Hiring & Unconscious Behaviours, Why Assessments Should Allow People to Get ‘in the Zone’

Jiaying Law

People Scientist

image of a person who's unconscious behaviours are measured through a game-based assessment

While we are assessing our applicants, we all want our screening or assessment tools to perfectly and accurately tell us about their abilities. Sadly, here’s a not-so-fun fact: 

Not a single assessment is able to  100% accurately predict someone’s future performance. 

Even with the best assessments, things like social desirability, test anxiety, or test motivation could greatly affect its efficiency and accuracy. In addition to choosing a reliable and valid assessment, what we need to consider is how they can eliminate as much of these “noises” as possible. 

How do we do that? One way is making sure that our candidates can act naturally during the assessments, without thinking about other things or what is coming next. That is, the assessment needs to provide an environment where candidates can be themselves.

In this article, we will touch upon the topics below:

  • When do we tend to act naturally? – Being in the Flow
  • What conditions can increase the opportunity for us to enter the flow state?
  • How do gamified assessments/ game-based assessments help to provide an environment for cultivating flow experience?

Being in the Flow – the moment when our implicit mind takes charge

Do you remember moments when you were so into doing something you didn’t realise the time was running? The wind seemed to stop blowing and your behaviour occurred as naturally as your breathing. In those moments, you’re so involved in the tasks at hand until yourself and them have become one. Nothing else seems to matter.

Congrats! You’re “in the zone”!

Characteristics of Flow

This psychological state – Flow (a.k.a. optimal experience) – was introduced by Mihaly Csikszentmihalyi in the year of 1975, describing a state whereby people are extremely concentrated and being absolutely “absorbed” into the activity they go through at the moment (Csikszentmihalyi, 1990). 

During the flow state, a person can perform at their peak level, in which their cognitive resources are fully directed into mastering specific tasks (Csikszentmihalyi, 1990). Particularly, people would have the optimal experience towards those tasks and are intrinsically feeling rewarded by engaging with those tasks. They are temporarily removed from self-consciousness regarding concern for other things, such as thoughts from the past and worries for the future. 

The only thing occupying their mind is the present. 

An example for a piano player: When they are in the flow state, they do not worry about whether they would play a wrong note or what the response of the audience would be. They just “put their soul” into the music and you would expect a satisfying expression on their faces when the song finishes. 

Another example in the workplace: Imagine a colleague staring at their screen, being so immersed into it they couldn’t even hear you calling them several times. They are probably in the flow state where their attention is fully invested into what is going on on their screen. “It’s been a productive day!” could be their conclusion for the workday. 

Some other characteristics of the flow state include a sense of control over one’s own behaviour, distortion of temporal experience (change in time perception), feeling of effortlessness and ease, merging of self-awareness and actions (actions become spontaneous and they occur almost automatically) (Nakamura, & Csikszentmihalyi, 2002; Abuhamdeh, 2020). 

Flow in Our Brains

Such a unique experience is incredibly valuable to us, which has motivated researchers to figure out what is going on in our brains when we are experiencing flow (e.g., Dietrich, 2003, 2004; Ulrich et al., 2014). 

Let me first briefly introduce the two systems of cognitive processing: explicit and implicit systems (Dietrich, 2004). 

  • Explicit system (conscious): A rule-based system that is within our conscious awareness, which controls a higher-order of cognitive processes, such as planning, solving problems, strategic thinking etc. 
  • Implicit system (unconscious): A skill- or experience-based system that is outside of our conscious awareness, which helps us to automatically process incoming information when our conscious mind is fully occupied. 

The part in our brains called prefrontal cortex (PFC), which is in charge of higher cognitive functions such as self-reflective consciousness, memory, temporal integration and working memory, shows a decrease in activity while we are in the flow (Dietrich, 2003; Ulrich et al., 2014). This means that our explicit system is less active. Due to the fact that we simply do not have enough cognitive resources during reduced PFC processing, what follows next is the disappearance of self-consciousness, no worry of failure, a sense of timelessness, and no distractions (Dietrich, 2004). 

