What's the best way to teach: first give the theory, then the problem, or vice versa?

There are several approaches to teaching students using educational material. One method is to first explain the theory and then present a problem to solve. Another approach suggests first presenting the problem so that students can think about it on their own, and then explaining the theoretical aspects. Both methods can include a demonstration of an example solution to a similar problem. Which of these approaches is more effective for students?

The cognitive load experienced by the student plays an important role in the problem-solving process. The higher this load, the more difficult the solution may be. However, the success of the task completion is equally important. The easiest and most comfortable option is not always the most effective. Sometimes, by facing difficulties and spending more time thinking, a person can gain a deeper understanding and greater benefit from the process. How can we find the optimal balance between these aspects to achieve the best learning outcomes?

Anna Gorbunova, a lecturer and research assistant at the Laboratory for Student Experience Research at the HSE Institute of Education, shared the results of her research aimed at analyzing pedagogical support during problem solving and the sequence of learning tasks. In her report, "Pedagogical Support in Problem Solving and the Sequence of Learning Tasks: Impact on Cognitive Load and Learning Outcomes," presented at the XIII International Russian Conference of Higher Education Researchers (IVO), she discussed how these factors influence students' cognitive load and their academic achievement. The study is currently being prepared for publication, which will allow its results to be shared more widely with the scientific community.

What Cognitive Load Consists of

Cognitive load is a term that describes the amount of information a person can process simultaneously. It plays a key role in learning and information comprehension. Understanding cognitive load allows us to better interpret research findings related to learning and perception. Effectively managing cognitive load helps improve information retention and enhance learning. It is important to consider how different information impacts cognitive abilities in order to optimize learning and make it more effective. Thus, research findings on cognitive load can help us better understand how we perceive and process information, as well as how educational methods can be improved. Human memory can be classified as short-term and long-term. Short-term memory, also known as working memory or RAM, is responsible for processing new information and its temporary storage. It is important to note that short-term memory has a limited capacity, making it effective only for quickly memorizing and processing data over a short period of time. Long-term memory, unlike short-term memory, is designed to store information over the long term and has a significantly larger capacity. Understanding these two types of memory helps to better organize the learning and memorization process.

Cognitive load is the amount of information currently being processed. If this volume becomes too large, the brain is unable to effectively transfer data from working memory to long-term memory, where all accumulated experience is stored. Therefore, for successful learning, it is necessary to optimize cognitive load to ensure effective assimilation of material and skill development. Optimizing cognitive load improves educational processes and promotes a deeper understanding of information.

Researchers distinguish three main types of cognitive load. The first type is intrinsic cognitive load, which is associated with the need to process new information and depends on the complexity of the material. The second type is extrinsic cognitive load, which arises due to external factors, such as the design of educational materials or teaching methods. The third type is Germane cognitive load, which promotes deep understanding and knowledge integration. Understanding these types of cognitive load helps optimize the learning process, improve information retention, and increase learning effectiveness.

Intrinsic cognitive load. This depends on the complexity of the material the student receives. The level of intrinsic load is influenced by the objective complexity of the information itself (for example, Newton's laws are easier to understand than quantum mechanics), as well as how difficult it is for a particular person to perceive (an expert may find the material simple, but a beginner in the topic may find it difficult to understand).
Extrinsic cognitive load. This is associated not with the educational material itself, but with any additional factors that interfere with the assimilation of information. For example, if extraneous sounds are constantly heard during a lesson, this is extrinsic cognitive load; it takes away a person's mental resources, which they need for learning. An inconvenient schedule and an inconvenient order of presentation of educational material can also be such factors.
Relevant cognitive load. This type of load is beneficial; it is aimed at ensuring that a person uses their brain resources as efficiently as possible. A clear structure of the material, additional examples, or algorithms needed to solve the problem—all this helps the brain process information and integrate it into long-term memory.

In this article, we examine in detail the theory of cognitive load, its basic principles, and its impact on learning. This concept helps us understand how limited attention and memory resources affect the process of information acquisition. Studying cognitive load allows us to optimize educational strategies and improve the quality of learning. Details about cognitive load theory can be found in our previous article.

