Student Nature, Part IV: Bibliography

As with the bibliography for Learning Evolved, the citations are close to APA Style. Entries starting with “A” are above the fold, and the rest are below

Albanese, Robert, & van Fleet, David D. (1985). Rational Behavior in Groups: The Free-Riding Tendency. The Academy of Management Review 10(2):244-255.
Alford, J., Funk, C., & Hibbing, J. (2005) Are Political Orientations Genetically Transmitted? American Political Science Review, 99(2), 154-168.
Alford, J. & Hibbing, J. (2004) .The Origin of Politics: An Evolutionary Theory of Political Behavior. Perspectives on Politics, 2(4), 707-723
Alford, J., & Hibbing, J. (2006). Could Political Attitudes Be Shaped by Evolution Working Through Genes? Tidsskriftet Politik: August 2006 edition.
Allen, Joseph P., et al. (2005). The Two Faces of Adolescents’ Success with Peers: Adolescent Popularity, Social Adaption, and Deviant Behavior. Child Development 76(3):747-.760.
Atran, Scott. (2003). Genesis of Suicide Terrorism. Science 299:1534-1539.


Barker, L. (2002). Teaching the Learning Course: Philosophy and Methods, in The Teaching of Psychology: Essays in Honor of Wilbert J. McKeachie and Charles L. Brewer, 379-393.
Baron-Cohen, Simon. (2006). A Political System Based on Empathy. Edge: The World Question Center. Available online: http://www.edge.org/q2006/q06_4.html#baroncohen.
Beins, B.C. (2002). Technology in the classroom: Traditions in psychology. In S. Davis & W.Buskist (Eds.). The teaching of psychology: Essays in honor of William J. McKeachie and Charles Brewer. Mahwah, NJ: Lawrence Erlbaum Associates, Inc. (pp. 307-321)
Benton, Stephen L., & Kiewra, Kenneth A. (1986). Measuring the Organizational Aspects of Writing Ability. Journal of Educational Measurement 23(4): 377-386.
Biggs, John (1999). Enriching Large-Class Teaching in Teaching for Quality Learning at University. Philadelphia, PA; Open University Press.
Bloom, Howard. (2000). Global Brain. Wiley & Sons: New York, NY.
Bower, B. (2006). The Bias Finders: A Test of Unconscious Attitudes Polarizes Psychologists. Science News, 169(16), 250.
Boyd, R., Gintis, H., Bowles, S., & Richardson, P. (2003) “The Evolution of Altruistic Punishment,” Proceedings of the National Academy of Sciences of the United States of America, 18 March 2003, 100(4), 3531-3535.
Buller, D.J. (2005). Adapting Minds. MIT Press: Cambridge, MA.
Camerer, C., Loewenstein, G., and Prelec, D. (2005). Neuroeconomics: How Neuroscience Can Inform Economics. Journal of Economic Literature, 43(1), 9-64.
Capsi, A., et al. (2003). Influence of Life Stress on Depression: Moderation by a Polymorphism in the 5-HTT Gene. Science. Vol. 301 No. 5631 pp. 386-289.
Carmen, I. (2006). Genetic Configurations of Political Phenomena: New Theories, New Methods. Paper presented at the Hendricks Conference on Biology, Evolution, and Political Behavior.
Castellanos, F.X., et al. (1998) Lack of an association between a dopamine-4 receptor polymorphism and attention-deficit/hyperactivity disorder: genetic and brain morphometric analyses. Molecular Psychiatry 3(5):431-434.
Craemer, Thomas. (2006). Evolutionary Model of Racial Attitude Formation Socially Shared and Idiosyncratic Racial Attitudes. Paper presented at the Hendricks Conference on Biology, Evolution, and Political Behavior.
Ding, Y., et al. (2002). Evidence of positive selection acting at the human dopamine receptor D4 gene locus. PNAS, 99(1) 309-314.
Driver, R., et al. (1994). Constructing Scientific Knowledge in the Classroom. Educational Researcher 23, 5-12.
Elkind, David. (1997) All Grown Up and No Place to Go. Perseus Books Group: New York, NY.
Fadok, D.S., Boyd, J., & Warden, J. (1995). Air Power’s Quest for Strategic Paralysis. Maxwell Air Force Base AL: Air University Press
Fass, Paula. (1989). Testing the IQ of Children. In Outside In: Minorities and the Transformation of American Education. Oxford University Press: New York, NY.
Fehr, E., & Gachter, S. (2000). “Cooperation and Punishment in Public Goods Experiments,” The American Economic Review, September 2000, Vol 90 No 4, 980-994.
Fels, Rendigs. (1993). This is what I do, and I like it. The Journal of Economic Education 24(4):365-370.
Fowler, J. (2006). Altruism and Turnout, The Journal of Politics, Vol. 68 No. 3, pp 674-683.
Gardner, H. (1983). Multiple Intelligences. Basic Books: New York, NY.
Gardner, H. (2003). Multiple Intelligences After Twenty Years. Paper presented at the American Educational Research Association.
Gould, Stephen J. (2000). More Things in Heaven and Earth. In H. Rose and S. Rose (Eds.) Alas, Poor Darwin: Arguments Against Evolutionary Psychology. Harmony: New York, NY.
Grady, D.L., et al. (2003). High prevalence of rare dopamine receptor D4 alleles in children diagnosed with attention-deficit hyperactivity disorder. Molecular Psychiatry 8(5):536-545.
Hammond, R., & Axelrod, R. (2006) The Evolution of Ethnocentricism. Journal of Conflict Resolution, 50(6).
Harpending, H., & Cochran, G. (2002) In Our Genes. PNAS, 99(1), 10-12.
Henrich, Joseph, et al. (2001). In Search of Homo Economicus: Behavioral Experiments in 15 Small-Scale Societies. American Economic Review 91(2):73-78.
Hoffman, Donald. (2006). A Spoon is Like a Headache. Edge: The World Question Center. Online: http://www.edge.org/q2006/q06_3.html#hoffman.
Huddy, Leonie, Feldman, Stanley, & Weber, Christopher. (2006). The Political Consequences of Perceived Threat and Felt Insecurity. Paper presented at the Hendricks Conference on Biology, Evolution, and Political Behavior.
Hursh, B. A. & Borzak, L. (1979). Toward Cognitive Development through Field Studies. The Journal of Higher Education 50, 63-78.
Igo, L. Brent, Kiewra, Kenneth A., & Bruning, Roger. (2004). Removing the Snare from the Pair: Using Pictures to Learn Confusing Words. Journal of Experimental Education 72(3):165-178.
Jervis, R. (2004). The Implications of Prospect Theory for Human Nature and Values. Political Psychology, 25(2), 163-176.
Johnson, Paul. E. (2006). Ecological Analysis of a System of Organized Interests. Paper presented at the Hendricks Conference on Biology, Evolution, and Political Behavior.
Kurzban, R., & DeScioli, P. (2005) “Characterizing reciprocity in groups: Information-seeking in a public goods game,” (Submitted), alternate draft at http://www.psych.upenn.edu/~descioli/kurzban%20descioli%20pgi%207%2012%2006.pdf.
Kurzban, Robert, & Houser, Daniel. (2005). Experiments Investigation Cooperative Types in Humans: A Complement to Evolutinoary Theory and Simulations. PNAS 102(5): 1803-1807.
Leuthold, Jane H. (1993). A Free Rider Experiment for the Large Class. The Journal of Economic Education 24(4):353-363.
Lieberman, M., Schreiber, D., & Ochsner, K. (2003). Is Political Cognition Like Riding a Bicycle: How Cognitive Neuroscience Can Inform Research on Political Thinking. Political Psychology, 2003, 24(4), 681-704.
Lisska, A.J.(1996). Teaching through the curriculum: The development of a comprehensive honors program. In J.K. Roth (Ed.) Inspiring Teaching: Carnegie Professors of the Year Speak. Bolton, MA: Anker Publishing Company, Inc. (pp. 90-99).
London, Jack. (1903). The Call of the Wild. Available online: http://en.wikisource.org/wiki/The_Call_of_the_Wild_%28London%29.
Lupia, A., & Menng, J. (2006). When Can Politicians Scare Citizens Into Supporting Bad Policies? A Theory of Incentives With Fear Based Content. Paper presented at the Hendricks Conference on Biology, Evolution, and Political Behavior.
Lynn, D.E., et al. (2005). Temperament and Character Profiles and the Dopamine D4 Receptor Gene in ADHD. The American Journal of Psychiatry 162:906-913.
Maalouf, Amin. (2003). In the Name of Identity: Violence and the Need to Belong (reprint edition). New York, NY: Penguin Group.
Marklein, M. B. (2005). College gender gap widens: 57% are women. USA Today. March 28, 2005 edition.
McCrudden, Matthew, Schraw, Gregory, Kendall, Hartley, & Kiewra, Kenneth A. (2004). The Influence of Presentation, Organization, and Example Context on Text Learning. Journal of Experimental Education 72(4):289-306.
McDermott, R. (2004) The Feeling of Rationality, The Meaning of Neuroscientific Advances for Political Science. Perspectives on Politics 2(4), 691-706,
McDermott, R. (2006). Testosterone, Cortisol, and Aggression in a Simulated Crisis Game. Paper presented at the Hendricks Conference on Biology, Evolution, and Political Behavior.
Meilinger, Phillip S. (2000). The Historiography of Airpower: Theory and Doctrine. The Journal of Military History 62(2):467-501.
Moffat, J. (2000). Representing the Command and Control Process in Simulation Models of Conflict. The Journal of the Operational Research Society 51(4):431-439.
Morgan, Michael. (2001). Fruity Genes. The Guardian. Available online: http://www.guardian.co.uk/Archive/Article/0,4273,4156478,00.html.
Morris, J., Squires, N., Taber, C., & Lodge, M. (2003). “The Automatic Activation of Political Attitudes: A Psychophysiological Examination of the Hot Cognition Hypothesis,” Political Psychology, 24, 727.
Morrisey, Kathleen, & Werner-Wilson, Ronald. (2005). The relationship between out-of-school activities and positive youth development: an investigation of the influences of communities and family. Adolescence 40(157):67-85.
Moshman, David. (2005). Adolescent Psychological Development (2nd ed.). Mahwah, NJ: Lawrence Erlbaum Associates.
Mutz, Diana C. (2006). Effects of “In-Your-Face” Television Discourse on Perceptions of a Legitimate Opposition. Paper presented at the Hendricks Conference on Biology, Evolution, and Political Behavior.
Olson, I., & Mashuetz, C. (2003). Facial Attractiveness is Appraised at a Glance. Emotion. 5(4), 498-502.
Pinker, S. (2002). The Blank Slate: The Modern Denial of Human Nature. Viking Adult: New York, NY.
Pinker, S. (2006). Groups of People May Differ Genetically in their Average Talents and Temperaments. Edge: The World Question Center. Available online: http://www.edge.org/q2006/q06_3.html#pinker.
Raskin, Robin. (2005). Neartly sixty years later the world’s first programmers are still doing gender battles. WITI Women, March 2005 edition.
Ridley, M. (2003). Nature via Nurture. Harper Collins: New York, NY.
Rockman, Matthew V., et al. (2005). Ancient and Recent Positive Selection Transformed Opioid cis-Regulation in Humans. PLoS Biology 3(12).
Sanfey, A., et al. (2003). The Neural Basis of Economic Decision-Making in the Ultimatum Game, Science, 300(5626), 1755-1758.
Sapolsky, R. (2006) A Natural History of Peace. Foreign Affairs. 85(1).
Sautter, John A. (2006). Empathy and Collective Action in the Prisoner’s Dilemma. Paper presented at the Hendricks Conference on Biology, Evolution, and Political Behavior.
Schraw, Gregory, & Bruning, Roger. (1996). Readers’ Implicit Models of Reading. Reading Research Quality 31(3):290-305.
Shergill, Sukhwinder, et al. (2003) Two Eyes for an Eye: The Neuroscience of Force Escalation. Science 301:187.
Singer, T., et al. (2006). Empathetic Neural Responses are Modulated by the Perceived Fairness of Others. Nature, 439(26).
Singh, Devendra. (1993) Adaptive Significance of Female Attractiveness: Role of Waist-to-Hip Ratio: Journal of Personality and Social Psychology 65(2):293-307.
Slavin, Robert E. (1996). Research on Cooperative Learning and Achievement: What We Know, What We Need to Know. Contemporary Educational Psychology 21(1):43-69.
Slavin, Robert E. (1999). Comprehensive Approaches to Cooperative Learning. Theory into Practice 38(2):74-79.
Smirnov, O., Arrow, H., Kennet, D., & Orbell, J. (2006). ‘Heroism’ in Warfare. Paper presented at the Hendricks Conference on Biology, Evolution, and Political Behavior.
Smith, K. (2006) Representational Altruism: The Wary Cooperator as Authoritative Decision Maker. American Journal of Political Science, Vol. 50 No. 4, pp 1013-1022.
Smith, K., et al. (2004). Evolutionary Theory and Political Leadership: Why Certain People Do Not Trust Decision-Makers. Paper Presented at the 2004 Midwest Political Science Association Conference in Chicago, 1-42.
Smith, M.L.R. (1999). The Intellectual Internment of a Conflict: The Forgotten War in Northern Ireland. International Affairs (Royal Institute of International Affairs 1944-) 75(1):77-97.
Spezio, M., & Adolphs, S. Emotional Processing and Political Judgement: Toward Integrating Political Psychology and Decision Neuroscience. Unpublished Manuscript. Available Online: http://www.uiowa.edu/~c030111/decisionmaking/grad2005/spezio.pdf.
Steinberg, L. (2001). We Know Some Things: Parent-Adolescent Relationship in Retrospect and Prospect. Journal of Research on Adolescence 11(1):1-19.
Steinberg, L., & Morris, A. (2001) Adolescent Development. Annual Review of Psychology, 52, 83-110..
Sullivan, P.F., et al. (1998). No Association Between Novelty Seeking and the Type 4 Dopamine Receptor Gene (DRD4) in Two New Zealand Samples. The American Journal of Psychiatry 155:98-101.
Talbot, Colin. (2003). How the Public Sector Got its Contradictions – The Tale of the Paradoxical Primate. Integrating the Idea of Paradox in Human Social, Political and Organisational Systems with Evolutionary Psychology. Human Nature Review 3:189-195.
Taylor, M.C. (1996). Creating global classrooms. In J.K. Roth (Ed.) Inspiring Teaching: Carnegie Professors of the Year Speak. Bolton, MA: Anker Publishing Company, Inc. (pp. 134-145).
Tooby, J., & Cosmides, L. (1992) The Psychological Foundations of Culture. In The Adapted Mind, Jerome Barkow, Leda Cosmides and John Tooby, eds. New York: Oxford University Pres.
von Lubitz, Dag K.J.E., Carrasco, Benjamin, Levine, Howard, & Richir, Simon. Medical Readiness in the Context of Operations Other Than War: Development of First Responder Readiness Using OODA_Loop Thinking and Advanced Distributed Interactive Simulation Technology. Paper presented at Empispher conference on Best Practice in Real-time Telemedicine.
Wade, Nicholas. (2006). Still Evolving, Human Genes Tell New Story. New York Times. March 7, 2006 edition.
Weisberg, Robert W. (1993). Creativity: Beyond the Myth of Genius. W.H. Freeman & Company: New York, NY.
Wilson, E. O., & Holldobler, B. (2005). Eusociality: Origin and Consequences. PNAS 102(38)-13367-13371.
Wrangham, R. (1999). Evolution of Coalitionary Killing. Yearbook of Anthropology 42:1-30.
Yandell, Lonnie. (2002) Web-based resources. In S. Davis & W.Buskist (Eds.). The teaching of psychology: Essays in honor of William J. McKeachie and Charles Brewer. Mahwah, NJ: Lawrence Erlbaum Associates, Inc. (pp. 295-305).
Zubizarreta, J. (1996). Improving teaching through teaching portfolio revisions: A context and case for reflective practice. In J.K. Roth (Ed.) Inspiring Teaching: Carnegie Professors of the Year Speak. Bolton, MA: Anker Publishing Company, Inc. (pp. 123-133).


