices to apply for jobs, so ensure your application process is mobile-friendly.

Engage in Proactive Sourcing

Reach Out to Passive Candidates: Actively seek out candidates who may not be actively looking for a job but could be a great fit for your organization. Use LinkedIn and other professional networks for this purpose.

Maintain a Talent Pool: Keep a database of previous applicants and strong candidates for future openings, allowing you to reach out when new roles become available.

Utilize Social Media Effectively

Promote Job Openings: Use social media platforms like LinkedIn, Facebook, and Twitter to share job postings and engage with potential candidates. This approach can also enhance your employer brand

Conduct Background Checks: There are several ways of learning about potential candidates. Checking out candidate profiles on job boards like LinkedIn or social media platforms can give companies a better understanding of their potential candidates, thus confirming whether they are the right fit for the organization.

Implement Data-Driven Recruitment

Analyze Recruitment Metrics: Track key metrics such as time-to-hire, cost-per-hire, and source effectiveness. This data can help refine your recruitment strategies over time. Using external hiring software like HackeEarth can streamline the recruitment process, thus ensuring quality hires without having to indulge internal resources for the same.

Use Predictive Analytics: In this age of fast paced internet, everybody makes data-driven decisions. Using predictive analytics to study employee data will help companies predict future trends, thus facilitating a productive hiring process.

Conclusion

External sources of recruitment play a very important role in an organization’s talent acquisition strategy. By employing various channels of recruitment such as social media, employee referrals and campus recruitment drives, companies can effectively carry out their hiring processes. AI-based recruitment management systems also help in the process. Implementing best practices in external recruitment will enable organizations to enhance their hiring processes effectively while meeting their strategic goals.

Progressive Pre-Employment Assessment - A Complete Guide

The Progressive Pre-Employment Assessment is a crucial step in the hiring process, as it evaluates candidates through various dimensions including cognitive abilities, personality traits, and role-specific skills.

While employers and recruiters have this in the palm of their hand, candidates who master it will successfully navigate the assessment and have a higher chance of landing that dream job. But what does it entail in the first place?

Candidates can expect to undergo tests that assess verbal, numerical, and work style capabilities, as well as a personality assessment. Hence, understanding the structure and purpose of the Progressive Pre-Employment Assessment can give candidates a competitive edge. But before one tackles online tests, we must first dissect what this assessment is and what it consists of.

The evolution of pre-employment assessments

Pre-employment assessments have undergone significant changes over the decades, from rudimentary tests to sophisticated, modern evaluations. Let’s put the two side by side.

  • Traditional methods:

    Initially, pre-employment assessments focused on basic skills and educational qualifications. These paper-based tests primarily assessed cognitive and verbal abilities, without any conclusions about the candidates’ output in very specific situations.

  • Modern techniques:

    Today, online assessments are prevalent, evaluating a variety of dimensions, including cognitive skills, personality traits, and behavioral evaluations. These tools offer a more comprehensive view of a candidate's job performance potential, while, at the same time, saving precious time for both parties involved.

In today’s competitive job market, progressive pre-employment assessments play a crucial as they not only measure technical skills and knowledge but also provide insights into a candidate's ethical bias, cultural fit, and communication skills.

Likewise, assessment tests have evolved to include situational judgment tests and culture fit analyses, which are pivotal in assessing the suitability of a candidate for specific roles. And this isn’t just in terms of skillsets—they help in identifying candidates who align well with the company's values and working environment.

This is mainly for the tests’ ability to accurately gauge a candidate's interpersonal skills and emotional intelligence, which are essential for roles that require teamwork and client interactions.

What are progressive pre-employment assessments?

Progressive pre-employment assessments are structured evaluations designed to judge a candidate’s abilities and fit for a role at Progressive Insurance. Unlike traditional aptitude tests, these assessments encompass various elements such as cognitive abilities, situational judgments, and personality traits.

These tests typically include verbal and numerical reasoning sections, as well as work style assessments that gauge behavioral tendencies. Through this merger of multiple dimensions, Progressive seeks to understand not just the skills and knowledge of the candidate, but also their ethical perspectives and communication skills.