How to Optimize Cognitive Load

For successful learning, it is important to reduce both intrinsic and extrinsic cognitive load, while increasing relevant load. Minimizing distractions is recommended, which will allow students to focus on internal cognitive processes. Creating a calm and organized learning environment will help improve concentration and enhance learning.

Creating a course that will help a novice student achieve professional mastery requires careful planning and a structured approach. First of all, it is important to define the target audience and their needs. Taking into account students' knowledge levels, it is necessary to develop a program that is logically consistent and covers all key aspects of the topic.

The course should include theoretical and practical classes, allowing students to apply their acquired knowledge in practice. It is important to integrate assignments and projects that will stimulate critical thinking and creativity, as well as help develop real-world problem-solving skills.

Using a variety of learning formats, such as video tutorials, text materials, webinars, and interactive assignments, is equally important. This will make the learning process more engaging and accessible. Provide regular feedback and support to students to help them overcome difficulties.

It is also worthwhile to provide opportunities for students to interact with each other, which facilitates the exchange of experiences and ideas. Adding assessment and certification upon course completion will enhance its value and motivation for students.

Thus, a well-designed course not only educates but also inspires students to further develop, preparing them for successful careers in their chosen field.

Anna Gorbunova shared information that in the problem-solving process, which was the focus of the study authors, two methods can be used to optimize the learning load.

Teacher support plays a key role in learning. Internal support is provided through the careful selection of problems that are appropriate for the topic and target audience. The teacher selects problems with open-ended or closed-ended questions that promote a deeper understanding of the material. External support includes additional resources, such as hints, worksheets with instructions, and solution algorithms, which help students overcome difficulties and achieve their goals. An effective combination of these types of support promotes higher-quality learning and skill development in students.

The second important aspect is choosing the most effective sequence for delivering educational materials, focused on the target audience of students. There are two main methods that assist in this process.

Deductive is the traditional and most common. First, the student is familiar with the theoretical explanation, looks at an example of a problem solution, and then independently solves the problem, based on the example. That is, they move from general information to specific questions.
The inductive method is usually associated with problem-based learning. It implies that the student immediately approaches the question or task, tries to think independently and find the answer, encounters difficulties, and only then receives a theoretical explanation.

Anna Gorbunova and her team studied the impact of various approaches on the cognitive load and educational outcomes of students. An important aspect of their study was the role of external support from the teacher, which consisted of offering students an algorithm for solving problems. This study aims to understand how structured support can optimize the learning process and increase its effectiveness.

How the Study Was Conducted

The study involved 254 law students, including both undergraduate and graduate students. The researchers randomly divided the participants into three groups and asked them to self-assess their knowledge of the fundamentals of argumentation and critical thinking. This study aims to identify the level of understanding and awareness of key concepts related to argumentation and critical thinking, which is an important aspect for future lawyers.

Still: the series "Elite" / Netflix

The groups of subjects were given the same educational material, which was presented in a different sequence.

Deductive sequence: first, students listened to Lecture 1, received an example with the solution algorithm 1, then listened to Lecture 2 and received an example with the solution algorithm 2, and only then were the students asked to independently solve problems 1 and 2.
Inductive sequence without pedagogical support: students were immediately asked to independently solve problems 1 and 2 and only then were they allowed to listen to Lecture 1, offered an example with the solution algorithm 1, then followed Lecture 2 and an example with the solution algorithm 2.
Inductive sequence with pedagogical support: here, students were first given an example with the solution algorithm and problem 1, then Lecture 1, then offered an example with the solution algorithm and problem 2, then Lecture 2.

In the first option, students began solving problems Only after studying the theoretical material and algorithms. In the second variant, they first attempted to solve the problems and then received explanations and algorithms. In the third variant, problems for independent work were immediately presented with solution algorithms, followed by the theoretical part. This approach allows for a deeper assimilation of the material and the development of independent work skills.

Anna Gorbunova explained that a solution algorithm refers to a similar example that is used to demonstrate an approach to solving a problem. For example, students need to identify the premises and conclusions of a given argument. As an algorithm, they are provided with an example analysis, where the premises and conclusions are clearly indicated. This helps to better understand the structure of the argumentation and develops critical thinking skills.

