Activa 3G: Psycho-physiological aspect of Interface Design

A cognitive task analysis on learning to ride a scooter in two different age groups

Akash K Seth
12 min readOct 11, 2020

The following study stems from the major project I undertook in my 4th semester on Cognitive Ergonomics. Through this project, I have tried to understand how humans process information in a crucial environment where decision making and situation awareness are highly critical.


To critically analyze a product or a system from the perspective of human performance and behavior.


A cognitive task analysis extends conventional task analysis. It is utilized to gather information about-

  • Overt observable behavior, and
  • Covert cognitive functions

The combination of these two forms an integrated whole. What is that?

When a task is performed, it always starts off with an end goal. The goal to become proficient, an expert at the said task. Here, an expert refers to a person who is able to execute the said task autonomously i.e. without recalling each step, almost like a reflex.

For a task to be performed one needs access to knowledge. All knowledge starts off as Declarative knowledge, which when implemented into practice transforms into a skill or procedural knowledge.

Fig. 1 — Deliverance and forms of knowledge

Learning has never been easy. In medieval times there was the way of learning through apprenticeship. A novice would stay in the shadows of a master and learn through imitation. However, this was true only for jobs that had more physical aspects to them. Today our jobs require a more cognitive approach where machines are running our lives. And thus it is essential to define new techniques and interventions using CTAs to understand how the brain perceives information to carry out the said task.

A CTA mainly focuses on work activities which -

  • Have emphasized cognitive components (E.g.- Calculation, decision making, etc.)
  • Are in safety-critical environments
  • Are in a complex, changeable environment(E.g.-where tasks cannot be predetermined)

As mentioned earlier, declarative knowledge forms the foundation for procedural knowledge, but how does one acquire expertise when all knowledge starts off as declarative or verbal knowledge.

Adaptive Control of Thought theory (ACT) by Anderson, John. R. given in 1992 discusses the three stages of automaticity. This theory breaks down the learning model into three simple stages of — Cognition, association, and Autonomous.

Fig. 2 — The three stages of the automaticity model by Anderson, John. R.

In this model, the first stages of cognition involve gathering knowledge of the steps to be taken to perform the task. The second stage of association focuses on performing as well as deciding the steps to be utilized and discarding the ones that are not needed. Practicing the associative stage over and over leads to the autonomous stage where tasks are done without counting on the steps.

When mapped on a graph of practice against time, the learning curve tends to decrease non-linearly.

Fig.3 — The learning curve
  • The cognitive stage is declarative in nature which mostly comprises instructions. It’s a faster stage since the transition from verbal to motor skill is within a span of minutes to hours. The gains are dramatically high and so is the performance variability. An individual is at large aware of the learning through these observational cues.
  • The associative stage is mostly implicit, consisting of training. The motor functions are mostly involved where one practices for days, months, and years. Hence the slow process. The gains are smaller and the performance variability is low. It is at this stage the individual starts losing awareness and the transition is on a more covert cognitive level.
  • The autonomous stage is implicit in nature consisting of cues. At this stage, the individual has become so proficient at the task that only motor skills are at play and the person is largely unaware. There are little attentional resources needed, and there is decreased interference. The individual has finally acquired automaticity.

So to answer the question raised earlier about how does one become an expert? Here’s a simple way to explain that-

Expertise= Declarative knowledge + Application + Practice + Autonomization

Experts are characterized for being great problem solvers, completing complex tasks quickly, and have ample storage for declarative knowledge allowing them to retrieve information from long-term memory. Experts are highly sought after for their abilities in the roles of an instructor, an educator, a consultant, etc. However, expertise is like a coin and the flip side has negative consequences too.

Incompetence caused by expertise

Experts in the role of educators, tend to omit 70% of the critical information required for novices to be able to do a task replicating that of the expert. So the automaticity that we discussed interferes with the articulation of actually how a task is performed when described by an expert since they aren’t aware of their own actions and decisions. Also, they tend to underestimate the difficulty and time required for a novice to complete the task. At this stage, they fail to recognize that experts were once novices too.

