Why and How to Use Worked Examples in the Workplace

Mirjam Neelen & Paul A. Kirschner

You want to prepare a recipe that involves carrying out a number of steps. How do you do that? You usually begin with step 1 and work through the steps to the last step. If you prepare the recipe again and again, you probably don’t have to look at the recipe for certain steps (e.g., you know that you have to whisk the egg-water mixture) and so forth until you can prepare the recipe without looking at it. This is a specific type of learning with what is known as a worked example.

Learning through worked examples is a very effective way to learn how to carry out a task or solve a problem in an area where they have little prior knowledge (aka ‘novices’). For knowledge workers in the workplace, however, this learning strategy is under-utilised. This is unfortunate because integrating worked examples for learning will likely save lots of time and money as it allows people to learn both efficiently and effectively.

A word of warning! A novice is not just someone who know little or nothing about a specific domain or topic. This blog is about carrying out new tasks. Take this example: Mirjam now works with a learning team that’s responsible for upskilling internal salespeople to enable them to sell technologies such as blockchain, artificial intelligence, extended reality, and so on to external clients. Let’s say these salespeople need to learn how to recognise if a client challenge can be solved by using blockchain technology and how to then explain the value of blockchain to the external client and create a project proposal. The internal salespeople are indeed very experienced when it comes to … sales. However, when it comes to selling blockchain solutions to clients, they’re novices. Not just because the technology is new to them but also because the task of selling a blockchain solution requires a different sales process. For example, instead of selling to one specific client, they now need to sell to a ‘client ecosystem’ otherwise the technology wouldn’t have any impact. So, don’t be fooled by the term ‘novice’ as even when an individual is proficient in topic X or Y, (s)he can still be a novice when it comes to a new problem that needs to be solved!

Now that that’s out of the way, let’s explore what worked examples are and why and when they’re effective. We’ll also explore some types of worked examples and give some concrete examples.

What are worked examples?

A true worked example is always product- and process-oriented. The product-oriented bit can be defined as a learning task describing a given begin state, a desired goal state, and a chosen solution; also called a case study if it reflects a real-life problem situation (Van Merriënboer & Kirschner, 2018) (like the recipe example above). The process-oriented part of the worked example pays attention to the problem-solving processes necessary to reach the goal and is called a modeling example (Van Merriënboer & Kirschner, (2018), p 71).” This can be a case-study where the process is explained or a modeling example where the model (a real person, a video registration or an animation) also explains the steps being taken as well as gives an explicit explanation of the rationale behind those steps, including strategic information, such as heuristics and systematic approaches to problem-solving.

The process-oriented part is really important. After all, knowing how to do something is not enough to understand it; that is, you also need to know why something is being done. And this understanding is necessary for all transfer, both near (to seemingly similar tasks or problems) and far transfer (learning applied in real life situations that are different from the learning context) (Van Gog, Paas, & Van Merriënboer, 2008; Van Merriënboer & Kirschner, 2018).

Worked examples come in many shapes and forms but what they all have in common is that they’re not only usable for simple, well-structured tasks or problems like the recipe example, but also for complex, ill-structured tasks or problems. This means tasks or problems with unknown elements and multiple acceptable solutions. They also possess multiple criteria for evaluating solutions and often require learners to make all kinds of judgments.

The worked example effect (the finding that example-based learning is more effective for problem-solving than the standard procedure of solving problems) has been derived from cognitive load theory (CLT) (e.g., Paas, Renkl, & Sweller, 2003). CLT will say that worked examples are a way to optimise learning while minimising irrelevant load. There are two types of cognitive load that impact on learning efficiency; intrinsic and extrinsic cognitive load. At some point, germane cognitive load was also part of CLT, however because now it’s considered to be very closely related to intrinsic cognitive load, it has become accepted that intrinsic and germane cognitive load are essentially indistinguishable when it comes to their prediction and measurement. Therefore, germane cognitive load is now considered redundant as a concept within CLT (Kirschner, Sweller, Kirschner, & Zambrano, 2018). Let’s see what intrinsic and extrinsic load are.

Intrinsic load deals with the inherent complexity of the information that needs to be processed. Complexity is defined in terms of element interactivity, which refers to the number of elements that must be simultaneously processed in working memory and their interaction with each other. It’s affected by both the nature of the task and by levels of learner expertise. For example, when the learner needs to learn to translate 50 words from one language into another within a certain amount of time, this task might be difficult, but it is not considered a complex task. The interaction between the elements is low because the learner can translate each word individually and this translation is not affected by the other words. However, if words need to be combined to make sentences, the task is intrinsically more complex (element interactivity increases) even though the learner uses less than 50 words to make the sentences. As Kirschner and colleagues explain:

All of the words in a sentence have relations with other words (e.g., gender, gender related articles, plurals, tense, verb conjugation, etc.) and thus must be considered as a whole unit in working memory when learning to carry out this task. We are often unable to make any change to any of the parts of the sentence without affecting other elements and so element interactivity and intrinsic cognitive load are high. Element interactivity is affected by both (p. 7).

Extraneous load is a form of working memory load that refers to the load imposed by information elements unrelated to the learning task but related to how that task is carried out; how learning takes place. Essentially, these elements can be controlled by the person who designs the learning experience. The load can be relevant and beneficial to learning (e.g., a worked example) or it can be harmful or irrelevant (e.g., discovery). This load can be varied by using different instructional procedures and strategies (also read Kirschner, Sweller, & Clark, 2006). We need to dive a bit into the underlying CLT assumptions to understand why worked examples are effective.

