research to gain knowledge

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1.2 Ways of Creating Knowledge

What constitutes knowledge.

To have a deep understanding of what research entails, we need to first consider the historical context of ways of creating knowledge and what constitutes knowledge. Remember that “Research is creating new knowledge”. Our knowledge, thoughts, perceptions and actions are influenced by our worldview, which is a collection of attitudes, values, tales, and expectations about the world. 3 One’s view of the world is at the heart of one’s knowledge. There are different methods of acquiring knowledge, including intuition, authority, logical reasoning and the scientific method. 4

Cambridge dictionary defines intuition as the knowledge from an ability to understand or know something immediately based on feelings rather than facts. 1 It is also described as instinctive knowing without the use of cognitive processes or emotionally charged judgments that result from quick, unconscious, and holistic associations. 5 The impression that something is right comes from intuition. Instincts and intuition are sometimes used interchangeably. 4 Justifications like “that feels right to me” are often used to support intuition. However, as there is no means to evaluate the accuracy of the knowledge based on intuition, there is no way to distinguish between accurate and inaccurate knowledge using such an approach. As a result, it is challenging to assess the correctness of intuition in the absence of action. 4 In research, intuition may lead to generating hypotheses, especially in areas with limited or no prior information. Nonetheless, the hypothesis has to be tested before the knowledge is accepted in modern healthcare settings.

Getting knowledge from an authority figure is another common way of acquiring knowledge. 6 Authority refers to a person or organisation having political or administrative power, influence and control. The information generated from such authority is regarded to be true since it was expressed by a social media influencer or an expert in a certain field. 4 This approach entails embracing novel concepts because an authority figure declares them true. 4 It is one of the quickest and simplest ways to learn; therefore, it can often be a good place to start. 6 Some of these authorities are parents, the media, physicians, priests and other religious leaders, the government, and professors. 4 Although we should be able to trust authority figures in an ideal world, there is always a chance that the information they provide may be incorrect or out of context. 4 War crimes such as the Holocaust and the Guatemala Syphilis research, where atrocities against humanity were committed, are only a few instances when people blindly listened to authoritative leaders without scrutinising the information they were given. 4 Information on research topics obtained from authorities could generate new ideas about the concept being investigated. However, these ideas must be subjected to rigorous scientific scrutiny rather than accepted at face value.

Logical reasoning

Logic reasoning or rationalism is any process of knowledge generation that requires the application of reasoning or logic. 4 This approach is predicated on the idea that reason is the primary source of knowledge. 6 It is based on the premise that people can discover the laws that govern the behaviour of natural objects through their efforts. 6 Human behaviour is frequently explained using rationalism. In order to reach sound conclusions utilising this method, premises are provided, and logical principles are followed. However, if any assumptions are wrong, then the conclusion will be invalid. 4 For example, if a student fails to attend a series of compulsory lectures or tutorials, the professor may reason that the student is taking a lackadaisical approach to the subject. However, the assumption that attendance is an indicator of engagement may be untrue and lead to an erroneous conclusion. Perhaps, the student may have been ill or genuinely absent for some other unavoidable reason. This highlights the disadvantage of rationalism, as relying solely on this approach could be misleading, leading to inaccurate conclusions. 4 Thus, while rationalism may be helpful when developing or thinking of a research hypothesis, all research hypotheses need to be tested using the scientific method.

Scientific method

The scientific method is an empirical method for systematically gathering and analysing data to test hypotheses and answer questions. 4 Let’s go back to our example of the professor who concluded that the student who skipped the required classes had a lax attitude. This could possibly be due to some prior interactions with students who had demonstrated a lack of interest in studying the subject. This illustration shows the fallacy of drawing conclusions solely from experience and observation. The amount of experience we have could be constraining, and our sensory perceptions may be misleading. 4 Therefore, it is important to use the scientific method, which allows the researcher to observe, ask questions, test hypotheses, collect data, examine the results and draw conclusions. While researchers often draw on intuition, authority, and logical reason to come up with new questions and ideas, they don’t stop there. 4 In order to test their theories, researchers utilise systematic approaches by making thorough observations under a variety of controlled situations to draw reliable conclusions. 6 Systematic techniques are used in scientific methods, and every technique or design has a set of guidelines or presumptions that make it scientific. 4 Thus, empirical evidence based on observations becomes an item of knowledge. In the following chapters, we will go into greater detail about what the scientific method comprises.

How does scientific method contribute to evidence?

While everyday activities such as cooking, as seen in the opening scenario, may involve research, this type of research may not involve a systematic or controlled approach. Scientific research requires a systematic approach, and it is defined as a systematic inquiry/data-gathering process used to investigate a phenomenon or answer a question. 4 Research is also a way of knowing that involves critical examination of various aspects of a given phenomenon that is under investigation. It requires formulation and understanding of principles that guide practice and the development and testing of new ideas/theories. 7 Research aims to be objective and unbiased and contributes to the advancement of knowledge. Research adds to existing knowledge by offering an understanding or new perspective on a topic, describing the characteristics of individuals or things, or establishing causal links between factors. 8

An Introduction to Research Methods for Undergraduate Health Profession Students Copyright © 2023 by Faith Alele and Bunmi Malau-Aduli is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License , except where otherwise noted.

1.1 Methods of Knowing

Learning objectives.

• Describe the 5 methods of acquiring knowledge
• Understand the benefits and problems with each.

Take a minute to ponder some of what you know and how you acquired that knowledge. Perhaps you know that you should make your bed in the morning because your mother or father told you this is what you should do, perhaps you know that swans are white because all of the swans you have seen are white, or perhaps you know that your friend is lying to you because she is acting strange and won’t look you in the eye. But should we trust knowledge from these sources? The methods of acquiring knowledge can be broken down into five categories each with its own strengths and weaknesses.

The first method of knowing is intuition. When we use our intuition, we are relying on our guts, our emotions, and/or our instincts to guide us. Rather than examining facts or using rational thought, intuition involves believing what feels true. The problem with relying on intuition is that our intuitions can be wrong because they are driven by cognitive and motivational biases rather than logical reasoning or scientific evidence. While the strange behavior of your friend may lead you to think s/he is lying to you it may just be that s/he is holding in a bit of gas or is preoccupied with some other issue that is irrelevant to you. However, weighing alternatives and thinking of all the different possibilities can be paralyzing for some people and sometimes decisions based on intuition are actually superior to those based on analysis (people interested in this idea should read Malcolm Gladwell’s book Blink) [1] .

Perhaps one of the most common methods of acquiring knowledge is through authority. This method involves accepting new ideas because some authority figure states that they are true. These authorities include parents, the media, doctors, Priests and other religious authorities, the government, and professors. While in an ideal world we should be able to trust authority figures, history has taught us otherwise and many instances of atrocities against humanity are a consequence of people unquestioningly following authority (e.g., Salem Witch Trials, Nazi War Crimes). On a more benign level, while your parents may have told you that you should make your bed in the morning, making your bed provides the warm damp environment in which mites thrive. Keeping the sheets open provides a less hospitable environment for mites. These examples illustrate that the problem with using authority to obtain knowledge is that they may be wrong, they may just be using their intuition to arrive at their conclusions, and they may have their own reasons to mislead you. Nevertheless, much of the information we acquire is through authority because we don’t have time to question and independently research every piece of knowledge we learn through authority. But we can learn to evaluate the credentials of authority figures, to evaluate the methods they used to arrive at their conclusions, and evaluate whether they have any reasons to mislead us.

Rationalism

Rationalism involves using logic and reasoning to acquire new knowledge. Using this method premises are stated and logical rules are followed to arrive at sound conclusions. For instance, if I am given the premise that all swans are white and the premise that this is a swan then I can come to the rational conclusion that this swan is white without actually seeing the swan. The problem with this method is that if the premises are wrong or there is an error in logic then the conclusion will not be valid. For instance, the premise that all swans are white is incorrect; there are black swans in Australia. Also, unless formally trained in the rules of logic it is easy to make an error. Nevertheless, if the premises are correct and logical rules are followed appropriately then this is sound means of acquiring knowledge.

Empiricism involves acquiring knowledge through observation and experience. Once again many of you may have believed that all swans are white because you have only ever seen white swans. For centuries people believed the world is flat because it appears to be flat. These examples and the many visual illusions that trick our senses illustrate the problems with relying on empiricism alone to derive knowledge. We are limited in what we can experience and observe and our senses can deceive us. Moreover, our prior experiences can alter the way we perceive events. Nevertheless, empiricism is at the heart of the scientific method. Science relies on observations. But not just any observations, science relies on structured observations which is known as systematic empiricism.

The Scientific Method

The scientific method is a process of systematically collecting and evaluating evidence to test ideas and answer questions. While scientists may use intuition, authority, rationalism, and empiricism to generate new ideas they don’t stop there. Scientists go a step further by using systematic empiricism to make careful observations under various controlled conditions in order to test their ideas and they use rationalism to arrive at valid conclusions. While the scientific method is the most likely of all of the methods to produce valid knowledge, like all methods of acquiring knowledge it also has its drawbacks. One major problem is that it is not always feasible to use the scientific method; this method can require considerable time and resources. Another problem with the scientific method is that it cannot be used to answer all questions. As described in the following section, the scientific method can only be used to address empirical questions. This book and your research methods course are designed to provide you with an in-depth examination of how psychologists use the scientific method to advance our understanding of human behavior and the mind.

• Gladwell, M. E. (2007). Blink: The power of thinking without thinking.  How to think straight about psychology (9th ed.). New York: Little, Brown & Company. ↵

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How To Gain Knowledge: 8 Popular Ways to Learn More

“Knowledge is a skyscraper. You can take a shortcut with a fragile foundation of memorization, or build slowly upon a steel frame of understanding.” – Naval Ravikant

Whether through formal education, real-life experiences, or continuous learning, gaining knowledge is a lifelong pursuit that enriches our personal and professional lives. 

There’s Power in Continuous Learning

Learning should not be confined to the years spent in school or college, but instead should be seen as a lifelong journey. With the rapid advancement of technology, access to knowledge has become easier than ever before. 

“Think of continuous learning as the adventurous, self-driven cousin of the more formal, structured continuing education. It’s a broad, all-encompassing approach that encourages a lifelong love of learning and adaptability,” said software developer Tom Cooper on LinkedIn . 

By actively seeking opportunities to expand our knowledge base, we not only enhance our professional prospects but also cultivate a mindset of growth and adaptability.

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Whether it’s acquiring knowledge about psychology to enhance our interpersonal skills, delving into the realms of philosophy to broaden our perspectives, or learning about nutrition and fitness to improve our health, the pursuit of knowledge opens doors to personal growth and allows us to lead fulfilling lives.

You’ll Foster Intellectual Growth and Cognitive Skills

The acquisition of knowledge stimulates our cognitive function and nurtures the growth of our intellectual capabilities. Whether through reading books, engaging in thoughtful discussions, or participating in online courses, actively seeking knowledge challenges our thinking, expands our horizons, and enhances our analytical and critical thinking skills. 

“Information is everywhere but its meaning is created by the observer that interprets it. Meaning is relative and there is no objective, over-arching meaning.” – Naval Ravikant  

By exposing ourselves to diverse ideas and perspectives, we develop the ability to think creatively, solve problems, and make informed decisions, ultimately leading to intellectual growth.

8 Ways to Gain Knowledge

The pursuit of knowledge is fueled by a curious mindset and a strong desire to learn. It goes beyond just acquiring information; it involves actively seeking knowledge and engaging in continuous learning. 

1. Reading Books

• Value: Books stand as timeless vessels of knowledge. They capture the essence of human thought, experience, and imagination over the ages, allowing us to journey into the depths of countless subjects. Whether fiction or non-fiction, every page offers insights that can significantly shape our perception and understanding of the world.
• Diverse Knowledge: Books cover an expansive range of topics. From history and science to philosophy and art, they cater to every curiosity, enabling readers to acquire a multifaceted education.
• Deep Exploration: Unlike short articles or news, books often delve deep into subjects, presenting thorough research, background, and analysis. This depth promotes a comprehensive understanding of topics.
• Development of Cognitive Skills: Reading not only provides information but also hones cognitive faculties. It enhances critical thinking, analytical prowess, and problem-solving capabilities. As readers analyze plots, arguments, or research, they naturally sharpen these skills.
• Challenging Beliefs: Books can serve as intellectual sparring partners. They challenge our pre-existing beliefs and viewpoints, prompting introspection, debate, and sometimes, a change of heart.
• Lifelong Learning: With millions of titles available and many more being published every year, books ensure that the quest for knowledge never has to end. They can be revisited, and new ones can be explored, making learning a lifelong endeavor.

2. Taking Courses

Value: Courses, whether online or in traditional classrooms, are structured forms of learning. They follow a specific syllabus that gradually takes a learner from basic to advanced concepts.

Benefits: Courses often come with the guidance of instructors, assignments to test your grasp, and peer discussions, which can provide varied perspectives on the same topic. Furthermore, at the end of a course, you typically receive a certificate or credential , which can be a tangible proof what you’ve done.

3. Attending Workshops

Value: Workshops are typically hands-on and practice-oriented sessions. They are shorter in duration than courses and focus on imparting specific skills or knowledge in an interactive environment.

