Category Archives: UNL / Cognition & Technology

The Wary Student, Part 10: Future Research

This study is part of a program of research which works to develop methods for increasing performance with a minimum of direct training. These projects assume that students are not rational agents and not reflective, that their understanding of their cognition is limited and that declarative knowledge typically does not alter scholar performance. Therefore, a battery of tests, surveys, and previous research is assembled to show how better behavior and superior procedural knowledge can be taught without relying on rational decision making, declarative knowledge, or like methods.

By establishing how wary student behavior is effected by cognitive load, this paper demonstrates how procedural learning can occur without descriptive learning. Related work has already been done, though it may frame the results as altering the environment to produce academic performance (Horn, PytlikZillig, Bruning, & Kauffman, 2003; Dempsey, PytlikZillig, & Bruning, 2005; PytlikZillig, Bruning, Horn, & Bodvarsson, 2005). The ultimatum game has been used as a device to show how rational behavior increases through practice, not necessarily rather than increased explicit understanding of concepts (Lusk & Hudson, 2004; Slonim & Roth, 1998).

In this research program, two studies at varying student cooperative behavior, a survey will examine expertise-related behavior, ongoing work focuses on recall behavior, and a theoretical project seeks to divest metacognition from rational agency. This research, and an already conducted experiment on how political orientation can alter cooperation, shows how high level behaviors (how students interact with each other) is altered by seemingly unrelated factors and unrelated with explicit beliefs about punishment. Work on creativity, talent, and expertise, of which a pilot study is already complete led, show while the behavior of expertise within a domain tends to be similar, the experts themselves then to be ignorant of what makes them successful. Additionally, a pre-existing program project of studying and note-taking behavior (Brenton, Kiewra, Whitfil, & Dennison, 1993; Igo, Bruning, McCrudden, & Kauffman, 2003; Titsworth & Kiewra, 2004; Igo, Bruning, & McCrudden, 2005a; 2005b) will be extended. Lastly, the literature of rationality (for example, Moshman, 2005) will be presented in a way that makes it clear how disbelief in the power of descriptive knowledge still allows educational psychologist to keep their well-worn and trusty tool kit.

The purpose of education is to improve performance. While performance boils down to reading and writing ability for some fields, for the mass of students a focus on explicit learning may be misguided. This study, and this research program, therefore seeks ways to improve performance without spending time on declarative knowledge that could be more valuably spent elsewhere.


The Wary Student, a tdaxp research project
1. Abstract
2. Cognitive Load
3. Cooperative Behavior
4. Method
5. The Experiments
6. Hypotheses
7. Main-Effect Results
8. Interaction-Effect Results
9. Discussion
10. Future Research
11. Bibliography

The Wary Student, Part 9: Discussion

The most parsimonious explanation for the results is that humans behave more rationally and less cooperatively when under cognitive load, at least when it comes to retribution. This echoes (Bazerman, White, & Lowenstein, 1995), which found the same increased rationality and decreased fairness when decisions had to be made simultaneously, and fits other findings (Robert & Carnevale, 1997) that socially complex situations create more rational behavior.

The interaction effect shows that cognitive load primarily effects those who would behave cooperatively, but that it has little effect on those who would behavior selfishly. This finding supports the view that humans cooperative warily. Cognitive load did not effect those who acted selfish because they had already ceased cooperating, so could only effect those who have cooperated somewhat already.

Interestingly, a one-way ANOVA with student belief on whether rulebreakers should be forgiven as a factor showed equivalent means across neutral cooperation (F = .253, p = .616), negative cooperation (F = .007, p = .935), and cognitive load (F = .029, p = .864) if the rulebreaker was sorry. Nearly identical results (F = 504, p = .479; F = .504, p = .479; F =.005 , p = 944; sic) were found without the “sorry” clause. In other words, descriptive knowledge about punishment did not translate into procedural knowledge about punishment and, unlike procedural knowledge, did not vary by cognitive load.


