Mirjam Neelen & Paul A. Kirschner
On February 2, Guy Wallace posted this interview with Dick Clark.
Dick and Guy discuss various topics, such as multitasking, advance organisers, VR for unlearning, feedback, and AI for cognitive task analysis (CTA). However, the larger chunk of the interview is on motivation and specifically research on persistence in the context of motivation. That’s the part we’re summarising here.
Clark compares research on how to get better at persisting at a task (motivation) from a psychological and neuroscience perspective and explains the connection. He does that in such a rich and clear way, that we felt it was worth capturing it.
First, the psychological perspective.
The psychological perspective
Clark zooms in on the Belief-Expectancy-Control (BEC) framework (e.g., Clark & Saxberg, 2018 or a summary in Clark & Saxberg, 2019) – used to measure motivation – to explain what we know about the ‘persistence’ part of motivation.
When we talk about motivation, we’re actually talking about three different things:
- Starting a task on time so that you can finish it according to the requirements (whatever they are).
- Persisting at the task. Once you begin, to persist and make sure you’re not getting distracted or discouraged.
- Investing enough mental effort in the task to succeed.
The biggest difficulty is – no surprise, we think – persisting. People get distracted, daydream, get fed up with something, and so forth.
Clark quickly touches on multitasking here. He says it’s a trend to say that we don’t need to persist at a task and that we should multitask instead. This is a complete fad. It’s not just that you literally can’t multitask (instead, you switch from one task to another), it’s that when you try to do it, it causes problems. You become less efficient, you make more mistakes, and so on. ‘Multitasking’ isn’t just failing to persist at a task, it’s hurtful to the quality of your performance for that task and each other task you switched to.
How can we get better at persisting at a task?
There are three things that can help influence the way you can successfully persist at a task.
- Beliefs – This is about finding connections between the task at hand and things that you believe to be valuable (it’s not about what a manager or the organisation values but what you as performer of the task value). When you can make the connection between your own beliefs/values and the task at hand, it’s easier to persist. Don’t be fooled though, under‑confidence is a problem, but overconfidence can be a bigger problem. People who are overconfident might initially persist, but when they fail, they don’t take responsibility and point their fingers at something or someone else.
- Expectancy – The expectation that the task might be challenging yet you can succeed (self-efficacy). For managers: Giving people tasks that are too difficult and thinking that your people will then work harder is foolish; they won’t believe they’re able to succeed and hence will likely give up.
- Control emotions – The ability to control any negative emotions you might have about the task or in general.
This isn’t all. There’s a fourth factor in addition what’s in the BEC framework, namely the ability to control attention. Clark admits he was hugely surprised that this turned out to be the key factor that determines if you persist at a task or give up. There are various factors that influence your ability to control your attention.
- Stick to the task – This sounds simple but isn’t, especially because the myth that we as humans are able to multitask is still flourishing. We can’t! We really can’t. We are literally unable to multitask, we switch between tasks instead and it impacts our performance on all tasks-that-we-switch-to-and-fro negatively both with respect to accuracy (we make more mistakes) and speed (we work slower). Period.
- Ignore seductive details, including very pleasurable daydreaming.
- Hold details of the tasks that you’re performing in your mind. As soon as you stop persisting, all the memory patterns in your various memory systems (episodic, sensory, working) suffer from decay. When you return to the task, you have to re-establish them. When you have to do this, you’ve both negatively impacted the efficiency and the effectiveness of the task you’re trying to complete. The number of errors increases as well.
Because attention control seems to be so critical to motivation in being able to persist at a task, it would be great if we would measure it and find ways to help people get better at it.
Next, Clark switches to neuroscience as research findings in that field help connect the dots with measuring motivation and the role of attention control.
The neuroscience perspective
There’s evidence in neuroscience that the brain has three critical networks that operate during learning and performance.
Network 1: Executive control network – You use this network when you focus externally (e.g., when working on a task). It helps you set priorities, accomplish goals, manage your time, consider other points of view, ignore distractions, be flexible in your thinking, regulate your emotions, and so forth. What’s also fascinating about this network is that it helps you reframe negative experiences. The new explanation is plausible enough for you to soften negative emotions so that you’re better able to deal with throwbacks or disappointments.