While our explicit systems are temporarily suppressed, our experience-based implicit system is taking charge. This is the time where our behaviour occurs outside the reach of our consciousness. With the automation of information processing, our actions are efficient and occur naturally based on our past experience (Moors & De Houwer, 2006). At the same time, our conscious awareness of effort putting into the activity is not on our radar anymore, contributing to the perception of ease during flow (Harris et al., 2017). 

What conditions can increase the opportunity for us entering the flow state?

Nakamura and Csikszentmihalyi (2002) has concluded the 3 main antecedentes for being in the flow:

Antecendent 1: Challenges x Skills

The first and foremost condition is that the tasks or activities should be perceived as demanding enough to be interesting, but not too difficult to cause frustration (Abuhamdeh, 2020). 

This means that the tasks’ difficulty and people’s ability should be a balanced ratio, in which people’s capability should match a decent amount of challenge within the tasks (Fong et al., 2015). If the balance is off, then we might have suboptimal experiences such as anxiety and boredom (Tse et al., 2020). That is, if an activity is too simple for our skills, then we would feel bored being in the activity. In the similar vein, if a task is too difficult for our ability, anxiety might knock on our doors when we are involved in the task. 

A very common example is within our career trajectory. Do you remember when you first stepped into your industry? I bet many of us start with something very small. As our career is evolving, we start seeking challenges because the initial tasks no longer provide us with sparks. This is because our skills are also getting mature during the path. 

In contrast, if we already started with something very difficult, then we could suffer from anxiety and self-blaming for not being competent enough. The only way to get ourselves out of this is to enhance our skills to keep up with the challenges. 

So, if we want to constantly pursue the optimal experience, then we need to enter the cycle of challenge-seeking and skill-building (See the graph below; Tse et al., 2020). The idea is to stay in the flow channel as much as possible to have the condition for cultivating a flow experience. There you go, the success formula for promoting your life satisfaction. 

Figure: Flow Theory by Csikszentmihalyi (1990), adapted from Cunha & Carvalho (2012)

Antecedent 2: Clear Proximal Goals

To be engaged in an activity, we first need to know the purpose and the direction of doing it. For instance, you might probably feel annoyed to answer a question knowing it doesn’t have a proper answer or to solve a maths question where you don’t understand what they ask. It is “meaningless” for us to even start with doing those, let alone being immersed in them. 

Thus, unless the activity itself has a clear rule to guide us or offer us a goal to pursue, we wouldn’t be able to fully dive into it (Chen et al., 1999). Try to recall the game you love to play. Don’t they all provide you with a goal to achieve? Be it completing levels, being at the first place, fighting enemies with teammates, and more.  

If you haven’t played games before, try to think of the sport you’ve been doing. We need to score goals in football to win, pass the finish line to complete a marathon or reach the top for rock climbing. All these activities have clear rules to follow and ultimate goals to achieve. 

During the process of achieving the final goal, there are plenty of small goals for each step. Just like a software engineer developing a new application. Each line of the code has its own meaning and is contributing to building up the whole application. Also with the chess player. Each of their moves is dedicated to the win at the end. It is important for us to progressively realise the next small goal to be constantly engaged in the activity, leading to the attainment of the ultimate goal (Dietrich, 2004).

Antecedent 3: Immediate Feedback

Apart from the mini goals, we also need to know how much we have accomplished, how well we have done, and are we on the right track for activity proceeding (Chen et al., 1999). This is when immediate feedback comes into play. 

Immediate feedback of our actions provide us real time information to determine our current status towards the mini goals at hand. Whether we are successful or not, immediate feedback conveys a symbolic message to our brains: either we stay at the same goal or carry on to the next step (Csikszentmihalyi, 1990).

