similarities of decision making and problem solving

Decision Making vs. Problem Solving

What's the difference.

Decision making and problem solving are two closely related concepts that are essential in both personal and professional settings. While decision making refers to the process of selecting the best course of action among various alternatives, problem solving involves identifying and resolving issues or obstacles that hinder progress towards a desired outcome. Decision making often involves evaluating different options based on their potential outcomes and consequences, while problem solving requires analyzing the root causes of a problem and developing effective strategies to overcome it. Both skills require critical thinking, creativity, and the ability to weigh pros and cons. Ultimately, decision making and problem solving are interconnected and complementary processes that enable individuals to navigate complex situations and achieve desired goals.

Further Detail

Introduction.

Decision making and problem solving are two essential cognitive processes that individuals and organizations engage in to navigate through various challenges and achieve desired outcomes. While they are distinct processes, decision making and problem solving share several attributes and are often interconnected. In this article, we will explore the similarities and differences between decision making and problem solving, highlighting their key attributes and how they contribute to effective problem-solving and decision-making processes.

Definition and Purpose

Decision making involves selecting a course of action from multiple alternatives based on available information, preferences, and goals. It is a cognitive process that individuals use to make choices and reach conclusions. On the other hand, problem solving refers to the process of finding solutions to specific issues or challenges. It involves identifying, analyzing, and resolving problems to achieve desired outcomes.

Both decision making and problem solving share the purpose of achieving a desired outcome or resolving a particular situation. They require individuals to think critically, evaluate options, and consider potential consequences. While decision making focuses on choosing the best course of action, problem solving emphasizes finding effective solutions to specific problems or challenges.

Attributes of Decision Making

Decision making involves several key attributes that contribute to its effectiveness:

• Rationality: Decision making is often based on rational thinking, where individuals evaluate available information, weigh pros and cons, and make logical choices.
• Subjectivity: Decision making is influenced by personal preferences, values, and biases. Individuals may prioritize certain factors or options based on their subjective judgment.
• Uncertainty: Many decisions are made under conditions of uncertainty, where individuals lack complete information or face unpredictable outcomes. Decision makers must assess risks and make informed judgments.
• Time Constraints: Decision making often occurs within time constraints, requiring individuals to make choices efficiently and effectively.
• Trade-offs: Decision making involves considering trade-offs between different options, as individuals must prioritize certain factors or outcomes over others.

Attributes of Problem Solving

Problem solving also encompasses several key attributes that contribute to its effectiveness:

• Analytical Thinking: Problem solving requires individuals to analyze and break down complex problems into smaller components, facilitating a deeper understanding of the issue at hand.
• Creativity: Effective problem solving often involves thinking outside the box and generating innovative solutions. It requires individuals to explore alternative perspectives and consider unconventional approaches.
• Collaboration: Problem solving can benefit from collaboration and teamwork, as diverse perspectives and expertise can contribute to more comprehensive and effective solutions.
• Iterative Process: Problem solving is often an iterative process, where individuals continuously evaluate and refine their solutions based on feedback and new information.
• Implementation: Problem solving is not complete without implementing the chosen solution. Individuals must take action and monitor the outcomes to ensure the problem is effectively resolved.

Interconnection and Overlap

While decision making and problem solving are distinct processes, they are interconnected and often overlap. Decision making is frequently a part of the problem-solving process, as individuals must make choices and select the most appropriate solution to address a specific problem. Similarly, problem solving is inherent in decision making, as individuals must identify and analyze problems or challenges before making informed choices.

Moreover, both decision making and problem solving require critical thinking skills, the ability to evaluate information, and the consideration of potential consequences. They both involve a systematic approach to gather and analyze relevant data, explore alternatives, and assess the potential risks and benefits of different options.

Decision making and problem solving are fundamental cognitive processes that individuals and organizations engage in to navigate through challenges and achieve desired outcomes. While decision making focuses on selecting the best course of action, problem solving emphasizes finding effective solutions to specific problems or challenges. Both processes share attributes such as rationality, subjectivity, uncertainty, time constraints, and trade-offs (in decision making), as well as analytical thinking, creativity, collaboration, iterative process, and implementation (in problem solving).

Understanding the similarities and differences between decision making and problem solving can enhance our ability to approach complex situations effectively. By leveraging the attributes of both processes, individuals and organizations can make informed choices, address challenges, and achieve desired outcomes.

Comparisons may contain inaccurate information about people, places, or facts. Please report any issues.

Problem Solving vs Decision Making: Difference and Comparison

Every person is, without a doubt, influenced by the worst-case situation for a significant period. Another difficult issue is not understanding the distinction between problem-solving and decision-making.

Decision-making and problem-solving are both psychological words that are frequently used interchangeably. Furthermore, it should be emphasised that these two terms are not interchangeable and are not synonymous.

Key Takeaways Problem-solving involves identifying and resolving issues or obstacles, while decision-making involves choosing different options or courses of action. Problem-solving is used to address a specific issue or challenge, while decision-making can be used in various contexts, such as business, personal life, or government. Problem-solving involves a step-by-step process of analysis and evaluation. At the same time, decision-making can be influenced by various factors such as personal values, emotions, or external pressures.

Problem Solving vs Decision Making

Problem-solving is the process of identifying and resolving a problem or challenge that is preventing an individual or organization from achieving its goal. Decision-making involves choosing a course of action or solution. This process can be complex and involve a variety of factors.

Problem-solving is a complex process that entails in-depth analysis. The identification of an issue is the first step in the problem-solving process. The main goal of problem-solving is to find the best solution.

Problem-solving is coupled with a specific goal. The results of problem-solving should be solution-oriented. The techniques and roads to resolution remain unknown when it comes to problem-solving. The purpose of problem-solving is to fix the problem or issue.

The process of decision-making leads to a final opinion and a course of action. The identification of opportunities is part of the decision-making process. The goal of the decision-making process is to avoid potential difficulties.

When making decisions, a variety of options are explored. The decision-making process can have a variety of results. The paths adopted in the event of decision-making are structured. The objectives of decision-making are unrelated to the resolution of a problem or issue.

Comparison Table

What is problem solving.

Problem-solving is a technique that can be used to solve a problem. When it comes to problem-solving, making the appropriate judgments is critical to reaching a specific outcome.

Problem-solving is a difficult process that entails extensive research. Identifying a difficulty is a common step in the problem-solving process.

In simple words or layman’s terms, problem-solving is simply solving problems, as the name suggests. Here, either an individual or a group tries to solve a problem in this process.

This involves high analytical skills for reaching better and faster solutions. This process also includes gathering information, facts and following or working parallel with human intuition .

The primary goal of problem-solving is to find the best solution possible. In general, problem-solving is linked to a specific goal. Problem-solving results must be solution-oriented.

The techniques and roads to resolution are unknown in the case of problem-solving. The purpose of problem-solving is to resolve the problem or issue.

What is Decision Making?

Making a decision is seen to be a procedure . Depending on the situation, the decision-making process may or may not entail problem-solving.

The decision-making process culminates in the formulation of a conclusion and a plan of action. Identifying opportunities is an important part of the decision-making process.

Decision-making focuses on the actions, ways and alternatives that are used to solve a particular problem. This is also a result of cognitive function.

Sometimes a psychological aspect of an individual is taken into consideration while stressing about making decisions. The needs and wants are taken care of. This process can also be considered as continuous interaction with the surrounding environment.

The goal of the decision-making process is to avoid any potential issues. While making decisions, various types of options are explored. Decision-making can have a variety of results.

The paths that are taken in decision-making are structured. The decision-making goals have nothing to do with resolving a problem or issue.

Main Differences Between Problem Solving and Decision Making

• Problem-solving can be considered a method. On the other hand, decision-making is considered a process.
• At the time of problem-solving, taking the right decisions is important to reach out a certain conclusion. On the other hand, the decision-making process sometimes includes solving problems and sometimes does not.
• The method of problem-solving is complex and includes deep analysis. On the other hand, the decision-making process leads to taking a final opinion and a course of action.
• The method of problem-solving involves the identification of a challenge. On the other hand, the decision-making process involves identifying opportunities.
• Creating the right solution is an important motive for problem-solving. On the other hand, avoiding potential problems is the motive of the decision-making process.
• Problem-solving is associated with a clear objective. On the other hand, different types of options are considered while taking decisions.
• The outcomes coming from problem-solving should be solution-driven. On the other hand, the outcomes of the decision-making can vary.
• In the case of problem-solving, the ways and paths to resolution are not known. On the other hand, in the case of decision-making, the paths taken are structured.
• The goal of problem-solving is to correct the issue or problem. On the other hand, the goals associated with the decision making is not related to the solving of an issue or problem.

• https://scholarsbank.uoregon.edu/xmlui/bitstream/handle/1794/22321/slovic_189.pdf?sequence=1
• http://www.sci.brooklyn.cuny.edu/~kopec/cis718/fall_2005/2/Rafique_2_humanthinking.doc

Last Updated : 11 July, 2023

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Chara Yadav holds MBA in Finance. Her goal is to simplify finance-related topics. She has worked in finance for about 25 years. She has held multiple finance and banking classes for business schools and communities. Read more at her bio page .

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20 thoughts on “problem solving vs decision making: difference and comparison”.

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I found the detailed analysis of problem-solving’s goal of correcting issues and the structured paths of decision-making to be particularly insightful, shedding light on their differing functions.

Indeed, the article’s delineation of these two processes clarifies how problem-solving involves methodical approaches towards resolution, while decision-making focuses on structured choices and actions.

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I agree, the table neatly summarizes the key factors of each process, making it easier to grasp the nuances and interconnectedness of problem-solving and decision-making.