Student Nature, a companion series to Learning Evolved
1. The Nature of the Student
2. The Natures of Our Students
3. Nature and Her Consequences
4. Bibliography

The Future is Coming On

The band “Gorrillaz” being their song “Clint Eastwood” with the following two verses:

Hey, I’m happy, I’m feeling glad,
I got sunshine in a bag.
I’m useless but not for long:
the future is coming on.

Finally, someone let me out of my cage.
Now, time for me is nothin’ ’cause I’m counting no age.
Nah, I couldn’t be there. Now you shouldn’t be scared.
I’m good at repairs and I’m under each snare.
Intangible, bet you didn’t think so,
I command you to, panoramic view:
look I’ll make it all manageable.
Pick and choose, sit and lose.

All you different crews,
chicks and dudes, who you think is really kicking tunes?

Earlier, I compared the narrator of the song to the Shia militias in Iraq.

neither_shall_they_be_caged

In particularly, I highlithed four main similarities

  1. Current US policy makes Iraqi democratic built on the demographic majority of the nation into enemies, instead of friends
  2. Current US policy is unsustainable, and America will inevitable embarece their naturla friends, the Shia (Iraqi) militias
  3. The Shia Iraqi Militias form the spine of the natural SysAdmin reconstruction force in Iraq
  4. The Shia Iraqi Militais have the ability to defeat our enemies, the Baathists and the Qaedists
  5. Defeat can only come from recognizing our natural alliance with the Shia militias.

Yet another story in the New York Times confirms my initial judgements:

American forces have already shifted some forces to new high-violence sectors and may make further adjustments. Shrinking the military zone controlled by the American Baghdad-based division, which now extends south to the cities of Najaf and Karbala, has also been discussed as a way to increase the density of American troops in the capital.

Erecting more barricades to section off parts of the city has been proposed by some officers. So has legitimizing some neighborhood watch [“militia” — tdaxp] organizations. That idea cuts against the policy to abolish militias but has been advocated by some military officials as a useful expedient.

We will win. So will the Iraqi people. The good guys will kill the bad guys.

The only losers are the Iraqi Sunni Arabs. We fought for three years to save them for the fate they, like the extrainsular Japanese and the European Germans, sowed.

Student Nature, Part III: Nature and Her Consequences

This series doe not argue that only genes matter. The emergent rules of complex systems (Bloom, 2000; Johnson, 2006, 2), in addition to more mundane matters such as instructional processes (Beins, 2002, 308; Fels, 1993, 365; Zubizarreta, 1996, 126), detailed syllabi (Barker, 2002, 382), and perhaps classroom size (Lisska, 1996, 93), effect education and classroom enjoyment in obvious ways. Still, genes interact with the environment, so both are important to educators. Just as series life decisions are correlated with an interaction between environment and genes (Capsi, 2003, 386), so education is as well. Next I outline how our genetic heritages should effect how we teach. Controversy should not keep us from the truth. A highly successful method of peer teaching, Cooperative Learning (see, for example, Slavin, 1999, 74)), is often not used because of aversion to the use of rewards that are external to the student (Slavin, 1996). Similarly, if genetic knowledge is ignored because it does not fit our pre-existing biases, shame on us.

Rationality may be overrated. Lieberman, Schreiber, and Ochsner noted that “”Because behavior is often driven by automatic mechanisms, self-reports of mental processes are notoriously unreliable and susceptible to many forms of contamination” (2003, 682). Yet many texts argue that reflection and self-reports are valuable tools (Moshman, 2005, 43) instead of dubious, context-specific guesswork (see, for example, Bower, 2006; Kurzban & DeScioli, 2005, 20-21). For instance, when asked to give as much force as they received, subjects will inadvertently hit harder than they were hit because of evolved quirks in our nervous system (Shergill, 2003, 187). This is because, literally, people do not know what they are doing. Further, people put much more value on losses than gains of equal magnitude, when logically there is no reason to do other than emotional predisposition (Jervis, 2004, 165-167). The emotional system is tied up with the logical thinking in the brain (McDermott, 2004, 693; Spezio & Adolphs, 13) so much so that “those who were instructed to think of reasons why they liked or disliked [a chose made in an experiment] ended up, on average, less happy with their choice… than subjects who were not asked to provide reasons” (Camerer, Lowenstein, and Prelec, 2003, 23). Does this call rational discourse into any doubt?


Likewise, group deliberations must be rethought. Constructed group identities lead to conflict (Maalouf, 2003, 21) because xenophobia and ethnocentricism are often genetically adaptive (Hammond & Axelrod, 2006, 10). Though it is clearly possible to reduce actual conflicts (Sapolsky, 2004), group aggression is a function of environment and genes, after all, the capacity for violence is in our genes. What to do with this? What to do with the fact that fear seems conducive to learning (Lupia & Menng, 2006, 3-4,7). We get nowhere if we do not ask.

Politics, too may be a concern. The finding that people like those who have similar attitudes to themselves (Mutz, 2006, 8) immediately strikes us as a problem for socialization, but learning that not only attitudes but also, and seperately (Alford & Hibbing, 2006, 13), political beliefs (Alford & Hibbing, 2004) are generally heritable shows us that socialization may have limits. Compound this with the historical politicalization of education (Fass, 307) as well as that differences are as conflicting as they are “enriching” (Taylor, 1996, 137), or even a world where terrorism is positively correlated with educational achievement (Atran, 2003, 1536) and you have a recipe for trouble.

In other papers, for other classes, I have argued for deliberative proceedings and group work. I believe these are effective tools and that student empowerment is vital for proper classroom education. I also believe that evolutionary theory and population genetics will give us educators important clues about how to best teach our students, whatever their age. But if we shirk from hard work because we are uncomfortable with some of the possibilities, or retreat with disgust as the questions raised we are like a farmer who, too lazy to reach his hands high, never picks the tastiest fruit.