Let us assume a case where an educator does not follow or has not been introduced to the concept of the stages of learning. There is no “CTA devised stepwise training manual” for them to refer to. Regardless, they anyhow have to do their job and move ahead. They fail to realize if the instructions were delivered to the learners and if they were able to perceive it like an expert’s mind.

Although the end goal has remained intact, i.e. — to be able to learn and master the task. These learners adopt all the possible means to fill the knowledge gap which might create a discrepancy. They might be able to figure out a superficial pattern that may function for a particular task but renders in vain on a regular basis.

This creates a chain when these novices are then appointed in the roles of educators and the cycle goes on. So are we at all producing experts or the system in itself is flawed to function?

For example, the millennials learned how to operate a smartphone without any assistance or external aid, all on their own owing to various factors.

Now their previous generation has seen a lot of technological advancement and is not particularly confident in using a smartphone. Hence they come to the millennial generation to be guided and instructed.

Although these young millennials often tend to underestimate the thinking processes and are not confident themselves on how to deliver this automated knowledge in their brains that they are largely unaware of.

This in turn creates confusion, tension, disharmony, and ultimately inhibits learning.

To understand this concept better let’s take into consideration a case study.


For this case study, the task chosen is riding a scooter. Unlike other tasks involving cognitive functions, this particular task comprises a greater risk, safety factor; and lies in a critical, complex and constantly changing environment. In this study, we will first be looking at a regular scooter rider and analyzing all the cognitive functions at play. Then this scooter rider is going to impart their knowledge to a novice, who is just getting started at learning and then compare the output to see the level of discrepancy. Further, there will be a comparison of the two personas highlighting the key aspects of the difference in cognitive functions. For this study let’s refer to the rider as User A and for the novice, Learner B.

User A

A little background — user A is a competent scooter rider, with an experience of over 6+ years of practice. They started learning the scooter at a young age owing to their curiosity and interest in wanting to do something they were strictly asked not to. With the right facilities available and the already existing sense of balance from riding bicycles, they were riding a two-wheeler within minutes of being given the instruction, obviously under supervision.

Over time they were riding two-wheelers frequently and eventually became proficient at it.

Now if one was to ask the user A about all the tasks involved in the riding a scooter they would shrug it off saying- “It’s as easy as riding a bicycle!”, which is true. This is for the cause that the process itself has become autonomous to them. They don’t need to recall all the steps, they just start doing it when required.

To understand the process better, user A was mapped using the Hierarchical task analysis (HTA) method.

Hierarchical Task Analysis

Fig.4 — Hierarchical Task Analysis of the task riding a scooter on User A

The preconditions or prerequisites were that the user knows how to ride a scooter, owns a fully functioning serviced scooter, and all the safety gear required. The entire task was divided into 4 steps which were further subdivided as follows —

  • Taking the scooter off of parking and getting seated
  • Turn on the ignition

In this step, the process diverges into two substeps due to two ways of turning the ignition on. It can either self start with the brakes held and pushing a button, or kick start in the event the battery runs dry.

In case the engine doesn’t start for the first time in either of the processes, then a common subtask is to pull the choke switch and repeat the process respectively.

  • Ride the scooter

This step is pretty straight forward in terms of substeps, however, it’s situational. One needs to adapt based on the situation. This is one of the most important subtasks since it is almost 70% of the entire task. Development is achieved over time, practice, and adaptation to the environment.

  • Stop and turn the ignition off

In this step the stopping part is covered in the previous step as well, so the only thing in addition is turning the ignition off. Followed by parking.

An experiment

Now the user A has to teach a novice learner B how to ride a scooter. This experiment was conducted at two different time intervals over a period of six months.

During phase one that lasted almost a week, the candidate was delivered with instructions followed by regular practice of 1–2 hours every day. In the second phase, the candidate was asked to recall all the instructions and explain it to the user A, and once qualified was allowed to proceed to ride the scooter supervised.


The goal of this experiment is to examine the differences in understanding and cognitive functions from the perspective of an expert — user A and a novice — learner B.

Learner B

Our candidate here is a 40 years young female, who recently has had an interest in wanting to learn how to ride a scooter. She has some previous knowledge from her lessons with her husband. A key component that has hindered her progress is the sense of balance since she doesn’t know how to ride a bicycle.