Looking at the software engineers’ example again. They could run the code every time they have completed a row, and they will know if the code is correct or not straight away. After getting feedback, they would know if they can proceed to the next line or to adjust the current line. That is the way to stay involved in building applications. 

Going back to the piano player’s example. A musician hears right away whether they are playing the right note at the very moment they press the keyboard. If it is right, then they are good. If wrong, then they will find a way to adapt what note to play next to complete the song (Dietrich, 2004). 

Immediate feedback delivers our current status and feeds the information to our implicit system as an instruction of what to do next. It builds a sequence with each step and keeps us engaging in the activities upon the last. For instance, Buil and colleagues (2018) found that if students know about how well their group is performing in real time, their engagement in a business simulation game would tend to increase. 

How gamified assessments/ game-based assessments(GBA) help to provide an environment for cultivating flow experience?

No matter whether it is traditional aptitude tests or personality tests, they often receive criticisms about low candidate engagement. Therefore, there might be some “noises” that hinder the accuracy and efficiency of the test itself. 

  • For traditional aptitude tests, they are categorised as maximum performance tests, in which they aim to get an idea about how high the candidates’ abilities are. For this reason, the tests could oftentime create anxiety for candidates as the challenge might be beyond their abilities. 
  • For personality tests, they could be quite lengthy and ask vague questions without providing clear context (Morgeson et al., 2007). This might be the reason why the candidate engagement is low because they have not given clear proximal goals during the test. 

Compared to the traditional assessments, gamification of assessments can open plenty of doors to incorporate features that could promote candidate engagements and enjoyment (e.g., Cowley et al., 2018; Fetzer et al., 2017; Bouvier et al., 2014; Bakhanova et al., 2020). Here’s some examples on how we can use the flow theory to enhance engagement, ultimately to induce as much natural behaviour as possible. 

Adaptive levels according to candidates’ ability

Unlike traditional assessments that have the same set of questions for everyone, GBA can include adaptive features for candidates. For example, the test could be ended if the candidate has failed a specific level twice in a row. It could maintain the difficulty and skill ratio, and make sure the candidate stays in the flow channel.  

Design clear rules and goals

The interactive nature of GBAs allows more opportunities to guide candidates during the tests. For example, most of the GBAs have a clear final goal or mini goals in between to lead candidates on how they need to behave. The scores or the behaviour they accumulated during the GBAs will contribute more or less to the final outcome.

Thus, compared to traditional assessments, GBAs are more feasible for building a sequence of actions to keep candidates engaged until the end. 

Immediate feedback

Along the same line as the previous point, GBA can give feedback on how well players did on specific tasks in real time. For example, if players make a wrong move in a problem-solving-related GBA, a chat bubble could pop up and let them know they’re wrong. In this case, candidates can acknowledge their current status and adjust their strategies in the next trial. 

Conclusion

To eliminate the “noises” that could hinder accuracy of assessments, one possible way is to create a flow experience for candidates. Flow is an optimal experience when people are fully absorbed into an activity. Our brains switch from explicit systems to implicit systems while we are in the flow.

To be in the flow state, the task difficulty and our ability should be in a balanced ratio while the tasks provide clear proximal goals and immediate feedback. GBA opens a lot of doors to incorporate those conditions into the process and therefore creates more opportunity for flow to occur. 