Student Nature, a companion series to Learning Evolved
1. The Nature of the Student
2. The Natures of Our Students
3. Nature and Her Consequences
4. Bibliography

Quick & Dirty Literature Review on Students with Learning Disabilities

Like my q&d lit review for the ultimatum game, this post is for my own benefit. If you want something actually interesting dealing with learning, read “Nature and Her Consequences” (part of my series on student nature), or Mark of ZenPundit‘s “Horizontal Thinking at Cooperative Commons” (which links to “Remember Lateral Thinking?). Or even check out my older series on learning — Classroom Democracy, Learning Evolved, and Liberal Education.


Identifying learning disabled students have been troublesome (Rechly, 1996; Scruggs & Mastropieri, 2002), as have been identifying learning-disabled adults (Adelman & Vogel, 1993, 227). Learning disabled students appear to be cluster into language-defecit, visual-deficit, reading-deficit, behavioral-deficit, and unknown defecits (Bender & Golearning disableden, 1990).
Teachers judge high-achieving students, with or without learning disabilities, positively while they view low-performing learnig disabled students less favorably than low-performing, non-learning-disabled students (Meltzer, & Katzir-Cohen, Miller, & Roditi, 2001) though this does not negatively effect l-d social confidence more than that for n-learning disableds (Vaughn & Haager, 1994) . Low-performing learning disabled students also face disproportionate social problems (Nowicki, 2003), though generally l-d boys do not have less friends than non-l-d boys (Bear, Juvonen, & McInerney, 1993). Low-performers are also associated with depression and suicide (Bender, Rosenkrans, & Crane, 1999).
Categorization of teacher-l-d interaction is complex but predictable (Cook, 2004). Likewise, perceived preperation of teachers appears to very, with some classes of teacherse feeling prepared (Guay, 1994) and others believing they are skill enough to adjust cirrcula to meet l-d’s needs (Simmons, Kameenui, & Chard, 1998). Interestingly, teacher preference and peer social status appear to be highly correlated (Garrett & Crump, 1980), perhaps as a result of widespread teacher ignorance of the best strategies in educating l-ds (Scruggs & Mastropieri, 1994).
Students with l-d may, especially, in writing, have more self-efficacy than they have skill (Klassen, 2002).
Interestingly, a student’s perception of acceptence by peers correlates with depression only for the learning disabled (Heath & Wiener, 1996).
Still, l-ds generally have more classroom behavior problems than nl-d students (Bender & Golearning disableden, 1988). Some of this may be due to the presense of ADHD in many l-d students (Tabassam & Grainger, 2002; Wiener, 1998).
While milearning disabledly learning disabled students tend to be more isolated than average students, generally mixing does occur: prosocial learning disabled students have prosocial peers, while antisocial learning disablede students have antisocial peers (Pearl et al., 1998). This isolation may involve the fact that l-d students perceive themselves to be less skillful than their peers, while most Children have an exagerated sense of their own skills (Scarpati, Malloy, & Fleming, 1996).
Perceptions of students have been judged through questionaires (Conderman, 1995). This reveals that beliefs about learning disabled students change with exposure (Kavale & Reese, 1991)
Asking learning-disabled adults to define learning-disable students has been done before (Reiff, Gerber, & Ginsberg, 1993).
More and more learning-disabled students are attending college (Stage & Milne, 1996) and the transition from dependency to independence, of which college is a part, has recently come into focus (Reiff & deFur, 1992). It is possible that the effect learning disabilities increases as time goes on (Bender & Wall, 1994). Students with learning disabilities looking for their first professional job, especially women, are likely to be more indecivie and have lower aspirations (Rojewski, 1996).
Perhaps a better way to view learning disability is as a risk factor, whose effect depends entirely on its interaction with other factors (Morrison & Cosden, 1997). A somber argument against this, however, is that “no intervention has been designed that eliminates the impact of having a disability” (Hocutt, 1996, 77) — a feat which shoulearning disabled be possible if l-d only acts as an interaction effect.
These findings are combined in exciting research that shows that l-ds in college view themselves as more socially accepted than non-l-ds (Cosden & McNamara, 1997) and display higher levels of resilience (Hall, Spruill, & Webster, 2002). Collegiate l-ds are as smart or smarter than the general population, though, which implies low-functioning l-ds may be selecting themselves out (Hughes & Smith, 1990).
Rojewksi states that students “with learning disabilities shoulearning disabled be prepared to deal with chance events and encounters in a purposeful and proactive manner” (1999, 274). The feasibility of this is problematic, however, as social interaction training seems to be only modestly useful (Forness & Kavale, 1996). Explicit problem-solving strategies were used less by learning disabled students than average students or gifted students (Montague & Applegate, 2000).
The effects of modular cognition is unclear. Learning-disability happens in specific domains, and is not global unless it actually occurs in all of the domains (Lyon, 1996). For instance, students who believe that their learning disability is limited in scope do better than those who believe it is nonchanging and global (Rothman & Cosden, 1996). However, a recognition of internal modularity — ascribing success to “luck, intense hard work, well-developed social skills, and perception” can be described as the “imposter syndrome” and can be viewed negatively (Shessel & Reiff, 1999, 312). Transition programs which focus on specific skills, rather than the more domain-general class of all students with -learning disabled, more adequately address the real need (Phelps & Hanley-Maxwell, 1997; Rojewski, 1992). On a more theoretical matter, than understanding of one’s own disability effects school competence but not global self estteem (Cosden, Elliot, Noble, & Kelemen, 1999) makes sene, as competence relates to practice while esteem relates to language,
Place matters for l-ds. Both state and region effects the school services that l-ds receive (McKenzie, 1991).
Peer teaching (Mastropieri, Scruggs, & Graetz, 2003) and assistance are effective processes for increasing learning comprehension among l-d students (Mastropieri & Scruggs, 2001) .
Computerized interaction between Children, both l-d and nl-d, has been studied before (Jellison, 2002).

Adelman, P.B. & Vogel, S.A. (1993). Issues in the Employment of Adults with Learning Disabilities. Learning Disability Quarterly 16(3): 219-232.
Bear, G.G., Juvonen, J., & McInerney, F. (1993). Self-Perceptions and Peer Relations of Boys with and Boys without Learning Disabilities in an Integrated Setting: A Longitudinal Study. Learning Disability Quarterly 16(2): 127-136.
Bender, W.N. & Golearning disableden, L.B. (1988). Adaptive Behavior of Learning Disabled and Non-Learning Disabled Children. Learning Disability Quarterly 11(1): 55-61.
Bender, W.N. & Golearning disableden, L.B. (1990). Subtypes of Students with Learning Disabilities as Derived from Cognitive, Academic, Behavioral, and Self-Concept Measures. Learning Disability Quarterly 13(3): 183-194.
Bender, W.N., Rosenkrans, C.B., & Crane, M. (1999). Stress, Depression, and Suicide among Students with Learning Disabilities: Assessing the Risk. Learning Disability Quarterly 22(2): 143-156.
Bender, W.N. & Wall, M.E. (1994). Social-Emotional Development of Students with Learning Disabilities. Learning Disability Quarterly 17(4): 323-341.
Conderman, G. (1995). Social Status of Sixth- and Seventh-Grade Students with Learnign Disabilities. Learning Disability Quarterly 18(1): 13-24.
Cook, B.G. (2004). Inclusive Teachers’ Attitudes toward Their Students with Disabilities: A Replication and Extension. The Elementary School Journal 104(4): 307-320.
Cosden, M., Elliot, K., Noble, S., & Kelemen, E. (1999). Self-Understanding and Self-Esteem in Children with Learning Disabilities. Learning Disability Quarterly 22(4): 279-290.
Cosden, M.A. & McNamara, J. (1997). Self-Concept and Perceived Social Support among College Students with and without Learning Disabilities. Learning Disability Quarterly 20(1): 2-12.
Forness, S.R. & Kavale, K.A. (1996). Treating Social Skill Deficits in Children with Learning Disabilities: A Meta-Analysis of the Research. Learning Disability Quarterly 19(1): 2-13.
Garrett, M.K. & Crump, W.D. (1980). Peer Acceptance, Teacher Preference, and Self-Appraisal of Social Status among Learning Disabled Students. Learning Disability Quarterly 3(#): 42-48.
Guay, D.M. (1994). Students with Disabilities in the Art Classroom: How Prepared Are We?. Studies in Art Education 36(1): 44-56.
Hall, C.W., Spruill, K.L., & Webster. R. E. (2002). Motivational and Attitudinal Factors in College Students with and without Learning Disabilities. Learning Disability Quarterly 25(2): 79-86.
Heath, N.L. & Wiener, J. (1996). Depression and Nonacademic Self-Perceptions in Children with and without Learning Disabilities. Learning Disability Quarterly 19(1): 34-44.
Hocutt, A.M. (1996). Effectiveness of Special Education: Is Placement the Critical Factor?. The Future of Children 6(1): 77-102.
Hughes, C.A. & Smith, J.O. (1990). Cognitive and Academic Performance of College Students with Learning Disabilities: A Synthesis of the Literature. Learning Disability Quarterly 13(1): 66-79.
Jellison, J.A. (2002). On-Task Participation of Typical Students Close to and Away from Classmates with Disabilities in an Elementary Music Classroom. Journal of Research in Music Education 50(4): 343-355.
Kavale, K.A. & Reese. J.H. (1991). Teacher Beliefs and Perceptions about Learning Disabilities: A Survey of Iowa Practitioners. Learning Disability Quarterly 14(2): 141-160.
Klassen, R. (2002). A Question of Calibration: A Review of the Self-Efficacy Beliefs of Students with Learning Disabilities. Learning Disability Quarterly 25(2): 88-102.
Lyon, G.R. (1996). Learning Disabilities. The Future of Children 6(1): 54-76.
Mastropieri, M.A. & Scruggs, T.E. (2001). Promoting Inclusion in Secondary Classrooms. Learning Disability Quarterly 24(4): 265-274.
Mastropieri, M.A., Scruggs, T.E., & Graetz, J.E. (2003). Reading Comprehension Instruction for Secondary Students: Challenges for Struggling Students and Teachers”>. Learning Disability Quarterly 26(2): 103-116.
McKenzie, R.G. (1991). Content Area Instruction Delivered by Secondary Learning Disabilities Teachers: A National Survey. Learning Disability Quarterly 14(2): 115-122.
Meltzer, L., Katzir-Cohen, T., Miller, L., & Roditi, B. (2001). The Impact of Effort and Strategy Use on Academic Performance: Student and Teacher Perceptions. Learning Disability Quarterly 24(2): 85-98.
Montague, M. & Applegate, B. (2000). Middle School Students’ Perceptions, Persistence, and Performance in Mathematical Problem Solving. Learning Disability Quarterly 23(3): 215-227.
Morrison, G.M. & Cosden, M.A. (1997). Risk, Resilience, and Adjustment of Individuals with Learning Disabilities. Learning Disability Quarterly 20(1): 43-60.
Nowicki, E.A. (2003). A Meta-Analysis of the Social Competence of Children with Learning Disabilities Compared to Classmates of Low and Average to High Achievement. Learning Disability Quarterly 26(3): 171-188.
Pearl, R., et al. (1998). The Social Integration of Students with Milearning disabled Disabilities in General Education Classrooms: Peer Group Membership and Peer-Assessed Social Behavior. The Elementary School Journal 99(2): 167-185.
Phelps, L.A. & Hanley-Maxwell, C. (1997). School-to-Work Transitions for Youth with Disabilities: A Review of Outcomes and Practices. Review of Educational Research 67(2): 197-226.
Reiff, H.B. & deFur, S. (1992). Definitions of Learning Disabilities from Adults with Learning Disabilities: The Insiders’ Perspectives. Learning Disability Quarterly 16(2): 114-125.
Reschly, D.J. (1996). Identification and Assessment of Students with Disabilities. The Future of Children 6(1): 40-53.
Rojewski, J.W. (1992). Key Components of Model Transition Services for Students with Learning Disabilities. Learning Disability Quarterly 15(2): 135-150.
Rojewski, J.W. (1996). Occupational Aspirations and Early Career-Choice Patterns of Adolescents with and without Learning Disabilities. Learning Disability Quarterly 19(2): 99-116.
Rojewski, J.W. (1999). The Role of Chance in the Career Development of Individuals with Learning Disabilities Learning Disability Quarterly 22(4): 257-278.
Rothman, H.R. & Cosden, M. (1995). The Relationship between Self-Perception of a Learning Disability and Achievement, Self-Concept and Social Support. Learning Disability Quarterly 18(3): 203-212.
Scarpati, S., Malloy, T.E., & Fleming, R. (1996). Interpersonal Perception of Skill Efficacy and Behavioral Control of Adolescents with Learning Disabilities: A Social Relations Approach. Learning Disability Quarterly 19(1): 15-22.
Scruggs, T.E. & Mastropieri, M.A. (1994). Successful Mainstreaming in Elementary Science Classes: A Qualitative Study of Three Reputational Cases. American Educational Research Journal 31(4): 785-811.
Scruggs, T.E. & Mastropieri, M.A. (2002). On Babies and Bathwater: Addressing the Problems of Identification of Learning Disabilities. Learning Disability Quarterly 25(3): 155-168.
Shessel, I. & Reiff, H.B. (1999). Experiences of Adults with Learning Disabilities: Positive and Negative Impacts and Outcomes. Learning Disability Quarterly 22(4): 305-316.
Simmons, D.C., Kameenui, E.J., & Chard, D.J. (1998). General Education Teachers’ Assumptions about Learning and Students with Learning Disabilities: Design-of-Instruction Analysis. Learning Disability Quarterly 21(1): 6-21.
Stage, F.K. & Milne, N.V. (1996). Invisible Scholars: Students with Learning Disabilities. The Journal of Higher Education 67(4): 426-445.
Tabassam, W., & Grainger, J. (2002). Self-Concept, Attributional Style and Self-Efficacy Beliefs of Students with Learning Disabilities with and without Attention Deficit Hyperactivity Disorder. Learning Disability Quarterly 25(2): 141-151.
Vaughn, S. & Haager, D. (1994). Social Competence as a Multifaceted Construct: How Do Students with Learning Disabilities Fare?. Learning Disability Quarterly 17(4): 253-266.
Weiner, J. (1998). The Psychiatric Morbidity Hypothesis: A Response to San Miguel, Forness, and Kavale. Learning Disability Quarterly 21(3): 195-201.

