Can you accurately judge a person by their shoes?

Yes, for some things.

Giliath et al. (2012) tested whether undergraduate students at the University of Kansas could accurately identify the traits of selected people by looking at their most commonly worn pair of shoes.

The researchers found that the observers could reliably judge the age, gender and income of the owners of the shoes. Interestingly, the observers were very accurate at predicting attachment anxiety.

Unfortunately, observers were not so good at predicting the Big Five personality traits: extraversion, conscientiousness, openness to experience, agreeableness and emotional stability. But of the five, they were most accurate at predicting agreeableness, though the researchers found that the observers were judging agreeableness from the clues they had picked up on age, income and gender, rather than from the shoes themselves.

So yes, you can judge a person by their shoes.

How to to follow through on your goals using framing.

Focus on intrinsic aspect of a goal, instead of the extrinsic. 

Vansteenkiste et al. (2007) explored the different effects that arose from intrinsic and extrinsic goals.

Intrinsic goal pursuit is said to be associated with more well-being and lower ill-being, because intrinsic goals tend to be associated with the satisfaction of the basic needs for autonomy, competence, and relatedness (Deci & Ryan, 2000; Ryan, 1995), whereas extrinsic goal pursuit is unrelated or even tends to detract from basic need satisfaction (Niemiec, Deci, & Ryan, 2006; Vansteenkiste, Neyrinck et al., in press).

Further, past research has shown that the more importance individuals attach to extrinsic, relative to intrinsic, goals, the more they show signs of poor psychological and social well-being, the more they report depressive and physical health complaints, and the more socially aggressive and prejudiced attitudes they adopt (e.g.,Duriez, Vansteenkiste, Soenens, & De Witte, 2006; Kasser & Ryan, 1993; for an overview, see Kasser, 2002; Kasser, Vansteenkiste, & Duckop, in press).

The difference between an extrinsic and intrinsic frame is primarily how similar the motivation for completing the goal is to the need to impress others or be validated by others.

…two types of goals have been studied: intrinsic goals (i.e., self-development, health and physical fitness, community contribution, and affiliation), which reflect people’s inherent growth tendencies and which are characterized by an inward-oriented frame, and extrinsic goals (i.e., financial success, power, status, and physical attractiveness), which reflect people’s desire to impress others by acquiring external signs of worth and which yield an outward-oriented focus

Ironically, focusing on intrinsic goals is more likely to help you achieve the aims of extrinsic goals than just focusing on extrinsic goals themselves.

To illustrate, the intrinsic goals of self-development and physical fitness might contribute to the satisfaction of competence by leading individuals to pursue challenging activities. The intrinsic goal of affiliation and helping the community might contribute to the formation of satisfying relational bonds, because these goals would lead one to be empathically concerned with and genuinely interested in other people (Vansteenkiste, Neyrinck et al., in press). In contrast, the effort that extrinsically oriented individuals put into an activity and the interest they show for other people is likely to be conditional, that is, depending on the extent to which one’s task engagement and other individuals help one in attaining one’s extrinsic ambitions. The unfortunate consequence of adopting such a narrow-focused approach towards activities (Vansteenkiste, Simons, Lens, Soenens, & Matos, 2005) and an “objectifying” stance towards others (Kasser, 2002) is that one is less likely to get one’s basic needs met.

Intrinsic framing also has a demonstrably positive effect on physical performance, as well.

It was found that framing participants’ exercise activities during a PE class in terms of an intrinsic goal resulted in increased performance and persistence over the short term (i.e., 1 week) and long term (i.e., 4 months) compared to an extrinsic goal condition (Vansteenkiste, Simons, Lens, Sheldon et al., 2004) and compared to a no-goal control group (Vansteenkiste, Simons, Soenens et al., 2004). Such results were found among 17–18-year-old adolescents and 11–12-year-old obese children (Vansteenkiste, Simons, Braet et al., 2006).

There is a questionnaire created by Duda (1989) called the Task and Ego Orientation in Sport Questionnaire, which is used to assess a participant’s task and ego goals.

