Do “overview” sections increase learning outcome?

Do “overview” sections increase learning outcome?

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Suppose a math textbook contains an overview chapter for each part of the textbook. The intent of those overview chapters is to motivate and introduce the new mathematical concepts which will be discussed in the respective part of the textbook. For example, why do we need the mathematical concept? How did the concept evolve in history? What will be the content of the next chapters?

In this context, will the overview sections facilitate learning? How important are overview chapters in textbooks for the success of learning?

Note: I reasked this question on

There is something called "advance organizer", that traces back to Ausubel (1960). It is some kind of overview, in which a short summary is given and (more important), in which the following topic is connected to prior knowledge (= Associations are being activated). In that sense it activates schemes, in order to assimiliate the new knoweldge to the old one or to accomodate/correct the prior knowledge. So, to be useful, advance organizers should have certain features:

  • Connections between the following topic and prior knowlege

  • Catch the attention of the student

  • Be concret, insted of abstract

F.e. Before teaching equations the teacher could give the analogy of a scale.

From a scientific perspective it is known, that advance organizers can have supportive effects on learning and retention (see f.e. Luiten, Ames & Ackerson, 1980)

Luiten, J., Ames, W., & Ackerson, G. (1980). A meta-analysis of the effects of advance organizers on learning and retention. American Educational Research Journal, 17(2), 211-218.

Yes, an overview chapter helps for most people.

An overview chapters allows the reader to develop a stronger associative network, for instance this read:

Sowa, J. F. (2006). Semantic networks. Encyclopedia of Cognitive Science.

Considering the importance that one is able to connect the dots while learning math, facilitating the development of the associative network is beneficial for learning. This effect is further elevated by visual learners.

I can suggest you these:

Presmeg, N. C. (2006). Research on visualization in learning and teaching mathematics. Handbook of research on the psychology of mathematics education, 205-235.

Gilbert, J. (2005). Visualization: A metacognitive skill in science and science education. Visualization in science education, 9-27.

For less visual learners, or those too lazy to appreciate the overview pages, I personally believe it will not reduce learning or provide any other harm for that matter.

Do &ldquooverview&rdquo sections increase learning outcome? - Psychology

Reflective Thinking: RT

What is reflective thinking?

The description of reflective thinking:

Critical thinking and reflective thinking are often used synonymously. Critical thinkingis used to describe:

". the use of those cognitive skills or strategies that increase the probability of a desirable outcome. thinking that is purposeful, reasoned and goal directed - the kind of thinking involved in solving problems, formulating inferences, calculating likelihoods, and making decisions when the thinker is using skills that are thoughtful and effective for the particular context and type of thinking task. Critical thinking is sometimes called directed thinking because it focuses on a desired outcome." Halpern (1996).

Reflective thinking,on the other hand, is a part of the critical thinking process referring specifically to the processes of analyzing and making judgments about what has happened. Dewey (1933) suggests that reflective thinking is an active, persistent, and careful consideration of a belief or supposed form of knowledge, of the grounds that support that knowledge, and the further conclusions to which that knowledge leads. Learners are aware of and control their learning by actively participating in reflective thinking – assessing what they know, what they need to know, and how they bridge that gap – during learning situations.

In summary, critical thinking involves a wide range of thinking skills leading toward desirable outcomes and reflective thinking focuses on the process of making judgments about what has happened. However, reflective thinking is most important in prompting learning during complex problem-solving situations because it provides students with an opportunity to step back and think about how they actually solve problems and how a particular set of problem solving strategies is appropriated for achieving their goal.

Characteristics of environments and activities that prompt and support reflective thinking:

  • Provide enough wait-time for students to reflect when responding to inquiries.
  • Provide emotionally supportive environments in the classroom encouraging reevaluation of conclusions.
  • Prompt reviews of the learning situation, what is known, what is not yet known, and what has been learned.
  • Provide authentic tasks involving ill-structured data to encourage reflective thinking during learning activities.
  • Prompt students' reflection by asking questions that seek reasons and evidence.
  • Provide some explanations to guide students' thought processes during explorations.
  • Provide a less-structured learning environment that prompts students to explore what they think is important.
  • Provide social-learning environments such as those inherent in peer-group works and small group activities to allow students to see other points of view.
  • Provide reflective journal to write down students' positions, give reasons to support what they think, show awareness of opposing positions and the weaknesses of their own positions.
  • Links to descriptions of reflective thinking activities in use with middle school kids:
    • Recommendations for prompting reflective thinking in the classroom:

      Why is reflective thinking important?