Components of a progressive assessment strategy

What sets progressive assessments apart? Well, as most employers just focus on the basic credentials and competencies, the comprehensive assessment strategy at Progressive includes several key components:

  1. Cognitive evaluations: These tests measure candidates' logical reasoning and problem-solving capabilities through verbal, numerical, and abstract reasoning questions.
  2. Personality assessments: These tests evaluate traits and tendencies to understand how a candidate might behave in various workplace scenarios. They aim to provide insight into their ethical bias and interpersonal skills.
  3. Behavioral evaluations: These sections analyze how candidates might act in specific situations, ensuring a good cultural fit and alignment with Progressive's values.
  4. Role-specific skills tests: These assessments focus on the specialized skills required for the position, ensuring the candidate has the necessary technical knowledge and expertise.

Implementing progressive assessments

Successful implementation of Progressive Assessments in the hiring process requires designing an effective assessment process and following best practices for administration. This ensures accuracy, better data security, and reliable decision-making. In particular, the implementation hinges on the feasibility of the original design.

Step 1 --- Designing the assessment process

Designing an effective Progressive Assessment involves understanding the specific needs of the role and the company's approach to hiring. Each test component — verbal, numerical, and work style — must align with the desired skills and personality traits for the role.

HR teams need to define clear objectives for each assessment section. This includes establishing what each part aims to evaluate, like the problem-solving or personality assessments. Incorporating legal and policy guidelines ensures the assessments are fair and non-discriminatory, which is crucial for avoiding legal issues.

Likewise, everaging online assessment tests provides flexibility and efficiency. These tests allow candidates to complete them remotely, easing logistics and scheduling concerns. Ensuring security is also essential, and implementing testing and other recruitment tools can help enhance data security and accuracy.

Step 2 --- Best practices for assessment administration

Administering assessments effectively revolves around consistency and fairness. Establish structured guidelines for the administration process to ensure each candidate undergoes the same conditions, promoting reliability. This includes standardizing the timing, environment, and instructions for all assessments.

Training HR representatives is vital. They should be well-versed in handling the assessments, from initial candidate interactions to evaluating the results. Regular training updates ensure the team remains knowledgeable about best practices and any new tools used in the assessment process.

Administering assessments also involves maintaining better data security and accuracy. This is achieved by utilizing secure online platforms and ensuring that only authorized personnel have access to sensitive data. Leveraging top API penetration testing tools is one approach to securing candidate data and preserving the integrity of the assessment process.

Implementing consistent feedback mechanisms for candidates can also improve the process. Providing insights on their performance helps candidates understand their strengths and areas for growth, which reflects positively on the company’s commitment to candidate experience.

Benefits of progressive assessments

Progressive assessments offer significant advantages in the hiring process, such as improving the accuracy of hiring decisions and enhancing the overall candidate experience. These benefits help companies find better-fitting candidates and reduce turnover rates.

1. Improved hiring accuracy

Progressive pre-employment assessments allow companies to evaluate candidates more comprehensively. By assessing personality traits, cognitive abilities, and ethical biases, employers can identify individuals who align with the company’s values and have the necessary skills for the job.

For example, personality assessments can pinpoint traits like empathy, communication, and problem-solving abilities. This helps employers select candidates who are not only qualified but also fit well within the team. Evaluating these qualities ensures that new hires can thrive in customer service roles where empathy and effective communication are crucial.

Moreover, using tools like the DDI Adaptive Reasoning Test helps to simulate real job tasks. This gives employers deeper insights into a candidate's capability to handle job-specific challenges. As a result, the company is more likely to experience lower turnover rates due to better candidate-job fit.

2. Enhanced candidate experience

A well-structured assessment process can significantly enhance the candidate experience. Clear instructions,fair testing procedures, and timely feedback create a positive impression of the company. Candidates appreciate transparency and feel valued when the process is designed with their experience in mind.

Implementing assessments that reflect actual job roles and responsibilities gives candidates a realistic preview of the job. This reduces later dissatisfaction and turnover. Additionally, personality assessments that highlight traits such as confidence and empathy provide a more engaging candidate experience.

Companies can also strengthen their employer brand by showcasing their commitment to a fair and comprehensive hiring process. Providing resources like practice tests helps candidates feel better prepared and less anxious about the assessment, leading to a more positive perception of the company.