Eschewing Omaha; Avoiding 680

Visited South Dakota, and (taking a cue from Father of tdaxp) avoided the I-80/I-680/I-229 hubbub in Nebraska and Omaha by traveling from Lincoln to Sioux City on beautiful U.S. Route 77


And On to the Coyote State!

While writing this short post I came across a website dedicated to the history of the U.S. (non-Interstate) Highway System. The history of the highway sign and the Highway 60 66 Controversy. Check it out.

Student Nature, Part II: The Natures of Our Students

Humans vary by sex, and not just in the preferred hip-to-waist ratio (Singh, 1993, 293). Firing the President of Harvard for wondering if this is true does not make facts go away (Pinker, 2006). Men are less empathetic than women (Baron-Cohen 2006; Singer et al., 266, 2006). Emotional differences between the sexes are widely recognized, even by critics of evolutionary psychology (see, for example, Buller, 2005, 317).

It is strange that genetic factors are controversial while environmental factors are widely recognized (see, for example, Elkind, 1997, 31), especially when such incontrovertible evidence like prisoners having elevated levels of testosterone (McDermott, 2006, 5)is considered. Is environmental determinism somehow less deterministic than determinism on the interaction of the environment and genetics? This has implicationss throughtout education. The existence of a disproportionately male engineering gender gap (as opposed to a disproportionately female university gender gap (Marklein, 2005) is problematic in one way if women are being unfairly excluded from opportunities (e.g., Raskin, 2005) but problematic in another way if many existing women engineers were forced into their career-paths by misguided environmental-determinists (Pinker, 2002, 359). This is not to say anything of the question if men and women learn best in different ways.


In the days where all undergrads were between 18 and 22 the interaction between DNA and age could be ignored. At most we were troubled with the issue of development (see, for example, Allen et al., 2005; Morrisey & Werner-Wilson 2005; Steinberg 2001; Steinberg & Morris, 2001). Yet once we see that certain ideas may become “hard” relatively early in life because of genetic factors (Alford, Funk, & Hibbing, 2005) the concept of teaching itself becomes troublesome. Likewise, old theories of learned development are being undermined by evidence of genetically-derived knowledge (Tooby & Cosmides, 1992), an idea once consigned to fiction (London, 1903). How will we deal with this knowledge?

Just as our experiences make students unique, so do their genes. Evolutionary simulations have shown that genetic populations instead of evolving toward agents with homogeneous behavioral strategies [that is, alleles], often evolve such that multiple strategies coexist at equilibrium” (Kurzban & Houser, 2005, 1803). This genetic polymorphism in students comes in two broad categories: genetic variation between individuals and genetic variation between groups (Rockman et al., 2005, 2214). In the future, educators will do well to be cognizant of these categories.

Some variation is merely between individuals. This is because variation between individuals is evolutionary useful for evolutionary groups (Smith et al, 2004, 5). As Sautter writes, “Evolution has cultivated a multitude of personality traits that vary amongst humans. This phenotypic variation allows for selective advantages on the group level” (2006, 4), even within just the past few thousand years (Wade, 2006). Fortunately, new technologies are helping us educate those who are smart in different ways (Yandell, 2002, 303) with different parts of their brains (Morgan, 2001) and with different “intelligences” (Gardner, 1983). But obviously we can now see only the shadows of the final consequences of the recognition genetic individuality.

But in other ways, populations vary (statistically) because of genetics, too. For instance, one pair of alleles, Dopamine Receptor D4 3 Repeat (DRD4 4R) and Dopamine Receptor D4 7 Repeat (DRD4 7R), was after some controversy found to be correlated with a type of ADHD (Castellanos et al, 1998; Grady et al, 2003) and perhaps other personality factors (Lynn, et al., 2005; Sullivan, et al., 1998).† The prevalence of “drd4 7r” varies by population, with some peoples (!Kung, Han Chinese and Sardinians) having very little of the “adhd” allele and other populations (American Indians, white Americans, Yanamamo) having elevated levels. Apparently this resulted from different evolutionary pressures (Ding, et al., 2002). Commenting on this, Harpending & Cochran (2002, 12) noted “It is probably no accident that two of the best known ethnographies of the twentieth century are titled ‘The Harmless People’ about the !Kung who have few or no 7R alleles, and ‘The Fierce People,’ about the Yanomamo with a high frequency of 7R.” As the population diversifies, population genetics will become more and more important to educators.


Student Nature, a companion series to Learning Evolved
1. The Nature of the Student
2. The Natures of Our Students
3. Nature and Her Consequences
4. Bibliography

Quick & Dirty Literature Review for the Ultimatum Game

Nothing particularly interesting. Merely a rough draft, using all new (to me) sources, of the nature of the ultimatum bargaining game. I presume that in an expanded and improved form this will re-appear, but for now I am posting it for my own reference.

Read on only if you’re very interested, or very bored.


Research has been done with gameplay and learning disabled students, such as autistics (Sally & Hill, 2006). It also also shown how attractive people both receive higher shares and are expected to give more (Solnick & Schweister, 1999), and likewise how being participants artificially divded into high and low status groups treat each other differently (Ball and Eckel, 1996), It has even be shown how research itself is a type of ultimatum game (Bonetti, 1998).

At least among some cultural groups, adolescents are more generous than adults (Hoffmann & Tee, 2006). Relatedly, moral reasoning in game play increases in early adolescence — between the ages of 11 and 13 (Takezawa, Gummerum, & Keller, 2006). Reasoning takes ability into account. For instance, players act as if higher-skill players should earn more, but lower-skill players should not be expected to give as much (Ruffle 1998).

People use different strategies while playing the ultimatum game. Researchers in Russia observed that play-types seem to split into players who want at least a fair outcome for themselves and those who want a fair outcome for both players (Bahry & Wilson, 2006). Another study observed that players seem to be split into those who are sensitive to other’s injustice to them, to injustice against others, and unjust profiting (Fetchenhauer & Huang, 2004). An unfair action is more likely to be perceived to be injust if it was intentional as opposed to unintentional (Kagel, Kim, & Moser, 1996).

Game play also varies across type of game. For instance, players who maximize for expected reward may behave fairly in ultimatum games but unfairly in dictator games (Haselhuhn & Mellers, 2005) and behave more fairly when making one decision at a time than many decisions simultaneously (Bazerman, White, & Lowenstein, 1995). Similarly, behavior in the ultimatum game changes if the actions are described in terms of an everyday social interaction rather than as straight-forward bargaining (Larrick & Blount, 1997).

Still, game performance is not static. Behavior in the ultimatum game is influenced by norms of a people (Henrich, et al., 2005) and even a workplace (Kay, Wheeler, Bagh, & Ross, 2004). Knowledge about theoretical performance maximizing behavior changes performance (Lusk & Hudson, 2004), as does group decision making (which appears to improve rational behavior) (Robert & Carnevale, 1997). Likewise, chaotic conditions make it harder to learn how to maximize performance for responders than for proposers (Gale, Binmore, & Samuelson, 1995).

Perceptions of distributive justice are important (Humprey, Ellis, Conlon, & Tinsley, 2004) as is honesty (Croson, Boles, & Murnighan, 2003). As feelings of guilty are also important (Ketelaar & Au, 2003). Thus, it is not surprising that social awareness and thus awareness of would-be fair outcomes changes behavior, too (Handgraaf, Dijk, Wilke, & Vermunt, 2003). Some of the consequcnes of this are nonintuitive: for instance, it can be better to play an economic game from a powerless position, and this appears to cause the other player to be more concerned for your welfare (van Dijk & Vermunt, 2000). Similarly, changing the relative power of the players does not substantially alter play performance (Weg & Smith, 1993).

Reciprocity in playing games means rewarding kind actions and punishing bad ones (Falk & Fischbacher, 2006). A similar concept, altruism in the ultimatum game has been observed in among the Nigerian Igos (Gowdy, Iorgulescu, & Onyweiwu, 2003). American lawyers, explaining decisions they had made, also listed fairness as a greater cause of their actions than envy or altruism-as-such (Bethwaite & Tompkinson, 1996).