      Modern society is becoming more complex, information is becoming available and changing more rapidly prompting users to constantly rethink, switch directions, and change problem-solving strategies. Thus, it is increasingly important to prompt reflective thinking during learning to help learners develop strategies to apply new knowledge to the complex situations in their day-to-day activities. Reflective thinking helps learners develop higher-order thinking skills by prompting learners to a) relate new knowledge to prior understanding, b) think in both abstract and conceptual terms, c) apply specific strategies in novel tasks, and d) understand their own thinking and learning strategies.

      Links to more information on reflective thinking:

      Reflective thinking and middle school kids:

      • Teachers should model metacognitive and self-explanation strategies on specific problems to help students build an integrated understanding of the process of reflection.
      • Study guides or advance organizer should be integrated into classroom materials to prompt students to reflect on their learning.
      • Questioning strategies should be used to prompt reflective thinking, specifically getting students to respond to why, how, and what specific decisions are made.
      • Social learning environments should exist that prompt collaborative work with peers, teachers, and experts.
      • Learning experiences should be designed to include advice from teachers and co-learners.
      • Classroom activities should be relevant to real-world situations and provide integrated experiences.
      • Classroom experiences should involve enjoyable, concrete, and physical learning activities whenever possible to ensure proper attention to the unique cognitive, affective, and psychomotor domain development of middle school students.

      How does K a AMS support reflective thinking?

      K a AMS model of PBL and its relationship to reflective thinking:

      • Provide teacher questions designed to prompt students to identify and clarify overall and subordinate problems.
      • Provide many opportunities to engage students in gathering information to look for possible causes and solutions.
      • Provide ideas and activity sheets to help students evaluate the evidence they gather.
      • Provide questions that prompt students to consider alternatives and implications of their ideas.
      • Provide questions and activities that prompt students to draw conclusions from the evidence they gathered and pose solutions.
      • Provide opportunities for students to choose and implement the best alternative.
      • Encourage students to monitor and reevaluate their results and findings throughout the entire unit.

      KaAMS incorporates prompts and scaffolding suggestions to promote reflective thinking by:

      • Structuring lesson plans to support reflective thinking.
      • Providing lesson components that prompt inquiry and curiosity.
      • Providing resources and hand-on activities to prompt exploration.
      • Providing reflective thinking activities that prompt students to think about what they have done, what they learned, and what they still need to do.
      • Providing reflection activity worksheets for each lesson plan to prompt students to think about what they know, what they learned, and what they need to know as they progress through their exploration.

      Links to additional information on critical and reflective thinking:

      Bobo Doll Experiment

      During the 1960s, Albert Bandura conducted a series of experiments on observational learning, collectively known as the Bobo doll experiments.

      Two of the experiments are described below:


      Bandura (1961) conducted a controlled experiment study to investigate if social behaviors (i.e., aggression) can be acquired by observation and imitation.

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      Bandura, Ross, and Ross (1961) tested 36 boys and 36 girls from the Stanford University Nursery School aged between 3 to 6 years old.

      The researchers pre-tested the children for how aggressive they were by observing the children in the nursery and judged their aggressive behavior on four 5-point rating scales.

      It was then possible to match the children in each group so that they had similar levels of aggression in their everyday behavior. The experiment is, therefore, an example of a matched pairs design.

      To test the inter-rater reliability of the observers, 51 of the children were rated by two observers independently and their ratings compared. These ratings showed a very high reliability correlation (r = 0.89), which suggested that the observers had a good agreement about the behavior of the children.


      • Aggressive model is shown to 24 children
      • Non-aggressive model is shown to 24 children
      • No model shown (control condition) - 24 children

      Stage 1: Modeling

      24 children (12 boys and 12 girls) watched a male or female model behaving aggressively towards a toy called a 'Bobo doll'. The adults attacked the Bobo doll in a distinctive manner - they used a hammer in some cases, and in others threw the doll in the air and shouted "Pow, Boom."

      Another 24 children (12 boys and 12 girls) were exposed to a non-aggressive model who played in a quiet and subdued manner for 10 minutes (playing with a tinker toy set and ignoring the bobo-doll).

