Browsing Category

Learning Theories & Models

Andragogy – Adult Learning Theory (Knowles)

Summary: Andragogy refers to a theory of adult learning that details some of the ways in which adults learn differently than children. For example, adults tend to be more self-directed, internally motivated, and ready to learn. Teachers can draw on concepts of andragogy to increase the effectiveness of their adult education classes.

Originator: Malcom Shepherd Knowles (1913-1997)

Keywords: learning, learning theory, adults, education, self-directive, self-concept, experiences, readiness, motivation, content, process, practical learning

Andragogy (Adult Learning Theory)

Andragogy, also known as adult learning theory, was proposed by Malcom Shepard Knowles in 1968.[i] Previously, much research and attention had been given to the concept of pedagogy – teaching children. Knowles recognized that there are many differences in the ways that adults learn as opposed to children. His thoughts surrounding andragogy sought to capitalize on the unique learning styles and strengths of adult learners.

Knowles’ Five Assumptions of Adult Learners

Knowles theory of andragogy identified five assumptions that teachers should make about adult learners.

  1. Self-Concept – Because adults are at a mature developmental stage, they have a more secure self-concept than children. This allows them to take part in directing their own learning.
  2. Past Learning Experience – Adults have a vast array of experiences to draw on as they learn, as opposed to children who are in the process of gaining new experiences.
  3. Readiness to Learn – Many adults have reached a point in which they see the value of education and are ready to be serious about and focused on learning.
  4. Practical Reasons to Learn – Adults are looking for practical, problem-centered approaches to learning. Many adults return to continuing education for specific practical reasons, such as entering a new field.
  5. Driven by Internal Motivation – While many children are driven by external motivators – such as punishment if they get bad grades or rewards if they get good grades – adults are more internally motivated.

Four Principles of Andragogy

Based on these assumptions about adult learners, Knowles discussed four principles that educators should consider when teaching adults.

  1. Since adults are self-directed, they should have a say in the content and process of their learning.
  2. Because adults have so much experience to draw from, their learning should focus on adding to what they have already learned in the past.
  3. Since adults are looking for practical learning, content should focus on issues related to their work or personal life.
  4. Additionally, learning should be centered on solving problems instead of memorizing content.

Current Applications

In later years, Knowles would recognize that some points in his theory did not apply to all adults. In addition, some of what he wrote about education could also apply to children. He began to see learning on a spectrum between teacher-directed and student-directed. In his later work, he emphasized how each situation should be assessed on an individual basis to determine how much self-direction would be helpful for students.

Andragogy has received critique over the years, as some of its assumptions have not been empirically proven.[ii] However, many researchers believe that the self-directed approach to learning discussed by Knowles is applicable in a number of settings.

For example, online learning can benefit from Knowle’s discussion of self-directive learning, as students often receive less supervision from teachers in an online environment.

Other researchers have used androgagy to consider how lectures can become more effective modes of learning through more actively engaging adult students. For example, teachers can use Socratic dialogue, small group discussions, and student-led teaching to make lectures more self-directive and engaging.[iii]


[i] Merriam, S. B. (2001). Andragogy and self-directed learning: Pillars of adult learning theory. Merriam, S. B. (Ed.), The new update on adult learning theory: New directions for adult and continuing education. (pp.1-13)

[ii] Blondy, L.C. (2007). Evaluation and application of andragogical assumptions to the adult online learning environment. Journal of Interactive Online Learning, 6(2), 116-130

[iii] Palis, A. G. & Quiros, P. A. (2014). Adult learning principles and presentation pearls. Middle East African Journal of Opthamology, 21(2), 114-122.

SWOT Analysis Tool

Summary: SWOT is an acronym that stands for strengths, weaknesses, opportunities and threats. A SWOT analysis is a tool or technique that can be used in business, design or personal settings to evaluate a project or company and to create constructive goals and strategies.

Originators: George Albert Smith Jr., Kenneth Andrews, Albert S. Humphrey (1927-2005)

Keywords: decision making, goals, strengths, weaknesses, opportunities, threats, strategy tool, management, business, external issues, internal issues, growth, performance


The exact origin of SWOT Analysis has been debated.[i] Some people believe that it originated in the 1950s at Harvard Business School and was the work of professors George Albert Smith Jr and Kenneth Andrews. Others believe it was created by Albert S. Humphrey in the 1960s during his time at the Stanford Research Institute. Regardless of its origins, SWOT analysis has become quite popular, and may be one of the most widely used management decision-making tools among business managers.