Benefits: Attending workshops can provide immediate, actionable insights. They often involve real-world scenarios, group activities, or live demonstrations, making learning more engaging and practical. Plus, workshops can be a great place to network with like-minded individuals and industry experts.

4. Seeking Guidance from Mentors or Experts

Value: Mentors and experts have been through the journey already. They’ve encountered challenges, made mistakes, and learned from them. As such, they can offer invaluable advice that’s rooted in real-world experience.

Benefits: Engaging with mentors can provide personalized feedback and direction. They can help in setting clear goals, avoiding common pitfalls, and accelerating the learning process. Furthermore, a mentor’s guidance often goes beyond just knowledge; they can provide emotional and moral support, especially when one faces doubts or challenges.

In essence, while self-study and individual exploration are pivotal, the structured learning from courses, the practical experience from workshops, and the seasoned wisdom from mentors significantly amplify our capacity to gain knowledge. This triad forms a strong foundation, ensuring we not only learn but also effectively apply and retain what we’ve learned.

5. Finding Relevant Sources

Value: In the vast sea of information, identifying and relying on relevant sources stands paramount. Accurate and valid knowledge is built upon the bedrock of credible information. To make informed decisions, nurture genuine understanding, and avoid misinformation, it’s imperative to turn to trustworthy sources.

• Precision and Validity: By focusing on reputable sources, such as academic journals and expert-authored books, you ensure that the information you consume is not only precise but also valid.
• Skillful Research : Mastering the art of finding relevant sources involves more than just a cursory Google search. Employing specific keywords, using advanced search filters, and discerning credible websites from unreliable ones are skills that can be developed over time. This focused approach ensures you access quality over quantity.
• Access to In-depth analysis: Academic journals, for instance, are treasure troves of comprehensive research. They are subjected to stringent peer-review processes, ensuring the content is both rigorous and reliable. Diving into such materials allows one to gain nuanced insights and an in-depth understanding of specific topics.
• Access subject matter experts at your company: Tap into and share knowledge from experts at your company, and record this info into a single source of truth .

6. Recommendations from Experts

Value: Networking and seeking advice from professionals or trusted individuals in a particular field can be a goldmine. These individuals can direct you to seminal works, key journals, or essential reading materials in the subject of interest. 

Benefits: Whether through mentorship, networking, or simply seeking advice, leveraging the expertise of experienced individuals can provide invaluable guidance and accelerate one’s own learning journey. Their firsthand experiences, anecdotes, and proven strategies offer a unique perspective that can contribute to personal and professional growth.

7. Industry Newsletters

• Value: Industry newsletters serve as a distilled source of information, specifically tailored to provide updates, insights, and trends that matter to professionals in that sector. They encapsulate the pulse of the industry, ensuring you don’t miss out on vital information.
• Timely Delivery: Receive up-to-the-minute news and insights directly, removing the need for proactive searching.
• Curated Content: Benefit from content that’s been selected for its relevance and importance, helping you stay ahead of the curve.
• Conciseness: Digestible, concise information ensures you can quickly grasp the essentials without being overwhelmed.

8. Relevant Social Media Accounts:

• Value: Today, social media isn’t just for leisure—it’s a significant hub for professional content. Platforms host a myriad of experts, influencers, and organizations that continually share industry-relevant content.
• Real-time Updates: Gain instant access to the latest happenings and thought leadership articles.
• Diverse Perspectives: Engage with a variety of voices from the industry, from top-tier CEOs to emerging professionals.
• Interactive Learning: Engage, comment, and discuss topics, ensuring a two-way flow of knowledge.

9. Conferences and Webinars

• Value: Conferences and webinars represent collaborative learning hubs. They bring together the best minds in an industry to share, discuss, and ideate, making them an indispensable resource for anyone serious about their profession.
• Networking Opportunities: Connect with industry peers, potential business partners, or mentors.
• Insights into Emerging Trends: Be the first to know and understand what’s on the horizon for your industry.
• Practical Knowledge: Learn actionable strategies and solutions from seasoned professionals.

10. Professional Networks:

• Value: Professional networks are ecosystems of knowledge. Whether online forums or offline associations, these networks foster a sense of community, making knowledge exchange more fluid and accessible.
• Continuous Learning: Engage in events, webinars, and discussions organized by the network.
• Collaborative Growth: Share insights, get feedback, and collaborate on projects or ideas.
• Strengthened Connections: Forge strong professional bonds that can be beneficial for career advancement or collaboration.

11. Accessing Online Courses

• Value: As we sail further into the digital age, online courses stand as shining beacons of accessible education. They bridge geographical divides, cater to diverse learning paces, and offer a plethora of subjects, making continuous learning feasible for all.
• Anytime, Anywhere Learning: The traditional confines of a classroom setting are dissolved. Whether it’s late at night or during a lunch break, learning now fits into any schedule.
• Self-paced Study: Online courses cater to all learning speeds, allowing individuals to revisit topics or accelerate as they see fit.
• Platforms like Coursera, Udemy, and Khan Academy host courses on nearly every topic imaginable, from niche arts to mainstream business strategies.
• Simple Sign-Up: Engaging with a course is often as simple as creating an account on a platform and selecting the desired course.
• Countless Options: With thousands of courses available, learners can constantly find new areas to explore or deepen their expertise in familiar ones.
• Tailored to Individual Needs: Instead of a one-size-fits-all approach, online courses offer the freedom to choose subjects and levels aligned with personal and professional goals.
• Empowered Decision Making: By evaluating personal interests, skill development targets, and career goals, learners can craft a fulfilling and relevant educational journey.

Gaining knowledge is more accessible than ever, but the abundance of information can be overwhelming. Start by setting clear objectives; understanding what you wish to learn gives direction to your quest. Next, choose reputable sources. Engaging in active learning by taking notes, participating in discussions, or teaching someone else can solidify understanding.

Always remember to practice critical thinking. Question what you learn, compare sources, and apply logic. Knowledge isn’t static; it’s a continually evolving entity. Regularly update your knowledge base , and be open to new ideas and methods. Gaining knowledge is a systematic and ongoing journey, but with the right strategies, it’s a fulfilling and invaluable endeavor.

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10 Methods To Acquire Knowledge Effectively

Knowledge is the basis of everything in existence. Without knowledge nothing would exist as we perceive it to be. It is imperative and indispensable. Knowledge is the building blocks of any foundation. Knowledge is the key to opening doors that would otherwise be locked. Commodities are only sought after due to knowledge and awareness.

1) Research Meticulously

Being immersed in this world of information can be a daunting task to handle and comprehend. Ensuring proper research is completed has been proven to be conducive to fact finding. The truth is what holds value when researching a particular topic. Try your best not to let emotions play a role in how you perceive what’s being explained. The Internet is a wonderful place to start, and it can end there as well. However, the addition of reading books is a surefire methodology to enhancing your research. Having clarity and precision is the difference between gaining knowledge or becoming bamboozled.

2) Read Books

The level of convenience is unmatched when reading a book, whether it is electronic or physical. This process can be done anywhere you decide to go, and has zero limitations. The Internet cannot always be accessed, and cannot be relied upon to broaden your horizons. The information provided in books is direct, as opposed to reading published articles online.

Reading stimulates the brain to focus solely on each word written down in the text, and expands the lens of imagination. The cognitive function changes direction when reading digitally. Shortcuts are taken, keywords are searched for, and the page disappears once its finished, making it impossible to turn back to the page for a review. That said, this doesn’t mean one method is better than the other. Balance is what matters. Don’t neglect the power of books.

3) Operate Consciously

Many people get caught up in the routine of doing what they need to survive, which can cause their actions to be mechanically inclined. Actions are then executed without thinking, while the procedure can be affected negatively. Sit back, clear your mind, and contemplate deeply on every move you make. Setting yourself into a trap is the most deadly decision you can make. Ameliorating circumstances are part of living a happy life. Remaining consciously aware of your surroundings and environment can prevent horrendous problems from occurring. Understand that your actions affect those who are around you, as well as people you may never meet. Push forward with firmness of purpose and constancy.

4) Develop Good Habits

We are all plagued with having bad habits. They are the flaws we all possess, but don’t settle for letting your bad habits outweigh the good. Every day is new and different; however, there are still responsibilities, duties, and tasks we are held accountable for. We have to do similar things everyday to survive, which are the habits we choose to develop. Replacing bad habits with good habits can take months, and it isn’t an easy feat. When you are locked in on something that isn’t improving your circumstances, it constitutes a bad habit.

Whatever the habit may be, acknowledge you’re wasting time doing so, and replace it with a passion that will benefit you. These habits can range from something as simple as cooking more, to setting a deadline for a project you’re creating.

5) Harness Productivity

Work ethic goes a long way in this life. There are times for playfulness and relaxation, but you must devote the entirety of your day to the grind. Everyday you must work towards something better. Apart from your job, you must work on something new that will stimulate your mind. There’s always work to be done. It could be working on yourself, helping others, growing a business, finding another job, or even something simple like cleaning and organizing your residence. Boredom is a result of being uninspired and not challenging yourself to become better.

6) Set Obtainable Goals

Create realistic deadlines for the goals you want to accomplish. Don’t fool yourself by trying to complete what you’re working towards too quickly. Moving hastily is a dangerous sojourn to embark on, and it must be regulated. Try to set a date that suits your schedule, and then push it ahead a few days. This way you may be able to complete the goal before the deadline. If you are focused on completing a goal too soon, and don’t meet the deadline, you will only get discouraged and possibly give up. Goals are like anchors; once they are set they will stay in alignment.

7) Encourage Others

Support people’s visions, and give them positive feedback on what they’re trying to accomplish. Let them know what they’re striving for is larger than them. Show up to their events. Constructive criticism is only warranted if you’re a genuine individual, and should only be expressed if there’s a personal relationship involved in the matter.

8) Believe In Yourself

Having faith in what you do is a tremendously insatiable power. It forces you to grow, helps you love yourself more, and constantly pushes you outside of your comfort zone. Understand the vast reality of what it takes to be what you want to become. If anyone doubts you, don’t bother listening to them, because if you indulge their negativity you’ll waste your time and energy. Definitely take what they say into consideration, but never let it diminish the vision you have been blessed with.

9) Embrace Pain

History has taught us that those who experience the most pain are the successful ones. Nothing will be given to you in this life; pain is an inevitable emotional state. You must learn how to enjoy the shackles of pain, push through it, and see the light at the end of the tunnel. Darkness is only the absence of light. We all have the ability to shed our own light.

10) Learn From Your Mistakes

Failure is a part of life. Without failure none of us would be able to learn. Your best teacher is the last mistake you made, and nothing can trump the consolidation of experience. Think critically about why you failed at particular actions, then make adjustments, strategize, and try again. The process of learning is a cyclical process like the Earth spinning on its axis.

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How People Learn II: Learners, Contexts, and Cultures (2018)

Chapter: 5 knowledge and reasoning, 5 knowledge and reasoning.

This chapter examines the development of knowledge as a primary outcome of learning and how learning is affected by accumulating knowledge and expertise. HPL I 1 emphasized these topics as well, but subsequent research has refined and extended understandings in a variety of learning domains. The first section of this chapter describes the problem of knowledge integration from the perspective of learning scientists and illustrates with research findings how people integrate their knowledge at different points in their development and in different learning situations. The second section describes what is known about the effects of accumulated knowledge and expertise on learning. The second half of the chapter discusses strategies for supporting learning. The committee has drawn on both laboratory- and classroom-based research for this chapter.

HPL I noted that the mind works actively to both store and recall information by imposing structure on new perceptions and experiences ( National Research Council, 2000 ). A central focus of HPL I was how experts structure their knowledge of a domain in ways that allow them to readily categorize new information and determine its relevance to what they already know. Because novices lack these frameworks, they have more difficulty assimilating and later recalling new information they encounter. This chapter expands on these themes from HPL I , citing relevant research reported since that study.

___________________

1 As noted in Chapter 1 , this report uses the abbreviation “ HPL I ” for How People Learn: Brain, Mind, Experience, and School: Expanded Edition ( National Research Council, 2000 ).

BUILDING A KNOWLEDGE BASE

Knowledge integration is a process through which learners put together different sorts of information and experiences, identifying and establishing relationships and expanding frameworks for connecting them. Learners must not only accumulate knowledge from individual episodes of experience but also integrate the knowledge they gain across time, location, circumstances, and the various formats in which knowledge appears ( Esposito and Bauer, 2017 ). How knowledge acquired in discrete episodes is integrated has been debated for decades ( Karmiloff-Smith, 1986 , 1990 ; Mandler, 1988 ; Nelson, 1974 ). Some researchers have suggested that infants are born with foundational knowledge that provides the elements necessary for learning and reasoning about their experiences ( Spelke, 2004 ; Spelke and Kinzler, 2007 ) or that infants can build from basic inborn reflexes to actively engage with the world and gradually build skills and knowledge ( Fischer and Bidell, 2006 ). Others have argued that all knowledge is generated through an individual’s direct experience with the world ( Greeno et al., 1996 ; Packer, 1985 ).