A task goal refers to the desire to gain understanding, insight, or skill. Learning is valued as an end in itself and competence is defined with regard to a self-referential or absolute standard. In contrast, an ego goal refers to the desire to obtain better or to avoid obtaining lower grades and test scores in an achievement situation compared to others; hence, success versus failure is defined on the basis of a normative standard of competence.

This questionnaire has been used in many studies to find what correlates with task and ego goals.

These studies have generally found that task goals are associated with adaptive outcomes, including positive affect (Ntoumanis & Biddle, 1999), being self-disciplined in PE classes (Papaioannou, 1999; Spray & Wang, 2001), self-reported use of skill development and learning strategies (Lochbaum & Roberts, 1993; Solmon & Boone, 1993), self-determined exercise motivation (e.g., Standage, Duda, & Ntoumanis, 2003; Standage & Treasure, 2002), flow experiences (Papaioannou & Kouli, 1999), and actual physical activity engagement (e.g.,Dempsey, Kimieck, & Horn, 1993). Ego goals, in contrast, have been found to be associated with less-adaptive outcomes, including somatic anxiety (Papaioannou & Kouli, 1999), less intrinsic motivation (e.g.,Ferrer-Caja & Weiss, 2000), less free choice behavior (Cury, Famose, & Sarrazin, 1997), and social loafing (Swain, 1996), although some studies found an ego orientation to positively predict physical activity engagement outside school (Wang, Chatzisarantis, Spray, & Biddle, 2002).

So, focus on goals that are intrinsically motivated, like self-development, fitness, and affiliation; rather than extrinsically motivated goals such as power, wealth, and physical attractiveness. However, if you do want to have resolute desire to follow an extrinsically motivated goal, frame it  intrinsically. For example, if you want to lose weight or gain muscle to look more attractive, pay particular attention to to the intrinsic benefits such as how much further you can run, how much more weight you can lift, or how much healthier you are.

What simple trick can you use to make a statistic seem more truthful?

We are more likely to believe something is true, if it is framed in a negative way.

Hilbig (2009) performed three experiments to find whether there was a link between framing and the perceived truth of a statistic.

The first experiment was conducted as an online-survey. After providing consent and demographic information, participants were shown statistical information from the crime domain and instructed to provide a truth rating. As information, the success rate of crimes from the category of rape and aggravated sexual coercion (denoted ‘rape’ in what follows) was presented. The actual success rate (85%) was used. Half of the participants were told that 85% of attempted instances of rape were successful (negative frame), while the other half were told that 15% were unsuccessful (positive frame). All participants were then asked to judge the truth of the stated information on a 4-point scale.

The mean rating of truth from the negative frame group was significantly higher than that of the positive frame group. The second experiment replicated these results.

Following the logic of Experiment 1, the information frame was again manipulated. Thirty eight participants (30 female, aged M = 17.3, SD = .50, recruited from a high school course of introductory psychology) were randomly assigned to two groups. These were shown the actual clearance rate of rape (70%), either framed positively (70% of cases cleared) or negatively (30% of cases not cleared) and asked to judge, again on a 4-point scale, the truth of the provided statement.

Again, participants rate the statistic as more likely if it emphasised the negative.

The principal logic of [the third experiment] was again to manipulate the frame of the information presented (between participants) while holding the actual validity constant. In contrast to the previous experiments, the information was not from the crime domain but from demographics. Specifically, participants were shown the probability of a marriage to be divorced within the first 10 years which is, in Germany, about 20% (Federal Statistical Office, n.d.). Participants were randomly assigned to one of two conditions: in the positive frame, they were informed that 80% of marriages lasted 10 years or longer whereas their counterparts in the negative frame were informed that 20% of marriages were divorced within the first 10 years. Like in the previous experiments, participants rated the truth of this statement on a 4-point scale. The experiment was run using simple 1-page questionnaires dispersed to a community sample of 33 participants.

This third experiment also clearly demonstrated negativity bias. The exact results of each study are shown in the graph below.

Fig. 1. Mean truth ratings (original scale ranging from 1 to 4) for the negative vs. positive framing conditions in each of the experiments. Error bars represent one standard error of the mean.

However, this effect is not confined to estimations of truth.