SWOT Analysis gathers data about internal issues within a company or project – strengths and weakness – and external issues outside of the company or project – opportunities and threats. It then analyzes this data to inform future goals, decisions, and strategies. The ultimate goal of SWOT analysis is to achieve a more successful outcome; for a company, the goal may be to improve performance and enhance growth.

Application of SWOT Analysis

One of the most appealing feature of SWOT analysis is its universal applicability. SWOT analysis can hypothetically be used by any type of organization as a decision-making tool. It can also be used by individuals for similar purposes. Consider the following examples.

EdTech designers – As a project is created, SWOT analysis can identify factors that lead to the eventual success of the project, while also considering risks and areas that need improvement.

Small and medium companies – SWOT analysis of small and medium companies can consist of formulating, implementing, and evaluating strategies that lead to improvements in productivity, performance, and successful operation of the company.[ii]

Farming and agricultural development – Researchers have shown the use of SWOT Analysis in the context of farming and agricultural development in Iran.[iii]

Private schools – SWOT analysis was used in an attempt to improve two different private schools. The researchers stated that the analysis benefited one of the schools by allowing it to “advance in the face of growing challenges thereby leading to its stability and increased productivity."[iv]

Nursing policy – Researchers have used SWOT analysis to consider the nursing policies of multiple European countries. Their analysis allowed them to identify factors that prevented collaboration between countries.[v]

You can download a printable SWOT Analysis Template below (in Word and PDF formats).


[i] Madsen, D. O. (n.d.). SWOT analysis: A management fashion perspective. Retrieved from

[ii] Houben, G., Lenie, K., & Vanhoof, K. (1999). A knowledge-based SWOT –analysis system as an instrument for strategic planning in small and medium sized enterprises. Decision Support Systems, 26, 125-135.

[iii] Ommani, A. R. (2011). Strengths, weaknesses, opportunities and threats (SWOT) anlysis for farming businesses management: Case of wheat farmers of Shadervan District, Shoushtar Township, Iran. African Journal of Business Management, 5(22), 9448-9454.

[iv]Ifediora, C. O., Idoko, O. R., & Nzekwe, J. (2014). Organizations stability and productivity: The role of SWOT anlysis an acronym for strength, weakness, opportunities and threat. Internatinal Journal of Innovative and Applied Research, 2(9), 23-32.

[v] Uhrenfeldt, L., Lakanmaa, R., & Basto, M. L. (2014). Collaboration: A SWOT anlysis of the process of conducting a review of nursing workforce plilicies in five European countries. Journal of Nursing Management, 22(4), 485-498.

Transformative Learning Theory (Mezirow)

Summary: Transformative learning is a theory of adult learning that utilizes disorienting dilemmas to challenge students’ thinking. Students are then encouraged to use critical thinking and questioning to consider if their underlying assumptions and beliefs about the world are accurate.

Originator: Jack Mezirow (1923-2014)

Keywords: adult education, higher education, academic development, disorienting dilemmas, assumptions, beliefs, worldview, change, transformation, critical reflection

Transformative learning theory was developed by Jack Mezirow in the late 1900s. He used this theory to describe how people develop and use critical self-reflecting to consider their beliefs and experiences, and over time, change dysfunctional means of seeing the world. Mezirow was interested in peoples’ worldviews and what leads people to change their particular view of the world.[i]

Mezirow describes transformative learning as “learning that transforms problematic frames of reference to make them more inclusive, discriminating, reflective, open, and emotionally able to change."[ii]

So, what must happen for a person to change their view of the world? Mezirow believed that this occurs when people face a “disorienting dilemma." Disorienting dilemmas are experiences that don’t fit into a person’s current beliefs about the world. When faced with a disorienting dilemma, people are forced to reconsider their beliefs in a way that will fit this new experience into the rest of their worldview. This often happens through “critical reflection" in the context of dialogue with other people.[iii]

A Case Study

Researcher Michael Christie presents the following case study as a real life example of transformative learning theory in action. Christie describes his experience teaching adult woman in a Graduate Diploma course for Adult and Vocational Educators. Throughout the course, he asked his students to “keep a critical incident file of their experiences."

The content of the course provided many new ideas that functioned as disorienting dilemmas for these woman. The woman were forced to think through their assumptions in a number of areas, including beliefs about gender roles. Christie states, “For example, the belief that ‘a woman’s place is in the home’ was undermined, the assumptions underpinning it challenged, and a new perspective enacted."