Network 2: Default mode – This is the network you always ‘end up in’ when you’re not actively working on something outside of yourself, like a work task. It becomes active when you take a break, start daydreaming, begin internally focusing on your thoughts, emotions, analyze how much control you have over something you’re trying to achieve. It also has to do with making ethical and moral judgements. This network seems to be a bit ‘insecure’ in that it’s oversensitive to a lack of control. When you’re not succeeding, you feel negative emotions and start withdrawing because you feel you don’t have control. It’s deactivated when you’re working on a task. Don’t be fooled! This network is PRESENT. It takes up almost 90% of the energy your brain uses. This implies that 90% of the time you’re in this default mode or – better – the default mode uses that amount of energy (e.g., Raichle & Snyder, 2007).
Network 3: Salience network – This network functions as a switcher. It decides which ‘stimulus’ is most important to pay attention to at any given moment. It’s constantly looking for ‘value’ (benefits versus risk). It moves you from the executive control network to the default mode when it decides that something inside yourself is more important than the task you’re working on. It’s super important yet simple from the perspective that all it does is look for what it believes to be most valuable (based on our value/belief system).
See how you can connect the dots now when it comes to the things that influence our ability to persist at a task? The salience network is about your beliefs and values and determines where you’re going to focus our attention, the default mode plays a role in your expectancy around how capable you are to complete a task successfully (e.g., do you have enough control to be able to achieve success), emotion control – required to keep going – happens in the executive control network. And there’s the key that binds all these things together (the emotional/affective and cognitive part of motivation), which is attention control.
Suggestions for L&D
Given that attention control seems to be the key for your ability to motivate yourself to persist at a task, Clark suggests that learning professionals should familiarise themselves with beliefs/values, expectancy, and control models, (e.g., the BEC framework).
Another task for L&D is to learn how to measure people’s general ability to control their attention. There are instruments, but Clark thinks they need to be made more user friendly and adaptable to general populations in work settings. Who jumps on this opportunity to commoditise these? The military uses these already!
Last but not least, learning professionals should learn what we know about the strategies we can teach people to control their attention better. Keep an eye out for Clark’s work as he’s going to dive into this research and create a list of ‘attention control management strategies’ that the research has identified.
Let’s persist on learning more around how we can help people persist at their tasks so that we can all be more successful!
References
Clark, R. E., & Saxberg, B. (2018). Engineering motivation using the belief-expectancy-control framework. Interdisciplinary Education and Psychology, 2(1), 1-26. Retrieved from https://www.researchgate.net/profile/Bror_Saxberg2/publication/327948706_Engineering_Motivation_Using_the_Belief-Expectancy-Control_Framework/links/5bf4303ea6fdcc3a8de45121/Engineering-Motivation-Using-the-Belief-Expectancy-Control-Framework.pdf
Clark, R. E., & Saxberg, B. (2019). 4 Reasons Good Employees Lose Their Motivation. Harvard Business Review. Retrieved from https://hbr.org/2019/03/4-reasons-good-employees-lose-their-motivation
Menon, V., & Uddin, L. Q. (2010). Saliency, switching, attention and control: a network model of insula function. Brain structure and function, 214(5-6), 655-667.
Raichle, M. E., & Snyder, A. Z. (2007). A default mode of brain function: a brief history of an evolving idea. Neuroimage, 37(4), 1083-1090.
3-Star learning experiences 
This interview with Dick Clark is priceless! Thank you for publishing it.
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Great stuff! Much to learn from this. The BEC model has implications for so much. For example: “To persist, we need to hold details of the task in our minds” (from my notes on this vid). When attention wanders, brains can “lose state” quickly, and need to rebuild it. So, making rebuilding faster, should be a Good Thing.
When programming, I tell students to outline the structure of a program first, in comments. That helps them structure the task, and focus attention on one part of the task at a time. However, it should also help state restoration. When (not if) your mind wanders, you can quickly review the comments to rebuild state.
Just one implication of BEC for learning.
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