The uttimatum game has also been studied through computer simulations. Adaptive algorithms can yield in-game behavior similar to that observed in humans (Calderon & Zarama, 2006). The computer programs show how fairness can evolve if players are generally able to know how the other agent has played in the past (Nowak, Page, & Sigmund, 2000).

The connection to game-play excellence with creativity is worth considering. Stubbornness and persistence are associated in computer simulations with success, but so is the less-well-regarded attitude of capriciousness (Napel, 2003). General personality traits, such as independence and tough-mindedness, are also important (Brandstatter & Konigstein, 2001);

Explicit beliefs matter, as well. An interaction between fair beliefs and self-interested explained begaining behavior in both Japan and the United States (Buchan, Croson, Johnson, & Iacobucci, 2004).
Technical measuring devises have been used to study ultimatum game behavior. For instance, the right dorsolateral prefrontal cortext (van ‘t Wout, Kahn, Sanfey, & Aleman, 2005) among other brain areas (Camerer, 2003).

The ultimatum game has been manipulated to create new games before. It has been changes to minimize the outcome of the proposing player (Gneezy, Haruvy, & Roth, 2003) as well as to incorporate elections (Sulkin & Simon, 2001) or democratic committe-style decision making (Messick, Moore, & Bazerman, 1997). Guth, Huck, and Muller altered it to prevent equal splits, and observed that proposed divisions decreased fair offers more than they expected (2001). Likewise, by reducing the size of the pie while decisions are being made, different choices are made (Suleiman, 1996). Similarly, when a rejection does not lead to all getting zero, but other predetermined positive figures, game play changes as well (Knez & Camerer, 1995). Further, when a third player is made completely dependent on the receiver player, it was found that the giving power is more generous and the receiving power less protective against exploitation (Oppewal & Tougareva, 1992).

A practical question is how the stakes of the game change behavior, and this is not nailed down yet. Increased stakes do seem to make subjects more pliant toward small rewards, but changing the stake size does not (Munier & Zaharia, 2002). Other researchers, while showing that reciprical kindness appears to explain most game behavior, note that the effective of changing the stakes is marginal when compared to the relative percentage offered (Dickenson, 2000).

Bahry, D.L., & Wilson, R.K. (2006). Confusion or fairness in the field? Rejections in the ultimatum game under the strategy method. Journal of Economic Behavior & Organization 60(1):37-54.
Bazerman, M.H., White, S.B., & Lowenstein, G.F. (1995). Perceptions of fairness in interpersonal and individual choice situations. Current Directions in Psychological Sciences 4(2): 39-43.
Ball, S.B., & Eckel, C.C. (1996). Buying status: Experimental evidence on status in negotiation. Psychology & Marketing 13(4): 381-405.
Bethwaite, J. & Tompkinson, P. (1996). The ultimatum game and non-selfish utility functions. Journal of Economic Psychology 17(2): 259-271.
Bonetti, S. (1998). Experimental economics and deception. Journal of Economic Psychology 19(3): 377-395.
Brandstatter, H., & Konigstein, M. (2001). Personality influences on ultimatum bargainin decisions. European Journal of Personality 15(1): S53-S70.
Buchan, N.R., Croson, R.T.A., Johnson, E.J., & Iacobucci, D. (2004). When do fair beliefs influence bargaining behavior? Experimental bargaining in Japan and the United States.. Journal of Consumer Research 31(1): 181-190.
Calderon, J.P., & Zarama, Roberto. (2006). How Learning Affects the Evolution of Strong Reciprocity. Adaptive Behavior 14(3):211-221.
Camerer, C.F. (2003). Strategizing in the Brain. Science 300(5626): 1673-1675.
Croson, R., Boles, T., & Murnighan, J.K. (2003). Cheap talk in bargaining experiments: Lying and threats in ultimatum games.. Journal of Economic Behavior & Organization 51(2): 143-159.
Dickenson, D.L. (2000). Ultimatum decision-making: A test of reciprocal kindness. Theory and Decision 48(2): 151-177.
Falk, A. & Fischbacher, U. (2006). A Theory of Reciprocity. Games and Economic Behavior 54(2):293-315.
Fetchenhauer, Detlef & Huang, Xu. Justice sensitivity and distributive decisions in experimental games. Personality and Individual Differences 36(5): 1015-1029.
Gale, J., Binmore, K.G., & Samuelson, L. (1995). Learning to be imperfect: The ultimatum game. Games and Economic Behavior 8(1): 56.90
Gneezy, U., Haruvy, E., & Roth, A.E. (2003). Find More Like ThisBargaining under a deadline: Evidence from the reverse ultimatum game.. Games and Economic Behavior 45(2): 347-368.
Gowdy, J., Iorgulescu, R., & Onyeiwu, S. (2003). Fairness and Retaliation in a Rural Nigerian Village. Social Journal of Economic Behavior & Organization 52(4): 469-479.
Guth, W., Huck, S., & Muller, Wieland. (2001). The Relevance of Equal Splits in Ultimatum Games.. Games and Economic Behavior 37(1): 161-169.
Handgraaf, M.J.J., van Dijk, E., Wilke, H.A.M., & Vermunt, R.C. (2003). The salience of a recipient’s alternatives: Inter- and intrapersonal comparison in ultimatum games. Organizational Behavior and Human Decision PRocesses 90(!): 165-177.
Haselhuhn, M.P., & Mellers, B.A. (2005). Emotions and Cooperation in Economic Games. Cognitive Brain Research 23(1): 24-33.
Henrich, J., et al. (2005). ‘Economic man’ in cross-cultural perspective: Behavioral experiments in 15 small-scale societies.. Behavioral and Brain Sciences 28(6): 795-855.
Hoffmann, , R. & Tee, J. (2006). Adolescent-adult interactions and culture in the ultimatum game.. Journal of Economic Pscyhology 27(1):98-116.
Humphrey, S.E., Ellis, A.P.J., Conlon, D.E., & Tinsley, C.H. (2004). Understanding Customer Reactions to Brokered Ultimatums: Applying Negotiation and Justice Theory. Journal of Applied Psychology 89(3): 466-482.
Kagel, J.H., Kim, C., & Moser, D. (1996). Fairness in ultimatum games with asymmetric information and asymmetric payoffs. Games and Economic Behavior 13(1): 100-110.
Kay, A.C., Wheeler, S.C., Bargh, J.A., & Ross, L. (2004). Material priming: The influence of mundane physical objects on situational construal and competitive behavioral choice. Organizational Behavior and Human Decision Processes 95(1): 83-96.
Ketelaar, T., & Au, W.T. (2003). The effects of feelings of guilt on the behaviour of uncooperative individuals in repeated social bargaining games: An affect-as-information interpretation of the role of emotion in social interaction.. Cognition & Emotion: 17(3): 429-453.
Knez, M.J., & Camerer, C.F. (1995). Outside Options and Social Comparison in Three-Player Ultimatum Game Experiments. Games and Economic Behavior 10(1): 65-94.
Larrick, R.P. & Blount, S. (1997). The claiming effect: Why players are more generous in social dilemmas than in ultimatum games. Journal of Personality and Social Psychology 72(4): 810-825.
Lusk, J.L., & Hudson, D. (2004). Effect of Monitor-Subject Cheap Talk on Ultimatum Game Offers. Journal of Economic Behavior & Organization 54(#): 439-443.
Messick, D.M., Moore, D.A., & Bazerman, M.H. (1997). Ultimatum bargaining with a group: Underestimating the importance of the decision rule. Organizational Behavior and Human Decision Processes 69(2): 87-101.
Munier, B., & Zaharia, C. (2002). High stakes and acceptance behavior in ultimatum bargaining: A contribution from an international experiment.. Theory and Decision 53(3): 187-207.
Napel, S. (2003). Aspiration Adaption in the Ultimatum Game. Games and Economic Behavior 43(1): 86-106.
Nowak, M.A., Page, K.M., & Sigmund, K. (2000). Fairness versus reason in the ultimatum game. Science 289(5485): 1772-1775.
Robert, C. & Carnevale, P.J. (1997). Group choice in ultimatum bargaining. Organizational Behavior and Human Decision Processes 72(2): 256-279.
Ruffle, B.J. (1998). More Is Better, But Fair Is Fair: Tipping in Dictator and Ultimatum Games. Games and Economic Behavior 23(2): 247-265.
Sally, D., & Hill, E. (2006). The development of interpersonal strategy: Autism, theory-of-mind, cooperation and fairness. Journal of Economic Psychology 27(1):73-97.
Solnick, S.J. & Schweitzer, M.E. (1999). The influence of physical attractiveness and gender on ultimatum game decisions. Organizational Behavior and Human Decision Processes 79(3): 199-215.
Suleiman, R. (1996). Expectations and fairness in a modified Ultimatum game. Journal of Economic Psychology 17(5): 1996.
Sulkin, T., & Simon, A.F. (2002). Habermas in the lab: A study of deliberation in an experimental setting.. Political Psychology 22(4): 809-826.
Takezawa, M., Gummerum, Michaela, & Keller, Monika. (2006). A stage for the rational tail of the emotional dog: Roles of moral reasoning in group decision making.. Journal of Economic Psychology 27(1):117-139.
Oppewal, H., & Tougareva, E. (1992). A three-person ultimatum game to investigate effects of differences in need, sharing rules and observability on bargaining behaviour. Experimental Economics 13(2): 203-213.
van Dijk, E. & Vermunt, Riel. (2000). Strategy and fairness in social decision making: Sometimes it pays to be powerless.. Journal of Experimental Psychology 26(1):1-25.
van ‘t Wout, M., Kahn, R.S., Sanfey, A.G., & Aleman, A. (2005). Repetitive transcranial magnetic stimulation over the right dorsolateral prefrontal cortex affects strategic decision-making.. Neuroreport: For Rapid Communication of Neuroscience Research 16(16): 1849-1852.
Weg, E., & Smith, V. (1993). On the failure to induce meager offers in ultimatum games. Journal of Economic Psychology 14(1): 17-32.

Student Nature, Part I: The Nature of the Student

In the context of education, the human mind expresses genetic factors in four ways: universally among the species, differently by age, differently by sex, differently by group, or differently by type. The old models of explaining human behavior, some more economic, some more psychological, are dying (Carmen, 2006, 1). It is time for a new model, of genetics in education, to be born.

Before I begin, it is important to realize that some people are not more or less “fit” than others – genetic factors in no way implies social darwinism. Educationally, some of our most valuable abilities, reading and writing, rely on genetic factors that developed accidentally (Gould 114). In evolution we are all winners. Of all the humans who have ever lifted, each and every one of the ancestors of every human who now exists succeeding in something very unlikely: having descendants who are alive even today. Not only are we all equally human: we are all equally winners.


The most obvious genetic factor is our common humanity. Our human nature is seen in the information-processing system of the brain, our natural cooperativeness, and the universal learning tools we all have.