I appreciate the detailed explanations of both problem-solving and decision-making processes, which are crucial elements in various aspects of life and business.

The article’s emphasis on the goal-oriented nature of problem-solving and the opportunity identification in decision-making is quite enlightening.

The distinction between problem-solving’s solution-driven outcomes and the structured paths taken in decision-making effectively portrays the dissimilarity in their objectives.

Indeed, understanding the deep analysis and unknown techniques of problem-solving, as opposed to the structured paths and goal of avoiding potential problems in decision-making, provides valuable insights.

Absolutely, the article makes it clear that these two processes have different motives and ultimate goals, shedding light on their multifaceted nature.

The detailed description of problem-solving and decision-making processes provides a comprehensive understanding of their intricacies and interplay in various contexts.

Absolutely, the article’s clear distinction between the two processes and the comparison table help in elucidating the methods and outcomes involved in problem-solving and decision-making.

The article effectively portrays the aims and mechanisms of problem-solving and decision-making, emphasizing the importance of clear identification and identification of opportunities in each process.

This article provides a clear distinction between problem-solving and decision-making, highlighting the different processes and goals involved.

Absolutely, the comprehensive comparison table is especially helpful in summarizing the disparities between problem-solving and decision-making.

I couldn’t agree more. The identification of opportunities in decision-making is a key difference, showing how it’s not just about solving problems, but also about making choices.

The article’s detailed explanation of problem-solving and decision-making sheds light on their distinctive motives, processes, and outcomes, providing valuable insights into their complex nature.

I couldn’t agree more. The article effectively highlights how problem-solving aims to resolve specific issues, while decision-making focuses on choosing alternatives and preventing potential problems.

Absolutely, the comprehensive descriptions underscore the different considerations and end goals of problem-solving and decision-making, elucidating their roles in addressing challenges and formulating solutions.

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Making the Difference: Problem Solving vs Decision Making

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Do you ever find yourself stuck between a rock and hard place, unable to decide what the best course of action is?

I have. Whether it’s what desk to put in our new conservatory space (and I’ll tell you what we ended up deciding later), or who to invite to meetings, or managing to order everyone else’s food and then getting so overwhelmed with having made decisions all day for all the people that I couldn’t choose anything for myself.

I left the café with nothing for me and ended up with a couple of slices of peanut butter toast at home.

Making decisions can be difficult for even the most experienced project managers. But before making any decision, it’s important to understand the difference between problem solving and decision making.

Ready to get into it?

Problem solving involves diagnosing issues that arise during projects while decision making requires taking appropriate steps based on those diagnoses. While they may appear similar at first glance, there are key differences in how each process should be approached – understanding these differences will help you make more informed decisions!

Let’s explore both processes as well as their similarities and differences.

What is problem solving?

You’ve been solving problems since you were a baby: how to stand up, how to get your socks off, how to get your parents to bring you your favorite sippy cup.

As an adult, we solve problems every day at work and at home.

So it probably sounds a bit odd to want to define problem solving before we go any further. Surely we all know what we are talking about as we do it all the time?

Humor me. Problem solving is the process of identifying and analyzing a problem, generating potential solutions, and selecting the best solution to address the issue. It involves breaking down complex problems into smaller components and then finding ways to solve them.

The problem solving process

If you think that description sounds linear, then you’d be right. Problem solving fits neatly into a process, one that we don’t even know we’re following most of the time.

The problem solving process typically consists of four steps:

• Identify the problem
• Generate possible solutions
• Evaluate each option
• Select an appropriate course of action.

That does make it sound easy. Wicked problems need a slightly different approach (PMI has a problem solving training course that is brilliant and will help with that).

But for now, let’s stick with a high-level approach that works for most problems.

1. Identify the problem

First, it’s important to understand what caused the issue in order to determine how best to resolve it.

You’d be surprised at how many managers don’t bother to find the root cause of the problem to truly understand it. Use techniques like the 5 Whys or an Ishikawa diagram to dig down into what the problem actually is.

2. Generate possible solutions

Brainstorming is one way to come up with different ideas for potential solutions. You could also interview experts, review lessons learned or innovative solutions from previous projects, research what the rest of your industry is doing or consult customers on what they’d like to see. There are no silly ideas at this point!

Choose the creative approach that gets you a range of options to review.

Read next: How to improve problem solving with lessons learned.

3. Evaluate each option

Once you have several options to consider, you can evaluate each one based on its effectiveness and cost before deciding which one is most suitable for your situation.

Use pairwise prioritisation, multi-criteria decision making or analytical hierarchy process (AHP) to help with the evaluation.

4. Select an appropriate course of action

Now you’ve got all the options for solving your problem, you can actually solve it by choosing a course of action that will sort it out. This is where decision making comes in. in this step you make the decision.

Finally, implement your chosen solution and monitor its progress over time so that any necessary adjustments can be made as needed.

Benefits of problem solving skills

There are many benefits associated with having effective problem solving skills.

These include improved decision making abilities (more on that in a minute), increased creativity, better communication skills, greater confidence when faced with challenging situations, enhanced ability to think critically, more efficient use of resources, improved relationships between colleagues or team members due to shared understanding of goals and increased productivity levels due to fewer mistakes being made during projects or tasks.

(Breathe. That was a long sentence, sorry.)

All these advantages make problem solving an invaluable skill in both personal life and professional life scenarios.

What is decision making?

Basically, decision making is the process of selecting a course of action from a number of alternatives. It involves gathering information, weighing options, and choosing the best option for achieving a desired outcome.

But how is that different to problem solving?

Decision making is the process of doing Step 4 of the problem solving process. It’s the choice making, option selection, conclusion of the analysis and thinking.

It’s decisive (duh), purposeful, specific. It removes the ambiguity of the ‘what do we do?’ and helps the team move towards the ‘OK, how do we do that?’

It brings action to a situation.

The decision making process

There is a simple method for decision making too, although the actual decision itself might be tough to make.

• Identify that a decision is required
• Ensure you have the data to make the decision
• Make the decision
• Tell whoever needs to implement the decision

1. Identify that a decision is required

The decision-making process typically begins with identifying what decision needs to be made. Are you making the right decision, or is there something else, deeper, different that is really what’s required?

In this step you also want to identify who is making the decision. That could be your project sponsor, a panel, you by yourself, a committee or whoever. Getting this step clear saves headaches later.

2. Ensure you have the data to make the decision

Do you have all the info you need to make the decision? If not, get it.

When decisions are made quickly but thoughtfully, they can save time and resources while still producing quality results.

Major decisions need more time spent on this step to make sure you understand all the variables.

3. Make the decision

After considering all potential solutions, it’s time to make a choice based on what will yield the best results for everyone involved.

This is the hard part: make the decision! The person or people responsible for this should weigh up the data and use their professional judgement to choose the right course of action. Decision trees can be useful here to avoid unconscious bias (or conscious bias!).

Obviously this is harder for complex decisions. What vendor to choose for a 3-year outsourcing arrangement is harder to decide than what venue to book for a team away day.

4. Tell whoever needs to implement the decision

Great – you’ve made the call and know what to do, but does the rest of the team? Don’t keep the decision to yourself!

Make sure whoever needs to know the next steps is aware that the decision has been made so they can implement it and take the right action.

Having confidence in decisions leads to greater trust between team members and better collaboration overall, which can lead to improved project outcomes over time. Well-made decisions often create opportunities for growth within teams by allowing them to learn from their mistakes as well as their successes along the way.

Similarities between problem solving and decision making

Problem solving and decision making sound very similar, right?

Well, that is true. Both processes involve gathering information, analyzing it, and coming up with solutions or courses of action. They both require critical thinking skills to identify potential solutions or options that are most likely to be successful.

The processes use a similar flow

Both processes involve identifying a problem or issue, researching possible solutions, evaluating those solutions based on criteria such as cost-effectiveness or feasibility, selecting an option from among the available choices, implementing the chosen solution, and you’d also want to monitor its effectiveness over time.

The process can be iterative if necessary; if one solution does not work out as expected then another may need to be tried until a satisfactory outcome is achieved.

They both produce a satisfactory solution

Problem solving and decision making usually lead to some kind of action being taken in order to address a given issue or situation. Problem solving often involves finding creative solutions for complex problems, while decision making typically entails selecting a course of action from several possibilities after carefully evaluating each option’s advantages and disadvantages.

But ultimately, the goal is for something positive (or at least neutral) to come out of the helpful process so that whatever challenge was initially presented can be effectively addressed.

Despite being so similar you could pretty much interchange them in some circumstances, there are some differences.

Differences between problem solving and decision making

Although they have similarities in terms of the process used to come up with a solution, their goals differ significantly.

Process goals are different

The goal of problem solving is to find a solution to an existing issue. It involves identifying the cause of a problem and then finding ways to address it. Problem solving often requires input from multiple stakeholders who can provide different perspectives on how best to solve the issue at hand.

On the other hand, decision making focuses on choosing the best option from multiple alternatives. This could include selecting between competing products or services or deciding which strategy will be most effective for achieving certain objectives.

In other words: decision making doesn’t necessarily mean there is a problem. We make decisions every day about small things and big things, but they aren’t all problems that need the creative step of solutioning.

Sometimes a decision just needs to be taken and the options are clearly known.

They require different stakeholders

Another key difference between problem solving and decision making is that while problem solving typically requires input from multiple stakeholders, decision making is usually done by one individual or group who has access to all relevant information needed for the decision-making process.

To give you an example. Let’s say on a technical project the development team hit a problem. They have to bring in various subject matter experts to research and identify the parameters involved. They consult, brainstorm and debate. It’s a group effort, and it’s likely to end in a solution.

However, if I need my project sponsor to choose between two risk treatments, I’ll take him my recommendation and a summary of options and he’ll simply choose. Done.