The Wary Student, a tdaxp research project
1. Abstract
2. Cognitive Load
3. Cooperative Behavior
4. Method
5. The Experiments
6. Hypotheses
7. Main-Effect Results
8. Interaction-Effect Results
9. Discussion
10. Future Research
11. Bibliography

The Wary Student, Part 8: Interaction-Effect Results

Because the negative cooperation p value missed .01 (.033) significance because of the Bonferroni correction, an analysis of covariance (ANCOVA) was attempted in order to increase the power of the statistical tests. The ANCOVA analysis attempts to use a second variable (called a “covariate” or CV) to explain some of the sample variation in the dependent variable (DV), which increases the observed power of the independent variable (IV). In order to run an ANCOVA, two assumptions must be made: first the CV is correlated with the DV but not the DV, and that the DV and and the IV do not interact. This second requirement called the homogeneity of regression, is similar to the homogeneity of variance test used in the ANOVA

Only one of the assumptions for ANCOVA was met. A perason’s correlation showed that the test for neutral cooperation was positively correlated with negative cooperation (F = .298, p < .01) but not correlated with cognitive load (F = .004, p = .955). Then, to test the homogeneity of regression assumption a two-way ANOVA was run with both the IV and the CV as independent variables. The results failed to allow an ANCOVA, but are fascinating in their own right.


Raw visualization of the interaction effect.
Cognitive load decreases the negative cooperation of those who were neutrally cooperative

Specifically, the two-way ANOVA results (F = 22.257, p = .0000048, η2 = .112) show a strong interaction effect. That is, cognitive load strongly effects the negative cooperative behavior of those who are neutrally cooperative. In this two-factor ANOVA, both cognitive load (F = 25.144, p = 0.0000013) and neutral cooperation (F = 15.171, p = 0.00014) were significant. Tukey post-hoc tests were not run because both condition and neutral cooperation had only two levels. Among those who accepted the unfair allocate resources, increased cognitive load barely altered the degree of negative cooperation (decreasing it from an average of .09 to .07 points). However, among those who rejected the unfair division, higher cognitive load reduced negative cooperation (from n = 21, μ = .8571, to n = 20, μ = 0).


The Wary Student, a tdaxp research project
1. Abstract
2. Cognitive Load
3. Cooperative Behavior
4. Method
5. The Experiments
6. Hypotheses
7. Main-Effect Results
8. Interaction-Effect Results
9. Discussion
10. Future Research
11. Bibliography

The Wary Student, Part 7: Main-Effect Results

For every hypothesis, a homogeneity of variance test (HOV) was first run, using both Leven’s criterion and a calculated Fmax value. Next, an analysis of variance (ANOVA) was used to attempt to reject the appropriate null hypothesis. Two measures of practical effect size are reported. η2, which explains the fraction of the variation within the sample explained by the IV, can be calculated at SSb / (SSb + SSw). ω2, which shows the fraction of the variation in the sample that is explained by the IV, is derived with the formula ω2 = (SSb – (k – 1)(MSw)) / (SSb + SSw + MSw). Then, in the next section, an interaction effect is discussed.

Hpositive: Does Cognitive Load impact Positive Cooperation?

The HOV and ANOVA give the following results:

Purpose Test Value Interpretations
HOV Levene’s F(1,177) = 4.340
p = .039
Reject homogeneity of variance
HOV Fmax 1.61 / 1.27 = 1.43 Safe to assume homogeneity of variance
Between Participants ANOVA F = 2.257
p = .135
η2 = .013
ω2 = .007
No statistically significant effect

The results do not allow the null hypothesis. While the practical significance of cognitive load on positive cooperation is 7%, the statistical effect, the p value of .135 indicates that results could be achieved by chance 13.5% of the time. For comparison, because three hypotheses are being made a p value of .0033 would be needed to even say that the results would only be found by change 5% of the time. While evolutionary responses have been found even after cognitive load has been shown to be ineffective (Hewstone, Hantzi, & Johnston, 1991; Kurzban, Tooby, & Cosmides, 2001), the results are clearly not encouraging. Finally, while the homogeneity results were ambiguous, with Fmax and Levene’s test giving different results, this is not a concern as failing to reject HOV increases the chance of a false positive, which is not an issue in this case.


Hneutral: Does Cognitive Load impact Neutral Cooperation?

The HOV and ANOVA give the following results:

Purpose Test Value Interpretations
HOV Levene’s F(1,179) = .013
p = .013
Reject homogeneity of variance
HOV Fmax 1.61 / 1.27 = 1.41 Safe to assume homogeneity of variance
Between Participants ANOVA F = .003
p = .955
η2 = 0
ω2 = 0
No statistically significant effect

The results were neutral cooperation were even less promising that the results for positive cooperation. Not only was there no practical significance to the results, such results would be found by change nearly 96% of the time. As for the previous hypothesis, problematic results on the HOV tests are a non issue as the null hypothesis Hneutral is not rejected.