      Animation created by Wes Venables

      Stage 2: Aggression Arousal

      All the children (including the control group) were subjected to 'mild aggression arousal.' Each child was (separately) taken to a room with relatively attractive toys.

      As soon as the child started to play with the toys, the experimenter told the child that these were the experimenter's very best toys and she had decided to reserve them for the other children.

      Animation created by Wes Venables

      Stage 3: Test for Delayed Imitation

      • The next room contained some aggressive toys and some non-aggressive toys. The non-aggressive toys included a tea set, crayons, three bears and plastic farm animals. The aggressive toys included a mallet and peg board, dart guns, and a 3 foot Bobo doll.

      • The child was in the room for 20 minutes, and their behavior was observed and rated though a one-way mirror. Observations were made at 5-second intervals, therefore, giving 240 response units for each child.

      Animation created by Wes Venables


      • Children who observed the aggressive model made far more imitative aggressive responses than those who were in the non-aggressive or control groups.

      • There was more partial and non-imitative aggression among those children who had observed aggressive behavior, although the difference for non-imitative aggression was small.

      • The girls in the aggressive model condition also showed more physical aggressive responses if the model was male, but more verbal aggressive responses if the model was female. However, the exception to this general pattern was the observation of how often they punched Bobo, and in this case the effects of gender were reversed.

      • Boys were more likely to imitate same-sex models than girls. The evidence for girls imitating same-sex models is not strong.


      Bobo doll experiment demonstrated that children are able to learn social behavior such as aggression through the process of observation learning, through watching the behavior of another person. The findings support Bandura's (1977) Social Learning Theory.

      This study has important implications for the effects of media violence on children.


      There are three main advantages of the experimental method.

      1. Experiments are the only means by which cause and effect can be established. Thus, it could be demonstrated that the model did have an effect on the child's subsequent behavior because all variables other than the independent variable are controlled.

      2. It allows for precise control of variables. Many variables were controlled, such as the gender of the model, the time the children observed the model, the behavior of the model and so on.

      Limitations of the procedure include:

      Academic Sources

      Designing and Assessing Courses and Curricula, Third Edition, 2008. Robert M. Diamond. Jossey-Bass: San Francisco, CA.)

      Harden, R. M. (2002). Learning outcomes and instructional objectives: is there a difference?. Medical teacher, 24(2), 151-155.

      Bonner, S. E. (1999). Choosing teaching methods based on learning objectives: An integrative framework. Issues in Accounting Education, 14(1), 11-15.

      Starr, C. W., Manaris, B., & Stalvey, R. H. (2008). Bloom’s taxonomy revisited: specifying assessable learning objectives in computer science. ACM SIGCSE Bulletin, 40(1), 261-265.

      Bloom, B. S. (ed.). Taxonomy of educational objectives: Handbook 1: Cognitive domain. Longmans, Green and Company, New York, 1956.

      Part B of IDEA is the section which lays out the educational guidelines for school children 3-21 years of age. By law, states are required to educate students with disabilities (Martin, Martin, & Terman, 1996). IDEA provides financial support for state and local school districts. However to receive funding, school districts must comply with six main principles set out by IDEA:

      • Every child is entitled to a free and appropriate public education (FAPE).
      • When a school professional believes that a student between the ages of 3 and 21 may have a disability that has substantial impact on the student's learning or behavior, the student is entitled to an evaluation in all areas related to the suspected disability.
      • Creation of an Individualized Education Plan (IEP). The purpose of the IEP is to lay out a series of specific actions and steps through which educational providers, parents and the student themselves may reach the child's stated goals.
      • That the education and services for children with disabilities must be provided in the least restrictive environment, and if possible, those children be placed in a "typical" education setting with non-disabled students.
      • Input of the child and their parents must be taken into account in the education process.
      • When a parent feels that an IEP is inappropriate for their child, or that their child is not receiving needed services, they have the right under IDEA to challenge their child's treatment (due process). (DREDF, 2008 Kastiyannis, Yell, Bradley, 2001 Turnbull, Huerta, & Stowe, 2004).