Applications of Transformative Learning Theory

Disorienting dilemmas often occur in the context of academic learning environments, as teachers provide space to critically engage with new ideas. Teachers who want to utilize transformative learning in their classrooms can consider implementing the following opportunities for students.

  • Providing opportunities for critical thinking – Teachers can create opportunities for critical thinking through providing content that introduces new ideas. Students then need the opportunity to engage with new content through journaling, dialoguing with other students, and critically questioning their own assumptions and beliefs.
  • Providing opportunities to relate to others going through the same transformative process – Transformation often happens in community as students bounce ideas off one another and are inspired by the changes friends and acquaintances make.
  • Providing opportunities to act on new perspectives – Finally, research indicates that it is critical for teachers to provide the opportunity for students to act on their new found beliefs. There is some indication that true transformation cannot take place until students are able to actively take steps that acknowledge their new belief.



[i] Christie, M., Carey, M., Robertson, A., & Grainger, P. (2015). Putting transformative learning theory into practice. Australian Journal of Adult Learning, 55(1), 10-30

[ii] Mezirow, J. (2009). Transformative learning theory. In J. Mezirow, and E. W. Taylor (Eds), Transformative Learning in Practise: Insights from Community.

[iii] Howie, P. & Bagnall, R. (2013). A beautiful metaphor: Transformative learning theory. International Journal of Lifelong Education, 32(6), 816-836.

Also check out:

Stereotype Threat (Steele, Aronson)

Summary: Stereotype threat occurs when people are at risk for living up to a negative stereotype about their group. For example, a woman may fail to reach her career goal of being a scientist because of how she changes her behavior in response to perceptions about her own gender.

Originators: Claude Steele and Joshua Aronson

Keywords: stereotypes, vulnerability, self-defeating behavior, performance, gender, race, intelligence

Stereotype threat is a term that was created by social scientists Claude Steele and Joshua Aronson. They completed an important early study in 1995 which defined stereotype threat as “being at risk of confirming, as self-characteristic, a negative stereotype about one’s group."[i]

In this study, Steele and Aronson observed the performance of Black and White students on academic tests. Steele and Aronson created the study in response to a negative stereotype about Black students which pervades culture – Black students are portrayed as less intelligent and less competent than White students. Because of this stereotype, Steele and Aronson wondered if Black students would “protectively dis-identify with achievement in school and related intellectual domains." This desire to disengage from intellectual pursuits could possible lead Black students to live up to their negative stereotype.

The results of the study confirmed the researcher’s suspicion. When test instructors emphasized the role of race before the test, Black students performed worse than White students. When instructors did not emphasize race, Black and White students performed equally well.

In essence, stereotype threat occurs when people fear that they will live up to a negative stereotype about their group. In response to their fear, they participate in disengaging and self-defeating behaviors that ironically cause them to live up to the feared stereotype.

Stereotype Threat Impacts Peoples’ Behavior

Stereotype threat has been shown to impact peoples’ behavior in the following ways.[ii]

  • Reduced effort – People who fear they might live up to a stereotype sometimes reduce their effort so they can have an excuse if they fall into that stereotype. For example, people may not prepare for a test so they have an excuse when they do poorly.
  • Disengaging – People who are stereotypically not good at something (such as woman in mathematics) will often disengage from that field or area.
  • Changing aspirations and career goals – Some people go as far as to change their life aspirations and career goals in response to stereotype threat.

How to Reduce Stereotype Threat

Stereotype threat has been studied extensively, with a heavy emphasis on how to reduce this phenomenon in various populations. Research shows that the following strategies can be effective. Many of these are practical strategies that can be carried out in classrooms and other settings.

  • Providing role models. People who observe role models from their group engaging in certain fields and activities are more likely to think they can do the same thing. One study showed that woman who read about other woman who had succeeded in fields of architecture, law, medicine, and intervention performed better on a mathematics test than those who didn’t.[iii]
  • Encouraging self-affirmation – One study showed that having African students engage in a self-affirming journal exercise before the start of a semester closed the racial achievement gap by 40%.[iv]
  • Emphasizing motivation and effort – African American students who were taught that intelligence is “a malleable rather than fixed capacity" that can be increased through motivation and effort received better grades than those who were not taught this.[v]

Although stereotype threat is a significant concern for many vulnerable groups of people, research consistently shows that the effects of stereotype threat can be reduced through following strategies such as these.[v]

Over three hundred studies have investigated stereotype threat in a wide variety of areas.[vi]


[i] Steele, C. M., & Aronson, J. (1995). Stereotype threat and intellectual test performance of African Americans. Journal of Personality and Social Psychology, 69(5), 797-811.