First, it has been argued that negative instances are often more informative (Peeters & Czapinski, 1990) – parallel to the higher informativeness of disconfirming evidence (Leyens & Yzerbyt, 1992). So, there could be a simple direct association between valence and (perceived) veracity.

 We also tend to dwell on the negative and discuss it with each other.

 Secondly, there is evidence for increased elaboration of negative instances which has been termed ‘informational negativity effect’ (e.g. Lewicka, 1997; see also Lewicka, Czapinski, & Peeters, 1992).

Negativity bias doesn’t operate in its own, but alongside many other effects.

Finally, there is a noteworthy body of literature which confirms that more elaboration, deeper processing, and high processing motivation can increase the persuasiveness of messages (e.g. Petty and Briñol, 2008 and Shiv et al., 2004). Similarly, though investigating the realm of wishful thinking rather than negativity bias, Bar-Hillel, Budescu, and Amar (2008) showed that the causal link ‘I focus on, therefore I believe in’ (p. 283) is well-supported. Also, elaboration can increase the perceived truth of past-events, even and especially when these never happened, which has been explained as an effect of constructive processing (Kealy, Kuiper, & Klein, 2006).

What do effective language learners do differently?

Nearly all adults have wished to learn another language at some point in their lives, but not many actually accomplish it. Wong and Nunan, in their 2011 study, have attempted to outline specifically what effective language learners do that ineffective language learners don’t .

They list four styles of language learning developed by Willing (1994):

Communicative: These learners were defined by the following learning strategies: they like to learn by watching, listening to native speakers, talking to friends in English, watching television in English, using English out of class, learning new words by hearing them, and learning by conversation.

Analytical: These learners like studying grammar, studying English books and newspapers, studying alone, finding their own mistakes, and working on problems set by the teacher.

Authority-oriented: The learners prefer the teacher to explain everything, having their own textbook, writing everything in a notebook, studying grammar, learning by reading, and learning new words by seeing them.

Concrete: These learners tend to like games, pictures, film, video, using cassettes, talking in pairs, and practicing English outside class

In Wong and Nunan’s study they asked students learning english in Hong Kong to complete a questionnaire.

All undergraduate students were sent an email inviting them to complete the survey within a designated period of time. In all, 674 students responded to the survey. Of these, 77 reported that they had received grade A in the “Use of English” examination. Another 33 reported that they had received grades E and F on that exam. Thus the two groups being compared in this criterion groups design consisted of the “more effective learners” (n = 77) and the “less effective learners” (n = 33),

They then determined which learning style each student prefered.

Table 1. Learning style preferences of more and less effective students (n = 110).

                                   Communicative      Authority-oriented      Analytical      Concrete
More effective              41                           10                        13                   1
Less effective               11                            12                         4                   3

Interestingly, more than 50% of the more effective students preferred the communicative style of learning. But Wong and Nunan didn’t stay with broad styles, they identified exactly what techniques more and less effective learners employed.

The five most popular strategies of more effective learners were:

1.“I like to learn by watching/listening to native speakers.

2.“I like to learn English words by seeing them.”

3.“At home, I like to learn by watching TV in English.”

4.“In class, I like to learn by conversation.”

5.“I like to learn many new words.”

 

The five most popular strategies of less effective learners were:

1.“I like the teacher to tell me all my mistakes.”

2.“I like to learn English words by seeing them.”

3.“I like the teacher to help me talk about my interests.”

4.“I like to have my own textbook.”

5.“I like to learn new English words by doing something.”

Furthermore:

A chi-square analysis revealed significant differences between more and less effective students on nine of the thirty items on the questionnaire. They were as follows:

Item 6. In English class, I like to learn by reading.

Item 13. I like the teacher to explain everything to us.

Item 18. I like to study English by myself (alone).

Item 24. I like to learn many new words.

Item 29. At home, I like to learn by reading newspapers, etc.

Item 30. At home, I like to learn by watching TV in English.

Item 33. I like to learn by talking to friends in English.

Item 34. I like to learn by watching, listening to native speakers.

Item 35. I like to learn by using English outside class in stores etc.