Hnegative: Does Cognitive Load impact Negative Cooperation?

The HOV and ANOVA give the following results:

Purpose Test Value Interpretations
HOV Levene’s F(1,179) = 29.568
p < .001
Cannot reject homogeneity of variance
HOV Fmax .697 / .315 = 1.99 Safe to assume homogeneity of variance
Between Participants ANOVA F = 7.109
p = .008
η2 = .038 ω2 = .033
Statistically significant effect at corrected .05 and uncorrected .01 level, which explains % of variance in the population

While results were poor with positive and neutral cooperation, the negative null hypothesis can be firmly rejected. The p value of .008 is enough to say that the results would be achieved by change less than 2.5% of the time, even after adjusting for running three hypotheses. The ANOVA indicates that the cognitive load condition explained more than 3% of the variation within the population. Because the null hypothesis is rejected, the disagreement between Levene’s test (which fails to reject heterogeneity of variance) and Fmax becomes a concern. Adding a factor to the analysis, as is done in the next section, clarifies the results for this hypothesis and removes the fear that unequal variance is unduly biasing the results.


The Wary Student, a tdaxp research project
1. Abstract
2. Cognitive Load
3. Cooperative Behavior
4. Method
5. The Experiments
6. Hypotheses
7. Main-Effect Results
8. Interaction-Effect Results
9. Discussion
10. Future Research
11. Bibliography

The Wary Student, Part 6: Hypotheses

Substantively, three hypothesis were made: increasing cognitive load will alter positive cooperation, increasing cognitive load will alter neutral cooperation, and increasing cognitive load will alter negative cooperation. In statistical notation, the null hypotheses for these can be written as follows:

Hpositive,0,: μpositive cooperation,high cognitive load = μpositive cooperation,low cognitive load,
Hneutral,0: μneutral cooperation, high cognitive load = μneutral cooperation, low cognitive load
Hnegative,0: μnegativecooperation,high cognitive load = μnegative cooperation, low cognitive load.

Because three separate questions are tested using the same sample variation, a Bonferroni adjusted was made. Therefore, results are reported using both .05 and a .017 (α = α / k = .05 / 3 = .017) levels, and .01 and .0033 ( α = α / k = .01 / 3 = .0033) levels. Through the experiment, the independent variable (IV) is cognitive load condition, and the dependent variable (DV) is the type of cooperation being examined.


The Wary Student, a tdaxp research project
1. Abstract
2. Cognitive Load
3. Cooperative Behavior
4. Method
5. The Experiments
6. Hypotheses
7. Main-Effect Results
8. Interaction-Effect Results
9. Discussion
10. Future Research
11. Bibliography

The Wary Student, Part 5: The Experiments

The experimental set-up was a variation of Alford & Hibbing (2006a) and tdaxp & Johnson (2007). 181 undergraduate students in the political science department of a large midwestern university were recruited to be participants over a period of six days. The experiment was designed and prepared with OpenOffice.org drawing software, the Audacity sound editor, and the perl programming language and finally implemented with MediaLab research software. Participants answered survey questions and played economics games. The experiment was contrived to simulate interaction with fellow classmates in distance education group work

Two games were studied as part of this research. Before the participants played these games, they were randomly assigned into a high-cognitive load or a low-cognitive load condition. The experiment differed from both tdaxp & Johnson (2007) and Alford & Hibbing (2006a) in that the tasks were framed as part of a group project, instead of as an economic game. Framing effects have been observed before (Larrick & Blount, 1997), and may have their effect, because ultimatum game performance chances depending on the norms of a people (Henrich, et al., 2005) or a workplace (Kay, Wheeler, Bagh, & Ross, 2004).

First, positive cooperation is studied. Participants were seated at computers and told they were testing new interfaces for distance education. They were told that their actions in the first part of the experiment will only effect the grades of other students. However, they would have an opportunity to gain additional extra credit at a later part of the task. The participants were instructed that the students they were assisting was at another campus, and that all identities would remain anonymous. After a structured introduction, the students were given a series of mathematical problems to solve both for themselves and for the other students. Which problem would help which student was clearly labeled. Positive cooperative behavior is measured by the number of altruist attempts participants made to solve the other student.