[ii] Stroessner, S. & Good, C. (n.d.) Stereotype threat: An overview. Retrieved from

[iii] McIntyre, R. B., Paulson, R., & Lord, C. (2003). Alleviating women’s mathematics stereotype threat through salience of group achievements. Journal of Experimental Social Psychology, 39, 83-90.

[iv] Cohen, G. L., Garcia, J., Apfel, N. & Master, A. (2006). Reducing the racial achievement gap: A social-psychological intervention. Science, 313, 1307-1310.

[v] Aronson, J., Fried, C. B., & Good, C. (2002). Reducing the Effects of Stereotype Threat on African American College Students by Shaping Theories of Intelligence. Journal of Experimental Social Psychology, 38, 113-125.

[vi] Stroessner, Steve; Good, Catherine. “Stereotype Threat: An Overview”. Reducing Stereotype Retrieved 6 March 2011.

Social Proof

Summary: Social proof describes a psychological phenomenon in which people mirror the actions and opinions of others. In other words, people’s decisions are often impacted by the preferences and modeling of individuals or groups around them.

Keywords: informational social influence, marketing, group norms, standards of behavior, testimonials, crowds, social modeling, sales, business, conformity, group conformity, social media

Originator: Muzafer Sheraf (1906-1988)


Social proof was first described in scientific research by a psychologist named Muzafer Sheraf. Sheraf was interested in the impact of groups on individual decision making. In relation to this interest, he completed a famous experiment on group conformity in 1936.[i]

In this study, Sheraf asked participants to observe a blinking light. A blinking light in a dark room often appears to move, even when it remains still. Based on this common perception, Sheraf asked participants to indicate how many inches they thought the blinking light moved. Sheraf first asked participants to guess an answer when they were alone. Then, he asked them the same question again while they were surrounded by a group of other participants. Sheraf found that participants changed their initial answers once they moved to the group setting. Across the board, people changed their number to closer reflect what other group members had guessed.

The concept of social proof came out of studies such as this one. Researchers consistently observe a tendency for individuals to move towards group conformity. Individuals often change their behaviors, opinions, and decisions to match the people around them.


Using Social Proof to Influence People

Social proof is commonly used in marketing and social media to influence people to buy products. Listed below are a variety of different types of social proof that are used in the context of marketing.[ii]

Social proof uses the influence of social media friends. For example, a business might indicate how many of a person’s Facebook friends “liked" a particular product they sell. People are more influenced to buy something when they know that their friends like the product.

  • Social proof uses the influence of celebrities. Research shows that people are more likely to buy a product when it is endorsed by a familiar and well-liked celebrity.
  • Social proof uses the influence of professional certifications and testimonials. Experts in an area may be called upon to endorse a product or provide a testimonial of how they have enjoyed a product.
  • Social proof uses the influence of crowds. Sometimes businesses indicate the number of people who have bought a product. When people know that a product or service is popular, they are more likely to want to buy it.


Social Proof and Personal Decisions

Social proof is a great marketing strategy and an effective means of influencing people to make certain choices. However, individuals should consider if social proof is always the best way to make decisions.

Quite notably, Sharif’s original study indicated that people were not aware of the extent to which they were impacted by the group. When participants where asked if they thought they were influenced by the group, most of them believed they had not been influenced. However, it was clear from the results of the study that people were wrong to believe this.

Negative forms of social proof can lead to bad decision making and giving into peer pressure. A prime example of this is college students who abuse alcohol and drugs.[iii] Research has drawn connections between social proof and this common dangerous behavior in college students. On a college campus, so many people engage in substance abuse that this behavior is observed to be the norm. Incoming students are apt to conform with the group and begin abusing substances just like the older students around them.

It is not always wrong to make decisions based on social proof. However, Sharif’s study provides an important caution that people should develop self-awareness surrounding this topic, so they can know when their decisions are being influenced by the people around them.



[i] Sherif, M. (1936). The psychology of social norms. Oxford, England: Harper.

[ii] Talib, Y. Y. A. & Saat, R. M. (2017). Social proof in social media shopping: An experimental design research. SHS Web of Conferences, 34

[iii] Cullum, J., O’Grady, M., Armeli, S., & Tennen, H. (2012). Change and stability in active and passive social influence dynamics during natural drinking events: A longitudinal measurement-burst study. Journal of Social and Clinical Psychology, 31(1), 51-80.