Decisions are made based on what is known about a situation rather than relying on external opinions or advice when trying to make an informed choice about what course of action should be taken next.

They produce different results

The nature of both processes also differs in terms of the types of solutions they produce. Problem solving typically results in creative solutions that can be implemented over time, while decision making produces immediate choices from among existing alternatives without necessarily creating something new or unique.

Both processes involve the identification of a problem or issue, the collection of information to evaluate possible solutions, and an analysis of potential outcomes. The main difference between them is in their goals: problem solving seeks to identify the root cause of an issue and develop a solution that will address it; decision making focuses on selecting from among available options.

Both processes require careful consideration of facts and opinions before any action is taken. Problem solving often involves more people than decision making as it requires collaboration to identify underlying causes and brainstorm potential solutions. Decision makers may consult with others for input but ultimately make decisions independently based on their own judgment.

Still got a question?

What is the difference between decision and decision making.

A decision is the act of making a choice between two or more alternatives. Decision making is the process by which decisions are made. It involves gathering information, analyzing data, evaluating alternatives and choosing a course of action based on this analysis. The outcome of the process is the decision. The decision-making process also includes monitoring progress to ensure that goals are being met and taking corrective action if needed.

What is the importance of problem-solving and decision making?

Problem-solving and decision making are essential skills for project managers and managers in general. The processes keep work moving by making sure problems get solved and decisions get made so team members are not blocked from finishing their tasks.

What are the steps in problem-solving and decision making?

Problem-solving and decision making involve a series of steps that can help ensure the best possible outcome. The first step is to identify the problem or opportunity, then analyze it by gathering relevant information and evaluating potential solutions. After considering all options, select an appropriate solution and develop an action plan for implementation. Finally, monitor progress to ensure success and make necessary adjustments along the way. By following these steps, project managers can effectively manage projects while minimizing risks and maximizing results.

Before you go…

Sometimes there isn’t a right decision – it’s simply important to make a decision. As for the desk, in the end, we used a piece of furniture we already had upstairs and didn’t buy one at all.

I spent a morning measuring and researching options, and I’ll never get that time back, but that’s OK.

As a leader, you should be skilled at solving problems and making decisions, and the processes that support them. However, you don’t have to be doing all the solving and making all the calls yourself. As long as you facilitate the process and get the right people in the room, you can step back and let the experts do their thing.

Let the right people do the work and create an environment where your projects move forward because everyone’s got what they need to keep things moving.

Project manager, author, mentor

Elizabeth Harrin is a Fellow of the Association for Project Management in the UK. She holds degrees from the University of York and Roehampton University, and several project management certifications including APM PMQ. She first took her PRINCE2 Practitioner exam in 2004 and has worked extensively in project delivery for over 20 years. Elizabeth is also the founder of the Project Management Rebels community, a mentoring group for professionals. She's written several books for project managers including Managing Multiple Projects .

Problem Solving Vs Decision Making: An In-depth Comparison

Problem-solving and decision making are two of the most essential aspect of any work or job. In a corporate field, you often have to face problems. Hence, you have to be smart enough to analyze data, find adequate problems, and do something about the situation.

Also, decision-making is part and parcel of our life. It can be personal or professional. But taking essential decisions based on logic and thoughts can be challenging.

However, there are really some differences between problem-solving and decision making. And knowing these differences will let you differentiate them in an easy way.

So, let’s start exploring this side-by-side comparison of Problem-solving and decision making.

Table of Contents

What is a problem-solving skill?

Problem-solving means identifying a problem, examining it, taking valuable inputs, and trying to reach a solution based on data and logic. A problem solver brainstorms the problem and then tries to reach a solution. There are some steps of problem-solving.

Acknowledging the problem

The first step is to acknowledge the problem and collect valuable data related to the problem.

The most important part of problem-solving is to analyze the problem based on the data and find questions on that problem.

Finding multiple solutions

Any problem can be solved in different ways. But to get to the best result, you have to choose the most effective one.

Evaluation and decision making

After evaluating all the solutions, you can choose the best solution for you. Again the solution should be based on facts and logic so that the chances of getting it right will be high.

What is decision-making skill?

Decision-making is the last step of problem-solving. Decision-making is more of a process. It is the process to choose a solution based on your knowledge, analyzing the data, gathering facts, developing logic, and finally with a touch of wisdom.

The decision-making process may vary from Organization to Organization. A decision can be taken in different methods. Some of them are discussed below:

Discussion based decision

In this method, a group or team discusses possible solutions and then agrees on one particular decision. This type of decision-making can take time and can result in disputes of opinions.

Voting based decision

This method also considers multiple decisions, but it is different from discussion-based decisions. In a voting-based decision, there won’t be any discussion. Instead, the solution with more votes is taken as a final decision. Individual decision without any argument

In this method, the decision taker takes decisions only based on his knowledge and wisdom. It is the fastest way to take a decision. Though, it won’t always be preferable as it doesn’t consider others’ opinions.

Difference between problem-solving and decision making

There are some differences between problem-solving and decision-making. Decision-making is the process that leads to the best possible outcome. On the other hand, problem-solving finds a problem, and searches for the reasons behind it. After searching for the reasons, you as a problem solver find the way out of it.

Sometimes, you’ll get confused whether these two are different or the same. But, they’re not. Problem-solving is a lengthy process with different segments like analyzing data, evaluating the problems, looking for alternate solutions, etc. But, in decision making, you have to take a call on the alternative solutions and find the best result.

Experience, knowledge, and wisdom are important in making a decision. Decision-taking doesn’t always have to be about problem-solving, instead, it is the process to make a call among different options.

problem-solving and decision-making: which one is the better skill?

In plain sight, decision-making is an easy call. But so many things are dependent on decision-making. Choosing an option between alternative options can be tricky at times.

On the other hand, problem-solving is a more slow and steady process. To solve a problem, you should identify the problem first. Then consider the contexts. After analyzing the data, you can expect to find some solutions. The skill of problem-solving asks a lot from an individual. So, from the perspective of hard work and dedication, problem-solving is the better skill.

Are problem-solving and decision-making the same thing?

No, it’s not the same. Decision-taking is a process to choose the better outcome from some possible alternatives. But, in problem solving, a lot of research work has to be done. Without making enough effort, problem-solving is not possible.

Decision-making determines the journey of a project or work. So, the importance of wise decision-making is very much.

Problem-solving and decision taking may not be the same. They both are important in shaping a person’s skill set. You need to have both to excel in life. Problem-solving needs decision making and decision-making needs problem-solving.

Problem-solving and decision making is a skill that is developed day by day. You need to practice regularly to develop it as a skill. However, problem-solving and decision making is very important in corporate life. Problem-solving is a process to fix something that isn’t working correctly. To find a proper solution and to identify whether the solution is sustainable is problem-solving.

Decision-making is the process to determine the best outcome from a thing. It is very important to have the capability and wisdom to take a decision confidently. Decision-taking ability will always help you in every aspect of your life.

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The Difference Between Problem Solving and Decision Making

Decision making and problem solving are two related but different skill sets that apply to distinct business challenges. Sometimes leaders use decision-making techniques when they should be using a problem-solving approach, and vice versa. Knowing the difference between problem solving and decision making and understanding which skill to utilize in a particular situation will help you overcome challenges more quickly.

Seeking a Solution, or Choosing Between Options?

Both decision making and problem solving use information to inform a certain action, but that’s where the similarities end. Problem solving is the process of finding a solution to an ongoing, intermittent, or one-time failure of a process or system to perform at an acceptable level — or perform at all. It consists of identifying the causes through asking basic questions like “where,” “how,” “who,” and “why” to find the solution. Decision making involves choosing between different courses of action by evaluating each based on a set of criteria. It requires implementing an action plan based on what you have learned from problem solving.

A helpful way to illustrate the difference between problem solving and decision making is to consider the difference between a detective and a judge. As anyone who has seen an episode of Law & Order knows, a detective is a problem-solver. Their role is to determine who committed the crime based on evidence. A judge is a decision-maker. They weigh evidence, circumstances, and precedent to arrive at a judgment.

Understanding Differences in Processes and Outcomes

The process of decision making is clear: each option is evaluated based on a set of parameters or criteria. But the outcome is uncertain until a specific decision is made and time tells how well it worked — or didn’t work.

The process of problem solving is not immediately clear. Initially you might not understand the root of the problem, which makes it difficult to know where to start. For example, you can see that the conveyor belt in your warehouse isn’t working, but what made the motor controlling it stop working remains a mystery until you diagnose the problem, system by system. Once the problem is determined and addressed, the outcome is clear: the conveyor belt is again working.

In business, typical problems could be:

• Customer churn is increasing. Solution: expand product offering.
• The organization’s carbon footprint is too big and costly. Solution: implement green initiatives.
• A team is struggling to keep up with leads and organize customer data. Solution: implement a customer relationship management [CRM] system.

The associated complex decisions would be:

• Determining what new product to launch
• Selecting the green strategies that best balance cost and effectiveness
• Identifying which CRM solution is right for your organization

Problem solving and Decision Making: Best Practices

Whether problem solving or decision making, there are some factors you should consider to make the process as successful and efficient as possible. When problem solving, make sure to gather as many facts as you can, which will help make the solution more obvious. For example, app development companies will often take a “ test and learn ” approach to determine what customers want and need in an app. They’ll create a beta version, provide it free-of-charge to customers, and then analyze that data to develop a paid app that meets customer needs.

 When making decisions, be action-oriented. This means that you should be able to act on your decisions. Many of your decisions, especially those concerning complex issues, should involve other key employees and subject matter experts for the best results. Gather a team with diverse backgrounds, experiences and perspectives to help you consider a wide range of options.  Be open to feedback; even the most carefully made decision may not work out as expected when implemented. And lastly, you should adopt a decision-making framework that enables you to make the best decisions possible on a consistent basis, in a variety of scenarios.