More recent work suggests that the integration of knowledge is a natural byproduct of the formation and consolidation of episodic memories ( Bauer, 2009 ; Bauer et al., 2012 ). As described in Chapter 4 , when a memory is consolidated, the learner associates representations of the elements of the experience (e.g., sights, sounds, tactile sensations) and these associations serve to help stabilize that memory. At the same time, these representations may also be linked with older memories from previous experiences that have already been stored in long-term memory ( Zola and Squire, 2000 ). The fact that old and new memory traces can be integrated shows that these traces are not fixed. Instead, elements common to the new and stored memory traces reactivate the old memory and, as the new memory is consolidated, the old memory may be reconstructed and undergo consolidation again ( Nader, 2003 ). When information from either learning episode is later retrieved, elements of both memory traces will be reactivated and will be simultaneously available for reintegration. As memory traces with common elements are simultaneously activated and linked, knowledge is expanded and memories are iteratively reworked. Figure 5-1 illustrates how this happens.

These linked traces may then be integrated with additional new information that comes to the learner later, and another new memory trace undergoes consolidation. Interestingly, it is exactly this process of integration of information from different episodes that may explain why people are sometimes unable to explain when and where they gained particular knowledge. Because the information generated by memory integration was not actually experienced as a single event, the information was not tagged with its origin ( Bauer and Jackson, 2015 ).

The studies of knowledge acquisition in children and college students presented in Box 5-1 illustrate the capacity to integrate unconnected infor-

mation and retain this knowledge starting at a very young age. These studies underscore the active role of the learner; that is, even young children do not simply accrue knowledge from what they have experienced directly but build knowledge from the many things that they have figured out on their own, which, over time, they can do with less repetition and external support.

As discussed in Chapter 2 , adequate sleep is important for integration and learning. The brain continues the work of encoding and consolidation during sleep and facilitates generalizations across learning episodes ( Coutanche et al., 2013 ; Van Kesteren et al., 2010 ). Specifically, activation of the hippocampus (which plays a key role in memory integration) during sleep seems to allow connections between memory traces to be formed across the cortex. This process promotes the integration of new information into existing memory traces, allows for abstraction across episodes ( Lewis and Durant, 2011 ), and leads to the possibility of building novel connections, which may be both creative and insightful or may be bizarre ( Diekelmann and Born, 2010 ).

BOX 5-1 Examples of Developmental Differences in the Process of Knowledge Acquisition

Knowledge and expertise.

When people repeatedly engage with similar situations or topics, they develop mental representations that connect disparate facts and actions into more effective mental structures for acting in the world. For example, when people first move to a new neighborhood, they may learn a set of discrete routes for traveling between pairwise locations, such as from home to school and from home to the grocery store. Over time, people naturally develop a mental representation of spatial relationships, or mental map, that stitches these discrete routes together. Even if they have never traveled between the school and the grocery store, they can figure out the most efficient route by consulting their mental map ( Thorndyke and Hayes-Roth, 1982 ). The observation that experts in a domain have developed frameworks of information and understanding through long experiences in a particular area was a central focus of HPL I . In this section, we briefly describe some of the benefits of expert knowledge (a more detailed discussion of the benefits of expertise appears in HPL I ) and then discuss the knowledge-related biases that may come with expertise.

Benefits of Expertise

One of the most well-documented benefits of the acquisition of knowledge is an increase in the speed and accuracy with which people can complete recurrent tasks: remembering a solution is faster than problem solving. Another benefit is that people who develop expertise can handle increasingly complex problems. One way this occurs is that people master substeps, so that each substep becomes a chunk of knowledge that does not require attention (e.g., Gobet et al., 2001 ). People also learn to handle complexity by developing mental representations that make specific tasks easier to complete. When Hatano and Osawa (1983) studied abacus masters, they found that even without an abacus in front of them, the masters had prodigious memories for numbers and could carry out addition problems with very large numbers because they had developed a mental representation of an abacus, which they manipulated virtually. These abacus masters did not show similarly superior ability to remember or keep track of letters or fruits—tasks that were not aided by manipulating a virtual abacus.

A third benefit is an increase in the ability to extract relevant information from the environment. Experts not only have better-developed knowledge representations than novices have but also can perceive more information that is relevant to those representations. For example, radiologists are able to see telling patterns in an x-ray that appear merely as shadows to a novice ( Myles-Worsley et al., 1988 ). The ability to discern more precise information complements a more-differentiated mental representation of those phenomena.

An implication of this ability is that students need to learn to see the relevant information in the environment to help differentiate concepts, such as the difference between a positive and a negative curvilinear slope ( Kellman et al., 2010 ).

A fourth benefit of acquiring expert knowledge is that it helps people use their environment as a resource. Using what is known as distributed cognition, people can offload some of the cognitive demands of a task onto their environment or other people ( Hollan et al., 2000 ). For instance, a major goal of learning is to develop knowledge of where to look for resources and help, and this is still important in the digital age. Experts typically know which tools are available and who in their network has specialized expertise they can call upon.

Finally, acquiring knowledge helps people gain more knowledge by making it easier to learn new and related information. Although some cognitive abilities related to learning novel information decline, on average, with age, these declines are offset by increases in knowledge accumulated through the life span, which empowers new learning. For example, in a study of young adults and older adults (in their 70s) who listened to a broadcast of a baseball game, the older adults who knew a lot about baseball recalled more of the broadcast than the young adults who knew less about baseball. This occurred despite the fact that the younger adults had superior executive functioning ( Hambrick and Engle, 2002 ).

Bias as a Natural Side Effect of Knowledge

As people’s knowledge develops, their thinking also becomes biased. But the biases may be either useful or detrimental to learning. The word “bias” often has negative connotations, but bias as understood by psychologists is a natural side effect of knowledge acquisition. Learning biases are often implicit and unknown to the individuals who hold them. They appear relatively early in knowledge acquisition, as people begin to form schemas (conceptual frameworks) for how the world operates and their place within it. These schemas help individuals know what to expect and what to attend to in particular situations (e.g., in a doctor’s office versus at a friend’s party) and help them develop a sense of cultural fluency—that is, to know how things work “around here” ( Mourey et al., 2015 ).

Psychologists distinguish two types of bias: one is intrinsic to learning and primarily useful and empowering to the learner; the second occurs when prior experiences or beliefs undermine the acquisition of new knowledge and skills.

An aphorism from the context of medical diagnosis illustrates the two types of bias: “When you hear hoof-beats, think of horses not zebras.” In the United States, horses are much more common than zebras so one is much more likely to encounter the common “horses” than the rare “zebras.” Of course, one should modify assumptions in light of additional evidence: if the

large mammal from which the hoof-beats emanate has black and white stripes, it is much more likely to be a zebra than a horse. Thus, if one sees a striped animal in a zoo but insists that it is a horse and not a zebra, this resistance to new information is a strong form of the limiting effects of bias on learning. A person may fail even to notice the zebra at the zoo because he was so strongly expecting to see a horse instead and was attuned to notice only that kind of animal.

Making matters even more complicated, two people who have different prior levels of expertise, or different beliefs, might legitimately have different interpretations when initially presented with the same information. But if sufficient additional information suggests a particular interpretation, they should converge on an answer, especially if the higher level of expertise is brought to bear.

Beliefs about human-caused global climate change are a good example of the biases that blind individuals to new evidence. Despite nearly universal consensus among climate scientists that global climate change is taking place and that this change is induced by humans’ behavior, a considerable proportion of adults in the United States do not accept these interpretations of the evidence. One might expect that higher levels of science literacy would be associated with greater agreement with the scientific consensus. However, Kahan and colleagues (2012) found that it is among the individuals with the highest levels of science literacy that the most stark polarization is apparent. Those who only seek out and attend to information consistent with their prior beliefs will create an “echo-chamber” that further biases their learning. Often this echo-chamber effect is socially reinforced, as individuals prefer to discuss the topic in question with others whom they know hold beliefs similar to their own.

Stereotypes perpetuate themselves through learned bias, but not all learning biases are considered to have negative consequences. For example, some positive biases promote well-being and mental health ( Taylor and Brown, 1988 ), some may promote accuracy in perceptions of other people ( Funder, 1995 ), and others may be adaptive behaviors—for example, selective attention and action in situations in which errors have a high cost ( Haselton and Buss, 2000 ; Haselton and Funder, 2006 ). Hahn and Harris (2014) have written a useful historical overview of research on bias in human cognition.

Still other biases refine perception and serve to blur distinctions within categories that are not meaningful while highlighting subtle cross-category distinctions that may be important. For example, very young infants respond equally to phonological contrasts that matter in their language (e.g., “r” and “l” if the baby lives in an English-speaking context) and those that do not matter (e.g., “r” and “l” in a Japanese-speaking context). Over time, infants lose this discriminatory capability. This loss is actually a benefit, reflecting the baby’s increasing efficiency in processing his own language context, and is a mark of

learning ( Kuhl et al., 1992 ). In the other direction, dermatologists may learn from experience and formal training to distinguish subtle features of moles and skin growths that signal malignancy, features that to an untrained eye are indistinguishable from those of benign growths.

Biases affect the noncognitive aspects of learning as well. In a variable world, highly stable task environments are not guaranteed and so training to high efficiency may actually create a mindset that makes new learning more difficult, impeding motivation and interest in continuous growth and development. For instance, a person who has learned how to organize her schedule using a specific tool may be reluctant to learn a new tool because of the perception that it will take too much time to learn to use it, even though it may be more efficient in the long run. In this example, it is not that the person is unable to learn the new tool; rather, her beliefs about the amount of effort required affect her motivation and interest in learning. This kind of self-attribution, or prior knowledge of oneself, can have a large influence on how people approach future learning opportunities, which in turn influences what they will learn ( Blackwell et al., 2007 ).

KNOWLEDGE INTEGRATION AND REASONING

We have seen that building a knowledge base requires doing three things: accumulating information (in part by noticing what matters in a situation and is therefore worth attending to); tagging this information as relevant or not; and integrating it across separate episodes. These three activities can happen relatively quickly and automatically, or they can happen slowly through deliberate reflection. However, these processes alone are not sufficient for integrating and extending knowledge. Learners of all ages know many things that were not explicitly taught or directly experienced. They routinely generate their own novel understanding of the information they are accumulating and productively extend their knowledge.

Inferential Reasoning

Inferential reasoning refers to making logical connections between pieces of information in order to organize knowledge for understanding and to drawing conclusions through deductive reasoning, inductive reasoning, and abductive reasoning ( Seel, 2012 ). Inferential thinking is needed for such processes as generalizing, categorizing, and comprehending. The act of reading a text is a good example. To comprehend a text, readers are required to make inferences regarding information that is only implied in the text (see, e.g., Cain and Oakhill, 1999 ; Graesser et al., 1994 ; Paris and Upton, 1976 ). Some types of inferences help readers track the meaning of a text by integrating different information it supplies, for example by recognizing anaphoric

references (words in a text that require the reader to refer back to other ideas in the text for their meaning). Other types of inferences allow a reader to fill in gaps in the text by recruiting information from beyond it (i.e., background knowledge), in order to understand information within the text. Though these types of inferences are essential for understanding, they are thought to survive in working memory only long enough to aid comprehension ( McKoon and Ratcliff, 1992 ).

Other inferences that learners make survive beyond the bounds of working memory and become incorporated into their knowledge base. For example, a person who knows both that liquids expand with heat and that thermometers contain liquid may integrate these two pieces of information and infer that thermometers work because liquid expands as heat increases. In this way, the learner generates understanding through a productive extension of prior learning episodes.

Effective problem solving typically requires retrieved knowledge to be adapted and transformed to fit new situations; therefore, memory retrieval must be coordinated with other cognitive processes. One way to help people realize that something they have learned before is relevant to their current task is to explicitly give them a hint that it is relevant ( Gick and Holyoak, 1980 ). For example, such hints might be embedded in text, provided by a teacher, or incorporated into virtual learning platforms. Another strategy for helping people realize that they already know something useful is to ask people to compare related problems in order to highlight exactly what they have in common, increasing the likelihood that they will recall previously acquired knowledge with similar properties ( Alfieri et al., 2013 ; Gentner et al., 2009 ).

Kolodner et al. (2003) gives the example of an architect trying to build an office building with a naturally lit atrium. She realizes that a familiar library’s design, which includes an exterior wall of glass, could be reused for the office building, but would fit the building’s needs better if translucent glass bricks were used instead of a clear, glass pane. This kind of design-based reasoning is incorporated into problem-based learning ( Hmelo-Silver, 2004 ) activities. Problem-based learning emphasizes that memories are not simply stored to allow future reminiscing, but are formed so that they can be used, reshaped, and flexibly adapted to serve broad reasoning needs. The goal of problem-based learning is to instill in learners flexible knowledge use, effective problem-solving skills, self-directed learning, collaboration, and intrinsic motivation. These goals are in line with several of the goals identified in other contexts as important for success in life and work ( National Research Council, 2012b ).