Backward Design

Summary: Backward Design is a model for designing instructional materials where the instructor or designer begins the design process with a focus on the desired results (i.e., the outcome) of instruction.

Originator / Contributors: Grant Wiggins and Jay McTighe

Keywords: Outcomes, Evidence, Experiences, Instruction, Backward Design, Wiggins, McTighe

Backward Design can be summarized as a process or model for designing instructional materials where the instructor or instructional designer focuses on the desired end results (i.e., the outcome) of a class or course instruction. Rather than beginning the planning process with a focus on supporting exercises, resources or long-used textbooks, the designer focuses on the learners and begins the design process by asking what learners should be able to understand and do after the provided instruction. The designer then identifies what types of evidence are sufficient proof of the desired end result. The designer works “backwards" from that end goal and intentionally plans and develops supporting instruction and learning experiences around the desired outcomes and evidence[1].

Backward Design can be summarized in a three-step process:

1: Identify Desired Outcomes: Articulate what learners should be able to understand and do after provided instruction.

2: Identify Acceptable Evidence: Determine what types of assessments and measures would clarify (or serve as evidence of) when and whether students can perform the desired outcome.

3: Plan Learning Experiences and Instruction: Develop exercises, materials and instruction around the desired outcomes and evidence.

By way of example, consider a paralegal instructor who wants students, as a result of her instruction, to be able to prepare case briefs. She could begin a class by sharing a summary of cases she finds fascinating and then spend time discussing the cases with students. However, this might not be the preferred use of instructional time when the goal is helping students understand how to produce a case brief and why being able to do so matters.

With Backward Design’s focus on the desired result (for example, preparing a clear, well-written case brief), instruction can be tailored to support this desired product. Backward Design focuses on essential questions (for example, the value of case briefs, how to read and understand a legal opinion, application of case briefing in professional contexts) such that students develop a deeper appreciation for the practical relevance of their work.

Following the Backward Design three-step process:

1: Desired Outcomes: Students should be able to prepare a written case brief after reading a judicial opinion.

2: Acceptable Evidence: A marked up judicial opinion and a supporting written case brief that follows a standard, professional format.

3: Plan Learning Experiences and Instruction: The instructor might model note-taking when reading a judicial opinion, provide a template for a case brief, and then illustrate case briefing in a step-by-step manner. Students might prepare case briefs in a step-by-step fashion that follows the instructor’s modeling and template.

Backward Design focuses on what students need to know, understand and be able to do as a result of provided instruction[3]. The desired result is the catalyst for all related instructional and assessment planning. Emphasis is placed on essential questions and what is most important for students to understand and know (student learning), rather than on materials, topics and content an instructor might be most comfortable with (student teaching). Student understanding is a central focus of the backward design methodology[3].

Pursuant to the Backward Design model, desired results of instruction might be based upon national, state and local standards. Results might be tied to professional goals and workplace needs, as well. This model prioritizes knowledge and focuses on what is most important for students to understand and achieve. Arguably, if design begins with the end in mind, instruction is more likely to clearly focus on the identified desired results[3].

Some argue that this model places too heavy a focus on the result (or test) at the expense of the learning journey or experience[2]. Others caution that there are risks of incorrectly identifying which knowledge is essential for students to understand. There are concerns for too narrow a focus on results, where a design does not address all elements of a lesson or workplace needs and results in little flexibility to incorporate alternate paths to achieve a final goal. Finally, the Backward Design process can be time consuming (to learn and in practice)[3].


For links to Backward Design templates and additional resources, see: Jay McTighe Design Tools, Templates and Resources

For videos of Grant Wiggins explaining Understanding by Design, see:

“Grant Wiggins – Understanding by Design (1 of 2)" at Grant Wiggins – Understanding by Design (1 of 2)

“Grant Wiggins – Understanding by Design (2 of 2)" at Grant Wiggins – Understanding by Design (2 of 2)

For a video of Jay McTighe explaining Understanding by Design, see:

“What is Understanding by Design? Author Jay McTighe Explains" at “What is Understanding by Design?”


  1. Bowen, Ryan S. (2017). Understanding by Design. Vanderbilt University Center for Teaching. Retrieved on September 7, 2017 from
  2. Meier, E.B. (n.d.). Understanding by Design Wiggins & McTighe. [PowerPoint slides]. Retrieved from
  3. Wiggins, G. and McTighe, J. (1998) Understanding by Design. Alexandria, VA: Association for Supervision and Curriculum Development.