Memory is another component hindering her progress. She had received lessons at different points of time and every time she needed to start from scratch due to not being able to recall.

Also, the sounds and vibrations from the accelerating engine increase her sense of fear causing diverged attention and increased errors.

Cognitive Task Analysis (CTAs)

To identify the bottlenecks and better understand the cognitive functions, the learning procedure was mapped into four phases. Each of these phases was used to work on individual shortcomings and improve on them.

Phase 1 — Experiencing the vehicle

Task: The candidate was asked to move the scooter around without turning on the engine using only feet, in an empty service lane covering a distance of 100 meters.


  • To establish balance and a connection to the vehicle/system.
  • To get a feel, weight, and dimensions of the vehicle.
Fig.5 — Candidate pushing the vehicle forward with feet


  • Due to the curvature of the road, the weight of the vehicle was more inclined to one side demanding the candidate to apply an extra amount of counterforce causing fatigue and disbalance after moving a short distance.
  • The candidate had to be advised to use the handle to steer to aid against the vehicle’s weight and also to keep the vehicle moving forward.

Phase 2 — Understanding controls

Task: The scooter is parked on a double stand. Then the candidate is given a series of instructions, explaining the operations and simultaneously asked to execute the same.

Objective: To impart declarative knowledge and make the candidate understand the operations.

The candidate’s journey through this phase is mapped out into a tabular format. This journey is further subdivided into three parts namely- before ignition, during acceleration, and after.

Fig. 6 — The candidate is given the instructions on the control operations on the dashboard and executes them
Table 1: Tabulating the execution of operations


  • The candidate smoothly executes most of the operations in the ‘before and after stage’ with a little hesitation which they resolve by recalling.
  • In the middle stage, the candidate’s perception of the sound and vibrations from a racing engine is startling. It makes her anxious and worried.
  • While accelerating both of the candidate’s hands turn together.

Phase 3 — Assisted driving

Moving forward to the next phase was a giant leap from instructions to the association.

Task: The participant rides the scooter assisted by the pillion rider who provides for balance and support. Also, the pillion rider controls the brakes to prevent any mishaps.

Objective: To let the candidate ride the scooter aided by a pillion rider and observe the transition from theoretical knowledge to practical execution.


  • The candidate fearing the risk of falling keeps her feet close to the ground.
  • After a couple of days, the candidate puts her feet on the bottom mat, however, more of the control is still with the pillion rider.
  • Eventually, the pillion rider hands over the control to the candidate while they are not noticing.
  • Steering while in motion is still quite difficult for the candidate, often resorting to coming to a halting stop and turning.

Phase 4 — Testing

This next phase took place after a period of almost 5 months.

Task: The candidate is asked to give a walkthrough of all the controls and operations. And then to execute the task of riding the scooter assisted by a pillion rider.

Objective: The following exercise was conducted as a test to perceive the candidate’s memory retention, errors, mental processing, etc.

Fig.7 — Candidate giving a walkthrough of the controls and operations


  • The candidate remembers most of the operations and delivers the walkthrough with little confusion and hesitation.
  • The candidate is still agitated by the sound of an accelerating engine.
  • There is a significant improvement in the practice session with the pillion rider. The candidate has taken up a little more control of the vehicle.


In the following cognitive behavior study, it is important to note that the work activity is in a safety-critical, complex, and changeable environment. There isn’t a said group of methods that can be followed. The cognitive component needs to adjust and modify according to the situation and executed simultaneously. Failing to do so can result in mishaps.

It can also be stated that the learning curve as discussed previously has an undetermined factor i.e. the age difference. In the two users that were studied, the age difference is a generation gap.

While the younger user instantly learned the activity, the older user had difficulty. However, it is crucial to note that despite it, when the older user was taught the activity with certain devised steps and measures, they showed promising progress.

So coming back to the question asked previously about the status of the system of knowledge delivery, it can be concluded that when taken properly devised methods and approach to teaching anybody a task regardless of their generation, it is possible to achieve progress and eventually reach the expertise to be called an expert.