The students were then informed that their task was over. They were informed that another portion of the experiment was to measure cooperative behavior in distance education classes. Unbeknownst to the student, the second portion of the experiment would be an ultimatum game, “where one of the players can firmly commit himself in advance under a heavy penalty that he will insist under all conditions upon a certain specified demand (which is called his ultimatum)” (Harsanyi, 1961, 190).

The ultimatum game has been studied in educational settings (Stanley & Tran, 1998; Stodder, 1988; Oxoby, 2001), for professional populations (Bethwaite & Tompkinson, 1996), and across the world (Bowles & Gintis, 2000; Gowdy, Iorgulescu, & Onyweiwu, 2003). It has been summarized as follows:

In the Ultimatum Game, two players are offered a chance to win a certain sum of money. All they must do is divide it. The proposer suggests how to split the sum. The responder can accept or reject the deal. If the deal is rejected, neither player gets anything. The rational solution, suggested by game theory, is for the proposer to offer the smallest possible share and for the responder to accept it. If humans play the game, however, the most frequent outcome is a fair share. (Nowak, Page, & Sigumd, 2000, 1773)

The participant was then informed that the other student was given the opportunity to split extra credit points with the participant. These extra credit points were designed to reward cooperative students. The participant was informed that the other student believed that a 4-to-1split of extra points was fair. If this was accepted, the other student’s point total would be raised by 4 extra credit points while the participant’s score would be raised by only one. Alternatively if the participant refused, neither would gain these additional extra credit points. Rejection of the unfair split, an altruist act as it reduces personal gain and potentially teaches the other student a lesson that the participant could not benefit from, is defined as neutral cooperation.

Next, participants were informed they would be able to “punish” the other student with points they had earned for attending the experiment. If the participant had accepted the unfair split, then he or she had potentially six points to punish with. Alternative, if the participant had behaved neutrally cooperatively, only five such points would be available. The magnitude of retributive punishment measured is defined as negative cooperation.
Following the completion of the experiment, participants were debriefed and thanked for their time. Deception was used in the study, so that all participants received ten points of extra credit regardless of their performance.
Hypotheses

Substantively, three hypothesis were made: increasing cognitive load will alter positive cooperation, increasing cognitive load will alter neutral cooperation, and increasing cognitive load will alter negative cooperation. In statistical notation, the null hypotheses for these can be written as follows:
Hpositive,0,: μpositive cooperation,high cognitive load = μpositive cooperation,low cognitive load,
Hneutral,0: μneutral cooperation, high cognitive load = μneutral cooperation, low cognitive load
Hnegative,0: μnegativecooperation,high cognitive load = μnegative cooperation, low cognitive load.
Because three separate questions are tested using the same sample variation, a Bonferroni adjusted was made. Therefore, results are reported using both .05 and a .017 (α = α / k = .05 / 3 = .017) levels, and .01 and .0033 ( α = α / k = .01 / 3 = .0033) levels. Through the experiment, the independent variable (IV) is cognitive load condition, and the dependent variable (DV) is the type of cooperation being examined.


The Wary Student, a tdaxp research project
1. Abstract
2. Cognitive Load
3. Cooperative Behavior
4. Method
5. The Experiments
6. Hypotheses
7. Main-Effect Results
8. Interaction-Effect Results
9. Discussion
10. Future Research
11. Bibliography

The Wary Student, Part 4: Method

Cognitive load is composed of the the “the number and nature of component skills involved.. and the complexity of the goal hierarchy” (Paas & van Merrienboer, 1994, 355). This load can be subdivided into the intrinsic, germane, and extrinsic (Sweller, van Merrienboer, & Paas, 1998), or the essential, the incidental, and the representational (Mayer & Moreno, 2003). While other studies have examined cognitive load by reducing its extrinsic component (Bannert, 2002) or altering its intrinsic component (Gerjets, Scheiter, & Catrabone, 2004), this research will examine the effects of raising cognitive load.

The experiment varied extrinsic/incidental cognitive load in three ways: visually, audibly, and internally. When instructions for a task are complex, physical visual integration of the material is important to reduce cognitive load (Chandler & Sweller, 1991), so information is physically separated where possible in the high cognitive load condition. Likewise, cognitive load is increased when music is combined with instructions on an audible channel (Moreno & Mayer, 2000), so overlapping sound channels were used to increase bad audible cognitive load. Additionally, internal cognitive load can be overloaded by presenting redundant information on visual and auditory channels. These aspects of cognitive load are the the split-attention effect (where information is physically separated on a page) and redundancy effect (where information is repeated in different media) (Kalyuga, Chandler, & Sweller, 2000). The effect of this load on different forms of cooperation – positive, neutral, and negative – will be the studied in an experiment.