Age-Related Changes in Knowledge and Reasoning

People’s learning benefits from a steady increase, over many decades, in the accumulation of world knowledge (e.g., Craik and Salthouse, 2008 ;

Hedden and Gabrieli, 2004 ). This accumulation makes it easier for older adults not only to retrieve vocabulary and facts about the world ( Cavanagh and Blanchard-Fields, 2002 ) but also to acquire new information in domains related to their expertise. For example, physicians acquire medical expertise, which enables them to comprehend and remember more information from medical texts than novices can ( Patel et al., 1986 ). It is also thought that older adults can compensate for declines in some abilities by using their extensive world knowledge. For instance, medical experts depend less on working memory because they can draw on their expertise to reconstruct only those facts from long-term memory that are relevant to a current need (e.g., Patel and Groen, 1991 ).

The knowledge learners accumulate throughout the life span is the growing product of the processes of both learning new information from direct experience and generating new information based on reasoning and imagining ( Salthouse, 2010 ). These two cognitive assets together—accumulated knowledge and reasoning ability—are particularly relevant to healthy aging. Reasoning and knowledge abilities tend to be correlated. That is, people who have comparatively higher reasoning capacity are likely to acquire correspondingly more knowledge over the life span than their peers ( Ackerman and Beier, 2006 ; Beier and Ackerman, 2005 ). Reasoning ability is a major determinant of learning throughout life, and it is through reasoning, especially in contexts that allow people to pursue their interests, that people develop knowledge throughout their life span ( Ackerman, 1996 ; Cattell, 1987 ).

On average, however, the trajectories of reasoning and knowledge acquisition are different across the life span. A number of research studies have described the general trajectories of age-related changes in ability, using a variety of measures and research designs (cross-sectional and longitudinal), and have shown a fairly consistent trend in which the development of knowledge remains steady as reasoning capacity (the ability to quickly and accurately manipulate multiple distinct pieces of factual information to make inferences) drops off ( Salthouse, 2010 ). However, there is considerable individual variability in the trajectories, which reflect individual health and other characteristics, as well as educational and experiential opportunities and even social engagement. Yet, even though there is an average decline in inferential reasoning capacity through adulthood, there is not a corresponding decline in the ability to make good decisions—a more colloquial use of the word “reasoning.” In other words, the research does not suggest that the average 14-year-old reasons better about what to do in a complex or emotional real-world situation than would an average 50-year-old. Instead, it describes the 14-year-old’s stronger ability to quickly manipulate multiple distinct pieces of factual information to make logical and combinatorial inferences.

The growth or decline of abilities can be expected to vary not only between individuals but also within the same person over time ( Hertzog et al.,

2008 ). Two 50-year-olds may have extremely different cognitive profiles, such that one may generally have the same ability profile as an average 30-year-old and the other may more closely resemble an average 70-year-old. Within the same person, abilities will decline or grow at varying rates as a function of that individual’s continuing use of some skills and intellectual development in particular domains; losses and declines are associated with disuse of other skills. (Factors that influence cognitive aging are discussed in Chapter 9 .) As mentioned, new learning depends on both reasoning ability and knowledge acquisition ( Ackerman and Beier, 2006 ; Beier and Ackerman, 2005 ). Even though reasoning abilities decline with age, knowledge accumulated throughout the life span facilitates new learning, as long as the information to be learned is aligned with existing domain knowledge. When people select environments for education, work, and hobbies that capitalize on their already-established knowledge and skills as they age, their selectivity allows them to capitalize on their repertoire of knowledge and expertise for learning new information ( Baltes and Baltes, 1990 ).

Cognitive abilities change throughout the life span in a variety of ways that may affect a person’s ability to learn new things (see Hartshorne and Germine, 2015 , for discussion). For instance, as people age, learning may rely more on knowledge and less on reasoning and quick manipulation of factual information. However, examining peoples’ cognitive abilities and learning becomes increasingly complex as people develop past the age of formal education. One reason is that the ways in which people learn become increasingly idiosyncratic outside of a standardized educational curriculum, and understanding this process requires assessing knowledge gained through a wide variety of adult experiences that different individuals amass over a lifetime ( Lubinski, 2000 ). The unique complexities of adult learning and development are discussed in Chapter 8 .

Effects of Culture on Reasoning

As described in Chapter 2 , learning is inherently cultural, given that a person’s experiences in a culture affect biological processes that support learning, perception, and cognition. In the area of reasoning, for example, researchers have explored fundamental differences in peoples’ reasoning about three basic domains of life: physical events (naïve physics), biological events (naïve biology), and social or psychological events (naïve psychology) (see e.g., Carey, 1985 , 2009 ; Goswami, 2002 ; Hirschfeld and Gelman, 1994 ; Spelke and Kinzler, 2007 ; also see Ojalehto and Medin, 2015c , for a review). These distinctions are compelling in the sense that each reflects a set of intuitive principles and inferences. That is, each domain is defined by entities having the same kind of causal properties. These might be marked, for example, by the way they move: physical entities are set into motion by external forces,

while biological entities may propel themselves. These domains are important for understanding cognition because researchers have suggested that whereas the perception of physical causality is universal, causal reasoning in the biological and psychological domains is culturally variable.

Two studies illustrate ways to examine these issues. Morris and Peng (1994) presented two types of animated displays to American and Chinese participants. One set of displays depicted physical interactions (of geometrical shapes), whereas the other set depicted social interactions (among fish). The participants’ answers to questions about what they had seen suggested differences in attention to internal and external causes across the groups, but those differences depended on the domain (social or physical). The authors concluded that attribution of causality in the social domain is susceptible to cultural influences but that causality in the physical domain is not.

Beller and colleagues (2009) asked German, Chinese, and Tongan participants to indicate which entity they regarded as causally most relevant for statements such as “The fact that wood floats on water is basically due to . . . ”. Ratings varied by the cultural background of respondents and also by the phenomena participants were considering. In general, the German and Chinese participants, but not the Tongan participants, considered a carrier’s capability for buoyancy only when the floater was a solid object, such as wood, but not when it was a fluid, such as oil ( Beller et al., 2009 ; see also Bender et al., 2017 ). This is an area of research that has barely been explored, but results to date suggest that the perception of physical causality may in fact not be universal and may be learned in culturally mediated ways.

STRATEGIES TO SUPPORT LEARNING

People are naturally interested in strengthening their ability to acquire and retain knowledge and in ways to improve learning performance. Researchers have explored a variety of strategies to support learning and memory. They have identified several principles for structuring practice and engaging with information to be learned to improve memory, to make sense of new information, and to develop new knowledge.

Several scholars have looked across the research on the effectiveness of specific strategies for supporting learning ( Benassi et al., 2014 ; Dunlosky et al., 2013 ; Pashler et al., 2007 ). The authors of these three studies looked for strategies that (1) have been examined in several studies, using authentic educational materials in classroom settings; (2) show effects that can be generalized across learner characteristics and types of materials; (3) promote learning that is long-lasting; and (4) support comprehension, knowledge application, and problem solving in addition to recall of factual material. These three analyses identified five learning strategies as promising:

• retrieval practice;
• spaced practice;
• interleaved and varied practice;
• summarizing and drawing; and
• explanations: elaborative interrogation, self-explanation, and teaching.

Strategies for Knowledge Retention

The first three strategies are ways of structuring practice that are particularly useful for increasing knowledge retention.

Retrieval Practice

Some evidence shows that the act of retrieval itself enhances learning and that when learners practice retrieval during an initial learning activity, their ability to retrieve and use knowledge again in the future is enhanced ( Karpicke, 2016 ; Roediger and Karpicke, 2006b ). The benefits of retrieval practice in general have been shown to generalize across individual differences in learners, variations in materials, and different assessments of learning. For example, researchers have found effects across learner characteristics in children ( Lipko-Speed et al., 2014 ; Marsh et al., 2012 ). Studies have also suggested that retrieval practice can be a useful memory remediation method among older adults ( Balota et al., 2006 ; Meyer and Logan, 2013 ; also see Dunlosky et al., 2013 , for a review of effective learning techniques). However, most of this research has addressed retrieval of relatively simple information (e.g., vocabulary), rather than deep understanding.

Research has also demonstrated the effects of retrieval practice on recall of texts and other information related to school subjects. For example, Roediger and Karpicke (2006a) had students read brief educational texts and practice recalling them. Students in one condition read the texts four times; students in a second group read three times and recalled the texts once by writing down as much as they could remember; and students in a third group read the material once and then recalled it during three retrieval practice periods. On a final test given 1 week after the initial learning session, students who practiced retrieval one time recalled more of the material than students who only read the texts, and the students who repeatedly retrieved the material performed the best. The results suggest that actively retrieving the material soon after studying it is more productive than spending the same amount of time repeatedly reading.

Attempting retrieval but failing has also been shown to promote learning. Failed retrievals provide feedback signals to learners, signaling that they may not know the information well and should adjust how they encode the material the next time they study it ( Pyc and Rawson, 2010 ). The act of failing to retrieve may thus enhance subsequent encoding ( Kornell, 2014 ).

Such studies suggest that self-testing can be an effective way for students to practice retrieval. However, evidence from surveys of students’ learning strategies and from experiments in which learners are given control over when and how often they can test themselves suggests that students may not test themselves often or effectively enough ( Karpicke et al., 2009 ; Kornell and Son, 2009 ). Many students do not engage in self-testing at all, and when students do test themselves, they often do so as a “knowledge check” to see whether they can or cannot remember what they are learning. While this is an important use of self-testing, few learners self-test because they view the act of retrieval as part of the process of learning. Instead, they are likely to retrieve something once and then, believing they have learned it for the long term, drop the item from further practice.

Spaced Practice

Researchers who have compared spaced and massed practice have shown that the way that learners schedule practice can have an impact on learning ( Carpenter et al., 2012 ; Kang, 2016 ). Massed practice concentrates all of the practice sessions in a short period of time (such as cramming for a test), whereas spaced practice distributes learning events over longer periods of time. Results show greater effects for spacing than for massed practice across learning materials (e.g., vocabulary learning, grammatical rules, history facts, pictures, motor skills) ( Carpenter et al., 2012 ; Dempster, 1996 ), stimulus formats (e.g., audiovisual, text) ( Janiszewski et al., 2003 ), and for both intentional and incidental learning ( Challis, 1993 ; Toppino et al., 2002 ). Studies have shown benefits of spaced practice for learners of ages 4 through 76 ( Balota et al., 1989 ; Rea and Modigliani, 1987 ; Simone et al., 2012 ; Toppino, 1991 ). Cepeda and colleagues (2006) found that spaced practice led to greater recall than massed practice regardless of the size of the lag between practice and recall.

There are many possible reasons why spaced practice might be more effective than massed practice. When an item, concept, or procedure is repeated after a spaced interval, learners have to fully engage in the mental operations they performed the first time because of forgetting that has occurred. But when repetitions are immediate and massed together, learners do not fully engage during repetitions. In the case of reading, one possible reason why massed re-readings do not promote learning is that when people reread immediately, they do not attend to the most informative and meaningful portions of the material during the second reading, as illustrated by Dunlosky and Rawson (2005) in a study of self-paced reading.

A few researchers have attempted to identify the spacing intervals that promote the most memory—a “sweet spot” where spaced practice confers benefits before too much forgetting has occurred ( Cepeda et al., 2008 ; Pavlik and Anderson, 2008 ). For example, a study of vocabulary learning among fifth

graders suggested that a 2-week interval showed the best results ( Sobel et al., 2011 ). Another classroom-based study of spacing effects focused on first-grade children learning to associate letters and sounds during phonics instruction ( Seabrook et al., 2005 ). The children who received spaced practice during the 2-week period significantly outperformed the children who received a single massed practice session each day.

In general, the literature on spaced practice suggests that separating learning episodes by at least 1 day, rather than focusing the learning into a single session, maximizes long-term retention of the material. However, it is important to note that wider spacing is not necessarily always better. The optimal distribution of learning sessions depends at least in part on how long the material needs to be retained in memory (i.e., when the material will be recalled or tested). For example, if the learner will be tested 1 month or more after the last learning session, then the learning should be distributed over weeks or months.

Interleaved and Variable Practice

The way information is presented can significantly affect both what is learned ( Schyns et al., 1998 ) and how well it is learned ( Goldstone, 1996 ). Variable learning generally refers to practicing skills in different ways, while interleaving refers to mixing in different activities. Varying or interleaving different skills, activities, or problems within a learning session—as opposed to focusing on one skill, activity, or problem throughout (called blocked learning)—may better promote learning. Both strategies may also involve spaced practice, and both also present learners with a variety of useful challenges, or “desirable difficulties.” Researchers have identified potential benefits of variable and interleaved practice learning, but they have also found a few benefits for blocked practice.

Several studies have shown benefits for blocking, at least for category learning ( Carpenter and Mueller, 2013 ; Goldstone, 1996 ; Higgins and Ross, 2011 ). Moreover, when given the option, a majority of learners preferred to block their study ( Carvalho et al., 2014 ; Tauber et al., 2013 ). Interleaving can boost learning of the structure of categories; that is, learning that some objects or ideas belong to the same category and others do not ( Birnbaum et al., 2013 ; Carvalho and Goldstone, 2014a , 2014b ; Kornell and Bjork; 2008 ). Other researchers have examined interleaved practice in mathematical problem-solving domains ( Rohrer, 2012 ; Rohrer et al., 2015 ).