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5 thoughts on “the difference between problem solving and decision making”.

Hi Ken. Problem solving is a skill based on creativity and the ability to see things from many points of view. Decision making in particular requires the ability to manage emotions and a strong sense of responsibility. These are two very important skills in every area and in great demand at work. In the business environment, every good leader should be provided with them to perform at his best in his role.

Thank you for the insight. Agreed – creativity is key for problem solving. Thank you again for visiting the blog, and if you’re interested in learning more on the topic, you might find our Complex Decision Making for Leaders guide helpful. https://alignorg.com/guide/complex-decision-making-for-leaders/

I need help about the similarities of problem solving and decision making

We have an Executive Guide that might help you. You can find it here: https://alignorg.com/guide/complex-decision-making-for-leaders/ .

Every problem solving procedure is made of at least one process of divergent and convergent thinking. In the first part after determining the problem we should look for many many possible solutions in hand (which is one of the many many definitions of creativity). This is the divergent part of thinking (one to many). After having the options in hand, we encounter the second obstacle, i.e. looking for the best option from the many. This second part needs some convergent thinking and decision making skills (many to one). Then, I think the decision making in many cases is a part of problem solving procedure.

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The SkillsYouNeed Guide to Interpersonal Skills

Making decisions and solving problems are two key areas in life, whether you are at home or at work. Whatever you’re doing, and wherever you are, you are faced with countless decisions and problems, both small and large, every day.

Many decisions and problems are so small that we may not even notice them. Even small decisions, however, can be overwhelming to some people. They may come to a halt as they consider their dilemma and try to decide what to do.

Small and Large Decisions

In your day-to-day life you're likely to encounter numerous 'small decisions', including, for example:

Tea or coffee?

What shall I have in my sandwich? Or should I have a salad instead today?

What shall I wear today?

Larger decisions may occur less frequently but may include:

Should we repaint the kitchen? If so, what colour?

Should we relocate?

Should I propose to my partner? Do I really want to spend the rest of my life with him/her?

These decisions, and others like them, may take considerable time and effort to make.

The relationship between decision-making and problem-solving is complex. Decision-making is perhaps best thought of as a key part of problem-solving: one part of the overall process.

Our approach at Skills You Need is to set out a framework to help guide you through the decision-making process. You won’t always need to use the whole framework, or even use it at all, but you may find it useful if you are a bit ‘stuck’ and need something to help you make a difficult decision.

Decision Making

Effective Decision-Making

This page provides information about ways of making a decision, including basing it on logic or emotion (‘gut feeling’). It also explains what can stop you making an effective decision, including too much or too little information, and not really caring about the outcome.

A Decision-Making Framework

This page sets out one possible framework for decision-making.

The framework described is quite extensive, and may seem quite formal. But it is also a helpful process to run through in a briefer form, for smaller problems, as it will help you to make sure that you really do have all the information that you need.

Problem Solving

Introduction to Problem-Solving

This page provides a general introduction to the idea of problem-solving. It explores the idea of goals (things that you want to achieve) and barriers (things that may prevent you from achieving your goals), and explains the problem-solving process at a broad level.

The first stage in solving any problem is to identify it, and then break it down into its component parts. Even the biggest, most intractable-seeming problems, can become much more manageable if they are broken down into smaller parts. This page provides some advice about techniques you can use to do so.

Sometimes, the possible options to address your problem are obvious. At other times, you may need to involve others, or think more laterally to find alternatives. This page explains some principles, and some tools and techniques to help you do so.

Having generated solutions, you need to decide which one to take, which is where decision-making meets problem-solving. But once decided, there is another step: to deliver on your decision, and then see if your chosen solution works. This page helps you through this process.

‘Social’ problems are those that we encounter in everyday life, including money trouble, problems with other people, health problems and crime. These problems, like any others, are best solved using a framework to identify the problem, work out the options for addressing it, and then deciding which option to use.

This page provides more information about the key skills needed for practical problem-solving in real life.

Further Reading from Skills You Need

The Skills You Need Guide to Interpersonal Skills eBooks.

Develop your interpersonal skills with our series of eBooks. Learn about and improve your communication skills, tackle conflict resolution, mediate in difficult situations, and develop your emotional intelligence.

Guiding you through the key skills needed in life

As always at Skills You Need, our approach to these key skills is to provide practical ways to manage the process, and to develop your skills.

Neither problem-solving nor decision-making is an intrinsically difficult process and we hope you will find our pages useful in developing your skills.

Start with: Decision Making Problem Solving

See also: Improving Communication Interpersonal Communication Skills Building Confidence

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• Critical Thinking

Decision-making and Problem-solving

Appreciate the complexities involved in decision-making & problem solving.

Develop evidence to support views

Analyze situations carefully

Discuss subjects in an organized way

Predict the consequences of actions

Weigh alternatives

Generate and organize ideas

Form and apply concepts

Design systematic plans of action

A 5-Step Problem-Solving Strategy

Specify the problem – a first step to solving a problem is to identify it as specifically as possible.  It involves evaluating the present state and determining how it differs from the goal state.

Analyze the problem – analyzing the problem involves learning as much as you can about it.  It may be necessary to look beyond the obvious, surface situation, to stretch your imagination and reach for more creative options.

seek other perspectives

be flexible in your analysis

consider various strands of impact

brainstorm about all possibilities and implications

research problems for which you lack complete information. Get help.

Formulate possible solutions – identify a wide range of possible solutions.

try to think of all possible solutions

be creative

consider similar problems and how you have solved them

Evaluate possible solutions – weigh the advantages and disadvantages of each solution.  Think through each solution and consider how, when, and where you could accomplish each.  Consider both immediate and long-term results.  Mapping your solutions can be helpful at this stage.

Choose a solution – consider 3 factors:

compatibility with your priorities

amount of risk

practicality

Keys to Problem Solving

Think aloud – problem solving is a cognitive, mental process.  Thinking aloud or talking yourself through the steps of problem solving is useful.  Hearing yourself think can facilitate the process.

Allow time for ideas to "gel" or consolidate.  If time permits, give yourself time for solutions to develop.  Distance from a problem can allow you to clear your mind and get a new perspective.

Talk about the problem – describing the problem to someone else and talking about it can often make a problem become more clear and defined so that a new solution will surface.

Decision Making Strategies

Decision making is a process of identifying and evaluating choices.  We make numerous decisions every day and our decisions may range from routine, every-day types of decisions to those decisions which will have far reaching impacts.  The types of decisions we make are routine, impulsive, and reasoned.  Deciding what to eat for breakfast is a routine decision; deciding to do or buy something at the last minute is considered an impulsive decision; and choosing your college major is, hopefully, a reasoned decision.  College coursework often requires you to make the latter, or reasoned decisions.

Decision making has much in common with problem solving.  In problem solving you identify and evaluate solution paths; in decision making you make a similar discovery and evaluation of alternatives.  The crux of decision making, then, is the careful identification and evaluation of alternatives.  As you weigh alternatives, use the following suggestions:

Consider the outcome each is likely to produce, in both the short term and the long term.

Compare alternatives based on how easily you can accomplish each.

Evaluate possible negative side effects each may produce.

Consider the risk involved in each.

Be creative, original; don't eliminate alternatives because you have not heard or used them before.

An important part of decision making is to predict both short-term and long-term outcomes for each alternative.  You may find that while an alternative seems most desirable at the present, it may pose problems or complications over a longer time period.

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Decision Making vs. Problem Solving

Decision Making vs. Problem Solving is an important distinction to make. But first, let’s be clear about what a decision is. A decision is a choice. The decision may be complicated and involve many steps and components but, at its essence, a decision is simply a choice.

Decision making and problem solving are similar in that they both seek the positive resolution of an issue. In life we are usually confronted with a problem and often it is unclear how to solve the problem. Decision making is a tool that can be used to solve a problem.

In general, problem solving takes a larger view and usually involves implementing a strategy. That strategy usually includes making one or more decisions. There is an overlap. However, it is generally deemed that decision making is a subset of problem solving.

Here is an example of the distinction:

The Problem: World Hunger

The Solution: Break the problem into small decisions to be made:

• How do we raise the money to purchase the food?
• How do we determine who will receive the food?
• How do we transport the food to the destination?
• How do we prevent corrupt officials from stealing the food?
• How do we deliver the food to the recipients?

Taken together, a series of decisions can solve most problems and rare is the problem that is not solved, at least in part, by making decisions.

The important thing to remember is that when you are confronted with a problem, look for ways to break it down into discrete decisions to be made.

Problem Solving and Decision Making - Two Essential Skills of a Good Leader

Problem solving and decision making are two fascinating skillsets. We call them out as two separate skills – and they are – but they also make use of the same core attributes.

They feed on a need to communicate well, both through questioning and listening, and be patient and not rushing both processes through. Thus, the greatest challenge any leader faces when it comes to solving problems and decision making is when the pressure of time comes into play. But as Robert Schuller highlights in his quote, allowing problem-solving to become the decision means you’ll never break free from the problem.

“Never bring the problem-solving stage into the decision-making stage. Otherwise, you surrender yourself to the problem rather than the solution.”—Robert H. Schuller

So how does a leader avoid this trap? How do they ensure the problem solving doesn’t become the be-all and end-all?

The 7 steps of Effective Problem Solving and Decision Making

A vital hurdle every leader must overcome is to avoid the impulsive urge to make quick decisions . Often when confronted with a problem, leaders or managers fall back in past behaviours. Urgency creates pressure to act quickly as a result, the problem still exists, just side-lined until it rears its ugly head again.