During the study, the researchers assessed the cognitive load of the subjects using surveys with questions about their perception of the material. Questions included: "How difficult did you find this material?", "Was it convenient for you to study it?", "How often were you distracted while studying?" and others. These data help us understand how various factors influence information comprehension and learning.

Anna noted that there is an alternative way to measure cognitive load using physiological indicators, such as heart rate or eye movements. However, this requires expensive equipment. Furthermore, Anna emphasizes, recent studies show that surveys have higher validity.

What hypotheses did the researchers put forward?

Before the study, the scientists formulated a number of hypotheses. These hypotheses served as the basis for further analysis and research aimed at identifying patterns and characteristics of the phenomenon under study. Formulating hypotheses is an important stage in the scientific process, as it determines the direction of research and helps focus on key aspects of the topic. Based on the data obtained during experiments, scientists could test their assumptions and make necessary adjustments to the theoretical basis of their conclusions.

The highest cognitive load, both internal and external, should be with an inductive sequence without support. The lowest should be with a deductive sequence (because everything is explained there). This means that students will find it most difficult to solve problems without preparation or solution algorithms, while the simplest is a traditional sequence, where independent work on the problem follows an explanation.
The level of relevant load and educational outcomes in the deductive method should be higher than in the inductive method with support. In the inductive method without support, the relevant cognitive load and student performance are the lowest.

However, the results of the experiment only partially confirmed the hypotheses.

What were the results?

The results of the experiment showed that intrinsic cognitive load, determined by the complexity of the educational material, does not depend on the order in which it is presented. The researchers did not find statistically significant differences in this indicator among the three groups of participants. This suggests that intrinsic cognitive load is more related to the quality of the presentation of the educational material, that is, how clearly it is formulated, than to its form or type. Thus, to improve the effectiveness of learning, it is important to focus on the clarity and accessibility of information presentation.

Extrinsic cognitive load significantly affects students' learning. Solving problems without prior preparation and support became a challenge for them. In this situation, students focused more on trying to master the task than on understanding and memorizing new material. At the same time, when using the deductive and inductive sequences with support, the level of external cognitive load was comparable. This indicates that the correct organization of the learning process can significantly facilitate the assimilation of information and improve the effectiveness of learning.

To understand the complexity of learning, the sequence in which the material is presented—whether it is a deductive or inductive approach with support—does not matter. The main thing is the effectiveness of the methodology that facilitates the assimilation of knowledge.

The useful relevant load was highest in the group using the inductive method with support. In the groups that used the deductive approach and the inductive method without support, the indicators were similar. This demonstrates the importance of support in learning and the effectiveness of the inductive method for achieving better results.

The study showed that students using the deductive method of learning demonstrate the best results. This group first listened to the lecture and studied the examples, and then solved the problems independently. Slightly less successful were students who studied the inductive method with support, which included studying the problem-solving algorithm and the problems themselves before the lecture. The weakest results were observed among students who solved the problems without prior preparation or examples. These findings highlight the importance of a structured learning approach that combines theory and practice.

Reading is an important aspect of our lives that contributes to the development of the mind and broadening of horizons. Books, articles and other materials enrich us with new knowledge and ideas. It's important not only to read but also to analyze what you read. This helps deepen your understanding of topics and retain information. Regular reading improves concentration and critical thinking skills. It also develops imagination and creativity. Therefore, it's worth paying attention to reading, choosing a variety of genres and topics to maximize the benefits of this process. The forgetting curve is a concept that describes how quickly a person forgets information after learning it. It demonstrates that without repetition and reinforcement, most information is lost quickly. To help students retain information long-term, it's important to implement active learning strategies. Using techniques such as repetition, association, and practice in context can significantly improve retention. Furthermore, the use of technology, such as digital flashcards and mobile learning apps, helps create an effective review environment. It's also important to consider the individual characteristics of each student, adapting teaching methods to their needs. Thus, understanding the forgetting curve and applying effective strategies will help students not only remember information but also apply it successfully in the future.

What conclusions have scientists drawn?