The Wary Student, a tdaxp research project
1. Abstract
2. Cognitive Load
3. Cooperative Behavior
4. Method
5. The Experiments
6. Hypotheses
7. Main-Effect Results
8. Interaction-Effect Results
9. Discussion
10. Future Research
11. Bibliography

The Wary Student, Part 3: Cooperative Behavior

Cooperative behavior depends on the behavior of others (Alford & Hibbing, 2004). People “want a reputation as a fair, desirable, possibly generous, but certainly not foolish person [but also] worry about members oft the group who would take advantage of others if given the chance” (Hibbing & Alford, 2004, 65). Wary cooperation is a typical human behavior, and folks are “inherently disposed to be group oriented, high sensitive to be taken advantage of, and willing to incur costs to punish others who are perceived as putting themselves above the group” (Smith, 2006, 1013). This study extends previous research to see if cognitive load, like social interactions, can alter cooperative behavior.

The perception of justice is an important factor in predicting cooperative behavior, as it does to other aspects of human behavior (Gold, Darley, Hilton, & Zanna, 1984; Tang, Tang, & Tang, 2000; Hibbing & Theiss-Morse, 2001). Fairness can effect student resistance to teacher-imposed order (Paulsel & Chory-Assad, 2005). Teachers may encourage peer interaction and peer punishment,, either explicitly (Mann, 2006) or by using technological tools that encourage its spontaneous emergence (Ronen & Langley, 2004).


Types of Cooperative Behavior

That students often don’t use tools to maximize their position is often seen as a problem (PytlikZillig, Horn, & White, 2003). Yet, viewing potentially disruptive students as social altruists helps to get the most of out every student. Deviant students can help provide examples of rules for other learners (Stevenson, 1991). Indeed, “classrooms are not characterized simply by the things teachers do to students to further their learning. Instead, classrooms take on their characteristics as teachers and students alternatively influence and our influenced by one another” (Copeland, 1980, 164). Other studies and surveys have discussed the reciprocal nature of this learning (Klein, 1971; Doyle, 1979).


Research on cooperative behavior frames altruism in evolution terms (Alford & Hibbing, 2004; Hibbing & Alford, 2004), as cognitive load research emphasizes its own evolutionary component (Sweller, 2004; 2006; van Merrienboer & Sweller, 2005). Evolution and cognitive theories complement each other (Bjorklund & Pellegrini, 2002): for instance, gut reactions are driven by a lower-order system (Shiv, 2003) that is not available for introspection (Kahneman, 2003) and is revealed under cognitive load (Lieberman, Gaunt, Bilbert, & Trope, 2002). While certainly some evolved mechanisms can rely on conscious thought (Barrett, Federick, Haselton, & Kurzban, 2006; Tooby & Cosmide, 2005), this study is firmly in line with those (Barrett, Federick, Haselton, & Kurzban, 2006; Tooby & Cosmide, 2005) that have tested evolutionary hypotheses with cognitive load.

Likewise, educational psychologists study behavior because of its impact on performance. Behavior, like intelligence, strongly predicts school performance, and behavior is more amenable to modification than intelligence (Harper, Guidubaldi, & Kehle, 1978). Similarly, continued and intense practice (behavior) in an area has a great deal of influence on developing expertise (Weisberg, 1993; Kiewra, 1994; Csikszentmihalyi, 1996), more so than even native talent in that field (Gardner, 1998).


The Wary Student, a tdaxp research project
1. Abstract
2. Cognitive Load
3. Cooperative Behavior
4. Method
5. The Experiments
6. Hypotheses
7. Main-Effect Results
8. Interaction-Effect Results
9. Discussion
10. Future Research
11. Bibliography

The Wary Student, Part 2: Cognitive Load

The portion of cognitive ability that is required to perform some task is referred to as cognitive load (Sweller, 1988). Cognitive load, while discovered in their contemporary form in the 1980s and 1990s (Sweller & Chandler, 1991), they have been observed for generations (Miller, 1937; Sonneschein, 1982 Sweller & Chandler, 1994) in many domains (Mwangi & Sweller, 1998). People use their cognitive abilities to interact with each other. Group interaction between students “does not naturally occur, but has to be explicitly initiated and maintained by them” (Hron & Friedrich, 2003, 72) and can be cognitively expensive (Dillenboug, 1999; Knowles, Morris, Chiu, & Hong, 2001).