Author Credit: J. Schneider

Model of Hierarchical Complexity

The Model of Hierarchical Complexity, sometimes referred to as the MHC in educational psychology, is a framework used to explore and organize the patterns of human development. It is a theory used when working with behavioral development in particular.

The MHC functions to give rank or order to the developmental complexity of a certain behavior. It is the basis for other hierarchical theories of development, such as Piaget. It was originally developed by Michael Commons, an American behavioral scientist.

Contributors: Michael Commons (1939 — present)

Key Concepts

Task Analysis

MHC is based on a system of task analysis in which tasks are broken down into minute steps and then analyzed based on their complexity in relation to the individual’s development. [1] The task is initiated when the individual is presented with a stimulus, and their behavior(s) in reaction to that task are what are analyzed for their developmental complexity. For example, an infant presented with a bright-colored toy would not reach toward the object or even train their eyes in its direction, but an older baby further along in the development process would do so.

Stages of hierarchical complexity

0 — calculatory stage

Characterized by having solely the capacity for computation, this stage functions as the “control" of sorts as it can be used to describe the hierarchical complexity of computers.

1 — automatic stage

Individual can respond to one environmental stimulus at a time.

2 — sensory or motor stage

Individual can move their limbs and parts of their face and view things. They begin to react to conditioned stimuli and form responses with discrimination.

3 — circular-sensory-motor stage

Individual can reach for, touch, or grab things. In terms of speech, individual will babble and is beginning to grasp phonemes (word parts).

4 — sensory-motor stage

Individual responds to stimuli based on their established concept of it.

5 — nominal stage

Individual can use names for objects as well as make commands. They begin to identify relationships between the concepts they have established and can name those as well.

6 — sentential stage

Individual can imitate others and acquire words or sentences through imitation, as well as following a sequence of acts presented by others.

7 — preoperational stage

Individual practices early deductive reasoning, engages in imitation, and can follow and tell a story or sequence of events.

8 — primary stage

Individual begins to make simple logical reasoning with regard to rules and time, also begins to grasp simple arithmetic.

9 — concrete stage

Individual can engage more deeply with arithmetic problems, understand more about social and group relations, and establish relationships with others and self.

10 — abstract stage

Individual begins to understand variables such as stereotypes and logic skills become more formalized.

11 — formal stage

Individual can argue using linear logic, can solve problems with one unknown, such as in algebra.

12 — systematic stage

Individual can establish and understand systems and understands relationships and logic problems with more than one variable or unknown.

13 — metasystematic stage

Individual can form relationships between systems and understand similarities and differences.

14 — paradigmatic stage

Individual can fit these new “metasystems" to form larger-picture paradigms, as well as point out inconsistencies between the various metasystems.

15 — cross-paradigmatic stage

Individual can see relationship between multiple paradigms, such as “this perspective is like that perspective because they both incorporate…"

16 — meta-cross-paradigmatic or performative-recursive stage

Individual can reflect on the similarities and differences between paradigmatic relationships. For example, “these two perspectives are inter-related because…"

These stages are linked to an age or developmental milestone in an individual’s life in various stage models. Some stage-based theories even use the same names as the MHC’s 16 stages, though most do not encompass it in its entirety.


Some developmental psychologists feel that the MHC phases are overly precise. Their criticism is that the MHC goes into too much detail of the various complexities of task analysis, and that the phases are less significant beyond stage 12, the systematic stage.


  1. Commons, M. L. (2008). Introduction to the model of hierarchical complexity and its relationship to postformal action. World Futures, 64(5-7), 305-320.

Backup Systems (Redundancy)

Summary: The concept of backup systems, also known as redundancy, originated in the field of engineering. Many mechanical systems are created in such a way that if one part of the system fails, the system as a whole will still be able to function due to the presence of backup components. Redundancy and backup plans should play an important role in many decision-making processes for the purpose of risk reduction.

Originator: Jon von Neumann (1903-1957)

Keywords: reliability, reliability engineering, redundancy, independent backup system, mechanical engineering, risk reduction, safety plan, disaster recovery, backup software

Backup systems were first described in the field of mechanical engineering by Jon von Neumann. In his well-known work, Probabilistic Logics and Synthesis of Reliable Organisms from Unreliable Components, Neumann described how computers can be built with redundant parts as a “technique [that] can be used to control error."[i] In the years to come, redundancy would become an essential concept in designing complex mechanical systems.