Carvalho and Goldstone (2014a) found that the effectiveness of the presentation methods (interleaved or blocked) depended on whether the participant engaged in active or passive study. They also found that interleaving concepts improved students’ capacity to discriminate among different categories, while blocked practice emphasized similarities within each category. These results

suggest that interleaved study improves learning of highly similar categories (by facilitating between-category comparisons), whereas blocked study improves learning of low-similarity categories (by facilitating within-category comparisons).

Interleaved study naturally includes delays between learning blocks and thus easily allows for spaced practice, which has the potential benefits for long-term memory discussed above. However, it may be beneficial because it helps learners to make comparisons among categories, not because it allows time to elapse between learning blocks ( Carvalho and Goldstone, 2014b ). The mechanisms that underlie the benefits of either interleaved or blocked study (e.g, possible effects on attentional processes) are ongoing topics of research. As with other strategies, the optimal way to present material—interleaved or blocked—and the mechanisms most heavily involved will likely depend on the nature of the study task.

Strategies for Understanding and Integration

The other two strategies for which there is strong evidence—summarizing and drawing and developing explanations—draw on inferential processes that research shows to be effective for organizing and integrating information for learning.

Summarizing and Drawing

Summarizing and drawing are two common strategies for elaborating on what has been learned. To summarize is to create a verbal description that distills the most important information from a set of materials. Similarly, when learners create drawings, they use graphic strategies to portray important concepts and relationships. In both activities, learners must take the material they are learning and transform it into a different representation. There are differences between them, but both activities involve identifying important terms and concepts, organizing the information, and using prior knowledge to create verbal or pictorial representations.

Both summarization and drawing have been shown to benefit learning in school-age children ( Gobert and Clement, 1999 ; Van Meter, 2001 ; Van Meter and Garner, 2005 ). Literature reviews by Dunlosky and colleagues (2013) and Fiorella and Mayer (2015a , 2015b ) have identified factors that appear to contribute to the effectiveness of summarization and drawing activities.

A few studies have suggested that the quality of students’ summaries and drawings is directly related to how much they learn from the activities and that learners do these activities more effectively when they are trained and guided ( Bednall and Kehoe, 2011 ; Brown et al., 1983 ; Schmeck et al., 2014 ). For example, the effectiveness of drawing activities is enhanced when learners

compare their drawings to author-generated pictures ( Van Meter et al., 2006 ). Similarly, providing learners with a list of relevant elements to be included in drawings and partial drawings helps learners create more complete drawings and bolsters learning ( Schwamborn et al., 2010 ).

A group of researchers compared summarization and drawing and suggested that their effectiveness depends on the nature of the learning materials. For example, Leopold and Leutner (2012) asked high school students who were studying a science text about water molecules, which contained descriptions of several spatial relations, to either draw diagrams, write a summary of the text, or to re-read the text (the control condition). Those who created drawings performed better on a comprehension test than those who re-read the texts. However, those who created written summaries performed worse than those who re-read. The authors concluded that the drawing was more effective in this case because the learning involved spatial relations.

Note-taking, either writing by hand or typing on a laptop, is a form of summarizing that has also been studied. For example, Mueller and Oppenheimer (2014) found that students who hand-wrote notes learn more than those who typed notes using a laptop computer. The researchers asked students to take notes in these two ways and then tested their recall of factual details, conceptual understanding, and ability to synthesize and generalize the information. They found that students who typed took more voluminous notes than those who wrote by hand, but the hand-writers had a stronger conceptual understanding of the material and were more successful in applying and integrating the material than the typers. The researchers suggested that because writing notes by hand is slower, students doing this cannot take notes verbatim but must listen, digest, and summarize the material, capturing the main points. Students who type notes can do so quickly and without processing the information.

Mueller and Oppenheimer (2014) also examined the contents of notes taken by college students in these two ways across a number of disciplines. They found that the typed notes—which were closer to verbatim transcriptions—were associated with lower retention of the lecture material. Even when study participants using laptops were instructed to think about the information and type the notes in their own words, they were no better at synthesizing material than students who were not given the warning. The authors concluded that typing notes does not promote understanding or application of the information; they suggested that notes in the students’ own words and handwriting may serve as more effective memory prompts by recreating context (e.g., thought processes, conclusions) and content from the original lecture.

Developing Explanations

Encouraging learners to create explanations of what they are learning is a promising method of supporting understanding. Three techniques for doing this have been studied: elaborative interrogation, self-explanation, and teaching.

Elaborative interrogation is a strategy in which learners are asked, or are prompted to ask themselves, questions that invite deep reasoning, such as why, how, what-if, and what-if not (as opposed to shallow questions such as who, what, when, and where) ( Gholson et al., 2009 ). A curious student who applies intelligent elaborative interrogation asks deep-reasoning questions as she strives to comprehend difficult material and solve problems. However, elaborative interrogation does not come naturally to most children and adults; training people to use this skill—and particularly training in asking deep questions—has been shown to have a positive impact on comprehension, learning, and memory ( Gholson et al., 2009 ; Graesser and Lehman, 2012 ; Graesser and Olde, 2003 ; Rosenshine et al., 1996 ). For example, in an early study, people were asked either to provide “why” explanations for several unrelated sentences or to read and study the sentences. Both groups were then tested on their memory of the sentences. Those who asked questions performed better than the group that just studied the sentences ( Pressley et al., 1987 ). Studies with children have also shown benefits of elaborative interrogation ( Woloshyn et al., 1994 ), and the benefits of elaborative interrogation can persist over time (e.g., 1 or 2 weeks after learning), though few studies have examined effects of elaborative interrogation on long-term retention.

Most studies conducted by researchers in experimental psychology have used isolated facts as materials in studying the effects of elaboration and have assessed verbatim retention, but researchers in educational psychology have also looked at more complex text content and assessed inference making ( Dornisch and Sperling, 2006 ; Ozgungor and Guthrie, 2004 ). For example, McDaniel and Donnelly (1996) asked college students to study short descriptions of physics concepts, such as the conservation of angular momentum, and then answer a why question about the concept (e.g., “Why does an object speed up as its radius get smaller, as in conservation of angular momentum?”). A final assessment involved both factual questions and inference questions that tapped into deeper levels of comprehension. The authors found benefits of elaborative interrogation for complex materials and assessments and also found that those who engaged in elaborative interrogation outperformed learners who produced labeled diagrams of the concepts in each brief text.

Self-explanation is a strategy in which learners produce explanations of material or of their thought processes while they are reading, answering questions, or solving problems. In the most general case, learners may simply be asked to explain each step they take as they solve a problem ( Chi et al., 1989b ; McNamara, 2004 ) or explain a text sentence-by-sentence as they read it ( Chi

et al., 1994 ). Self-explanation involves more open-ended prompts than the specific “why” questions used in elaborative interrogation, but both strategies encourage learners to elaborate on the material by generating explanations. Other examples of this work include self-explanations of physics.

An early study of self-explanation was carried out by Chi and colleagues (1994) . Eighth-grade students learned about the circulatory system by reading an expository text. While one group just read the text, a second group of students produced explanations for each sentence in the text. The students who self-explained showed larger gains in comprehension of concepts in the text. A subsequent study showed similar results ( Wylie and Chi, 2014 ). Self-explanation has now been explored in a wide range of contexts, including comprehension of science texts in a classroom setting ( McNamara, 2004 ), learning of chess moves ( de Bruin et al., 2007 ), learning of mathematics concepts ( Rittle-Johnson, 2006 ), and learning from worked examples on problems that require reasoning ( Nokes-Malach et al., 2013 ). Self-explanation prompts have been included in intelligent tutoring systems ( Aleven and Koedinger, 2002 ) and systems with game components ( Jackson and McNamara, 2013 ; Mayer and Johnson, 2010 ). However, relatively few studies have examined the effects of self-explanation on long-term retention or explored the question of how much self-explanation is needed to produce notable results ( Jackson and McNamara, 2013 ).

A few studies have explored the relationship between self-explanation and prior knowledge in learning ( Williams and Lombrozo, 2013 ). For example, Ionas and colleagues (2012) investigated whether self-explanation was beneficial to college students who were asked to do chemistry problems. They found that prior knowledge moderated the effectiveness of self-explanation and that the more prior knowledge of chemistry the students reported having, the more self-explanation appeared to help them learn. Moreover, for students who had just a little prior knowledge, using self-explanation seemed to impede rather than support performance. The researchers suggested that learners search for concepts or processes in their prior knowledge to make sense of new material; when the prior knowledge is weak, the entire process fails. They concluded that educators should thoroughly assess the learners’ prior knowledge and use other cognitive support tools and methods during the early stages of the learning process, as learners strengthen their knowledge base.

Finally, teaching others can be an effective learning experience. When learners prepare to teach they must construct explanations, just as they do in elaborative interrogation and self-explanation activities. However, elaborative interrogation and self-explanation both require that the learner receive fairly specific prompts, whereas the act of preparing to teach can be more open-ended. Teaching others is often an excellent opportunity to hone one’s own knowledge ( Biswas et al., 2005 ; Palincsar and Brown, 1984 ), and learners in this kind of interaction are likely to feel empowered and responsible in a

way that they do not feel when they are the passive recipients of knowledge ( Scardamalia and Bereiter, 1993 ). Peers may be able to express themselves to each other in ways that are particularly relevant, immediate, and informative. Although peer learning and teaching are often quite effective, teachers and instructors typically come closer to injunctive norms and provide better models to observe.

A foundational study of the effects of teaching on learning by Bargh and Schul (1980) has served as a template for subsequent studies. Bargh and Schul asked participants to study a set of materials and either prepare to teach the material to a peer or simply study it for an upcoming test. Both groups were tested on the material without teaching it; only the expectation to teach had been manipulated. Students who prepared to teach others performed better on the assessment than students who simply read and studied the material. Effects of preparing to teach have been replicated in studies since Bargh and Schul’s foundational work (e.g., Fiorella and Mayer, 2014 ).

The benefits of teaching are evident in other contexts. For example, research on tutoring has shown that while students certainly learn by being tutored, the tutors themselves learn from the experience (see Roscoe and Chi, 2007 ). Reciprocal teaching is another strategy, used primarily in improving students’ reading comprehension ( Palincsar, 2013 ; Palincsar and Brown, 1984 ). In reciprocal teaching, students learn by taking turns teaching material to each other. The students are given guidance: training in four strategies to help them recognize and react to signs of comprehension breakdown (questioning, clarifying, summarizing, and predicting) ( Palincsar, 2013 ).

The research suggests several possible reasons why teaching may benefit learners. Preparing to teach requires elaborative processing because learners need to generate, organize, and integrate knowledge. Also, as mentioned, the explanations that people create may promote learning in the same way that elaborative interrogation and self-explanations promote learning. The process of explaining to others is active and generative, and it encourages learners to focus on deeper questions and levels of comprehension. Explaining in a teaching context also involves retrieval practice, as the teacher actively engages in retrieving knowledge in order to explain instructional content and answer questions. Although researchers have documented benefits of explanation, there are cautions to bear in mind. For example, a few researchers in this area have noted that in developing explanations learners may tend to make broad generalizations at the expense of significant specifics ( Lombrozo, 2012 ; Williams and Lombrozo, 2010 ; Williams et al., 2013 ). Children tend to prefer a single explanation for two different phenomena (e.g., a toy that both lights up and spins), even when there are two independent causes ( Bonawitz and Lombrozo, 2012 ). Likewise, when diagnosing diseases based on observable symptoms, adults tend to attribute the two symptoms to a single disease, even when it is more likely that there are two separate diseases ( Lombrozo, 2007 ;

Pacer and Lombrozo, 2017 ). The tendency to prefer simple, broad explanations over more complex ones may affect what people learn and the inferences they draw. For each of the different types of explanation strategies, researchers have noted reasons for educators to plan carefully when and how they can be used most effectively.

CONCLUSIONS

Learners identify and establish relationships among pieces of information and develop increasingly complex structures for using and categorizing what they have learned. Accumulating bodies of knowledge, structuring that knowledge, and developing the capacity to reason about the knowledge one has are key cognitive assets throughout the life span.

Strategies for supporting learning include those that focus on retention and retrieval of knowledge as well as those that support development of deeper and more sophisticated understanding of what is learned. The strategies that have shown promise for promoting learning help learners to develop the mental models they need to retain knowledge so they can use it adaptively and flexibly in making inferences and solving new problems.

CONCLUSION 5-1: Prior knowledge can reduce the attentional demands associated with engaging in well-learned activities, and it can facilitate new learning. However, prior knowledge can also lead to bias by causing people to not attend to new information and to rely on existing schema to solve new problems. These biases can be overcome but only through conscious effort.

CONCLUSION 5-2: Learners routinely generate their own novel understanding of the information they are accumulating and productively extend their knowledge by making logical connections between pieces of information. This capacity to generate novel understanding allows learners to use their knowledge to generalize, categorize, and solve problems.

CONCLUSION 5-3: The learning strategies for which there is evidence of effectiveness include ways to help students retrieve information and encourage them to summarize and explain material they are learning, as well as ways to space and structure the presentation of material. Effective strategies to create organized and distinctive knowledge structures encourage learners to go beyond the explicit material by elaborating

and to enrich their mental representation of information by calling up and applying it in various contexts.