Good problem solving opens opportunity. A notable example of this is the first principles thinking executed by the likes of Elon Musk and others. Understanding the fundamentals blocks of a process and the problem it’s creating can lead to not just the problem but accelerate beyond it.

So, to avoid the trap, and use problem solving and decision making effectively , you should embody yourself with the following seven steps.

1.      What is the problem?

Often, especially in time-critical situations, people don’t define the problem. Some label themselves as fire-fighters, just content with dowsing out the flames. It is a reactionary behaviour and one commonplace with under-trained leaders. As great as some fire-fighters are, they can only put out so many fires at one time, often becoming a little industry.

The better approach is to define the problem, and this means asking the following questions:

• What is happening? ( What makes you think there is a problem?)
• Where is it taking place?
• How is it happening?
• When is it happening?
• Why is it happening?
• With whom is it happening? (This isn’t a blame game…all you want to do is isolate the problem to a granular level.)
• Define what you understand to be the problem in writing by using as few sentences as possible. (Look at the answers to your what, where, why, when, and how questions.)

2.      What are the potential causes?

Having defined the problem it is now time to find out what might be causing the problem. Your leadership skills: your communication skills need to be strong, as you look to gather input from your team and those involved in the problem.

Key points:

• Talk to those involved individually. Groupthink is a common cause of blindness to the problem, especially if there is blame culture within the business.
• Document what you’ve heard and what you think is the root cause is.
• Be inquisitive. You don’t know what you don’t know, so get the input of others and open yourself up to the feedback you’ll need to solve this problem.

3.      What other ways can you overcome the problem?

 Sometimes, getting to the root cause can take time. Of course, you can’t ignore it, but it is important to produce a plan to temporarily fix the problem. In business, a problem will be costing the business money, whether it be sales or profit. So, a temporary fix allows the business to move forward, providing it neutralises the downside of the original problem.

4.      How will you resolve the problem?

At this stage, you still don’t know what the actual problem is. All you have is a definition of the problem which is a diagnosis of the issue. You will have the team’s input, as well as your opinions as to what the next steps should be.

If you don’t, then at this stage you should think about reassessing the problem. One way forward could be to become more granular and adopt a first-principles approach.

• Break the problem down into its core parts
• What forms the foundational blocks of the system in operation?
• Ask powerful questions to get to the truth of the problem
• How do the parts fit together?
• What was the original purpose of the system working in this way?
• Name and separate your assumptions from the facts
• Remind yourself of the goal and create a new solution

Solve hard problems with inversion

Another way is to invert the problem using the following technique:

1. Understand the problem

Every solution starts with developing a clear understanding of what the problem is. In this instance, some clarity of the issue is vital.

2. Ask the opposite question

Convention wisdom means we see the world logically. But what if you turned the logical outcome on its head. Asking the opposite questions brings an unfamiliar perspective.

3. Answer the opposite question

It seems a simple logic, but you can’t just ask the opposite question and not answer it. You must think through the dynamics that come from asking the question. You're looking for alternative viewpoints and thoughts you've not had before.

4. Join your answers up with your original problem

This is where solutions are born. You’re taking your conventional wisdom and aligning it with the opposite perspective. So often the blockers seen in the original problem become part of the solution.

5.      Define a plan to either fix the problem permanently or temporarily

You now know the problem. You understand the fix, and you are a position to assess the risks involved.

Assessing the risks means considering the worst-case scenarios and ensuring you avoid them. Your plan should take into the following points:

• Is there any downtime to implementing the solution? If so, how long, and how much will it cost? Do you have backup systems in place to minimise the impact?
• If the risk is too great, consider a temporary fix which keeps current operations in place and gives you time to further prepare for a permanent fix.
• Document the plan and share it with all the relevant stakeholders. Communication is key.

Here we see the two skills of problem solving and decision making coming together. The two skills are vital to managing business risks as well as solving the problem.

6.      Monitor and measure the plan

Having evolved through the five steps to this stage, you mustn’t take your eye off the ball as it were.

• Define timelines and assess progress
• Report to the stakeholders, ensuring everyone is aware of progress or any delays.
• If the plan doesn’t deliver, ask why? Learn from failure.

7.      Have you fixed the problem?

Don’t forget the problem you started with. Have you fixed it? You might find it wasn’t a problem at all. You will have learnt a lot about the part of the business where the problem occurred, and improvements will have taken place.

Use the opportunity to assess what worked, what didn’t, and what would have helped. These are three good questions to give you some perspective on the process you’ve undertaken.

Problem solving and decision making in unison

Throughout the process of problem solving, you’re making decisions. Right from the beginning when the problem first becomes clear, you have a choice to either react – firefight or to investigate. This progresses as move onto risk assessing the problem and then defining the solutions to overcome the issue.

Throughout the process, the critical element is to make decisions with the correct information to hand. Finding out the facts, as well as defeating your assumptions are all part of the process of making the right decision.

Problem solving and decision making – a process 

Problem solving isn’t easy. It becomes even more challenging when you have decisions to make. The seven steps I’ve outlined will give you the ability to investigate and diagnose the problem correctly.

• What is the problem?
• What are the potential causes?
• What other ways can you overcome the problem?
• How will you resolve the problem?
• Define a plan to either fix the problem permanently or temporarily.
• Monitor and measure the plan.
• Have you fixed the problem?

Of course, this logical step by step process might not enable you to diagnose the issue at hand. Some problems can be extremely hard, and an alternative approach might help. In this instance, first principles thinking or using the power of inversion are excellent ways to dig into hard problems. Problem solving and decision making are two skills every good leader needs. Using them together is an effective way to work.

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Difference Between Problem Solving and Decision Making

• Categorized under Language | Difference Between Problem Solving and Decision Making

Problem Solving vs Decision Making

Life is filled with complexities, and one of them is to know the difference between problem solving and decision making. People tend to use ‘problem solving’ and ‘decision making’ interchangeably. Although they are somewhat related, these two phrases are not synonymous and are completely different. The major difference between the two is; problem solving is a method while decision making is a process.

Problem solving, as the name implies, is solving a problem. Meaning, it is a method wherein a group or an individual makes something positive out of a problem. Decision making, on the other hand, is a process that is done many times during problem solving. Decision making is the key that will help in reaching the right conclusion in problem solving. Problem solving is more an analytical aspect of thinking. It also uses intuition in gathering facts. Decision making, on the other hand, is more of a judgment where, after thinking, one will take a course of action. However, these two need a certain set of skills for each to be more effective.

To understand the differences between the two a little better, it is best to define each of them. With the definition of each term, it will be easier for you to distinguish one from the other.

Problem solving is more of a mental process. It is included in the larger problem process, namely, problem finding and problem shaping. Problem solving is the most complex process among all the intellectual functions of a human being. It is very complex. It is considered a higher order of the cognitive process. It is very complex in that it needs regulation and modulation of the basic skills of a human being. When an organism or artificial intelligence system is undergoing a problem and needs to be transferred into a better state to achieve a certain goal, then this needs problem solving.

Decision making is concerned on what action should be made. It is still a process of cognitive function, but it focuses on what action to take and what alternatives are available. Decision processes will always end up with a final choice; this choice may be an action or an opinion about a certain issue. When looking at decision making in a psychological aspect, the decision of an individual is based on his or her needs and the values that a person is looking for. When looking at decision making in a cognitive aspect, it is a continuous process related to the interaction of the person and his or her environment. In the normative aspect of decision making, on the other hand, it is focused more on the logical and rational way of making decisions until a choice is made.

Problem solving is a method; decision making is a process.

Decision making is needed during problem solving to reach the conclusion.

Decision making will lead to a course of action or final opinion; problem solving is more analytical and complex

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Cite APA 7 Magno, E. (2015, January 13). Difference Between Problem Solving and Decision Making. Difference Between Similar Terms and Objects. http://www.differencebetween.net/language/difference-between-problem-solving-and-decision-making%e2%80%a8/. MLA 8 Magno, Eva. "Difference Between Problem Solving and Decision Making." Difference Between Similar Terms and Objects, 13 January, 2015, http://www.differencebetween.net/language/difference-between-problem-solving-and-decision-making%e2%80%a8/.

You say “Problem solving is a method; decision making is a process.”

Yet in the 4th paragraph discussing problem solving you use the word “process” repeatedly without explaining with examples how it is a method.

So shd I say that choice making is the same as decision making?

Good but not illustrated

Pls Explain in table

Decision making typically involves the selection between of some collection of options from within a larger set which includes those options as well as a number of additional options. The larger the total set of options within which the subset is being selected, the more criteria are needed to give you a basis for the decision.

People tend to think of a decision as being “difficult” when in respect of the options being selected from, none of them look like they have obviously better outcomes … or sometimes even “none of the choices are good ones”.

Problem solving whereas has a wider remit. Effective problem solving typically involves the process of iterative re-specification of what the problem actually is, in a cycle with low-cost experiments to determine whether that way of defining the problem tends to give rise to more of what we want or less or what we want.

Thank you so much

Featured addition

Provide further explanations regarding the two aspects of problem solving and decision making. Thank you.

If one is a method and the other is a process, what is the difference between a method and process?

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Written by : eva. and updated on 2015, January 13 Articles on DifferenceBetween.net are general information, and are not intended to substitute for professional advice. The information is "AS IS", "WITH ALL FAULTS". User assumes all risk of use, damage, or injury. You agree that we have no liability for any damages.