      Temporary Compliance

      Behaviorist theory, derived from work with laboratory animals, is indirectly responsible for such programs as piece-work pay for factory workers, stock options for top executives, special privileges accorded to Employees of the Month, and commissions for salespeople. Indeed, the livelihood of innumerable consultants has long been based on devising fresh formulas for computing bonuses to wave in front of employees. Money, vacations, banquets, plaques—the list of variations on a single, simple behaviorist model of motivation is limitless. And today even many people who are regarded as forward thinking—those who promote team-work, participative management, continuous improvement, and the like—urge the use of rewards to institute and maintain these very reforms. What we use bribes to accomplish may have changed, but the reliance on bribes, on behaviorist doctrine, has not.

      Moreover, the few articles that appear to criticize incentive plans are invariably limited to details of implementation. Only fine-tune the calculations and delivery of the incentive—or perhaps hire the author as a consultant—and the problem will be solved, we are told. As Herbert H. Meyer, professor emeritus in the psychology department at the College of Social and Behavioral Sciences at the University of South Florida, has written, “Anyone reading the literature on this subject published 20 years ago would find that the articles look almost identical to those published today.” That assessment, which could have been written this morning, was actually offered in 1975. In nearly forty years, the thinking hasn’t changed.

      Do rewards work? The answer depends on what we mean by “work.” Research suggests that, by and large, rewards succeed at securing one thing only: temporary compliance. When it comes to producing lasting change in attitudes and behavior, however, rewards, like punishment, are strikingly ineffective. Once the rewards run out, people revert to their old behaviors. Studies show that offering incentives for losing weight, quitting smoking, using seat belts, or (in the case of children) acting generously is not only less effective than other strategies but often proves worse than doing nothing at all. Incentives, a version of what psychologists call extrinsic motivators, do not alter the attitudes that underlie our behaviors. They do not create an enduring commitment to any value or action. Rather, incentives merely—and temporarily—change what we do.

      Rewards do not create a lasting commitment. They merely, and temporarily, change what we do.

      As for productivity, at least two dozen studies over the last three decades have conclusively shown that people who expect to receive a reward for completing a task or for doing that task successfully simply do not perform as well as those who expect no reward at all. These studies examined rewards for children and adults, males and females, and included tasks ranging from memorizing facts to creative problem-solving to designing collages. In general, the more cognitive sophistication and open-ended thinking that was required, the worse people performed when working for a reward. Interestingly enough, the researchers themselves were often taken by surprise. They assumed that rewards would produce better work but discovered otherwise.

      The question for managers is whether incentive plans can work when extrinsic motivators more generally do not. Unfortunately, as author G. Douglas Jenkins, Jr., has noted, most organizational studies to date—like the articles published—have tended “to focus on the effects of variations in incentive conditions, and not on whether performance-based pay per se raises performance levels.”

      A number of studies, however, have examined whether or not pay, especially at the executive level, is related to corporate profitability and other measures of organizational performance. Often they have found slight or even negative correlations between pay and performance. Typically, the absence of such a relationship is interpreted as evidence of links between compensation and something other than how well people do their jobs. But most of these data could support a different conclusion, one that reverses the causal arrow. Perhaps what these studies reveal is that higher pay does not produce better performance. In other words, the very idea of trying to reward quality may be a fool’s errand.

      Consider the findings of Jude T. Rich and John A. Larson, formerly of McKinsey & Company. In 1982, using interviews and proxy statements, they examined compensation programs at 90 major U.S. companies to determine whether return to shareholders was better for corporations that had incentive plans for top executives than it was for those companies that had no such plans. They were unable to find any difference.

      Four years later, Jenkins tracked down 28 previously published studies that measured the impact of financial incentives on performance. (Some were conducted in the laboratory and some in the field.) His analysis, “Financial Incentives,” published in 1986, revealed that 16, or 57%, of the studies found a positive effect on performance. However, all of the performance measures were quantitative in nature: a good job consisted of producing more of something or doing it faster. Only five of the studies looked at the quality of performance. And none of those five showed any benefits from incentives.

      Another analysis took advantage of an unusual situation that affected a group of welders at a Midwestern manufacturing company. At the request of the union, an incentive system that had been in effect for some years was abruptly eliminated. Now, if a financial incentive supplies motivation, its absence should drive down production. And that is exactly what happened, at first. Fortunately, Harold F. Rothe, former personnel manager and corporate staff assistant at the Beloit Corporation, tracked production over a period of months, providing the sort of long-term data rarely collected in this field. After the initial slump, Rothe found that in the absence of incentives the welders’ production quickly began to rise and eventually reached a level as high or higher than it had been before.