CONCLUSION 5-4: The effectiveness of learning strategies is influenced by such contextual factors as the learner’s existing skills and prior knowledge, the nature of the material, and the goals for learning. Applying these approaches effectively therefore requires careful thought about how their specific mechanisms could be beneficial for particular learners, settings, and learning objectives.

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There are many reasons to be curious about the way people learn, and the past several decades have seen an explosion of research that has important implications for individual learning, schooling, workforce training, and policy.

In 2000, How People Learn: Brain, Mind, Experience, and School: Expanded Edition was published and its influence has been wide and deep. The report summarized insights on the nature of learning in school-aged children; described principles for the design of effective learning environments; and provided examples of how that could be implemented in the classroom.

Since then, researchers have continued to investigate the nature of learning and have generated new findings related to the neurological processes involved in learning, individual and cultural variability related to learning, and educational technologies. In addition to expanding scientific understanding of the mechanisms of learning and how the brain adapts throughout the lifespan, there have been important discoveries about influences on learning, particularly sociocultural factors and the structure of learning environments.

How People Learn II: Learners, Contexts, and Cultures provides a much-needed update incorporating insights gained from this research over the past decade. The book expands on the foundation laid out in the 2000 report and takes an in-depth look at the constellation of influences that affect individual learning. How People Learn II will become an indispensable resource to understand learning throughout the lifespan for educators of students and adults.

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14 Ways to Acquire Knowledge: A Timeless Guide from 1936

By maria popova.

Among its highlights is a section titled 14 Ways to Acquire Knowledge — a blueprint to intellectual growth, advocating for such previously discussed essentials as the importance of taking example from those who have succeeded and organizing the information we encounter , the power of curiosity , the osmosis between learning and teaching , the importance of critical thinking (because, as Christopher Hitchens pithily put it , “what can be asserted without evidence can be dismissed without evidence” ), the benefits of writing things down , why you should let your opinions be fluid rather than rigid, the art of listening , the art of observation , and the very core of what it means to be human .

14 WAYS TO ACQUIRE KNOWLEDGE PRACTICE Consider the knowledge you already have — the things you really know you can do . They are the things you have done over and over ; practiced them so often that they became second nature. Every normal person knows how to walk and talk. But he could never have acquired this knowledge without practice . For the young child can’t do the things that are easy to older people without first doing them over and over and over . […] Most of us quit on the first or second attempt. But the man who is really going to be educated, who intends to know , is going to stay with it until it is done. Practice! ASK Any normal child, at about the age of three or four, reaches the asking period , the time when that quickly developing brain is most eager for knowledge. “When?” “Where?” “How?” “What?” and “Why?” begs the child — but all too often the reply is “Keep still!” “Leave me alone!” “Don’t be a pest!” Those first bitter refusals to our honest questions of childhood all too often squelch our “Asking faculty.” We grow up to be men and women, still eager for knowledge, but afraid and ashamed to ask in order to get it. […] Every person possessing knowledge is more than willing to communicate what he knows to any serious, sincere person who asks. The question never makes the asker seem foolish or childish — rather, to ask is to command the respect of the other person who in the act of helping you is drawn closer to you, likes you better and will go out of his way on any future occasion to share his knowledge with you. Ask! When you ask, you have to be humble. You have to admit you don’t know! But what’s so terrible about that? Everybody knows that no man knows everything, and to ask is merely to let the other know that you are honest about things pertaining to knowledge. DESIRE You never learn much until you really want to learn. A million people have said: “Gee, I wish I were musical!” “If I only could do that!” or “How I wish I had a good education!” But they were only talking words — they didn’t mean it. […] Desire is the foundation of all learning and you can only climb up the ladder of knowledge by desiring to learn. […] If you don’t desire to learn you’re either a num-skull [ sic ] or a “know-it-all.” And the world wants nothing to do with either type of individual. GET IT FROM YOURSELF You may be surprised to hear that you already know a great deal ! It’s all inside you — it’s all there — you couldn’t live as long as you have and not be full of knowledge. […] Most of your knowledge, however — and this is the great difference between non-education and education — is not in shape to be used , you haven’t it on the tip of your tongue. It’s hidden, buried away down inside of you — and because you can’t see it, you think it isn’t there. Knowledge is knowledge only when it takes a shape, when it can be put into words, or reduced to a principle — and it’s now up to you to go to work on your own gold mine, to refine the crude ore. WALK AROUND IT Any time you see something new or very special, if the thing is resting on the ground, as your examination and inspection proceeds, you find that you eventually walk around it . You desire to know the thing better by looking at it from all angles. […] To acquire knowledge walk around the thing studied. The thing is not only what you touch, what you see; it has many other sides, many other conditions, many other relations which you cannot know until you study it from all angles. The narrow mind stays rooted in one spot; the broad mind is free, inquiring, unprejudiced; it seeks to learn “both sides of the story.” Don’t screen off from your own consciousness the bigger side of your work. Don’t be afraid you’ll harm yourself if you have to change a preconceived opinion. Have a free, broad, open mind! Be fair to the thing studied as well as to yourself. When it comes up for your examination, walk around it ! The short trip will bring long knowledge. EXPERIMENT The world honors the man who is eager to plant new seeds of study today so he may harvest a fresh crop of knowledge tomorrow. The world is sick of the man who is always harking back to the past and thinks everything wroth knowing has already been learned. … Respect the past, take what it offers, but don’t live in it. To learn, experiment ! Try something new. See what happens. Lindbergh experimented when he flew the Atlantic. Pasteur experimented with bacteria and made cow’s milk safe for the human race. Franklin experimented with a kite and introduced electricity. The greatest experiment is nearly always a solo . The individual, seeking to learn, tries something new but only tries it on himself. If he fails, he has hurt only himself. If he succeeds he has made a discovery many people can use. Experiment only with your own time, your own money, your own labor. That’s the honest, sincere type of experiment. It’s rich. The cheap experiment is to use other people’s money, other people’s destinies, other people’s bodies as if they were guinea pigs. TEACH If you would have knowledge, knowledge sure and sound, teach. Teach your children, teach your associates, teach your friends. In the very act of teaching, you will learn far more than your best pupil. […] Knowledge is relative; you possess it in degrees. You know more about reading, writing, and arithmetic than your young child. But teach that child at every opportunity; try to pass on to him all you know, and the very attempt will produce a great deal more knowledge inside your own brain. READ From time immemorial it has been commonly understood that the best way to acquire knowledge was to read. That is not true. Reading is only one way to knowledge, and in the writer’s opinion, not the best way. But you can surely learn from reading if you read in the proper manner. What you read is important, but not all important. How you read is the main consideration. For if you know how to read , there’s a world of education even in the newspapers, the magazines, on a single billboard or a stray advertising dodger. The secret of good reading is this: read critically ! Somebody wrote that stuff you’re reading. It was a definite individual, working with a pen, pencil or typewriter — the writing came from his mind and his only . If you were face to face with him and listening instead of reading , you would be a great deal more critical than the average reader is. Listening , you would weigh his personality, you would form some judgment about his truthfulness, his ability. But reading , you drop all judgment, and swallow his words whole — just as if the act of printing the thing made it true ! […] If you must read in order to acquire knowledge, read critically . Believe nothing till it’s understood, till it’s clearly proven. WRITE To know it — write it! If you’re writing to explain, you’re explaining it to yourself ! If you’re writing to inspire, you’re inspiring yourself ! If you’re writing to record, you’re recording it on your own memory. How often you have written something down in order to be sure you would have a record of it, only to find that you never needed the written record because you had learned it by heart! […] The men of the best memories are those who make notes, who write things down . They just don’t write to remember, they write to learn. And because they DO learn by writing, they seldom need to consult their notes, they have brilliant, amazing memories. How different from the glib, slipshod individual who is too proud or too lazy to write, who trusts everything to memory, forgets so easily, and possesses so little real knowledge. […] Write! Writing, to knowledge, is a certified check. You know what you know once you have written it down! LISTEN You have a pair of ears — use them! When the other man talks, give him a chance. Pay attention. If you listen you may hear something useful to you. If you listen you may receive a warning that is worth following. If you listen, you may earn the respect of those whose respect you prize. Pay attention to the person speaking. Contemplate the meaning of his words, the nature of his thoughts. Grasp and retain the truth. Of all the ways to acquire knowledge, this way requires least effort on your part. You hardly have to do any work. You are bound to pick up information. It’s easy, it’s surefire. OBSERVE Keep your eyes open. There are things happening, all around you, all the time. The scene of events is interesting, illuminating, full of news and meaning. It’s a great show — an impressive parade of things worth knowing. Admission is free — keep your eyes open. […] There are only two kinds of experience: the experience of ourselves and the experience of others. Our own experience is slow, labored, costly, and often hard to bear. The experience of others is a ready-made set of directions on knowledge and life. Their experience is free; we need suffer none of their hardships; we may collect on all their good deeds. All we have to do is observe ! Observe! Especially the good man, the valorous deed. Observe the winner that you yourself may strive to follow that winning example and learn the scores of different means and devices that make success possible. Observe! Observe the loser that you may escape his mistakes, avoid the pitfalls that dragged him down. Observe the listless, indifferent, neutral people who do nothing, know nothing, are nothing. Observe them and then differ from them. PUT IN ORDER Order is Heaven’s first law. And the only good knowledge is orderly knowledge ! You must put your information and your thoughts in order before you can effectively handle your own knowledge. Otherwise you will jump around in conversation like a grasshopper, your arguments will be confused and distributed, your brain will be in a dizzy whirl all the time. DEFINE A definition is a statement about a thing which includes everything the thing is and excludes everything it is not. A definition of a chair must include every chair, whether it be kitchen chair, a high chair, a dentist’s chair, or the electric chair, It must exclude everything which isn’t a chair, even those things which come close, such as a stool, a bench, a sofa. […] I am sorry to state that until you can so define chair or door (or a thousand other everyday familiar objects) you don’t really know what these things are. You have the ability to recognize them and describe them but you can’t tell what their nature is. Your knowledge is not exact . REASON Animals have knowledge. But only men can reason. The better you can reason the farther you separate yourself from animals. The process by which you reason is known as logic. Logic teaches you how to derive a previously unknown truth from the facts already at hand. Logic teaches you how to be sure whether what you think is true is really true. […] Logic is the supreme avenue to intellectual truth. Don’t ever despair of possessing a logical mind. You don’t have to study it for years, read books and digest a mountain of data. All you have to remember is one word — compare. Compare all points in a proposition. Note the similarity — that tells you something new. Note the difference — that tells you something new. Then take the new things you’ve found and check them against established laws or principles. This is logic. This is reason. This is knowledge in its highest form.

The rest of You Can Do Anything! goes on to explore such facets of success as the fundamentals of personal achievement, manual and mental production, the art of the deadline, selling by giving, mastering personal energy, the necessary elements of ambition, and more.

— Published April 22, 2013 — https://www.themarginalian.org/2013/04/22/14-ways-to-acquire-knowledge-james-mangan-1936/ —

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How Your Brain Uses 3 Pathways to Knowledge

The scientific method is terrific—but remember intuition and experts..

Posted March 31, 2024 | Reviewed by Ray Parker

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• Intuition is a mysterious process that is hard to explain, but we use it, especially in creativity.
• The scientific method is fundamental for advancing scientific knowledge and gaining enlightenment.

Knowledge is power—but what happens when you're having trouble picking up new ideas?

It wasn't all that long ago in human history that our access to facts, figures, and statistics was very limited. Before artificial intelligence (AI), of course, there were search engines like Google and Bing. At first, they were available only on computers, but then the technology shrank down so small it could fit on a mobile smartphone that travels with you in a coat pocket.

Going back in time a little more, television, radio, and movie theaters were avant-garde. Entertainment, current events, and new ideas were spread on a mass scale using these innovations. Still, they were not interactive. You could never ask an old vacuum-tube television to pull up the funniest cat memes .

Now, imagine a world in which none of these exists. For 99 percent of human existence, this was precisely the world we inhabited. Here are three ways we have acquired knowledge throughout history and that we continue to use today.

1. Appeal to authority.

How do we come to know things? Put another way, "How do we know what we know?" Here are a few questions we can answer in our modern world with just a few clicks online.

• Why is everyone born with an appendix?
• What is the emotion of embarrassment ?
• Why is our cognitive system structured the way it is?
• Why do babies mostly follow a predictable developmental trajectory (e.g., walking, talking)?

Before the scientific revolution (and centuries before the internet), if we wanted to know the answer to questions like these, we could consult an expert—this could be a religious leader , educated philosopher, naturalist, or village shaman. These authority figures would be happy to reveal truths about the way the world works.

A 2012 survey found that 25 percent of Americans believed the sun revolves around the Earth. This represents a significant shift in beliefs compared to 400 years ago when most humans believed the earth was the center of the universe and everything revolved around us.