Common pitfalls in progressive assessments

Candidates often struggle with the cognitive abilities section, which requires strong analytical skills and problem-solving capabilities. The situational judgment tests can also be tricky as they assess empathy, decision-making, and customer service scenarios. Personality assessments can pose challenges as well, especially for those unsure how to present their personality traits aligned with the job role.

A significant issue is also misinterpretation of the test's format and expectations. Many find it daunting to navigate through various sections, such as verbal, numerical, and work style assessments. Lastly, some candidates might overlook the legal nuances of personality assessments or document redaction protocols, leading to compliance issues.

Strategies to overcome challenges

To tackle cognitive abilities assessments, candidates should engage in consistent practice with sample questions and mock tests. This helps enhance their analytical and problem-solving skills. For situational judgment tests, it is essential to practice empathy and customer service scenarios to develop a better understanding of role-specific challenges.

In personality assessments, being honest while demonstrating relevant personality traits like being a team player is crucial. Seeking guidance from study materials such as Job Test Prep can provide a realistic testing environment.

Understanding legal considerations, such as those around document redaction, is important for compliance. Utilizing a document redaction SDK can ensure adherence to required policies. Familiarity with each section's format will aid in navigating the assessments confidently and effectively.

Trends and innovations in employee assessments

There is a growing emphasis on AI-powered assessments —these tools analyze vast amounts of data to predict a candidate's job performance, ensuring a more objective and efficient selection process.



Personality assessments are evolving to include metrics like empathy and communication skills, which are crucial for roles in customer service and other people-centric positions.

Additionally, gamified assessments, which make the evaluation process engaging, are gaining popularity. They not only assess problem-solving skills but also gauge how candidates perform under pressure.

Organizations can prepare for the future by integrating cutting-edge technologies into their hiring processes. Investing in training for evaluators to accurately interpret new assessment metrics is crucial. This involves

understanding how to measure soft skills such as empathy and effective communication.

Moreover, companies should stay updated on legal requirements to maintain compliance and ensure fair assessment practices.

Encouraging candidates to focus on developing their personality traits, such as being team players and showing confidence, can also better prepare them for progressive assessments that look beyond technical skills.

The strategic value of progressive assessments

Progressive pre-employment assessments rigorously evaluate candidates on multiple fronts, including cognitive abilities, situational judgment, personality fit, and role-specific skills. This multifaceted approach not only helps in identifying the best match for specific roles but also reduces the risk of bad hires.

By investing in these assessments, companies can significantly enhance their recruitment processes. Consistent use of these tools leads to more informed decision-making, reducing turnover rates and ensuring employee retention.



Appropriate preparation and implementation of these assessments can streamline the hiring pipeline, saving time and resources. Furthermore, this approach bolsters team performance and aligns employee roles with their strengths, promoting a culture of efficiency and productivity. While Progressive is far from the only company using this approach, they’ve set a standard in terms of looking at candidates holistically and making sure they’re truly ready for the job.

Frequently Asked Questions

This section covers common inquiries related to the Progressive Pre-Employment Assessments, including differences from psychometric tests, benefits for small businesses, legal considerations, and the role of technology.

How do progressive assessments differ from psychometric testing?

Progressive assessments typically examine a candidate's ethical bias and personality traits. In contrast, psychometric tests focus on cognitive abilities and personality dimensions. The Progressive Pre-Employment Assessment includes verbal, numerical, and work style components, offering a broader evaluation spectrum.

Can small businesses benefit from implementing progressive assessment strategies?

Small businesses can gain significant advantages from adopting progressive assessment strategies. These assessments help identify candidates that align closely with the company’s values and culture, reducing turnover rates. Additionally, they provide insights into a candidate's ethical stance and work style, which are crucial for cohesive team dynamics.

What are the legal considerations when using pre-employment assessments?

Legal considerations include ensuring compliance with equal employment opportunity laws and avoiding discrimination based on race, gender, or disability. It is essential to validate the assessment tools and ensure they are scientifically proven to be fair. Companies must also maintain transparency about the purpose and usage of the assessments.

How can technology enhance the effectiveness of progressive assessments?

Technology can streamline the assessment process by allowing candidates to complete the tests remotely. Advanced analytics help in the accurate interpretation of results, ensuring a better match between the candidate and the job role. Many platforms offer practice tests that mirror the actual assessment, aiding in preparation and reducing test anxiety.

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