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Introduction

Practitioners in various domains are often faced with ill-structured problems. For example, teachers devise lesson plans that consider learners’ prior knowledge, curriculum guidelines, and classroom management strategies. Similarly, engineers must develop products that meet safety standards, yet achieve project guidelines that meet client needs. Given the types of problems that practitioners face in everyday decision-making, educators have increasingly begun to adopt inquiry-based learning, which better exposes learners to the types of issues faced within a domain (Hung et al., 2019; Koehler & Vilarinho-Pereira, 2021). This instructional approach includes multiple changes to the educational experience when compared to the teacher-centric classroom approach (Reigeluth & Carr-Chellman, 2009). As opposed to a didactic strategy to instruction, students take ownership of their learning and generate questions among their peers, while teachers serve as facilitators (Lazonder & Harmsen, 2016; Loyens & Rikers, 2011; Savery, 2009). The central focus of these strategies also includes ill-structured cases that are similar to the types of problems practitioners face. The complexity of these problems often consists of interconnected variables (latent, salient) and multiple perspectives, so there is rarely a single predetermined solution that satisfies all options (Ifenthaler, 2014). Additionally, these problems are challenging because they include multiple criteria for evaluation (Jonassen, 2011b; Ju & Choi, 2017), which makes it challenging to definitively determine when a ‘right’ answer has been achieved.

There are a number of skillsets needed for problem-solving instructional strategies, such as the inquiry process (Glazewski & Hmelo-Silver, 2018), collaboration (Koehler & Vilarinho-Pereira, 2021), and argumentation (Noroozi et al., 2017). Another important element of problem-solving includes decision-making; that is, the process by which individuals make choices as they resolve the ill-structured case. Understanding decision-making is important because individuals engage in a myriad of choices throughout the problem representation and solution generation phases of problem-solving (Ge et al., 2016). Moreover, learners must engage in multiple and interconnected decisions as they select evidence and determine causal chains during various stages of problem-solving (Shin & Jeong, 2021). The decision-making process is also closely linked with failure and the iterative choices needed to overcome errors in the problem-solving cycles (Schank et al., 1999; Sinha & Kapur, 2021). As such, decision-making is key for learners’ agency as they engage in self-directed learning and take ownership of ill-structured cases.

Despite its importance, the field of learning design only minimally addresses theories and models specifically associated with decision-making. The decision-making processes required for inquiry-based learning necessitates a more in-depth analysis because it is foundational to problem-solving as individuals weigh evidence, make strategic choices amidst an array of variables, and causal reasoning. In addition, an advanced understanding of this skill set would allow educators to develop systems that leverage specific decision-making strategies within design. Based on this gap, we survey broad decision-making paradigms (normative, descriptive, and prescriptive), along with case-based decision-making theory (Gilboa & Schmeidler, 1995; Kolodner, 1991). For each category, we then proffer an example that instantiates the theory. Finally, the article concludes with implications for practice.

Literature Review

Inquiry-based learning is an instructional strategy that affords learners with agency as they solve ill-structured problems. Although variations exist (problem-based learning, project-based learning, case-based instruction), the strategy often situates a contextual case to the learners that is representative of the domain (Lazonder & Harmsen, 2016; Loyens & Rikers, 2011). When compared with teacher-centric approaches where the instructor acts as the ‘sage on the stage’ (Reigeluth & Carr-Chellman, 2009), students in inquiry-based learning engage in a variety of learning actions in the problem representation and solution generation stage. The former necessitates learners define the problem, identify variables, and determine the underlying causal mechanisms of the issue (Delahunty et al., 2020; Ertmer & Koehler, 2018). Solution generation requires learners propose a way to resolve the issue, along with supporting evidence (Ge et al., 2016). This latter stage also includes how learners test out a solution and iterate based on the degree to which their approach meets its goals. As learners engage in these tasks, they must remedy knowledge gaps and work with their peers to reconcile different perspectives. Beyond just retention of facts, learners also engage in information seeking (Belland et al., 2020), question generation (Olney et al., 2012), causal reasoning (Giabbanelli & Tawfik, 2020; Shin & Jeong, 2021), argumentation (Ju & Choi, 2017; Noroozi & Hatami, 2019), and other higher-order thinking skills.

Another important aspect of inquiry-based learning also includes decision-making, which describes the choices learners select as they understand the problem and move towards its resolution. To that end, various theories and models that explicate the nuances of problem-solving have implicitly referenced decision-making. When describing the solution generation stage, Jonassen (1997) asserts that learners’ “resulting mental model of the problem will support the learner's decision and justify the chosen solution” (p. 81). Ge et al. (2016) proposed a conceptual model of self-regulated learning in ill-structured problem-solving in which “students not only must make informed decisions and select the most viable against alternative solutions, but also must support their decisions with defensible and cogent arguments” (p. 4). In terms of encountered failure during problem-solving, Kapur (2008) explains how students must “decide on the criteria for decision making or general parameters for solutions” (p. 391) during criteria development. Indeed, these foundation theories and models of problem-solving highlight the importance of decision-making in various aspects of inquiry-based learning.

Despite its importance, very little understanding is known within the learning design field about the specific decision-making processes inherent within problem-solving. Instead, there is a large body of literature dedicated to strategic approaches to self-directed learning (Xie et al., 2019), collaboration (Radkowitsch et al., 2020), and others. However, specific attention is needed towards decision-making to understand how learners seek out information, weigh evidence, and make choices as they engage in problem-solving. A review of theories argues for three distinct overarching theoretical paradigms of decision-making (Schwartz & Bergus, 2008): normative, descriptive, and prescriptive. There is also a related body of literature around case-based decision-making theory (Gilboa & Schmeidler, 1995), which describes how prior experiences are used to inform choices for new problems. Below we define the theory and related literature, along with a design example that instantiates the decision-making approach.

Outline of Decision-Making Theories and Constructs

Normative Decision-Making

Normative decision-making theoretical foundations.

Normative decision-making describes how learners make choices based on the following: (a) perceived subjective utility and (b) probability (Gati & Kulcsár, 2021). The former focuses on the values of each outcome, especially in terms of how the individual assesses expected benefits and costs associated with one’s goals and preferences. Alternatively, probability describes the degree to which individuals perceive that a selected action will lead to a specific outcome. Hence, a key assumption - and potential criticism - of normative decision-making is that individuals are logically consistent as they make choices under the constraints of rationality, which has been called into question.

Another important element of normative decision-making includes ‘compensatory models’; that is, how the benefits of an alternative outweigh the disadvantages. The most common compensatory model described in the literature is multi-attribute utility theory (MAUT), which is used to account for decision-making amidst multiple criteria (Jansen, 2011). MAUT thus aligns well with ill-structured problem-solving because it assumes that choices are made amongst a variety of competing alternatives. In a conservation example, one might select a green energy alternative to reduce carbon emissions, but it may be disruptive to the existing energy sources (e.g., fossil fuels) and raise costs in the short term. In the context of medicine, a surgery might ultimately resolve an issue, but it poses a risk for post-procedure infections and other complications. As individuals consider each alternative, MAUT is a way of “measuring the decision-maker’s values separately for a set of influential attributes and by weighting these by the relative importance of these attributes as perceived by the decision-maker” (Jansen, 2011, p. 101). MAUT component of normative decision-making specifically argues individuals progress in the following five steps (Von Winterfeldt & Edwards, 1993): 

• Individuals explicate the various alternatives and salient attributes associated with each choice.
• Each alternative is evaluated separately based on each attribute in terms of the following: complete (all essential aspects are addressed), operational (attributes can be meaningfully used), decomposable (deconstructing aspects of evaluation as to simplify evaluation process), non-redundant (remove duplicates of aspects), and minimal (keep a number of attributes focused and central to the problem).
• Individuals assign relative weights to each attribute
• Individuals sum the aggregate weight to evaluate each alternative.
• Individuals make a final choice.

Rather than pursue a less than optimal selection, MAUT argues that “they [individuals] strive to choose the most beneficial alternative and obtain all information relevant to the decision, and they are capable of considering all possible outcomes of the choice, estimating the value of each alternative and aggregating these values into a composite variable” (Gati et al., 2019, p. 123). Another characteristic is how individuals select the factors and assess the degree to which they can be compensated. Some individuals (e.g., expert, novice) may weigh a specific factor differently, even if the other aspects align with their desired outcomes. Given that individuals are not always rational and consistent in decision-making, some argue that the normative decision-making model is not truly representative of how individuals actually engage in everyday problem-solving (Gati et al., 2019; Jansen, 2011; Schwartz & Bergus, 2008). 

Normative decision-making theoretical application

Normative decision-making approaches applied to learning design make choices and probabilities salient to the learner, such as in the case of learner dashboards (Valle et al., 2021) or heuristics. Arguably, the most common application of decision-making in learning technologies for inquiry-based learning includes simulations, which situate individuals within an authentic context and posit a series of choices, and allow them to model choices (Liu et al., 2021). Systems that especially exhibit normative decision-making often consist of the following: (a) encourages learners to consider what is currently known about the phenomena vs. what knowledge the decision-makers lack, (b) makes probability associated with a choice clear, and (c) observes the outcomes of the decision.

One example of normative decision-making applied to design includes The Wildlife Module/Wildfire Explorer project developed by Concord Consortium. In this environment, learners are tasked with lowering wildfire risk in terms of fires and other natural hazards (see Figure 1). The decision-making is especially focused on choices around terrain and weather conditions, which add to or limit the amount of risk that is posed to each town. As learners make decisions, the interface allows individuals to manipulate variables and thus observe how certain choices will result in higher benefits relative to others. For instance, reducing the amount of brush in the area will better prevent wildfire when compared with cutting fire lines. In another instance, they explore how dry terrain and 30 mile per hour (MPH) winds would increase the potential wildfire risk of an area. The learning environment thus instantiates aspects of normative decision-making as learners select the parameters and discern its effects on the wildfire within the region.