In 1543, Nicolaus Copernicus challenged the ancient teaching of the Earth as the center of the universe but was unable to convince the masses. Later, Galileo Galilei boldly advocated Copernican theory, and he was forced to retract his beliefs before an inquisition. It wasn't until 1993 that the Vatican officially recognized the validity of his work. (The fact that just a decade ago, roughly one in four Americans still believed incorrectly that the sun revolved around the earth is distressing and worthy of a separate discussion.)

In the 1800s, Gregor Mendel postulated the existence of small units for transmitting genetic information even though he’d never seen them. For years, before minuscule genes were eventually seen under high-powered microscopes or astronomical black holes were observed in deep space, people could choose to accept the word of the scientists. Nonexpert laypeople had no other options. Either we trust the experts, or we just make up wild explanations on our own.

In the past, if we couldn’t see something for ourselves, we would have to accept the statements of authority figures. Even today, we still do this by talking with professionals or reading scholarly publications. Today, the internet serves as an authority, but beware: Not everything on the internet can be trusted.

2. Intuition .

Creative people sometimes refer to intuition or sudden insight that springs into conscious awareness as the most important step in acquiring knowledge. A person might find the solution to a problem they’ve been working on for years while simply walking down the street. There is no systematic approach to acquiring knowledge using this technique. It is a mysterious process that most people can’t explain—it just happens.

Mathematician John Nash, the focus of the 2001 movie "A Beautiful Mind," introduced a stable strategy for positive outcomes among multiple players in competition . In the film, he experiences an epiphany while sitting in a pub with friends, contemplating who will succeed at gaining the attention of an attractive woman. This insight into game theory ultimately led to the Nash Equilibrium and earned him the Nobel Prize in Economics.

Many artists rely on intuition because it is compatible with creative expression. A pure artist may bristle at the thought of using mathematical formulas to generate art. After all, how can you apply an equation to make things that should be appreciated primarily for their beauty or emotional power?

When June Carter and Johnny Cash first conceived the classic tune "Ring of Fire," it did not include the signature Mexican trumpet sounds. After spending several days working on the song, Johnny Cash claims to have had a dream where he heard Mexican trumpets. He did not rely on any scientific strategies, nor did he just ask an expert how to write a great tune. Almost overnight, the song itself ascended to legendary status.

The intuitive approach looks more magical than it probably is because the ideas that seem to pop into consciousness suddenly are usually coming from minds that have spent days, if not years, on a particular subject. Neither you nor I will wake up tomorrow with the formula for cold fusion, but a physicist who spent a career studying it might. The same can be said for mathematicians, singer-songwriters, and anyone who is dedicated to the pursuit of their passions.

3. The scientific method.

The scientific method is an empirical method for acquiring knowledge that has characterized the development of science since at least the 17th century. This approach is the gold standard for generating new ideas in modern science, including psychology. It is iterative, meaning that the process often involves revisiting and refining hypotheses based on new evidence or insights gained from experimentation.

Key components of this method include observations, questions, hypotheses, predictions, experiments, and analyses. Based on these steps, scientists conclude and evaluate whether their hypothesis is supported by the evidence. There is no need for intuition, and the process is more comprehensive than simply asking an expert to tell you the answer.

The scientific method can be used to reject old but often cherished ideas when their time has come. For example, many people have long believed that one must drink eight glasses of water a day for optimal health. However, when this folk psychology was exposed to scientific scrutiny , it was found to be untrue. Individuals who drank eight glasses of water per day were no healthier than those who drank less. Thank you, Scientific Method.

Despite the various methods for acquiring knowledge, one fundamental desire remains constant across individuals: We have an unquenchable thirst for new ideas and the kind of wisdom that will make our lives easier. The challenge is finding the best path forward to achieving meaningful insight into ourselves and the world we inhabit.

©2024 Kevin Bennett, Ph.D., all rights reserved

Bennett, K. (2018). Teaching the Monty Hall dilemma to explore decision-making, probability, and regret in behavioral science classrooms. International Journal for the Scholarship of Teaching and Learning, 12 (2), 1-7. https://doi.org/10.20429/ijsotl.2018.120213

Kevin Bennett, Ph.D., is a teaching professor of social-personality psychology at Penn State University Beaver Campus and host of Kevin Bennett Is Snarling, a podcast about danger, deception, and desire.

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2 Scientific Methods and Knowledge

The specific questions posed about reproducibility and replicability in the committee's statement of task are part of the broader question of how scientific knowledge is gained, questioned, and modified. In this chapter, we introduce concepts central to scientific inquiry by discussing the nature of science and outlining core values of the scientific process. We outline how scientists accumulate scientific knowledge through discovery, confirmation, and correction and highlight the process of statistical inference, which has been a focus of recently publicized failures to confirm original results.

• WHAT IS SCIENCE?

Science is a mode of inquiry that aims to pose questions about the world, arriving at the answers and assessing their degree of certainty through a communal effort designed to ensure that they are well grounded. 1 “World,” here, is to be broadly construed: it encompasses natural phenomena at different time and length scales, social and behavioral phenomena, mathematics, and computer science. Scientific inquiry focuses on four major goals: (1) to describe the world (e.g., taxonomy classifications), (2) to explain the world (e.g., the evolution of species), (3) to predict what will happen in the world (e.g., weather forecasting), and (4) to intervene in specific processes or systems (e.g., making solar power economical or engineering better medicines).

Human interest in describing, explaining, predicting, and intervening in the world is as old as humanity itself. People across the globe have sought to understand the world and use this understanding to advance their interests. Long ago, Pacific Islanders used knowledge of the stars to navigate the seas; the Chinese developed earthquake alert systems; many civilizations domesticated and modified plants for farming; and mathematicians around the world developed laws, equations, and symbols for quantifying and measuring. With the work of such eminent figures as Copernicus, Kepler, Galileo, Newton, and Descartes, the scientific revolution in Europe in the 16th and 17th centuries intensified the growth in knowledge and understanding of the world and led to ever more effective methods for producing that very knowledge and understanding.

Over the course of the scientific revolution, scientists demonstrated the value of systematic observation and experimentation, which was a major change from the Aristotelian emphasis on deductive reasoning from ostensibly known facts. Drawing on this work, Francis Bacon (1889 [1620]) developed an explicit structure for scientific investigation that emphasized empirical observation, systematic experimentation, and inductive reasoning to question previous results. Shortly thereafter, the concept of communicating a scientific experiment and its result through a written article was introduced by the Royal Society of London. 2 These contributions created the foundations for the modern practice of science—the investigation of a phenomenon through observation, measurement, and analysis and the critical review of others through publication.

The American Association for the Advancement for Science (AAAS) describes approaches to scientific methods by recognizing the common features of scientific inquiry across the diversity of scientific disciplines and the systems each discipline studies ( Rutherford and Ahlgren, 1991 , p. 2):

Scientific inquiry is not easily described apart from the context of particular investigations. There simply is no fixed set of steps that scientists always follow, no one path that leads them unerringly to scientific knowledge. There are, however, certain features of science that give it a distinctive character as a mode of inquiry.

Scientists, regardless of their discipline, follow common principles to conduct their work: the use of ideas, theories, and hypotheses; reliance on evidence; the use of logic and reasoning; and the communication of results, often through a scientific article. Scientists introduce ideas, develop theories, or generate hypotheses that suggest connections or patterns in nature that can be tested against observations or measurements (i.e., evidence). The collection and characterization of evidence—including the assessment of variability (or uncertainty)—is central to all of science. Analysis of the collected data that leads to results and conclusions about the strength of a hypothesis or proposed theory requires the use of logic and reasoning, inductive, deductive, or abductive. A published scientific article allows other researchers to review and question the evidence, the methods of collection and analysis, and the scientific results.

While these principles are common to all scientific and engineering research disciplines, different scientific disciplines use specific tools and approaches that have been designed to suit the phenomena and systems that are particular to each discipline. For example, the mathematics taught to graduate students in astronomy will be different from the mathematics taught to graduate students studying zoology. Laboratory equipment and experimental methods for studying biology will likely differ from those for studying materials science ( Rutherford and Ahlgren, 1991 ). In general, one may say that different scientific disciplines are distinguished by the nature of the phenomena of interest to the field, the kinds of questions asked, and the types of tools, methods, and techniques used to answer those questions. In addition, scientific disciplines are dynamic, regularly engendering subfields and occasionally combining and reforming. In recent years, for example, what began as an interdisciplinary interest of biologists and physicists emerged as a new field of biophysics, while psychologists and economists working together defined a field of behavioral economics. There have been similar interweavings of questions and methods for countless examples over the history of science.

No matter how far removed one's daily life is from the practice of science, the concrete results of science and engineering are inescapable. They are manifested in the food people eat, their clothes, the ways they move from place to place, the devices they carry, and the fact that most people will outlive by decades the average human born before the last century. So ubiquitous are these scientific achievements that it is easy to forget that there was nothing inevitable about humanity's ability to achieve them.

Scientific progress is made when the drive to understand and control the world is guided by a set of core principles and scientific methods. While challenges to previous scientific results may force researchers to examine their own practices and methods, the core principles and assumptions underlying scientific inquiry remain unchanged. In this context, the consideration of reproducibility and replicability in science is intended to maintain and enhance the integrity of scientific knowledge.

• CORE PRINCIPLES AND ASSUMPTIONS OF SCIENTIFIC INQUIRY

Science is inherently forward thinking, seeking to discover unknown phenomena, increase understanding of the world, and answer new questions. As new knowledge is found, earlier ideas and theories may need to be revised. The core principles and assumptions of scientific inquiry embrace this tension, allowing science to progress while constantly testing, checking, and updating existing knowledge. In this section, we explore five core principles and assumptions underlying science:

Nature is not capricious.

Knowledge grows through exploration of the limits of existing rules and mutually reinforcing evidence.

Science is a communal enterprise.

Science aims for refined degrees of confidence, rather than complete certainty.

Scientific knowledge is durable and mutable.

Nature Is Not Capricious

A basic premise of scientific inquiry is that nature is not capricious. “Science . . . assumes that the universe is, as its name implies, a vast single system in which the basic rules are everywhere the same. Knowledge gained from studying one part of the universe is applicable to other parts” ( Rutherford and Ahlgren, 1991 , p. 5). In other words, scientists assume that if a new experiment is carried out under the same conditions as another experiment, the results should replicate. In March 1989, the electrochemists Martin Fleischmann and Stanley Pons claimed to have achieved the fusion of hydrogen into helium at room temperature (i.e., “cold fusion”). In an example of science's capacity for self-correction, dozens of laboratories attempted to replicate the result over the next several months. A consensus soon emerged within the scientific community that Fleischmann and Pons had erred and had not in fact achieved cold fusion.

Imagine a fictional history, in which the researchers responded to the charge that their original claim was mistaken, as follows: “While we are of course disappointed at the failure of our results to be replicated in other laboratories, this failure does nothing to show that we did not achieve cold fusion in our own experiment, exactly as we reported. Rather, what it demonstrates is that the laws of physics or chemistry, on the occasion of our experiment (i.e., in that particular place, at that particular time), behaved in such a way as to allow for the generation of cold fusion. More exactly, it is our contention that the basic laws of physics and chemistry operate one way in those regions of space and time outside of the location of our experiment, and another way within that location.”

It goes without saying that this would be absurd. But why, exactly? Why, that is, should scientists not take seriously the fictional explanation above? The brief answer, sufficient for our purposes, is that scientific inquiry (indeed, almost any sort of inquiry) would grind to a halt if one took seriously the possibility that nature is capricious in the way it would have to be for this fictional explanation to be credible. Science operates under a standing presumption that nature follows rules that are consistent , however subtle, intricate, and challenging to discern they may be. In some systems, these rules are consistent across space and time—for example, a physics study should replicate in different countries and in different centuries (assuming that differences in applicable factors, such as elevation or temperature, are accounted for). In other systems, the rules may be limited to specific places or times; for example, a rule of human behavior that is true in one country and one time period may not be true in a different time and place. In effect, all scientific disciplines seek to discover rules that are true beyond the specific context within which they are discovered.

Knowledge Grows Through Exploration of the Limits of Existing Rules and Mutually Reinforcing Evidence

Scientists seek to discover rules about relationships or phenomena that exist in nature, and ultimately they seek to describe, explain, and predict. Because nature is not capricious, scientists assume that these rules will remain true as long as the context is equivalent. And because knowledge grows through evidence about new relationships, researchers may find it useful to ask the same scientific questions using new methods and in new contexts, to determine whether and how those relationships persist or change. Most scientists seek to find rules that are not only true in one specific context but that are also confirmable by other scientists and are generalizable—that is rules that remain true even if the context of a separate study is not entirely the same as the original. Scientists thus seek to generalize their results and to discover the limits of proposed rules. These limits can often be a rich source of new knowledge about the system under study. For example, if a particular relationship was observed in an older group but not a younger group, this suggests that the relationship may be affected by age, cohort, or other attributes that distinguish the groups and may point the researcher toward further inquiry.

Science Is a Communal Enterprise

Robert Merton (1973) described modern science as an institution of “communalism, universalism, disinterestedness, and organized skepticism.” Science is an ongoing, communal conversation and a joint problem-solving enterprise that can include false starts and blind alleys, especially when taking risks in the quest to find answers to important questions. Scientists build on their own research as well as the work of their peers, and this building can sometimes span generations. Scientists today still rely on the work of Newton, Darwin, and others from centuries past.