Anna Gorbunova emphasizes that clear instructions and detailed explanations significantly improve the working memory's ability to absorb new information. When designing the learning process, it is necessary to take into account the students' level of knowledge, which allows for effective structuring of the material and reduction of external load. Providing students with algorithms for solving problems is a useful tool. Therefore, Anna recommends, within the framework of problem-based learning, not leaving students without support when faced with new problems, but providing them with the necessary algorithms for solving them. This approach promotes a deeper understanding and assimilation of the material.

The question of whether it is worthwhile to immediately present a problem without a solution algorithm and then move on to a theoretical explanation remains open. Under certain conditions, this approach can be effective. In the next section of the article, we will take a closer look at when and how this method can be applied to maximize comprehension.

When the "problem first, explanation later" approach works

A study conducted by Tanmay Sinha and Manu Kapur, researchers from ETH Zurich, analyzed the results of 53 scientific studies on the effectiveness of the sequence of presentation of educational material. The researchers considered two approaches: one in which the explanation of the material follows the solution of the problem, and another in which the student first attempts to solve the problem and then receives the explanation. These findings could have a significant impact on teaching methods and approaches to the educational process.

Proponents of the first approach argue that a lack of preparation leads students to waste significant time and effort on incorrect attempts, which overloads their working memory and complicates the learning process. Meanwhile, opponents of this viewpoint believe that providing students with the opportunity to freely search for solutions promotes the development of their skills. By allowing students to draw on their existing knowledge and experience, they can reach more accurate conclusions and better understand the material.

Still: the TV series "Young Sheldon" / Warner Bros. Television

A key element of this approach is the concept of "productive failure." This method deliberately introduces a high probability of errors into the educational process at the initial stage of students' introduction to a new task or problem. During this period, students explore various solution methods, use their intuition, and propose their own ideas. Since they are not yet familiar with the theoretical foundations, their suggestions often turn out to be incorrect. Subsequently, the teacher organizes the explanation in a way that analyzes the errors made and answers any questions that arise. Research conducted by Sinha and Kapur shows that allowing students to make mistakes early on significantly reduces the likelihood of errors later in learning. Thus, "productive failure" becomes an important tool in developing deep understanding of the material and critical thinking in students.

A meta-analysis conducted by scientists found that the "problem first, explanation later" approach is often more effective than its opposite. However, several nuances should be considered. This teaching method helps to activate students' interest and deepen their understanding of the material, which ultimately contributes to better knowledge acquisition. It is important to remember that the effectiveness of this approach can vary depending on the context and individual characteristics of students.

This strategy most effectively demonstrates the transfer of declarative knowledge, that is, the explanation of concepts and relationships between objects and phenomena. Declarative knowledge is most often found in the humanities and social sciences. At the same time, when acquiring procedural knowledge related to the question "how to do it", both approaches show similar effectiveness, which is typical for technical disciplines.

The curriculum should include the concept of "productive failure", which plays an important role in the learning process. Sinha and Kapoor highlight the key elements of this concept. Productive failure allows students to learn from their mistakes, develop resilience, and critical thinking. It also helps develop skills for adapting to change and finding solutions to complex situations. It is important that educational programs support this concept by creating an environment in which mistakes are viewed as part of the learning process, not as an obstacle.

Group work on the initial solution to the problem and generating ideas;
Explanation based on students' hypotheses;
Teacher interaction with students in the form of a dialogue, rather than a lecture (even at the explanation stage).

When all the necessary conditions are present, teaching that begins with solving a specific problem or problem will be effective. This approach promotes a deeper understanding of the material and the development of the skills needed to successfully solve real-world issues.

The age of students significantly affects the effectiveness of a teaching strategy. Research shows that for students in grades two through five, the "problem first, explanation later" approach can have negative consequences. This is explained by the underdeveloped cognitive strategies of these children, which makes it difficult to use existing knowledge to generate and evaluate solutions. Therefore, Sinha and Kapur recommend scaffolding, presenting students with new tasks to help them better master the learning material and develop the necessary skills.

The researchers emphasize that it is premature to draw definitive conclusions at this time and suggest new avenues for further research. In particular, there is a lack of research on adult learning, which opens up opportunities for more in-depth study of this topic. More research is needed to understand the characteristics and effectiveness of teaching methods in this age group.