References

Abuhamdeh, S. (2020). Investigating the “flow” experience: Key conceptual and operational issues. Frontiers in psychology, 11, 158. https://doi.org/10.3389/fpsyg.2020.00158 

Bakhanova, E., Garcia, J. A., Raffe, W. L., & Voinov, A. (2020). Targeting social learning and engagement: What serious games and gamification can offer to participatory modeling. Environmental Modelling & Software, 134, 104846. https://doi.org/10.1016/j.envsoft.2020.104846 

Bouvier, P., Lavoué, E., & Sehaba, K. (2014). Defining engagement and characterizing engaged-behaviors in digital gaming. Simulation & Gaming, 45(4-5), 491-507. https://doi.org/10.1177/1046878114553571

Buil, I., Catalán, S., & Martínez, E. (2018). Exploring students’ flow experiences in business simulation games. Journal of computer assisted learning, 34(2), 183-192. https://doi.org/10.1111/jcal.12237

Chen, H., Wigand, R. T., & Nilan, M. S. (1999). Optimal experience of web activities. Computers in human behavior, 15(5), 585-608. https://doi.org/10.1016/S0747-5632(99)00038-2 

Cowley, B., Charles, D., Black, M., & Hickey, R. (2008). Toward an understanding of flow in video games. Computers in Entertainment (CIE), 6(2), 1-27. https://doi.org/10.1145/1371216.1371223 

Csikszentmihalyi, M., & Csikzentmihaly, M. (1990). Flow: The psychology of optimal experience (Vol. 1990). New York: Harper & Row.

Cunha, J. C., & Carvalho, S. (2012, July). Experienced Emotions through the Orff-Schulwerk Approach in Music Education-A Case Study Based on Flow Theory. In the Proceedings of the 12th International Conference on Music Perception and Cognition and the 8th Triennial Conference of the European Society for the Cognitive Sciences of Music

Dietrich, A. (2004). Neurocognitive mechanisms underlying the experience of flow. Consciousness and Cognition, 13(4), 746-761. https://doi.org/10.1016/j.concog.2004.07.002 

Fetzer, M., McNamara, J., & Geimer, J. L. (2017). Gamification, serious games and personnel selection. In H. W. Goldstein, E. D. Pulakos, J. Passmore, & C. Semedo (Eds.), The Wiley Blackwell handbook of the psychology of recruitment, selection and employee retention (pp. 293–309). Wiley Blackwell. https://doi.org/10.1002/9781118972472.ch14 

Fong, C. J., Zaleski, D. J., & Leach, J. K. (2015). The challenge–Skill balance and antecedents of flow: A meta-analytic investigation. The Journal of Positive Psychology, 10, 425–446. https://doi.org/10.1080/17439760.2014.967799 

Harris, D. J., Vine, S. J., & Wilson, M. R. (2017). Neurocognitive mechanisms of the flow state. Progress in brain research, 234, 221-243. https://doi.org/10.1016/bs.pbr.2017.06.012 

Moors, A., & De Houwer, J. (2006). Automaticity: a theoretical and conceptual analysis. Psychological bulletin, 132(2), 297. https://doi.org/10.1037/0033-2909.132.2.297 

Morgeson, F. P., Campion, M. A., Dipboye, R. L., Hollenbeck, J. R., Murphy, K., & Schmitt, N. (2007). Reconsidering the use of personality tests in personnel selection contexts. Personnel psychology, 60(3), 683-729. https://doi.org/10.1111/j.1744-6570.2007.00089.x  

Nakamura, J., and Csikszentmihalyi, M. (2002). The concept of flow. In C. R. Snyder and S. J. Lopez(Eds), Handbook of Positive Psychology (P89-105), Oxford University Press.

Pilke, E. M. (2004). Flow experiences in information technology use. International journal of human-computer studies, 61(3), 347-357. https://doi.org/10.1016/j.ijhcs.2004.01.004 

Tse, D. C., Nakamura, J., & Csikszentmihalyi, M. (2020). Beyond challenge-seeking and skill-building: Toward the lifespan developmental perspective on flow theory. The Journal of Positive Psychology, 15(2), 171-182. https://doi.org/10.1080/17439760.2019.1579362 

Ulrich, M., Keller, J., Hoenig, K., Waller, C., & Grön, G. (2014). Neural correlates of experimentally induced flow experiences. Neuroimage, 86, 194-202. https://doi.org/10.1016/j.neuroimage.2013.08.019 

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