While cognitive load theory focuses mostly on learning (Paas & Kester, 2006), researchers have studied how it effects behavior, too. Decision making (Todd & Benbasat, 1994; Dhar, Nowlis, & Sherman, 2000; Drolet & Luce, 2004), eating (Ward & Mann, 2000), fear conditioning (Carter, Hofstotter, Tsuchiya, & Koch, 2003), infidelity (DeStano, Bartlett, Braveman, & Salovey, 2002), lying (Vrij, Semin, & Bull, 1996; Vrij, Akehurst, & Knight, 2006), marketing (Ariely, 2000, Raghubir & Krishna, 1996), problem solving (Sweller, 1988), racism (Hewstone, Hantzi, & Johnston, 1991). and risk aversion (Benjamin, Brown, & Shapiro, 2006) have been been examined through cognitive load.

Further, in a distance environment this must be done without typical social cues that clarify meaning and tell people when to start and stop talking (Friedrich, Hron, & Hesse, 2001). Educational psychologists have begun to look seriously at how to turn this around and integrate social interaction into instructional web design (Lehman, Bruning, & Horn, 2003). Technology is not a silver bullet (Bruning, 2004) and can decrease performance when used incorrectly (Cramton, 2001). Therefore, considering how cognitive load already imposes size limits on groups (Cosmides & Tooby, 2004; Dillenbourg & Schneider, 1995) and forces students to rely on stereotypes (Fiske, 2000), the intersection of educational technology and cognitive load should be of particular concern to educational psychologists.


The Wary Student, a tdaxp research project
1. Abstract
2. Cognitive Load
3. Cooperative Behavior
4. Method
5. The Experiments
6. Hypotheses
7. Main-Effect Results
8. Interaction-Effect Results
9. Discussion
10. Future Research
11. Bibliography

The Wary Student, Part 11: Bibliography

Works alphabetically beginning with “A” above the fold. Everyone else below:

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. (2006a). The Neural Basis of Representative Democracy. Paper presented at the Hendricks Conference on Biology, Evolution, and Political Behavior.
Alford, J., & Hibbing, J. (2006b). Could Political Attitudes Be Shaped by Evolution Working Through Genes? Tidsskriftet Politik: August 2006 edition.
Ariely, D. (2000). Controlling the information flow: Effects on consumer’s decision making and preferences. The Journal of Consumer Research, 27(2), 233-248.


Bannert, M. (2002). Managing cognitive load – recent trends in cognitive load theory. Learning and Instruction, 12, 139-146.
Barrett, H. C., Frederick, D. A., Haselton, M. G. & Kurzban, R. (2006). Can manipulations of cognitive load be used to test evolutionary hypotheses? Journal of Personality and Social Psychology, 91(3), 513-518.
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.
Benjamin, D. J., Brown, S. A., & Shapiro, J. M. (2006). Who is ‘behavioral’? Cognitive ability and anomalous preferences. Unpublished manuscript. Available online: http://www.dklevine.com/archive/refs4122247000000001334.pdf.
Benton, S.L., Kiewra, K.A., Whitfil, J.M., & Dennison, R. (1993). Encoding and external-storage effects on writing processes. Journal of Educational Psychology, 85(2), 267-280.
Bethwaite, J. & Tompkinson, P. (1996). The ultimatum game and non-selfish utility functions. Journal of Economic Psychology, 17(2), 259-271.
Bowles, S. & Gintis, H. (1999). Is equality passe? Boston Review, 23(6). Retrieved online http://bostonreview.net/BR23.6/bowles.html.
Bruning, R. (2004). Technological contexts for cognitive growth. Chapter 10 in R. Bruning, G. Schraw, M. Norby, & R. Ronning. Cognitive psychology and instruction (4th ed.). Upper Saddle River, NJ: Merrill Prentice Hall.
Bjorklund, D. F., & Pellegrini, A. D. (2002). The origins of human nature: Evolutionary developmental psychology. Washington, DC: American Psychological Association.