Researchers have to be able to understand others' research in order to build on it. When research is communicated with clear, specific, and complete accounting of the materials and methods used, the results found, and the uncertainty associated with the results, other scientists can know how to interpret the results. The communal enterprise of science allows scientists to build on others' work, develop the necessary skills to conduct high quality studies, and check results and confirm, dispute, or refine them.

Scientific results should be subject to checking by peers, and any scientist competent to perform such checking has the standing to do so. Confirming the results of others, for example, by replicating the results, serves as one of several checks on the processes by which researchers produce knowledge. The original and replicated results are ideally obtained following well-recognized scientific approaches within a given field of science, including collection of evidence and characterization of the associated sources and magnitude of uncertainties. Indeed, without understanding uncertainties associated with a scientific result (as discussed throughout this report), it is difficult to assess whether or not it has been replicated.

Science Aims for Refined Degrees of Confidence, Rather Than Complete Certainty

Uncertainty is inherent in all scientific knowledge, and many types of uncertainty can affect the reliability of a scientific result. It is important that researchers understand and communicate potential sources of uncertainty in any system under study. Decision makers looking to use study results need to be able to understand the uncertainties associated with those results. Understanding the nature of uncertainty associated with an analysis can help inform the selection and use of quantitative measures for characterizing the results (see Box 2-1 ). At any stage of growing scientific sophistication, the aim is both to learn what science can now reveal about the world and to recognize the degree of uncertainty attached to that knowledge.

Scientific Uncertainty and Its Importance in Measurement Science.

Scientific Knowledge Is Durable and Mutable

As researchers explore the world through new scientific studies and observations, new evidence may challenge existing and well-known theories. The scientific process allows for the consideration of new evidence that, if credible, may result in revisions or changes to current understanding. Testing of existing models and theories through the collection of new data is useful in establishing their strength and their limits (i.e., generalizability), and it ultimately expands human knowledge. Such change is inevitable as scientists develop better methods for measuring and observing the world. The advent of new scientific knowledge that displaces or reframes previous knowledge should not be interpreted as a weakness in science. Scientific knowledge is built on previous studies and tested theories, and the progression is often not linear. Science is engaged in a continuous process of refinement to uncover ever-closer approximations to the truth.

CONCLUSION 2-1: The scientific enterprise depends on the ability of the scientific community to scrutinize scientific claims and to gain confidence over time in results and inferences that have stood up to repeated testing. Reporting of uncertainties in scientific results is a central tenet of the scientific process. It is incumbent on scientists to convey the appropriate degree of uncertainty in reporting their claims.

• STATISTICAL INFERENCE AND HYPOTHESIS TESTING

Many scientific studies seek to measure, explain, and make predictions about natural phenomena. Other studies seek to detect and measure the effects of an intervention on a system. Statistical inference provides a conceptual and computational framework for addressing the scientific questions in each setting. Estimation and hypothesis testing are broad groupings of inferential procedures. Estimation is suitable for settings in which the main goal is the assessment of the magnitude of a quantity, such as a measure of a physical constant or the rate of change in a response corresponding to a change in an explanatory variable. Hypothesis testing is suitable for settings in which scientific interest is focused on the possible effect of a natural event or intentional intervention, and a study is conducted to assess the evidence for and against this effect. In this context, hypothesis testing helps answer binary questions. For example, will a plant grow faster with fertilizer A or fertilizer B? Do children in smaller classes learn more? Does an experimental drug work better than a placebo? Several types of more specialized statistical methods are used in scientific inquiry, including methods for designing studies and methods for developing and evaluating prediction algorithms.

Because hypothesis testing has been involved in a major portion of reproducibility and replicability assessments, we consider this mode of statistical inference in some detail. However, considerations of reproducibility and replicability apply broadly to other modes and types of statistical inference. For example, the issue of drawing multiple statistical inferences from the same data is relevant for all hypothesis testing and in estimation.

Studies involving hypothesis testing typically involve many factors that can introduce variation in the results. Some of these factors are recognized, and some are unrecognized. Random assignment of subjects or test objects to one or the other of the comparison groups is one way to control for the possible influence of both unrecognized and recognized sources of variation. Random assignment may help avoid systematic differences between groups being compared, but it does not affect the variation inherent in the system (e.g., population or an intervention) under study.

Scientists use the term null hypothesis to describe the supposition that there is no difference between the two intervention groups or no effect of a treatment on some measured outcome ( Fisher, 1935 ). A commonly used formulation of hypothesis testing is based on the answer to the following question: If the null hypothesis is true, what is the probability of obtaining a difference at least as large as the observed one? In general, the greater the observed difference, the smaller the probability that a difference at least as large as the observed would be obtained when the null hypothesis is true. This probability of obtaining a difference at least as large as the observed when the null hypothesis is true is called the “ p -value.” 3 As traditionally interpreted, if a calculated p -value is smaller than a defined threshold, the results may be considered statistically significant. A typical threshold may be p ≤ 0.05 or, more stringently, p ≤ 0.01 or p ≤ 0.005. 4 In a statement issued in 2016, the American Statistical Association Board ( Wasserstein and Lazar, 2016 , p. 129) noted:

While the p -value can be a useful statistical measure, it is commonly misused and misinterpreted. This has led to some scientific journals discouraging the use of p -values, and some scientists and statisticians recommending their abandonment, with some arguments essentially unchanged since p -values were first introduced.

More recently, it has been argued that p -values, properly calculated and understood, can be informative and useful; however, a conclusion of statistical significance based on an arbitrary threshold of likelihood (even a familiar one such as p ≤ 0.05) is unhelpful and frequently misleading ( Wasserstein et al., 2019 ; Amrhein et al., 2019b ).

Understanding what a p- value does not represent is as important as understanding what it does indicate. In particular, the p -value does not represent the probability that the null hypothesis is true. Rather, the p- value is calculated on the assumption that the null hypothesis is true. The probability that the null hypothesis is true, or that the alternative hypothesis is true, can be based on calculations informed in part by the observed results, but this is not the same as a p- value.

In scientific research involving hypotheses about the effects of an intervention, researchers seek to avoid two types of error that can lead to non-replicability:

• Type I error—a false positive or a rejection of the null hypothesis when it is correct
• Type II error—a false negative or failure to reject a false null hypothesis, allowing the null hypothesis to stand when an alternative hypothesis, and not the null hypothesis, is correct

Ideally, both Type I and Type II errors would be simultaneously reduced in research. For example, increasing the statistical power of a study by increasing the number of subjects in a study can reduce the likelihood of a Type II error for any given likelihood of Type I error. 5 Although the increase in data that comes with higher powered studies can help reduce both Type I and Type II errors, adding more subjects typically means more time and cost for a study.

Researchers are often forced to make tradeoffs in which reducing the likelihood of one type of error increases the likelihood of the other. For example, when p -values are deemed useful, Type I errors may be minimized by lowering the significance threshold to a more stringent level (e.g., by lowering the standard p ≤ 0.05 to p ≤ 0.005). However, this would simultaneously increase the likelihood of a Type II error. In some cases, it may be useful to define separate interpretive zones, where p -values above one significance threshold are not deemed significant, p -values below a more stringent significance threshold are deemed significant, and p -values between the two thresholds are deemed inconclusive. Alternatively, one could simply accept the calculated p -value for what it is—the probability of obtaining the observed result or one more extreme if the null hypothesis were true—and refrain from further interpreting the results as “significant” or “not significant.” The traditional reliance on a single threshold to determine significance can incentivize behaviors that work against scientific progress (see the Publication Bias section in Chapter 5 ).

Tension can arise between replicability and discovery, specifically, between the replicability and the novelty of the results. Hypotheses with low a priori probabilities are less likely to be replicated. In this vein, Wilson and Wixted (2018) illustrated how fields that are investigating potentially ground-breaking results will produce results that are less replicable, on average, than fields that are investigating highly likely, almost-established results. Indeed, a field could achieve near-perfect replicability if it limited its investigations to prosaic phenomena that were already well known. As Wilson and Wixted (2018, p. 193) state, “We can imagine pages full of findings that people are hungry after missing a meal or that people are sleepy after staying up all night,” which would not be very helpful “for advancing understanding of the world.” In the same vein, it would not be helpful for a field to focus solely on improbable, outlandish hypotheses.

The goal of science is not, and ought not to be, for all results to be replicable. Reports of non-replication of results can generate excitement as they may indicate possibly new phenomena and expansion of current knowledge. Also, some level of non-replicability is expected when scientists are studying new phenomena that are not well established. As knowledge of a system or phenomenon improves, replicability of studies of that particular system or phenomenon would be expected to increase.

Assessing the probability that a hypothesis is correct in part based on the observed results can also be approached through Bayesian analysis. This approach starts with a priori (before data observation) assumptions, known as prior probabilities, and revises them on the basis of the observed data using Bayes' theorem, sometimes described as the Bayes formula.

Appendix D illustrates how a Bayesian approach to inference can, under certain assumptions on the data generation mechanism and on the a priori likelihood of the hypothesis, use observed data to estimate the probability that a hypothesis is correct. One of the most striking lessons from Bayesian analysis is the profound effect that the pre-experimental odds have on the post-experimental odds. For example, under the assumptions shown in Appendix D , if the prior probability of an experimental hypothesis was only 1 percent and the obtained results were statistically significant at the p ≤ 0.01 level, only about one in eight of such conclusions that the hypothesis was true would be correct. If the prior probability was as high as 25 percent, then more than four of five such studies would be deemed correct. As common sense would dictate and Bayesian analysis can quantify, it is prudent to adopt a lower level of confidence in the results of a study with a highly unexpected and surprising result than in a study for which the results were a priori more plausible (e.g., see Box 2-2 ).

Pre-Experimental Probability: An Example.

Highly surprising results may represent an important scientific breakthrough, even though it is likely that only a minority of them may turn out over time to be correct. It may be crucial, in terms of the example in the previous paragraph, to learn which of the eight highly unexpected (prior probability, 1%) results can be verified and which one of the five moderately unexpected (prior probability, 25%) results should be discounted.

Keeping the idea of prior probability in mind, research focused on making small advances to existing knowledge would result in a high replication rate (i.e., a high rate of successful replications) because researchers would be looking for results that are very likely correct. But doing so would have the undesirable effect of reducing the likelihood of making major new discoveries ( Wilson and Wixted, 2018 ). Many important advances in science have resulted from a bolder approach based on more speculative hypotheses, although this path also leads to dead ends and to insights that seem promising at first but fail to survive after repeated testing.

The “safe” and “bold” approaches to science have complementary advantages. One might argue that a field has become too conservative if all attempts to replicate results are successful, but it is reasonable to expect that researchers follow up on new but uncertain discoveries with replication studies to sort out which promising results prove correct. Scientists should be cognizant of the level of uncertainty inherent in speculative hypotheses and in surprising results in any single study.

Many different definitions of “science” exist. In line with the committee's task, we aim for this description to apply to a wide variety of scientific and engineering studies.

See http://blog ​.efpsa.org ​/2013/04/30/the-origins-of-scientific-publishing .

Text modified December 2019. In discussions related to the p -value, the original report used “likelihood” rather than “probability” and failed to note that the p -value includes the observed “and more extreme” results (See Section 3.2, Principles of Statistical Inference, Cox, 2006 ). Although the words probability and likelihood are interchangeable in everyday English, they are distinguished in technical usage in statistics.

The threshold for statistical significance is often referred to as p “less than” 0.05; we refer to this threshold as “less than or equal to.”

Statistical power is the probability that a test will reject the null hypothesis when a specific alternative hypothesis is true.

• Cite this Page National Academies of Sciences, Engineering, and Medicine; Policy and Global Affairs; Committee on Science, Engineering, Medicine, and Public Policy; Board on Research Data and Information; Division on Engineering and Physical Sciences; Committee on Applied and Theoretical Statistics; Board on Mathematical Sciences and Analytics; Division on Earth and Life Studies; Nuclear and Radiation Studies Board; Division of Behavioral and Social Sciences and Education; Committee on National Statistics; Board on Behavioral, Cognitive, and Sensory Sciences; Committee on Reproducibility and Replicability in Science. Reproducibility and Replicability in Science. Washington (DC): National Academies Press (US); 2019 May 7. 2, Scientific Methods and Knowledge.
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Methods: Ways of Gaining Knowledge

• First Online: 02 June 2022

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• Bernd-Olaf Küppers 9  

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Whether and to what extent the meaning content of natural phenomena is accessible to the exact sciences has long been a subject of controversy. At the center of this debate lies the scope of the scientific method, based as it is on simplification, abstraction and idealization. For this reason, hermeneutics, which aims at understanding meaningful phenomena through interpretation, has become the counterpart to the analytical method of scientific explanation. This chapter presents arguments to refute the principal objections to the reductionist research program and provides evidence that there is no need for a methodological reorientation of the exact sciences.

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Küppers, BO. (2022). Methods: Ways of Gaining Knowledge. In: The Language of Living Matter. The Frontiers Collection. Springer, Cham. https://doi.org/10.1007/978-3-030-80319-3_3

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