The engineering behind aircrafts is a prime example of how engineers use backup systems today. If an airplane experiences any form of mechanical failure while in the sky, this is clearly a major problem. Because of the inherent risk found in air travel, airplanes are built in a mechanically redundant way, with a number of backup systems in place. For example, most airplanes can run on only one engine, even though they have four engines in all. Up to three of these engines could fail, and the airplane would still be able to fly.

It has been argued that the redundancy of back-up systems should be used as a “design paradigm" for all modern technology. From airplanes to computers, from communication systems to emergency preparedness, backup systems should be an essential component of how society designs all important technology.

Backup Systems and Risk Reduction

When considered from the standpoint of making decisions, backup systems are a form of reducing risk in a variety of areas. The decision to include or not include backup systems can have a huge impact on communities, businesses, and individuals.

Backup systems are important to use in mechanical systems as described above, software systems, and for backing up data. Research shows that redundancy in software systems can reduce human error.[ii] And in terms of backup of data, many people know the importance of saving documents in multiple places to reduce the risk of losing information. For example, an important document might be saved on a computer hard drive, an external disc, and an online storage system. Some businesses have backup policies in place to ensure the safety of important documents.

Backup systems are especially important in decisions about emergency preparedness. In natural disasters, backup systems should be put into place to ensure that people have enough fuel, food, and shelter. When performing field work or travel in remote areas, redundancy in communication is important. A group should be able to communicate with the outside world through multiple means such as walkie talkies, cellphones, and flares to ensure help could find them should something go wrong.

Human backup systems are also important to consider.[iii] Are there enough operators to respond to 911 calls? Are there enough policeman to back up their coworkers and enough fireman for an area?

In situations where things could easily go wrong, redundancy is important to decrease the risk of negative outcomes.


[i] Downer, John. (2009). When failure is an option: Redundancy, reliability, and regulation in complex technical systems. Centre for Analysis of Risk and Regulation. Discussion paper No: 53.

[ii] Van den Brand, M. & Groote, J. F. (2015). Software engineering: Redundancy is key. Science of Computer Programming, 97(1), 75-81.

[iii] Hwang, S. L. & Li, Z. 2016). Human factors in digital systems. A study on human redundancy in execution of computerized emergency operating procedures. International Journal of Industrial Ergonomics, 51, 1-82.



Law of Large Numbers

Summary: The Law of Large Numbers is a statistical theory related to the probability of an event. This theory states that the greater number of times an event is carried out in real life, the closer the real-life results will compare to the statistical or mathematically proven results. In research studies, this means that large sample sizes average out to be more reflective of reality than small sample sizes.

Originators: Gerolama Cardano (1501-1576), Jacob Bernoulli (1654-1705)

Key Words: Probability, mathematics, sample size, anomalies, statistics, percentage, average, mean

The Law of Large Numbers was first observed by the mathematician Gerolama Cardano in the 16th century. Cardano noticed the theoretical presence of The Law of Large Numbers, but he never took the time to prove it mathematically. Another mathematician, Jacob Bernoulli, figured out the equations behind The Law of Large Numbers in 1713.[i]

A simple way to understand The Law of Large Numbers is to consider the probability of a coin toss. When a coin is tossed, there is a 50% chance that the coin will land on heads and a 50% chance that the coin will land on tails. This is a statistically proven fact. However, if a person tossed a coin in the air 5 times, there is a chance that the coin would land on heads every single time. This event would not seem to align with the mathematically proven probability of landing on tails 50% of the time.

How can we explain this? These real-life results don’t mean the math is wrong. They simply mean that the coin toss has to be carried out more times to accurately reflect what math says is true. If the same person tossed the coin in the air 500 times, by the end of all the tosses, the coin would have landed on heads an average of 250 times and on tails an average of 250 times. The real life coin toss is now more reflective of what math says to be true because it has been carried out a larger number of times.

Sample Sizes

The Law of Large Numbers is most applicable to scientific research and sample sizes.[ii] When scientists complete research studies, they make decisions about how many people will be in the study. This is an important decision because small sample sizes can greatly skew results due to the presence of anomalies. The larger the sample size, the more the results will reflect the true nature of the population that is being studied.

Consumers trying to understand scientific research should take sample size into consideration when determining the validity of a study. Scientists should do everything within in their power to work with large sample sizes, as this makes their work more accurate and thus more beneficial to society.