      On Incentives

      “The Pay-for-Performance Dilemma,” Herbert H. Meyer (Organizational Dynamics Winter 1975).

      “Financial Incentives” G. Douglas Jenkins, Jr. in Generalizing from Laboratory to Field Settings, edited by Edwin A. Locke (Lexington, MA: Lexington Books, 1986).

      “Why Some Long-Term Incentives Fail,” Jude T. Rich and John A. Larson in Incentives, Cooperation, and Risk Sharing, edited by Haig R. Nalbantian (Totowa, NJ: Rowman & Littlefield, 1987).

      “Output Rates Among Welders: Productivity and Consistency Following Removal of a Financial Incentive System,” Harold F. Rothe (Journal of Applied Psychology December 1970).

      “The Effects of Psychologically Based Intervention Programs on Worker Productivity: A Meta-Analysis,” Richard A. Guzzo, Richard D. Jette, and Raymond A. Katzell (Personnel Psychology Summer 1985).

      “One More Time: How Do You Motivate Employees?” Frederick Herzberg (Harvard Business Review January–February 1968).

      “An Elaboration on Deming’s Teachings on Performance Appraisal,” Peter R. Scholtes in Performance Appraisal: Perspectives on a Quality Management Approach, edited by Gary N. McLean, et al. (Alexandria, VA: University of Minnesota Training and Development Research Center and American Society for Training and Development, 1990).

      People, Performance, and Pay, Carla O’Dell (Houston: American Productivity Center, 1987).

      “Why Merit Pay Doesn’t Work: Implications from Organization Theory,” Jone L. Pearce in New Perspectives on Compensation, edited by David B. Balkin and Luis R. Gomez-Mejia (Englewood Cliffs, NJ: Prentice-Hall, 1987).

      “The New Performance Measures,” Monroe J. Haegele in The Compensation Handbook, Third Edition, edited by Milton L. Rock and Lance A. Berger (New York: McGraw-Hill, 1991).

      “Intrinsic and Extrinsic Motivational Orientations: Reward-Induced Changes in Preference for Complexity” Thane S. Pittman, Jolee Emery, and Ann K. Boggiano (Journal of Personality and Social Psychology March 1982).

      “Enemies of Exploration: Self-Initiated Versus Other-Initiated Learning,” John Condry (Journal of Personality and Social Psychology July 1977).

      “Toward a Theory of Task Motivation and Incentives” Edwin A. Locke (Organizational Behavior and Human Performance Volume 3, 1968).

      Intrinsic Motivation and Self-Determination in Human Behavior, Edward L. Deci and Richard M. Ryan (New York: Plenum Press, 1985).

      “Inferred Values and the Reverse-Incentive Effect in Induced Compliance,” Jonathan L. Freedman, John A. Cunningham, and Kirsten Krismer (Journal of Personality and Social Psychology March 1992).

      The Battle for Human Nature: Science, Morality and Modern Life, Barry Schwartz (New York: W.W. Norton and Company, 1986).

      One of the largest reviews of how intervention programs affect worker productivity, a meta-analysis of some 330 comparisons from 98 studies, was conducted in the mid-1980s by Richard A. Guzzo, associate professor of psychology at the University of Maryland, College Park, and his colleagues at New York University. The raw numbers seemed to suggest a positive relationship between financial incentives and productivity, but because of the huge variations from one study to another, statistical tests indicated that there was no significant effect overall. What’s more, financial incentives were virtually unrelated to the number of workers who were absent or who quit their jobs over a period of time. By contrast, training and goal-setting programs had a far greater impact on productivity than did pay-for-performance plans.

      Using the Approach in Counseling

      Counseling uses strength-based therapy as a way to introduce positive psychotherapy. The practitioner is focusing on the internal strengths, resourcefulness, and not as much on weaknesses, deficits, or failures (Basic Counseling Skills, n.d.).

      Doing so, helps the person build a mindset which helps to set their intention and focus on positive capacity building. As well as, understanding that they are resilient, and make more reasonable expectations not only of themselves but of others too (Basic Counseling Skills, n.d.).

      Strength-based therapy is a form of talk therapy where the client is the story-teller. The story can include traumas, pain, and any stressors (past or present). The practitioner guides the person to have the mindset of a survivor rather than a victim. Doing so gives the person understanding and control of the skills and strengths they possess (Basic Counseling Skills, n.d.).