Wildlife Module/Wildfire Explorer as Applying Normative Decision-Making

Descriptive Decision-Making

Descriptive decision-making theoretical foundations.

Whereas the normative decision-making approaches assume individuals make rational decisions that maximize choices, descriptive decision-making illustrates the gap between optimal decision-making and how people actually make choices (Gati et al., 2019). Although it is sometimes criticized for the lack of clarity, there are some elements of descriptive decision-making that have emerged. One key component includes satisficing, which posits that individuals attempt to make decisions based on how choices are maximized and meet specific goals. As outlined in the seminal work by Simon (1972), individuals aspire to engage in complex rational selections; however, humans have limited cognitive resources available to process the information available during decision-making. Because choices for ill-structured problems often have competing alternatives, individuals settle for decisions that meet some kind of determined threshold for acceptance in light of a given set of defined criteria. The theory further argues individuals will likely choose the first option that satisfices the desire; so while the final selection may be satisficing, it may not necessarily be the best and most rational decision (Gati et al., 2019). This is especially true in ill-structured problems that include multiple perspectives and constraints that make an ideal solution difficult. Rather, individuals instead strive for a viable choice that can be justified in light of multiple criteria and constraints.

Descriptive decision-making theoretical application

One example includes the EstemEquity project (Gish-Lieberman et al., 2021), which is a learning environment designed to address attrition rates for women of color in STEM through mentorship strategies aimed at building self-efficacy. Because the dynamics of mentorship can be difficult, the system relies heavily on decision-making and reflection upon choice outcomes (see Figure 2). The first steps of a scenario outline a common mentor/mentee challenge, such as a mentee frustrated because she feels as though the mentor is not listening to her underlying problem as she navigates higher education in pursuit of her STEM career. The learning environment then poses two choices that would resolve the issue. Although no single solution will fully remedy the ill-structured mentorship challenge, they must make value judgments about the criteria for success and the degree to which their decision meets the requirements. Based on the goals, the learning environment provides feedback as to how the choice satisfices given their determined threshold of optimal mentor and mentee relationships.

EstemEquity as Applying Descriptive Decision-Making

Prescriptive Decision-Making

Prescriptive decision-making theoretical foundations.

The aforementioned approaches highlight how individuals engage in sense-making as they make a selection among latent and salient variables. To better support ideal decision-making, the prescriptive approach is concerned with providing overt aids to make the best decisions (Divekar et al., 2012). Moreover, prescriptive decision-making “bridges the gap between descriptive observations of the way people make choices and normative guidelines for how they should make choices” (Keller, 1989, p. 260). Prescriptive decision-making thus provides explicit guidelines for making better decisions while taking into consideration human limitations. For example, physicians may use a heuristic that outlines a specific medication based on symptoms and patient characteristics (e.g., height, weight, age). Similarly, a mental health counselor may select a certain intervention approach when a client presents certain behavioral characteristics. In doing so, prescriptive decision-making outlines a series of “if-then” scenarios and details the ideal choice; that is, the pragmatic benefit of the decision to be made given a set of certain circumstances (Gati et al., 2019).

There are multiple challenges and benefits to the prescriptive approach to decision-making. In terms of the former, some question the degree to which a single set of heuristics can be applied across multiple ill-structured problems with varying degrees of nuance. That said, the prescriptive approach has gained traction in the ‘big data’ era, which compiles a considerable amount of information to make it actionable for the individual. An emerging subset of the field includes prescriptive analytics, especially in the business domain (Lepenioti et al., 2020). Beyond just presenting information, prescriptive analytics distinguishes itself because it provides the optimal solution based on input and data-mining strategies from various sources (Poornima & Pushpalatha, 2020). As theorists and practitioners look to align analytics with prescriptive decision-making, Frazzetto et al., (2019) argues: 

If the past has been understood (descriptive analytics; ‘DA’), and predictions about the future are available (predictive analytics; ‘PDA’), then it is possible to actively suggest (prescribe) a best option for adapting and shaping the plans according to the predicted future (p. 5).

Prescriptive decision-making theoretical application

Prescriptive decision-making approaches arguably are most used in adaptive tutoring systems, which outline a series of “if-then” steps based on learners’ interactions. ElectronixTutor is an adaptive system that helps learners understand electrical engineering principles within a higher educational context (see Figure 3). Rather than allowing the learner to navigate as desired or make ad-hoc selections, the recommender system leverages user input from completed lessons to prescribe the optimal lesson choice that best furthers their electrical engineering knowledge. For example, after successful completion on the “Series and Parallel Circuit” (the “if”), the system prescribes that the learner advance to the next “Amplifier” lessons (the “then”) because the system has determined that as the next stage of the learning trajectory. When a learner inputs the correct decision, they are prompted with the optimal selection the system deems as best advances their learning. Alternatively, a wrong selection constrains the choices for the learner and reduces the complexity of the process to a few select decisions. In doing so, the adaptive system implements artificial intelligence to prescribe the optimal path the learner should take based on the previous input from the learner (Hampton & Graesser, 2019).

Autotutor as Applying Prescriptive Decision-Making

Case-Based Decision-Making Theory

Case-based decision-making theoretical foundations.

The literature suggests case-based decision-making theory (CBDMT) is another problem-solving approach individuals employ within domain practice (Gilboa & Schmeidler, 1995). The premise behind CBDMT is that individuals recall previous experiences which are similar to the extant issue and select the solution that yielded a successful resolution (Huang & Pape, 2020; Pape & Kurtz, 2013). These cases are often referred to as ‘repeated choice problems’ whereby individuals see available actions as similar between the new problem and prior experiences (Ossadnik et al., 2013). According to the theory, memory is a set of cases that consists of the following constructs: problem, a potential act chosen in the problem, and ensuing consequence. Specifically, “the memory contains the information required by the decision-maker to evaluate an act, which is specific to the problem” (Ossadnik et al., 2013, p. 213). A key element in a case-based approach to decision-making includes the problem features, the assigned weights of said features, and observed consequences as a reference point for the new problem (Bleichrodt et al., 2017).

The CBDMT approach is similar to the normative approach to decision-making in that it describes how learners make a summative approach to decision-making; however, it differs in that it explicates how one leverages prior experience to calculate these values. Moreover, the value of a case for decision-making is evaluated through a comparison of related acts of other known issues when the new problem is assessed by the individual. Specifically, Gilboa and Schmeidler (1995) propose: “Each act is evaluated by the sum of the utility levels that resulted from using this act in past cases, each weighted by the similarity of that past case to the problem at hand” (p. 605). In this instance, utility refers to the benefits of the decision being made and the forecasting of outcomes (Grosskopf et al., 2015; Lovallo et al., 2012). The individual compares the new case to a previous case and then selects the decision with the highest utility outcome. As one gains expertise, CBDMT proffers one can “combine variations in memory with variations in sets of choice alternatives, leading to generalized versions” (Bleichrodt et al., 2017, p. 127) 

Case-based decision-making theoretical application

Because novices lack prior experiences, one might argue it may be difficult to apply CBDMT in learning design. However, the most often applied approach is by leveraging narratives as a form of vicarious experience (Jonassen, 2011a). In one example by Rong et al. (2020), veterinary students are asked to solve ill-structured problems about how to treat animals that go through various procedures. As part of the main problem to solve, learners must take into consideration the animal’s medical history, height, weight, and a variety of other characteristics. To engender learners’ problem-solving, the case profiles multiple decision points, and later asks the learners to make their own choice and justify its selection. Decision-making is supported through expert cases, which serve as vicarious memory and encourage the learners to transfer the lessons learned towards the main problem to solve (Figure 4). In doing so, the exemplars serve as key decision-making aids as novices navigate the complexity of the ill-structured problem.

Video Exemplars as Applying Case-Based Decision-Making Theory

Discussion and Implications for Design

Theorists of education have often discussed ways to foster various elements of ill-structured problem-solving, including problem representation (Ge et al., 2016), information-seeking (Glazewski & Hmelo-Silver, 2018), question generation (Olney et al., 2012), and others. While this has undoubtedly advanced the field of learning design, we argue decision-making is an equally foundational aspect of problem-solving that requires further attention. Despite its importance, there is very little discourse as to the nuances of decision-making within learning design and how each perspective impacts the problem-solving process. A further explication of these approaches would allow educators and designers to better support learners as they engage in inquiry-based learning and similar instructional strategies that engender complex problemsolving. To address this gap, this article introduces and discusses the application of the following decision-making paradigms: normative, descriptive, prescriptive, and CBDMT.

The above theoretical paradigms have implications for how these theories align with other design approaches of learning systems. In many instances, scaffolds are designed to support specific aspects of problem solving. Some systems are designed to support the collaborative process that occurs during inquiry-based learning (Noroozi et al., 2017), while other scaffolds outline the argumentation process (Malogianni et al., 2021). Alternatively, learning environments may embed prior narratives to model how practitioners solve problems (Tawfik et al., 2020). While each of these theories supports a critical aspect of problem solving, there are opportunities to further refine these learning systems by more directly supporting the decision-making process. For example, one way to align these design strategies and normative decision-making theories would be to outline the different choices and probabilities of expected outcomes. A learning system might embed supports that outline alternative perspectives or reflection questions, but could also include scaffolds that explicate optimal solution paths as it applies a prescriptive decision-making approach. In doing so, designers can simultaneously support various aspects of ill-structured problem solving.