The most trivially shared, inborn human adaption is that our brains are information-processing machines. The information-processing approach has been used to explain motivation (Albanese & van Fleet, 1985, 252), reading ability (Benton & Kiewra, 1986, 378; McCrudden, Schraw, Hartley, & Kiewra, 2004), and even warfighting (Meilinger, 2000; Moffat 2000; Smith, 1999). One particular information processing model was noted for “its multidimensional complexity and its dynamic nature that encompasses both time and space… [this information processing model] does not represent a linear process developing along the time axis but a process that develops simultaneously within the operational sphere where time is but one of the constituent elements.” (von Lubitz et al., 2004) We have a modular information processing system (Smirnov, Arrow, Kennet, & Orbell, 2006 4) that is influenced by genetic factors (Fadok, Boyd, & Warden, 1995) that directly leads to multiple intelligences (Gardner, 2003).

Humans are generally cooperative. People act as if they enjoy altruism, reporting feeling a “warm glow” (Leuthold, 1993, 353) when they help each other. Students learn (Driver et al., 1994, 10; Hursch & Borzak, 1979, 70) and act socially in a manner reminiscent of only a few other mammals (Wrangham, 1999, 1) and the social insects (Wilson & Holldobler, 2005, 13371). These social tendencies, which Smith described as “a preference for cooperation, a modest level of mistrust, an ability to persuade others of one’s own good faith, and an ability to detect lack of good faith in others” (2006,1014) are exactly the genetic adaptations what one would expect in a socially evolved species. This includes not only altruism but also altruistic punishment, the behavior of irrational vengeance seen in countless laboratory experiments (Fehr & Gachter, 2000, 993; Sanfey et al, 2003, 1755) and computer simulations (Boyd, Gintis, Bowles, & Richardson, 2003, 3532). And even if completely anonymous conditions, people still are generous to others (Fowler, 2006, 676). Humans are social animals who need each other in order to learn (Ridley, 2003, 208). Education should be designed to exploit this.

Our “species-nature” (Talbot, 2003) includes other learning tools we often take for granted. The human brain can learn how to take care of things automatically by repeated practice, a process called automaticity (Craemer, 2006, 4-5; Morris, Squires, Taber, & Lodge, 2003, 4). Closely related to this is analogical thinking, applying known strategies to a new tasks, documented in areas from economic games (Henrich, et al, 2001, 75) to creativity (Weisberg, 1993). Similarly, essential human needs such as security (Huddy, Feldman, & Weber, 2006, 2) and thus the increased attention to intimate partners (Biggs, 1999, 106), probably have a genetic basis as well. Additionally, the cogntive split between verbal and visual knowledge (Igo, Kiewra, & Bruning, 2004), to say nothing of conscious and unconscious knowledge (Hoffman, 2006; Schraw & Bruning, 1996, 302), appear to be universal. This includes intuition (the ability to make correct choices faster than one could have consciously viewed choices) (Olson & Marshuetz, 2005, 501) and other hitherto-unscientific theories. Any educational methodology that assumes that what students are consciously aware of and what they can explain is the limit of their knowledge would be very misguided.


Student Nature, a companion series to Learning Evolved
1. The Nature of the Student
2. The Natures of Our Students
3. Nature and Her Consequences
4. Bibliography

Nonkinetic "War" is called "Politics"

Despite his own theory’s internal incoherency and agenda-driven nature, John Robb nonetheless hosted a great discussion on 5GW, or “SecretWar.” In the comments, RyanLuke asked

If 5GW is getting others to do what you want them to do of their own free will (though maybe that is not the best definition?), where is the “war” part?

Purpleslog, a blogfriend who writes at his own site as well as Dreaming 5GW

It is limiting to equate war with just kinetic power and fighting.

War is conflict and competition between global actors to survive, hold, flourish and grow. This can be zero-sum or non-zero sum.

John Robb chimed in

Purpleslog, that’s called politics.

and I agreed with John

5GW is the use of meaningful violence to change one’s free will. That is, the victim believes he reached the decision through his normal processes, but in reality you are selectively killing, destroying, etc, in a way to bring about that decision.

I agree with John Robb that non-kinetic “war” is called politics. Politics and war are qualitatively different from each other. They should not be confused.

I made a mistake similar to Purpleslog’s eighteen months ago. Peaceful politics can be similar to violent war, and there may be a 5GP (5th Generation Politics) that complements 5GW (5th Generation War).

But war and peace are nonetheless distinct activities. They should not be confused.

Wary Motivation & Implicit Knowledge

Bruning, Roger, & Horn, Christy. (2000). Developing Motivation to Write. Educational Psychologist 35(1):25-37.

Bruning, Roger, & Flowerday, Terri. (1999). Response: Dempster and Corkill’s “Interference and Inhibition in Cognition and Behavior: Unifying Themes for Educational Psychology.” Educational Psychology Review 11(2):89-96.

Glover, John A., Zimmer, John W., & Bruning, Roger H. (1980). Information Processing Approaches Among Creative Students. The Journal of Psychology 105:93-97.

Hibbing, John R., & Alford, John R. (2004). Accepting Authoritative Decisions: Humans as Wary Cooperators. American Journal of Political Science 48(1):62-76.

Kiewra, Kenneth A., et al. (1997). Effects of Advance Organizers and Repeated Presentations on Students’ Learning. Journal of Experimental Education 65(2):

Hibbing, John R., & Theiss-Morse, Elizabeth. (2001). Process Preferences and American Politics: What the People Want Government to Be. The American Political Science Review 95(1):145-153.

Rankin, Joan L., Bruning, Roger H., & Timme, Vicky L. (1994). The Development of Beliefs about Spelling and Their Relationship to Spelling Performance. Applied Cognitive Psychology 8:213-232.

Todorov, A., Mandisodz, A. N., Goren, A., & Hall, C.C. (2005). Inferences of Competence from Faces Predict Elections Outcomes. Science 308:1623-1626.

Can you find the central theme?

In the field of educational psychology, the questions addressed in most detail by researchers and text authors are these: How are connections made? What conditions lead to effective encoding and retrieval strategies? and How can learners actively participate in their own cognitive processes? The questions not being asked include, What information is not being activated? Why is it bypassed? Is incorrect or inappropriate information being activated? and Could it be due to a deficit in inhibitory function?
(Bruning & Flowerday, 1999, 93)

Hayes and Daiker (1984) found that the single most important principle of response in a writing environment was positive reinforcement. (Bruning & Horn, 2000, 33)

If, as Wittrock suggests, learning is a generative, active process, then the present findings indicate that a major cognitive difference between creative and noncreative students lies in the greater ability of the former to access other sources of information to broaden the semantic base of their productions. (Glover, Zimmer, and Bruning, 1980, 96)

To our knowledge, this is the first empirical evidence that, controlling for perceptions of greed, the belief that decision makers are ambitious has an independence and relatively strong inverse effect on decision acceptance. Apparently, being treated badly by someone who did not necessarily want to be in a position to treat us badly is much more tolerable than being treated badly by someone who machinated to be in a position to treat us badly.
(Hibbing & Alford, 2004, 71)

Indeed, survey instruments rarely include questions about what government processes respondents would like to see. For example, every two years NES asks: “How much attention do you feel the government pays to what people like you think?” It does not ask: “How much attention should government pay to what people like you think?”
(Hibbing & Theiss-Morse, 2001, 147)

The present experiment replicated previous research findings that repeated presentations of a lecture increase both note taking and learning. It extended previous research, however, by showing that repeated presentations facilitate the learning of facts about topics, but not relations across topics. Apparently, students did not spontaneously integrate ideas across topics, even when given repeated opportunities to do so.
(Kiewra, et al., 1997)

Students who held the highest levels of efficacy for themselves as spellers, and who expected that good spelling had important consequences for themselves as writers, were, in fact, the best spellrs. The highest levels of performance, however, were reserved for those who attributed good spelling more to effort htan to ‘being smart'” (Rankin, Bruning, & Timme, 1994, 228)

We conducted an experiment in which 40 participants (19) were exposed to the faces of the candidates for 1 s (per pair of faces) and were then asked to make a competence judgment. The average response time for the judgment was about 1 s (mean = 1051.60 ms, SD = 135.59). These rapid judgments based on minimal time exposure to faces predicted 67.6% of the actual Senate races (P < 0.004) (20). The correlation between competence judgments and differences in votes was 0.46 (P < 0.001). (Todorov, et al., 2005, 1624)

The rest of the notes are, as always, below the fold


The general answer is that interference and inhibition were abandoned as psychology rushed into the 1960s and 1970s to embrace more contextualized, constructivist views of learning. In a highly influence American Psychologist article, for example, J.J. Jenkins (1974), a prominent memory theorist, described how he had come to doubt associationistic explanations of memory and moved to contextualist ones. More than associations were involved, he argued: the quality of events greatly affects what is observed in any experiment. Using this reasoning, he and others created a host of compelling experimental and naturalistic demonstrations of how contextual variables can affect learning and memory.
(Bruning & Flowerday, 1999, 90)

Many of the most cherised cognitive goals — reading, writing, learning strategies, problem solving decision making — require expertise built on repertoires of automatized responses. Acquiring this expertise involves basic learning processes of association, repetition, and extended practice to which the concepts of interference and inhibition are especially applicable. (Bruning & Flowerday, 1999, 91)

What the neurosciences are beginning to make possible are increasingly revealing glimpses of what is happening in the black box. Researchers can now “view” internal neurological processes (at least their physiological correlates) as they occur in specific brain regions as learners grapple with simple and complex learning problems.”
(Bruning & Flowerday, 1999, 91-92)

By demonstrating the concetps’ relevance in a variety of research areas, Dempster and Corkill show that the concepts can be extended well beyond the narrow “verbal learning” and “rote memory?” niches into which many educational psychologists had tucked them.” (Bruning & Flowerday, 1999, 93)

At a more specific level, however, we are less sanguine about the utility of interference and inhibition as explanatory concetps. Taking two examples provided by Dempster and Corkill, for instance, we think that performance difficulties that occur (1) when math problem types change e.g., 3 + 6 = ? becomes 3 + ? = 9) or (2) when learners are overloaded with too much information are more satisfactorily explained by concepts other than failure of inhibition or interference.
(Bruning & Flowerday, 1999, 94)

Motivational considerations are an integral pan of their vision as writers make trade-offs between costs and benefits of various goals and ways to use resources (Flower et al., 1994; Hayes, 1996). In any writing task–from a child’s brief book report to the reading-to-write assignment of college composition–writers must negotiate between what is expected and what can be done. Students need to be motivated to enter, persist, and succeed in this ill-defined problem space we call writing.
(Bruning & Horn, 2000, 26)

Snow (1983) argued that learning to read is facilitated by oral language experiences where parents scaffold understanding by speaking in literate ways. Writing needs the same kind of structure (Bruning & Horn, 2000, 27)

Gender also appears to play a role in the development of writing efficacy. Pajares and Valiente (1997) found, for example, that fifth-grade boys and girls did not differ in their writing performance but that girls perceived writing as more useful than boys, had greater self-efficacy, and worried less about it. In a sample of ninth graders, however, girls reported lower self-efficacy than boys, even though their actual writing performance did not differ. These findings may reflect a general downward trend for girls in perceptions of their academic competence (Phillips & Zimmerman, 1990). It may also be, as Cleary (1996) argued, that secondary schools and colleges emphasize a male-biased form of discourse requiring females to adapt to structures that may be less intuitive, interesting, or intrinsically motivating.
(Bruning & Horn, 2000, 29)