      These skills and strengths enable them to survive and flourish no matter how tough life gets.

      How the Policy & Practice Principles Interact

      Table of Contents

      These three principles do not operate in isolation. In fact, they are highly interconnected and reinforce each other in multiple ways. First, progress on any of the three makes progress on the other two more likely. For example, reducing sources of stress makes it easier to access and use executive function and self-regulation skills it also frees up time and energy to participate in responsive interactions. Likewise, helping parents and caregivers improve executive functioning supports their ability to engage in serve-and-return interactions with the children in their care and to create a more stable and predictable caregiving environment.

      Using these design principles to promote positive change on all three dimensions is our best chance to help adults provide safe and responsive caregiving, and to help children get (and stay) on track for healthy development.

      Second, each individual’s functioning has important effects on every other member of the family. It creates a self-propelled cycle of benefits to all. For example, when an adult caregiver creates a calm, orderly, predictable environment, children are likely to experience less stress, which supports their healthy development. Children’s improved behavior in turn reduces stress for caregivers, providing a greater opportunity for the adults to continue to build their own self-regulation and executive function skills.

      Unfortunately, the converse is also true: significant challenges in any one of these areas can lead to problems in the others. Using these design principles to promote positive change on all three dimensions is our best chance to help adults provide safe and responsive caregiving, and to help children get (and stay) on track for healthy development.

      The Design Principles in Action

      Understanding major influences on child development and how adults develop and use core skills—as well as recognizing the effects of excessive stress on both—is critical for improving outcomes for individuals and all of society. Drawing on a common understanding of how healthy development can be either promoted or derailed, practitioners and policy-makers can think in new ways about how we can better support families raising young children and address the “upstream” sources of problems more effectively.

      Below are three suggestions for how policymakers, system leaders, and practitioners can apply these design principles in their own contexts.

      1. Question, assess, and improve current policies and operations. To what extent do current policies and operations promote (or hinder) responsive relationships and the development of core capabilities? To what extent do they diminish (or increase) sources of stress? What is preventing us from doing better? To find the answers to these questions, leaders might conduct a series of observations and conversations with front-line workers who are engaged personally with both children and adults. This is likely to produce important information about how things work now and suggestions for how they might work better in the future.
      2. Test proposed changes in policy or system operations. When changes to laws and/or regulations are proposed, they are commonly evaluated for their potential economic and budgetary impact. The three design principles in this paper provide an additional framework for analyzing such proposals. Compared to current operations, how might the proposed changes affect prospects for responsive relationships, for developing core capabilities in both adults and children, and for reducing sources of stress? Given those likely impacts, how strong is the case for (or against) the changes as currently envisioned? How might the proposals be modified in order to produce more positive effects and/or fewer negative consequences, particularly for families living in areas of concentrated poverty or dealing with systemic racism or other sources of intergenerational trauma?
      3. Use an organizing framework for developing new policies or program strategies. Sometimes assessments of and changes to current policies are not enough. Making use of what has been learned from observations and conversations with workers and clients, leaders might ask questions like: Suppose we want our system to do the best possible job of reducing the sources of significant stress experienced by caregivers, children and providers of early childhood services. How would we redesign the system to do that? What are the changes we might adopt soon to get started, and what are the larger and more complex changes that we might aim for over time? How might the system help the most overburdened and under-resourced families build their assets to stave off instability?

      Back to top

      Operant Conditioning Involves Choice

      Another thing to know about operant conditioning is that the response always requires choosing one behavior over others. The student who goes to the bar on Thursday night chooses to drink instead of staying at home and studying. The rat chooses to press the lever instead of sleeping or scratching its ear in the back of the box. The alternative behaviors are each associated with their own reinforcers. And the tendency to perform a particular action depends on both the reinforcers earned for it and the reinforcers earned for its alternatives.