Diving deeper into CLT: Why are worked examples effective for problem-solving skills?

CLT assumes that the human information processing system is characterised by a) limited working-memory capacity, b) unlimited long-term memory capacity (long-term memory consists of a vast number of hierarchically organised schemata) and c) automatic processing (after being sufficiently practiced, schemata can operate under automatic processing and therefore require no or minimal working memory resources).

As a practice method, worked examples can make learning more efficient through reducing extraneous load. Worked examples enable learners to make more efficient use of their limited cognitive resources (Moreno, 2006), which allows for better schema construction and automation (Van Gog et al., 2008).

A worked example typically illustrates a principle or pattern, which helps the learner to abstract the important / relevant information for mapping to similar or even different problems. It helps the learner to go from surface structure to deep structure of problems, focus on structural aspects of problems to derive the underlying concept common to the examples.

For example, as the following figure illustrates, a complex ‘worked-out problem’ can often be broken down into sub-problems. The solution process of each sub-problem then needs to be clearly illustrated with steps. The underlying principle(s) employed for the worked example then need to be explained as well as the sub-goals and how they integrate to clarify the underlying principle.

Let’s look at some examples in a bit more detail.

Examples of worked examples

Modelling examples – These provide maximum guidance for the learner; they pay explicit attention to the process needed to reach an acceptable solution.

This example is from Van Merriënboer & Kirschner (2018) and focuses on the task ‘Searching for relevant research literature’ for a librarian.

The worked example could be a 2-day internship that allows the learner to observe a librarian who is highly proficient in carrying out literature searches. The observations would include a complete picture of the whole task, such as conversations that the librarian has with clients so that (s)he can determine the relevant field of study and select appropriate databases for the research question at hand. It should also include formulating search queries (e.g., thesauri, Boolean operators), as well as performing the search with relevant search programs and various databases. Finally, it should include evaluation and selection of useful search results. Throughout the process, the librarian should explain what (s)he’s doing and why it’s done in that particular way. Also, the learner needs to get explicit explanations on how systematic approaches to problem-solving (SAPs) and rules of thumb are used to reason through difficult situations or exceptions.

This type of worked examples is highly applicable for knowledge work, for example in the domain of sales, technology, consultancy, etcetera. For example, Patti Shank has worked out a worked example on writing realistic customer service dialogue.

Case studies could be a next step in the learning process. Case studies give learners descriptions of actual or hypothetical problem solutions situated in the real world. Learners need to actively participate in the given solution. For example, in the context of the task ‘Searching for relevant research literature’ for a librarian, the case study could include research questions, a manageable list of research articles that are directly relevant for the research question, and modelling examples of the search queries for required databases. Learners need to answer questions that require deep processing of the problem state and the solution steps. This helps them to compare that particular case with other cases in order to induce generalised solutions.

From there on, the level of guidance will slowly be ‘faded’, using other types of learning tasks (which we won’t discuss in this blog). This way, learners have an opportunity to increasingly become more proficient and independent.

To sum it up, worked examples are the bomb. They’re simply the most effective instructional method for novices when it comes to discovering or constructing a solution to a problem. They’re without a doubt superior to discovering the solution to a problem in a non-structured authentic environment and they’re based on evidence that has been replicated in numerous occasions in a wide variety of contexts. Yes, they’re a quite lot of work to create but they’re truly worth the investment, especially in the workplace where learning needs to focus on authentic on-the-job tasks!

References

Kirschner, P. A., Sweller, J., Kirschner, F., & Zambrano, J. (2018). From cognitive load theory to collaborative cognitive load theory. International Journal of Computer-Supported Collaborative Learning, (13) 213-233. Retrieved from https://link.springer.com/article/10.1007%2Fs11412-018-9277-y

Kirschner, P. A., Sweller, J., & Clark, R. E. (2006). Why minimal guidance during instruction does not work: An analysis of the failure of constructivist, discovery, problem-based, experiential, and inquiry-based teaching. Educational psychologist, 41(2), 75-86. Retrieved from https://www.tandfonline.com/doi/pdf/10.1207/s15326985ep4102_1

Paas, F., Renkl, A., & Sweller, J. (2003). Cognitive load theory and instructional design: Recent developments. Educational Psychologist, 38(1), 1-4. Retrieved from https://s3.amazonaws.com/academia.edu.documents/36183118/Educational_Psychologist_paas2.pdf?AWSAccessKeyId=AKIAIWOWYYGZ2Y53UL3A&Expires=1539266321&Signature=F44%2FO7W8WOCRzca3098%2FG%2FhxzAU%3D&response-content-disposition=inline%3B%20filename%3DCognitive_load_theory_and_instructional.pdf

Van Gog, T., Paas, F., & Van Merriënboer, J. J. (2008). Effects of studying sequences of process-oriented and product-oriented worked examples on troubleshooting transfer efficiency. Learning and Instruction, 18, 211-222. Retrieved from http://dspace.ou.nl/bitstream/1820/1667/1/VanGog-etal_LI_2008.pdf

Van Merriënboer, J. J. G., & Kirschner, P. A. (2018). Ten steps to complex learning: A systematic approach to four-component instructional design. New York, NY: Routledge.