Personal Decisions

The Law of Large Numbers is also an important reminder that individual instances don’t provide the whole story. There are times when people make decisions based on one event or instance they have experienced or heard about. This is often a bad way to make decisions.

For example, someone might hear a story about how their friend had a terrible reaction to a medication and refuse to take that medication based on that one example. However, this is a bad way to make a choice about medication, as one experience or story is often not reflective of the way things typically work. The medication may be extremely safe, and the one story simply reflects an anomaly. When making personal decisions it is important to gather a range of information. The Law of Large Numbers explains the theory and mathematics behind this important concept.


[i] Seneta, E. (2013). A tricentenary history of the law of large numbers. Bernoulli, 19(4), 1088-1121

[ii] Dinov, I. D., Christou, N., & Gould R. (2009). The law of large numbers: The theory, applications, and technology-based education. Journal of Statistics Education, 17(1), 1-19.



Summary: Scarcity is an economic term that describes the mindset people develop when they have many needs and not enough resources to meet those needs. When people operate out of a scarcity mindset, it can greatly impair their decision-making abilities.

Originators: Lionel Robbins (1898-1984), Sendhil Mullainathan (1972 to Present), Eldar Shafir (1959 to Present)

Keywords: paucity, poverty, scarcity mindset, resources, allocation of resources, cognitive load, goal-setting, short-term goals, long-term goals, finances, financial wellbeing, attention, effort, tunneling

Lionel Robbins was the first person to discuss the field of economics using the concept of scarcity of resources. In his article, An Essay on the Nature and Significance of Economic Science, Lionel stated, “Economics is the science which studies human behavior as a relationship between ends and scarce means which have alternative uses."[i]

The concept of scarcity has been further developed since then. Key research on the topic of scarcity has recently been completely by the behavioral scientists Sendhil Mullainathan and Eldar Shafir.

Perhaps the most pertinent example of scarcity is found in people who live in poverty. Research has found that living in a state of poverty impairs peoples’ decision-making abilities. This is because poverty leads to a scarcity mindset that negatively changes the way a person thinks, plans, and operates. Research has shown two main ways in which this happens.

First, living in a state of scarcity, “imposes a cognitive load that saps attention and reduces effort."[ii] Researchers studied low-income and high-income individuals who were faced with a large expense such as a car repair. They found that low-income individuals performed worse on an unrelated reasoning task when they were considering this repair than when they didn’t have additional expenses to consider. On the other hand, high-income individuals performed equally well on the task, whether they were considering an expense or not. The researchers hypothesized that this occurred because the high-income individuals did not have to worry about not being able to pay the expense, and therefore did not have to allocate any of their attention away from the reasoning task.

Second, living in a state of scarcity impairs peoples’ ability to make and carry out healthy long-term goals.[iii] The cognitive load described above leads to bad decision making. People become focused on present, short-term goals such as how to deal with immediate expenses. This is called tunneling – the brain becomes so focused on a particular short-term problem that it can’t focus on anything else.

People who engage in tunneling may make bad financial decisions such as playing the lottery or borrowing too much money. These bad decisions, that they hope will help them deal with the short-term problem of paying for a bill, can lead people into worse situations than they were in before.

From Scarcity to Abundance

Scarcity is also present in other situations such as when workers are not given enough resources to do their jobs or in the aftermath of a natural disaster when there aren’t enough goods to go around. Sometimes people even live out of a scarcity mindset when there are plenty resources to go around. When people make decisions from a scarcity mindset, they hoard resources, only think of themselves, and live with a lot of anxiety.

Steven Covey is a businessman who wrote a book entitled The Seven Habits of Highly Effective People. In the context of business, Covey encourages people to embrace an abundance mentality over a scarcity mentality as they make decisions about their lives and careers.[iv] People with an abundance mentality make decisions out of a mindset that there is enough to go around. They are more generous with their resources, more gracious when other people succeed, and less anxious that they will miss out. They make decisions out of a belief that there is enough to go around.


[i] Robbins, L. (1932). An essay on the nature and significance of economic science. London: Macmillan, First Edition. Retrieved from

[ii] Mani, A., Mullainathan, S., Shafirt, E., Zhai, J. (2013). Poverty impedes cognitive function. Science, 351(6149), 976-980.

[iii] Shah, A. K., Mullainathan, S., & Shafir, E., (2012). Some consequences of having too little. Science, 338(6107), 682-685.

[iv] Covey, S. (2004). The seven habits of highly effective people: Powerful lessons in personal change. NY, New York: Free Press.

privacy policy