There are also implications as it relates to the expert-novice continuum, which is often cited as a critical component of problem-solving (Jonassen, 2011a; Kim & Hannafin, 2008). Indeed, a body of rich literature has described differences as experts and novices identify variables within ill-structured problems (Jacobson, 2001; Wolff et al., 2021) and define the problem-space within contexts (Ertmer & Koehler, 2018; Hmelo-Silver, 2013). Whereas many post-hoc artifacts have documented outcomes that describe how novices grow during inquiry-based learning (e.g., concept map, argumentation scores), less is known about in situ decision-making processes and germane design strategies novice learners engage in when they are given problem-solving cases. For example, it may be that novices might benefit more from a prescriptive decision-making design strategy given the inherent complexity and challenges of cognitive load presented within an inquiry-based learning module. Alternatively, one might argue simulation learning environments designed for normative decision-making would make the variables more explicit, and thus better aid learners in their choice selection when presented with a case. The simulation approach often employed for normative decision-making might also allow for iterative decision-making, which may be especially advantageous for novices that are newly exposed to the domain. A further understanding of these decision-making approaches allows educators and designers to better support learners and develop systems that emphasize this higher-order learning skillset.

As learners engage in information-seeking during problem-solving, it follows that a choice is made based on the synthetization of multiple different sources (Glazewski & Hmelo-Silver, 2018). Future explorations around information seeking and decision-making would yield important insights for problem solving in multiple respects. For instance, the normative decision-making approach argues individuals assign values to various attributes and use this assessment to make a selection. As learners engage in inquiry-based learning, designers can use understanding of normative approaches to determine how individuals search for information to satisfice an opinion, use this to assess the probability of an action, and the resulting choice. From a descriptive decision-making approach, learners weigh various information sources as they seek out an answer that satisfices. Finally, a case-based decision-making theory approach may find learners search for information and related weights for the following: problem (q ∈ Q), a potential act chosen in the problem (a ∈ A), and ensuing consequence (r ∈ R). Although the design of inquiry-based learning environments often overlooks the intersection of information-seeking approaches and decision-making, a better understanding of the role of theory would aid designers as they construct learning environments that support this aspect of problem solving.

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8.2 Problem-Solving: Heuristics and Algorithms

Learning objectives.

• Describe the differences between heuristics and algorithms in information processing.

When faced with a problem to solve, should you go with intuition or with more measured, logical reasoning? Obviously, we use both of these approaches. Some of the decisions we make are rapid, emotional, and automatic. Daniel Kahneman (2011) calls this “fast” thinking. By definition, fast thinking saves time. For example, you may quickly decide to buy something because it is on sale; your fast brain has perceived a bargain, and you go for it quickly. On the other hand, “slow” thinking requires more effort; applying this in the same scenario might cause us not to buy the item because we have reasoned that we don’t really need it, that it is still too expensive, and so on. Using slow and fast thinking does not guarantee good decision-making if they are employed at the wrong time. Sometimes it is not clear which is called for, because many decisions have a level of uncertainty built into them. In this section, we will explore some of the applications of these tendencies to think fast or slow.

We will look further into our thought processes, more specifically, into some of the problem-solving strategies that we use. Heuristics are information-processing strategies that are useful in many cases but may lead to errors when misapplied. A heuristic is a principle with broad application, essentially an educated guess about something. We use heuristics all the time, for example, when deciding what groceries to buy from the supermarket, when looking for a library book, when choosing the best route to drive through town to avoid traffic congestion, and so on. Heuristics can be thought of as aids to decision making; they allow us to reach a solution without a lot of cognitive effort or time.

The benefit of heuristics in helping us reach decisions fairly easily is also the potential downfall: the solution provided by the use of heuristics is not necessarily the best one. Let’s consider some of the most frequently applied, and misapplied, heuristics in the table below.

In many cases, we base our judgments on information that seems to represent, or match, what we expect will happen, while ignoring other potentially more relevant statistical information. When we do so, we are using the representativeness heuristic . Consider, for instance, the data presented in the table below. Let’s say that you went to a hospital, and you checked the records of the babies that were born on that given day. Which pattern of births do you think you are most likely to find?

Most people think that list B is more likely, probably because list B looks more random, and matches — or is “representative of” — our ideas about randomness, but statisticians know that any pattern of four girls and four boys is mathematically equally likely. Whether a boy or girl is born first has no bearing on what sex will be born second; these are independent events, each with a 50:50 chance of being a boy or a girl. The problem is that we have a schema of what randomness should be like, which does not always match what is mathematically the case. Similarly, people who see a flipped coin come up “heads” five times in a row will frequently predict, and perhaps even wager money, that “tails” will be next. This behaviour is known as the gambler’s fallacy . Mathematically, the gambler’s fallacy is an error: the likelihood of any single coin flip being “tails” is always 50%, regardless of how many times it has come up “heads” in the past.

The representativeness heuristic may explain why we judge people on the basis of appearance. Suppose you meet your new next-door neighbour, who drives a loud motorcycle, has many tattoos, wears leather, and has long hair. Later, you try to guess their occupation. What comes to mind most readily? Are they a teacher? Insurance salesman? IT specialist? Librarian? Drug dealer? The representativeness heuristic will lead you to compare your neighbour to the prototypes you have for these occupations and choose the one that they seem to represent the best. Thus, your judgment is affected by how much your neibour seems to resemble each of these groups. Sometimes these judgments are accurate, but they often fail because they do not account for base rates , which is the actual frequency with which these groups exist. In this case, the group with the lowest base rate is probably drug dealer.

Our judgments can also be influenced by how easy it is to retrieve a memory. The tendency to make judgments of the frequency or likelihood that an event occurs on the basis of the ease with which it can be retrieved from memory is known as the availability heuristic (MacLeod & Campbell, 1992; Tversky & Kahneman, 1973). Imagine, for instance, that I asked you to indicate whether there are more words in the English language that begin with the letter “R” or that have the letter “R” as the third letter. You would probably answer this question by trying to think of words that have each of the characteristics, thinking of all the words you know that begin with “R” and all that have “R” in the third position. Because it is much easier to retrieve words by their first letter than by their third, we may incorrectly guess that there are more words that begin with “R,” even though there are in fact more words that have “R” as the third letter.

The availability heuristic may explain why we tend to overestimate the likelihood of crimes or disasters; those that are reported widely in the news are more readily imaginable, and therefore, we tend to overestimate how often they occur. Things that we find easy to imagine, or to remember from watching the news, are estimated to occur frequently. Anything that gets a lot of news coverage is easy to imagine. Availability bias does not just affect our thinking. It can change behaviour. For example, homicides are usually widely reported in the news, leading people to make inaccurate assumptions about the frequency of murder. In Canada, the murder rate has dropped steadily since the 1970s (Statistics Canada, 2018), but this information tends not to be reported, leading people to overestimate the probability of being affected by violent crime. In another example, doctors who recently treated patients suffering from a particular condition were more likely to diagnose the condition in subsequent patients because they overestimated the prevalence of the condition (Poses & Anthony, 1991).

The anchoring and adjustment heuristic is another example of how fast thinking can lead to a decision that might not be optimal. Anchoring and adjustment is easily seen when we are faced with buying something that does not have a fixed price. For example, if you are interested in a used car, and the asking price is $10,000, what price do you think you might offer? Using $10,000 as an anchor, you are likely to adjust your offer from there, and perhaps offer $9000 or $9500. Never mind that $10,000 may not be a reasonable anchoring price. Anchoring and adjustment does not just happen when we’re buying something. It can also be used in any situation that calls for judgment under uncertainty, such as sentencing decisions in criminal cases (Bennett, 2014), and it applies to groups as well as individuals (Rutledge, 1993).

In contrast to heuristics, which can be thought of as problem-solving strategies based on educated guesses, algorithms are problem-solving strategies that use rules. Algorithms are generally a logical set of steps that, if applied correctly, should be accurate. For example, you could make a cake using heuristics — relying on your previous baking experience and guessing at the number and amount of ingredients, baking time, and so on — or using an algorithm. The latter would require a recipe which would provide step-by-step instructions; the recipe is the algorithm. Unless you are an extremely accomplished baker, the algorithm should provide you with a better cake than using heuristics would. While heuristics offer a solution that might be correct, a correctly applied algorithm is guaranteed to provide a correct solution. Of course, not all problems can be solved by algorithms.

As with heuristics, the use of algorithmic processing interacts with behaviour and emotion. Understanding what strategy might provide the best solution requires knowledge and experience. As we will see in the next section, we are prone to a number of cognitive biases that persist despite knowledge and experience.

Key Takeaways

• We use a variety of shortcuts in our information processing, such as the representativeness, availability, and anchoring and adjustment heuristics. These help us to make fast judgments but may lead to errors.
• Algorithms are problem-solving strategies that are based on rules rather than guesses. Algorithms, if applied correctly, are far less likely to result in errors or incorrect solutions than heuristics. Algorithms are based on logic.

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Decision-Making and Problem Solving

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• Anna Saiti 4  

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Decision-making is a fundamental activity that significantly influences the efficiency of an organization. That is because this activity is at the heart of management in every typical organization. Therefore, one of the key prerequisites for an educational leader is to have effective decision-making skills.

During an average working day, a school head makes different kinds of decisions, regardless of their importance. Indeed, within the wider framework of a school unit’s activities, the resolution of problems and the decision-making are two fundamental elements that assess, to a significant degree, the effectiveness of the school’s performance. Consequently, it is absolutely necessary for all educational leaders to understand the process of decision-making and of resolving problems, since the sheer existence of schools (and indeed all typical organizations) depends on their decision-making processes. This chapter:

Analyses the meaning, types and the procedures for effective decision-making

Outlines suggestions (e.g. careful assessment of the credibility of information) on how to avoid wrong decisions

Emphasizes human weakness in the decision-making process (e.g. when a manager puts too much emphasis on the initial information and does not assess whether or not it is creditable)

Examines the meaning of the term “problem” and also summarizes the process and methods of problem solving in the field of education

Presents case studies related to the school reality

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