Cycles of goal setting coupled with feedback regarding progress toward the goals often are necessary to activate a full capability for self-monitoring and self-regulation (Cervone, 1993). (Bruning & Horn, 2000, 30)

Even when selected for sound pedagogical reasons, writing activities often are not set within larger social or communication frames that can create interest and a sense of writing’s relevance. (Bruning & Horn, 2000, 30)

Hiebert (1994) described authentic literacy tasks as activities that involve children in the immediate use of literacy for enjoyment and communication, distinguishing them from activities where literacy skills are acquired for some unspecified future use. (Bruning & Horn, 2000, 30)

Having genuine reasons for writing almost certainly has motivational consequences. Authentic tasks would seem to afford students the opportunity to express and refine their voice (e.g., Elbow, 1994; Schiwy, 1996). Words set down on a page to a real audience for a real purpose are their own, not borrowed (Elbow, 1994). Authentic tasks are likely to help students develop one or more distinctive styles of writing and to determine if these styles are “theirs.” (Bruning & Horn, 2000, 30)

The research on the impact of interest on writing has revealed a complex relation between knowledge, interest, and writing performance (Benton, Corkill, Sharp, Downey, & Khramtsova, 1995; Hidi & Anderson, 1992). Benton et al. (1995), for example, found that students with high topic knowledge and high interest wrote essays that included content-relevant information that was logical and well-organized, whereas writers with relatively less interest and knowledge generated more ideas unrelated to the topic. Although there was a strong relation between knowledge and interest, they were found to be separate constructs. (Bruning & Horn, 2000, 30)

Gaining and maintaining control of a writing task almost certainly are critical motivationally. No matter what the writer’s developmental stage or ability level, each act of writing poses a formidable challenge, having much in common with other ill-defined problems (Flower et al., 1990). In creating the problem space and in its later refinements, writers must balance the potential costs of various courses of action with their hypothesized benefits (Hayes, 1996). Do I need more information? Do I need to change the focus of what I’m writing? Do I have time to revise? Should I read over the paper one more time? Parameters defining this fluctuating problem space include the writer’s purposes for writing, the norms of the discourse community (as embodied by the teacher or other audiences), and the writer’s own knowledge and writing skill.
(Bruning & Horn, 2000, 31)

Students find cognitively complex learning activities inherently more interesting and demanding of mental effort (Meece & Miller, 1992); such tasks lead to higher levels of motivation because they create interest, allow for self-improvement, and afford opportunities to control one’s own learning (Turner, 1995). They prefer complex literacy assignments for much the same reasons (Miller et al., 1993). Writers need to believe, however, that if the task is complex it can be accomplished with reasonable effort. (Bruning & Horn, 2000, 31)

If anxiety rises to a high level, the result may be emotional and cognitive thrashing that disrupts writing entirely. (Bruning & Horn, 2000, 31-32)

Case study research has indicated that students respond favorably to specific and explicit ways to improve their writing (Straub, 1996, 1997); students are quite clear about their need for specific coaching about their writing. In a number of studies examining student response to teacher comments, students responded very well to comments that dealt with organization, development, and matters of form, but resisted comments that dealt with the value of their ideas or issues they did not consider germane to the writing task (Cleary, 1996; Larson, 1995; Straub, 1997). (Bruning & Horn, 2000, 32)

Students appear to be very aware of control issues in writing and recognize when the person giving feedback begins to exert too much control (Straub, 1996). (Bruning & Horn, 2000, 32)

Although we strongly believe that developing motivation to write is best conceived of as a process of building intrinsic motivation, rewards may play a productive role. Rewards can help build achievement-directed motivation when they are made contingent on student effort (Brophy, 1987; Stipek & Kowalski, 1989) and on progress in relation to short-term goals (Schunk, 1989). (Bruning & Horn, 2000, 32)

Reducing the aversiveness through reward may increase young writers’ general readiness to expend effort in goal-directed writing tasks (Eisenberger & Cameron, 1996) (Bruning & Horn, 2000, 32)

With this exposure can come feelings of loss of control and its attendant anxieties (Bandura, 1997), which can be amplified when conditions for successful performance and feedback are unclear. (Bruning & Horn, 2000, 33)

In classrooms where teachers create a climate of trust, caring, and mutual concern, students are motivated to engage (Connell & Wellborn, 1991; Wentzel, 1997). (Bruning & Horn, 2000, 34)

The Unusual Uses subtests were scored for fluency, flexibility, elaboration, and orginality by two independent raters. Reliability indices for these measures were .95 (fluency), .93 (flexibility), .94 (elaboration), and .87 (originaility). Scores on the four variables were summed for each S to provide an overall “creativity” rating, with the total score median used to determine creative and noncreative categories for analysis.
(Glover, Zimmer, and Bruning, 1980, 94)

The lack of consistent differences between creative and noncreative participants on the reading test or the essay posttest is congruent with research assessing relationships of creativity with other intellectual abilities. However, when summary and “flight of fancy” passages were analyzed, some important differences emerged between the two groupings.
The findings of significantly higher numbers of logical intrusions in both passages generated by creative Ss suggest that they may have related new information contained in the essay to existing “schemata” or previously existing knowledge structures, to a greater extent than noncreative Ss. The passages produced might, thus, be considerations of “new” and “old” information. Passages generated by the noncreative students tended, in teh main, to be less coherent and more straightforward compilations of “facts”: e.g., serial listings of essay relevent and irrelevent information.
(Glover, Zimmer, and Bruning, 1980, 95-96)

A central requirement — perhaps the central requirement — of civilo society is a willingness of its members to accept binding decisions and to view the makers of those decisions as legitimate.
(Hibbing & Alford, 2004, 62)

Since it is unrealistic to expect that legitimacy could be bought by magically increasing the resources avialable to distrituve to all residents, like a growing number of social scientists, we pay social attention to the possibility that different decision-making processes will have an impact. (Hibbing & Alford, 2004, 62)

As Popkin puts itthe prevailing wisdom is that people make judgements on the basis of “results and are generally ignorant of or indifferent about the methods by which the results are achieved.”
(Hibbing & Alford, 2004, 63)

In psychology, Tyler has led the way in demonstrating that people do “not react to the degree to which they received a personally beneficial decision. Instead, they react to how failry the decision was made by the authority…”
(Hibbing & Alford, 2004, 63)

“Some of these researchers, for example, have stressed people’s preference for relative as opposed to absolute gains. It turns out, people express high levels of satisfaction when they receive $3 from another player who keeps $3, but low levels of satisfaction when they receive $3 from another player who keeps $13. By holding constant the payoff offered to the receiver and then varying the size of the pot (and therefore the amount the other player proposes to keep), the crucial role of relativity becomes apparent (Frank 1999; Kahn and Murnighan, 1993) (Hibbing & Alford, 2004, 63)

Scholars from a variety of fields, including political science, have demonstrated the extent to which social context influences people’s reactions to decisions. People are affected by whether they have interacted (even briefly) with the decision maker prior to the decision, by whether they are likely to interact with the decicion maker again, by whether they perceive the decision maker to be a member of their “in-group,” and by whether the deciion maker is perceived to be a decent human being or to have “earned in a fair contest the right to be the decision maker… TYpically, for example, people are more willing to take a loss for themselves in order to punish someone who has behaved badly or to cooperate with someone who has behaved nobly (see, for example, Boyd and Richerson 1992; Henrich and Boyd 2001; Thaler 1992). (Hibbing & Alford, 2004, 63)

One common explnation for nonmaximizing behavior is that humans retain in their psyches a strong and innate desire for fair distributions (see Kravitz and Gunto 1992; Rawls 1971). Two problems with this explanation immediately suggest themselves: one empirical and one theoretical. In experiments, people do gravitate toward fair allocations, even if doing so is costly, but their tendency to be fair vanishes if steps are taken to protect their identity from the experimenter and, especially, from affected players (See Hoffman et al. 2000; see also Larimer 2002). people are less concerned with fairness than with the appearance of fairness. But even if this desire for fairness were more robust, we would still be left with the question of why humans woudl carry with tthem such a nonrational concern. A satisfactory theory ofr people’s behavior must go beyond the simple assertion that “this is the way people are.” (Hibbing & Alford, 2004, 64)

In brief, this theory flows from Darwinian biology and holds that, far from being an add-on, our sociality — that is, our frequent concern fro the welfare of our group and for our own place in the group, our eagerness to conform and to guage our own success by that of those around us, our desire and ability to “read” and to emphasize with other people, and out tendency to view members of outgroups with disfavor — is deeply ingrained in the human condition and has been for millions of years. (Hibbing & Alford, 2004, 64)

At a remarkably early age, babies display empathy (Pinker 2002). (Hibbing & Alford, 2004, 64)

The idea that behavior has even a modest biological basis is still upsetting to many people, including scholars. Btt upsetting or not, the evidence seems firm and is growing. Beavers know how to build a dam even when they have not seen other beavers do so; monkeys raised isolated in a lab fear a snake after viewing a videotape of another monkey’s fear of a snake buty can never be taught to be scared of other creatres and objects no matter how many videos they see of monkeys being scared of those things (Dawkins 1982; Mineka and Cook 1993). (Hibbing & Alford, 2004, 64)

In humans, people suffering from autism (a condition known to be at least partially genetic) help us to see the kinds of social skills that the vast majority of the population takes for granted. Most autistic individuals are said to lack a “theory of mind” meaning they are unable to view social situations from the perspective of another person … ; thus, they are often unable to form normal social relationships. Autistic individuals have difficulty understanding how to make other people happy since this requires empathic abilities they lack. The point is that the “sociality as a learned behavior” theory seems to suggest that all humans are first autistic but then most learn to be otherwise, a vision of human development that is not accepted by experts in the area. (Hibbing & Alford, 2004, 64)

We call individuals who follow these rulers wary cooperators since their first impulsive is to cooperate but they are ever wary of the behavior of others. (Hibbing & Alford, 2004, 65)

People thus spend much of their existence trying to avoid being perceived as a leech by those who are other-regarding and being played for a sucker by those who are self-serving.
(Hibbing & Alford, 2004, 65)

Specifically, the theory suggests that people are using decisions and decision processes to draw inferences about decision makers. Are decision makers concerned for others? Are they trying to feather their own nests? Are they driven by personal ambition? Recent public opinion research indicates that the substance of most individual political decisions is of only passing concern to most people but the traits of other people, and especially the traits of powerful other people, is of great concern (see Hibbing and Theiss-Morse 2003) As a result, other things being equal people should be more accepting of authoritative decisions when they are made by decision makers believed to be unconcerned with either acquiring power or with benefiting themselves at the expense of others. In other words, we predict that deiciosn will be more acceptable if they indicate that the decision maker is the kind of person who would help to make a viable social group.
(Hibbing & Alford, 2004, 65-66)