      To investigate this idea, choice has been studied in the Skinner box by making two levers available for the rat (or two buttons available for the pigeon), each of which has its own reinforcement or payoff rate. A thorough study of choice in situations like this has led to a rule called the quantitative law of effect (see Herrnstein, 1970), which can be understood without going into quantitative detail: The law acknowledges the fact that the effects of reinforcing one behavior depend crucially on how much reinforcement is earned for the behavior’s alternatives. For example, if a pigeon learns that pecking one light will reward two food pellets, whereas the other light only rewards one, the pigeon will only peck the first light. However, what happens if the first light is more strenuous to reach than the second one? Will the cost of energy outweigh the bonus of food? Or will the extra food be worth the work? In general, a given reinforcer will be less reinforcing if there are many alternative reinforcers in the environment. For this reason, alcohol, sex, or drugs may be less powerful reinforcers if the person’s environment is full of other sources of reinforcement, such as achievement at work or love from family members.

      Bobo doll experiment

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      Bobo doll experiment, groundbreaking study on aggression led by psychologist Albert Bandura that demonstrated that children are able to learn through the observation of adult behaviour. The experiment was executed via a team of researchers who physically and verbally abused an inflatable doll in front of preschool-age children, which led the children to later mimic the behaviour of the adults by attacking the doll in the same fashion.

      Bandura’s study on aggression—the experiment for which he is perhaps best known—was carried out in 1961 at Stanford University, where Bandura was a professor. For this study he used 3- and 5-foot (1- and 1.5-metre) inflatable plastic toys called Bobo dolls, which were painted to look like cartoon clowns and were bottom-weighted so that they would return to an upright position when knocked down. The subjects were preschoolers at Stanford’s nursery school and were divided into three groups: one group observed aggressive adult behaviour models another group observed nonaggressive behaviour models and the third group was not exposed to any behaviour models.

      The three groups were then divided by gender into six subgroups in which half of the subgroups would observe a same-sex behaviour model and half would observe an opposite-sex behaviour model. In the first stage of the experiment, the children were individually seated at a table in one corner of an experimental room and presented with diverting activities that had previously been shown to be of high interest to the children (e.g., stickers, pictures, prints) in order to discourage active participation and encourage mere observation. The behaviour model was then taken to the opposite corner—which contained another table and chair, a mallet, a Tinkertoy set, and a 5-foot Bobo doll—and was told he or she could play with these materials. In the aggressive behaviour model groups, the model abused the Bobo doll both physically (e.g., kicked, punched, threw, and assaulted with various objects) and verbally (e.g., made aggressive statements such as “Sock him in the nose” and “Pow” or nonaggressive statements such as “He sure is a tough fella” and “He keeps coming back for more”). In the nonaggressive behaviour model groups, the model ignored the Bobo doll and instead quietly assembled the Tinkertoys. After 10 minutes had elapsed, the behaviour models in both groups left the room.

      In the second phase of the experiment, the children were taken individually into a different experimental room, where they were presented with a new group of appealing toys (e.g., train, fire engine, cable car, jet airplane, spinning top, doll with wardrobe, baby crib, and doll carriage). To test the hypothesis that the observation of aggression in others would increase the likelihood of aggression in the observer, the children were subjected to aggression arousal in the form of being told after two minutes that they could no longer play with the toys. The children were then told that they could, however, play with the toys in another room, where they were presented with various toys that were considered both aggressive (e.g., 3-foot Bobo doll, mallet, and dart guns) and nonaggressive (e.g., crayons, paper, farm animals, tea set, ball, and dolls).

      In the final stage of the experiment, the children’s behaviour was observed over the course of 20 minutes and rated according to the degree of physically and verbally aggressive behaviour they modeled, the results of which yielded significantly higher scores for children in the aggressive behaviour model groups compared with those in both the nonaggressive behaviour model and control groups. Subsequent experiments in which children were exposed to such violence on videotape yielded similar results, with nearly 90 percent of the children in the aggressive behaviour groups later modeling the adults’ behaviour by attacking the doll in the same fashion and 40 percent of the those children exhibiting the same behaviour after eight months.

      Although the study yielded similar results for both genders, it nonetheless suggested at least some difference depending on the degree to which a behaviour is sex-typed—that is, viewed as more common of or appropriate for a specific gender. For example, the data suggest that males are somewhat more prone to imitate physical aggression—a highly masculine-typed behaviour—than are females, with male subjects reproducing more physical aggression than female subjects there were, however, no differences in the imitation of verbal aggression, which is less sex-typed. Additionally, both male and female subjects were more imitative of the male behaviour models than of the female models in terms of physical aggression but were more imitative of the same-sex models in terms of verbal aggression.