Scores were significantly higher on all of these items for the more effective students, except for item 13 “I like the teacher to explain everything to us.” On this item, it was the less effective students whose scores were significantly higher.

Not only did more effective learners employ significantly different strategies, but they also (not surprisingly) spent more time per week learning.

Forty per cent of more effective learners reported spending between 1 and 5 h a week on English out of class. Twenty-nine per cent spent more than 10 h a week on English out of class. In contrast, no less effective learners spent more than 10 h a week out of class, and 70 per cent spent less than an hour a week on English out of class. These data indicate that more effective learners have a much greater propensity for self-direction, independent learning and autonomy than less effective students.

Table 2. Number of hours per week spent learning and practicing English out of class.

                                       Less than 1 h     1–5 h      6–10 h      More than 10 h
More effective            14                31           10                    22
Less effective           23                6             4                      0

So far, we have seen that strategy and effort are important, but what about the students attitude towards the importance of learning a language?

Table 3. Perception of the importance of English.

                                        Extremely important  Somewhat important   Not very important
More effective                  75                                    2                              0
Less effective                   32                                   1                               0

As the table above demonstrates, nearly all of the students from both the less effective and more effective groups reported that learning english was extremely/very important. Their reporting that learning english was important had no effect on their capacity to actually learn the language. However, the was a large difference in reported enjoyment of learning english.

The aspect of enjoyment of learning English also revealed a significant difference between more and less effective students. Seventy-eight per cent of more effective but only twenty-seven per cent of less effective students reported enjoying English a great deal. On the other hand, twenty-four per cent of less effective students reported that they did not like learning English at all.

Table 4. Enjoyment in learning English.

                                                    A great deal       Somewhat      Not very/not at all
More effective students           60                    16                        1
Less effective students            9                      16                        8

Although more effective students overwhelmingly stated that they enjoyed learning english “a great deal”, this may be due to their enjoying their success at english. The less effective learners were likely not enjoying their slow progress.

The key variables differentiating the four language learning styles were cognitive style (field dependent versus field independent) and personality (active versus passive). Placing these on a grid creates four semantic spaces to which the four styles can be assigned

Fig. 1. The four language learning styles.

The more effective learners generally fell in the communicative quadrant of the grid. This style is a combination of active and field independent. Field independency is a type of cognitive thinking characterised by a person who uses their inner knowledge to solve problems, and doesn’t rely on the current frame of the problem. A field dependent cognitive style is the opposite: it is characterised by the use of outside knowledge to solve a problem and constance reference to the current frame.

The dominant style of the more effective language learners was communicative. These learners can be characterized as field independent and active.

The dominant style for the less effective language learners, on the other hand, was authority-oriented. These learners exhibit characteristics of field-dependence and passivity. This learner type prefers structure and sequential progression. They do better in ‘traditional’ classrooms and look on teachers as authority figures.

While the overall preferred style for the more effective learner was ‘communicative’, only three ‘communicative’ strategies emerged as significant: learning by watching TV, talking to friends in English and observing native speakers. These strategies are all consistent with the assertion by Norton and Toohey (2004) that effective language learners exercise human agency to gain access to communities. of language users that are external to the classroom.

So finally, the two rules of effective language drawn from this research are these:

1. Put in the hours.

This rule is the more obvious one. The more you work and the harder you work, the faster the results come.

2. Be active in you learning.

Do not rely on textbooks and teachers, but instead engage with the language by watching films in the language, reading newspapers and magazines, and talking to and observing speakers of the language. You do not need to be systematic in your approach; try to absorb a language through different channels and create an intuitive understanding.

Does your mind completely accept new knowledge?

No. Our childish understanding of the world lurks in our minds, even after we have learnt scientifically correct theories that refute that understanding.

The theory of knowledge restructuring tells us that once we have learnt new knowledge, the old knowledge is entirely replaced.

A number of recent findings have challenged this idea, however, by showing that early modes of thought do sometimes reemerge later in life. Alzheimer’s patients, for instance, have been shown to endorse teleological explanations for natural phenomena that typically only children endorse

Shtulman and Valcarcel (2012)

Whilst studies have shown that a child’s understanding of biology stays into adulthood, Shtulmand and Valcercel demonstrated that this phenomenon occurs across all knowledge groups.