The framework we employ for testing the theory utilizes the so-called ultimatum game. The theoyr was first introduced by Guth, Schmittberge, and Schwarze over 20 years ago (1982).”
(Hibbing & Alford, 2004, 66)

With regard to the allocator, rather than keeping all but a modest portion of the money, the modal decision is to split the pot equally between the allocator and the receiver and the median proposal is fo rthe allocator to give up about 40% to the receiver… To be specific, offers of 30% or less are rejected better than 50% of the time (Nowak, Page, and Sigmund 2000, 1773). As one scholar colorfully described it, the attitude of receivers toward allocators is often “take your offer of epsilon and shove it” (Thaler 1992, 35)
(Hibbing & Alford, 2004, 66)

In short, while psychological and economic experimental research has pointed us in a useful new direction, designs such as the ultimatum game need to be modified if they are to help us understand the political arena generally and people’s acceptance of authoritative and unfavorable decisions specifically.
(Hibbing & Alford, 2004, 66)

Once the instrument was completed, for purposes of realism, subjects wer asked to wait a monent for their “partner” to complete the survey; then the ultimatum game began.
(Hibbing & Alford, 2004, 67)

One of the pretest questions was “how far did you travel to get to the experimental site today?” In this last option, subjects were told teh computer would calculate the differential in travel of the “two” subjects and prorate the payoff accordingly, with those traveling farthe rin relative terms receiver the greater share.
(Hibbing & Alford, 2004, 67)

What makes our results unique is that they permit us to compare this acceptance rate with that generated by allocations made via other processes. When teh allocation was ostiensibly determined by calculations of the respective distances traveled by the two players, teh acceptance rate of the same $2 (of $20) allocation jumped to 71%, and when the allocation was determined by chance, the acceptance rate of, again, a $2 (of $20) allocation was even higher — 80%.”
(Hibbing & Alford, 2004, 68)

“When we control for outcome by freezing in a payoff that is small both in absolute and relative terms, substantial and significant variation is apparent in acceptance of that payoff depending entirely on the manner in which it was derived. Too often, analyssts assume people conflate a fair outcome with a fair process. Our findings help to pull apart these two very different concepts. Few could argue that an allocation of $18 for one person and $2 for another is a fair outcome, but if tha toutcome is believd to have resulted from a fair (random) process four out of five accept it.
(Hibbing & Alford, 2004, 69)

Out expectation is that subjects who believe the allocator decided to make the decision himself will perceive the decision maker as much less fair than subjects who believe the allocator left the decision up to chance or desert…. As can be seen in Figure 2, the results are perfectly supportive of this expectation.”
(Hibbing & Alford, 2004, 69)

But the extension of this finding to the political arena may be problmatic. Earnign a position does not equal coveting a position and previous expeirmental work has never analyzed the differnce.
(Hibbing & Alford, 2004, 70)

Here, the choice of how to make the allocation is Forced on Player 1…. As expected, receivers were much more willing to accept decisions made by decision makers who did not overtly crave power.
(Hibbing & Alford, 2004, 70)

Our hypothesis is that when people believe they have bene played for a sucker, little time and thinking are needed in formulating a response because the brain is hardwired to react neagatively to being played for a sucker but can afford to react to other scneariors at a more measured pace… As can be seen from Figure 4, results comform nicely to our expectations. Subjects who had been playerd for a sucker by an allocated who used his/her own discretion to keep $18 of th e$20 responded to the fairness/unfairness item relatively equickly, after just 6.6 seconds. But subjects who were not the victim of a self-serving allocator (but were simply unlucky or undeserving) took well over 10 seconds to respond to the fairness/infairness item, a different that was significant at teh .01 level.
(Hibbing & Alford, 2004, 72)

The concsensus, hwoever, certainly among economists, is that the evidence indicates a perference is a preference (whether it is monetary or not) and that the more telling issue is the size of the stakes (See Smith 2000, 16-17), which leads us to the second complaint. Results generated when $20 is at play, as was the case in our experiments, are not likely ot be similar to thsoe obtained when $200 or $2,000 is at play. We agree with this point ecompletely, and it has been amply demonstrated in previous research (see Brockner and Weisenfeld 1996; Cameron 1999).
(Hibbing & Alford, 2004, 73)

And just what do our findigns have to say about these effects? That if people are convinced the political process makes it impossible for decision makers to benefit themselves at the expense of non-decision makers, they will be surprisingly accepting of governmental decisions, even those that are unfavorable to them from a substantive point of view. This is especially true if the people believe that decision makers did not want to be decision makers in the first place.
(Hibbing & Alford, 2004, 74)

At the aggregate level, confidence in government dropped most dramatically in the late 1960s, when the economy was doing quite well, and shortly after Lane (1965, 877) declared that the new “age of affluence” woudl lead to “a reapproachment between men and their government and a decline of political alienation.” More recently, Seelye (1999, A15) notes with surprise that “most Americans still deeply distrust the Federal Government despite the end of the cold war, the robust economy, and the highest level of satisfaction in their own lives in 30 years.” There is even less support at the individual level. Cross-sectional analyses find no or only a modest relationship between poloicy satisfaction and institutional approval (Caldeira, 1986; Mueller 1973; Patterson and Caldeira 1990).
(Hibbing & Theiss-Morse, 2001, 146)

The belief that the government is out of touch with ordinary Americans is extremely common, but Figure 1 gives no indication that, on the whole, the people see government policies as out of line with their own preferences.
(Hibbing & Theiss-Morse, 2001, 147)

Kimball and Patterson (1997) find that disappointment with government is concentrated among those who expect elected officials to be honest, caring and altruistic but perceive them to be otherwise.
(Hibbing & Theiss-Morse, 2001, 147)

Again, process perceptions may explain the anomaly. Whereas people seem to believe the parties espouse different policies, they may view them as nearly identical in terms of processes. (Hibbing & Theiss-Morse, 2001, 149)

The benefit of repeated presentations of a lecture has been found by researchers using either audiotaped or videotaped instruction (Bromage & Mayer, 1986; Kiewra, Mayer, Christensen, Kim, & Risch, 1991; Mayer, 1983). In each study, recall was greater when students listened to or viewed a lecture presentation multiple times. (Kiewra, et al., 1997)

Advance organizers appear to have much the same effect as repeated presentations. Students who read an organizer in advance of a single presentation recall as many ideas as those receiving multiple presentations but no organizer (Mayer, 1983). (Kiewra, et al., 1997)

The matrix, however, was more computationally efficient (Larkin & Simon, 1987) than the outline was. One organizer is considered more computationally efficient than another if information is drawn more easily and quickly from it. (Kiewra, et al., 1997)

Authors of previous research have found an advantage for matrix organizers over linear organizers as a technique for increasing retention test performance (Benton, Kiewra, Whitfall & Dennison, 1993: Kiewra, DuBois, Christian, 8,: McShane, 1988; Kiewra, DuBois, et al., 1991: Robinson & Kiewra, 1995), with a few exceptions (e.g., Kiewra, Benton, Risch, Kim, & Christensen, 1995).
(Kiewra, et al., 1997)

In the present study, we compared matrix and linear organizers to each other and to a conventional organizer. We examined the three organizers in conjunction with repeated presentations of a lecture. We developed three dependent measures, each to tap a learning outcome that was considered appropriate to particular experimental treatments. We used a fact test that asked participants to respond true or false to 20 discrete facts about the lecture, a relational test that asked participants to compare old and new methods of radar across steps of the radar process, and a recall test that asked participants to recall all that they could about each radar step.
(Kiewra, et al., 1997)

The conventional organizer was more effective in enhancing overall recall, and particularly the recall of general topic information, as evidenced by analyses of the recall test scores. These results can be explained by the theory of transfer-appropriate processing (Morris, Bransford, & Franks, 1977). Performance was facilitated when information was processed in a manner consistent with the criterion task. The linear and matrix organizers, which emphasized relationships within and across topics, enhanced relational learning; in contrast, the conventional organizer, which provided general topic information, enhanced recall of associated topic information.
(Kiewra, et al., 1997)

Self-eficacy was the strongest predictor of spelling performance at all grade levels; attribution for ability entered into the regression for grade 4 students, while outcome expectations for school and writing were most important in grades 7 and 10. (Rankin, Bruning, & Timme, 1994, 213)

Individuals’ ratings of self-efficacy have been shown to relate strongly to general academic achievement (Schunk, 1984), reading (Bruning, Shell, and Colvin, 1987; Nicholls, 1979; Paris and Oka, 1986; Shell, Murphy and Bruning, 1989), writing (McCarthy, Meier, and Rinderer, 1985; Rankin, Bruning, Timme, and Katkanant, 1993; Shell et al, 1989), and spelling (Rankin et al, 1993). (Rankin, Bruning, & Timme, 1994, 214)

Causal attributions, like other belief variables, have also been shown to exert a powerful influence on expectations for future performance (Weiner, 1977, 1979, 1986); attributions for ability and effort have been shown to be among the most influential of these. Ability is considered to be a failry stable factor, while effort is presumably more changeable due to the belief that it is under an individual’s voluntary control (Schunk, 1984). Causal attributions reflecting an internal locus of control have been found to relate to perceptions of reading ability (NIcholls, 1979) and reading achievement (Paris and Oka, 1986).
(Rankin, Bruning, & Timme, 1994, 214)

Directions were read orally to all groups; individual items were read orally to the grade 4 students only. (Rankin, Bruning, & Timme, 1994, 217)

Attributions of effort or ability did not relate to actual spelling performance for these students. However, effort was related to spelling self-efficacy for grade 7 and 10 students, indicating that students who judge effort (Trying hard to spell correctly) to be important to good spelling tend to be those who have greater confidence in their ability as spellers. (Rankin, Bruning, & Timme, 1994, 223)

At grades 7 and 10, however, outcome expectancies, entered significantly into the prediction fo spelling performance. At both grades, outcome expectancy for school was a negative predictor of spelling performance (partial rs of -.188 and -.316 for grades 7 and 10, respectively), while outcome expectancy for writing was a positive predictor (partial rs of .174 and .150, respectively) (Rankin, Bruning, & Timme, 1994, 225)

Specifically, we show that inferences of competence, based solely on the facial appearance of political candidates and with no prior knowledge about the person, predict the outcomes of elections for the U.S. Congress.
(Todorov, et al., 2005, 1623)

Yet, from a psychological perspective, rapid automatic inferences from the facial appearance of political candidates can influence processing of subsequent information about these candidates. (Todorov, et al., 2005, 1623)

As shown in Table 1, the candidate who was perceived as more competent won in 71.6% of the Senate races and in 66.8% of the House races (13). Although the data for the 2004 elections were collected before the actual elections (14), there were no differences between the accuracy of the prospective predictions for these elections and the accuracy of the retrospective predictions for the 2000 and 2002 elections (15). (Todorov, et al., 2005, 1624)

Our findings have challenging implications for the rationality of voting preferences, adding to other findings that consequential decisions can be more “shallow” than we would like to believe (31, 32). Of course, if trait inferences from facial appearance are correlated with the underlying traits, the effects of facial appearance on voting decisions can be normatively justified. (Todorov, et al., 2005, 1625)