Carter, R.M., Hofstotter, C., Tsuchiya, N., & Koch, Christof. (2003). Working memory and fear conditioning. PNAS, 100(3), 1399-1404.
Chandler, P. & Sweller, J. (1991). Cognitive load theory and the format of instruction. Cognition and Instruction, 8(4), 293-332.
Cramton, C.D. (2001). The mutual knowledge problem and its consequence for dispersed collaboration. Organization Science, 12(3), 346-371.
Csikszentmihalyi, M. (1996). Creativity: Flow and the psychology of discovery and invention. HarperCollins: New York.
Copeland, W.D. (1980). Teaching-learning behaviors and the demands of the classroom environment. The Elementary School Journal, 80(4), 163-177.
Cosmides, L., & Tooby, J. (2004). Knowing thyself: The evolutionary psychology of moral reasoning and moral sentiments. In R. E. Freeman & P. Werhane (Eds.), Business, science, and ethics: The Ruffin series (No. 4, pp. 93–128). Charlottesville, VA: Society for Business Ethics.

Dempsey, M.S., PytlikZillig, L.M., & Bruning, R. (2005). Building writing assessment skills using web-based cognitive support features, in Lisa M. PytlikZillig, Mary Bodvarrson, & Roger Bruning, Eds. (pp. 83-106). Technology-based education: Brining researchers and practitioners together. Greenwich, CT: Information Age Publishing.
DeSteno, D., Bartlett, M., Braverman, J., & Salovey, P. (2002). Sex differences in jealousy: Evolutionary mechanism or artifact of measurement? Journal of Personality and Social Psychology, 83, 1103-1116.
Dhar, R., Nowlis, S.M., & Sherman, S.J. (2000). Trying hard or hardly trying: An analysis of context effects in choice. Journal of Consumer Psychology, 9(4), 189-200.
Dillenbourg, P. & Schneider, D. (1995). Mediating the mechanisms which make collaborative learning sometimes effective. International Journal of Educational Telecommunications, 1(2/3), 131-146.
Dillenbourg, P. (1999) What do you mean by collaborative learning?. In P. Dillenbourg (Ed) Collaborative-learning: Cognitive and Computational Approaches. (pp.1-19). Oxford: Elsevier.
Doyle, W. (1979). Classroom effects. Theory into Practice, 18(3), 138-144.
Drolet, A. & Luce, M.F. (2004). The rationalizing effects of cognitive load on emotion-based trade-off avoidance. Journal of Consumer Research, 31, 63-77.

Fiske, S.T. (2000). Stereotyping, prejudice, and discrimination at the seam between the centuries: Evolution, culture, mind, and brain. European Journal of Social Psychology, 30(3), 299-322.
Friedrich, H.F., Hron, A., & Hesse, F.W. (2001). A framework for designing and evaluating virtual seminars. European Journal of Education, 36(2), 157-174.

Gardner, H. (1998). Extraordinary minds. Basic Books: New York, NY.
Gerjets, P., Scheiter, K., & Catrabone, R. (2004). Designing instructional examples to reduce intrinsic cognitive load: Moral versus modular presentation of solution procedures. Instructional Science, 32, 33-58.
Gold, L.J., Darley, J.M., Hilton, J.L., & Zanna, M.P. (1984). Children’s perceptions of procedural justice. Child Development, 55(5), 1752-1759.
Gowdy, J., Iorgulescu, R., & Onyeiwu, S. (2003). Fairness and retaliation in a rural Nigerian village. Journal of Economic Behavior & Organization, 52(4), 469-479.

Harper, G.F., Guidubaldi, J., & Kehle, T.J. (1978). Is academic achievement related to classroom behavior? The Elementary School Journal, 78(3), 202-207.
Harsanyi, J.C. (1961). On the Rationality Postulates Underlying the Theory of Cooperative Games. The Journal of Conflict Resolution 5(2): 179-196.
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.
Hewstone, M., Hantzi, A., & Johnston, L. (1991). Social categorization and person memory: The pervasiveness of race as an organizing principle. European Journal of Social Psychology, 21(6), 517-528.
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The Wary Student, a tdaxp research project
1. Abstract
2. Cognitive Load
3. Cooperative Behavior
4. Method
5. The Experiments
6. Hypotheses
7. Main-Effect Results
8. Interaction-Effect Results
9. Discussion
10. Future Research
11. Bibliography