…we compare the speed and accuracy with which adults verify two types of statements: statements whose truth-value is known to remain constant across conceptual change (e.g., “The moon revolves around the Earth,” which is true on both naïve and scientific theories of astronomical phenomena) and syntactically analogous statements whose truth-value is known to reverse across that same change (e.g., “The Earth revolves around the sun,” which is true on a scientific theory but not a naïve theory).

They predicted that “if naïve theories survive the acquisition of a mutually incompatible scientific theory, then statements whose truth-value reverse across conceptual change should cause greater cognitive conflict than statements whose truth-value remain constant, resulting in slower and less accurate verifications for those statements”

In their study, participants were asked to answer 200 true or false questions. There were twenty questions in ten different categories of knowledge.

A quarter of the statements were true on both naïve and scientific theories of the domain (“steal is denser than foam”), a quarter were false on both naïve and scientific theories (“foam is denser than brick”), a quarter were true on naïve theories but false on scientific theories (“ice is denser than water”), and a quarter were true on scientific theories but false on naïve theories (“cold pennies are denser than hot pennies”).

Table 1. The five concepts covered in each domain.

Domain	Concept
Astronomy	Planet, star, solar system, lunar phase, season
Evolution	Common ancestry, phylogeny, variation, selection, adaptation
Fractions	Addition, division, conversion, ordering, infinite density
Genetics	Heritability, chromosome, dominance, expression, mutation
Germs	Contagion, contamination, infection, sterilization, microbe
Matter	Mass, weight, density, divisibility, atom
Mechanics	Force, velocity, acceleration, momentum, gravity
Physiology	Life, death, reproduction, metabolism, kinship
Thermodynamics	Heat, heat source, heat transfer, temperature, thermal expansion
Waves	Light, color, sound, propagation, reflection

The study found that questions that were inconsistent across the naïve and scientific theories in all knowledge areas listed above were not only answered slower than those that were consistent, but they were also answered incorrectly more often as well.

When students learn scientific theories that conflicts with earlier, naïve theories, what happens to the earlier theories? Our findings suggest that naïve theories are suppressed by scientific theories but not supplanted by them.

Framing: How do people make decisions and can you influence them?

Words are powerful tools.

The information we receive plays an important role in our decisions and beliefs, but it’s the different ways that information is presented that influence us the most. The Framing Effect demonstrates how radically different our decisions can be when the same information is arranged in a slightly different way.

In a 1981 study, Tversky and Kahneman gave participants a choice of two measures to counteract an imaginary disease that would spread from Asia to the U.S and potentially kill 600 people.

The participants were divided into two groups and given the same two possible solutions to pick from. The first group received a list of the two measures, which were worded to emphasise the lives that would be lost. The second group, however, received a list of measures that emphasised the lives that would be saved.

Lakshminarayanan (2010)

The results of the choices made by the participants are shown above. In the first group, which emphasised the loss of life, 22% of the participants opted to let 400 out of 600 people die, whereas the other 78% choose the choice in which there was a ⅓ chance that no one would die and a ⅔ chance that all 600 would die.

In the second group, which emphasised the amount of lives saved, the results were almost completely reversed. Rather than 22%, 72% of participants choose to save 200 out of 600 people (which is exactly the same as the first choice for the first group: letting 400 people die). And only 28%, instead of 78%, went for the risky measure.

The information was the same and so was the format, but the simple change of focus produced a remarkable effect.

The Framing Effect explains that people’s choices are influenced by an emphasis on gains or losses.

One of the most prominent framing effects is the tendency for decision makers to evaluate gambles relative to a reference point, and to act risk-seeking when prospects are framed as losses but risk-averse when identical prospects are framed as gains.

Lakshminarayanan (2010)

So, if you want to influence someone’s (or your own) choice, you must frame the choice with an emphasis on what they stand to gain or what they stand to lose. When you want someone to make a risky choice, accentuate the potential losses of not taking that route. On the other hand, if you want them to make a safe choice, highlight the potential gains.