Misconceptions Regarding the Brain: The ... - Wiley Online Library

MIND, BRAIN, AND EDUCATION

Misconceptions Regarding the Brain: The Neuromyths of Preservice Teachers Sefa Dündar1 and Nazan Gündüz1

ABSTRACT— Understanding preservice teachers’ misconceptions regarding the brain and neuroscience (neuromyths) can provide information that helps teachers to apply neuroscience knowledge in an educational context. The objective of this study was to investigate these misconceptions. Following preliminary research, a questionnaire comprising 59 challenging assertions in two categories (education and neuromyths) was developed as a data collection tool. The findings identify preservice teachers’ neuromyths, which were found to vary by teaching area.

Despite increasing research interest, the human brain remains to some extent mysterious. The growing volume of information about the brain, both in the media and in academic publications, is often accepted uncritically without filtering or questioning its authenticity. Misconceptions arising from misreading, misunderstanding, or misquoting information about the brain and its functions have been described as “neuromyths” (Organisation for Economic Cooperation, and Development, 2002). Geake (2008) characterized neuromyths as popular descriptions of brain functions that inform so-called “brain-based” educational practices. Samuels (2009) related the development of neuromyths to gaps between academic fields. The failure to properly incorporate neuroscience into educational practices has given rise to a number of such misinterpretations (Geake, 2008). Neuromyths are considered a major issue, affecting both the progress of cognitive neuroscience itself and

its application in the field of education. Although inaccurate, neuromyths have their basis in original scientific findings that have been wrongly interpreted, overgeneralized, exaggerated, debased, or oversimplified (Della Sala, 2007; Howard-Jones, 2010), Pasquinelli (2012) noted that neuromyths may develop through inaccurate interpretation of experimental results. For instance, research on cerebral hemispheric dominance and specialization has prompted the myth that humans can be categorized as either right-brained or left-brained. As a consequence, “training” of various kinds has been developed to help individuals to use both hemispheres effectively (Geake, 2008; Goswami, 2008). In addition to right- or left-brain learning, other examples of neuromyths include multi-intelligence, critical periods for the learning process, the effect of certain types of nutrients on brain functions, and the belief that we use only 10% of the brain’s capacity.

Education and Neuromyths In the United States, the period 1990–2000 was referred to as “The Decade of the Brain” because of the significant growth of interest in neuroscience research. These advances attracted the interest of researchers and practitioners in a number of fields, including education. However, teachers’ efforts to incorporate neuroscience findings in their educational practices are hindered by the complexity of neuroscience and the difficulty of transferring its findings to the classroom environment (Ansari, Coch, & De Smedt, 2011; Devonshire & Dommett, 2010; Jolles et al., 2005), leading to the emergence of the neuromyths in question (Coch & Ansari, 2009; Geake & Cooper, 2003; Howard-Jones, 2008; Howard-Jones, Franey, Mashmoushi, & Liao, 2009). 1 Department of Primary Mathematics Education, Education Faculty, The simplification of scientific findings in the popular Abant Izzet Baysal University, media has contributed to the development and propagation Address correspondence to Sefa Dündar, Department of Primary Mathematics Education, Education Faculty, Abant Izzet Baysal Univer- of neuromyths by suggesting that neuroscience knowledge sity, Bolu, Turkey; e-mail: [email protected] is readily applicable in classrooms (Beck, 2010; Wallace,

212

© 2016 International Mind, Brain, and Education Society and Wiley Periodicals, Inc.

Volume 10—Number 4

Sefa Dündar and Nazan Gündüz

1993). The tendency to believe this oversimplified media information may also indicate that teachers lack adequate knowledge of the subject, or that they are unable to reflect on neuroscience knowledge in a critical way. This suggests that neuromyths may in part develop as a consequence of teachers’ inadequate neuroscience literacy and critical capacity. This hypothesis finds some support in studies that investigate whether neuromyths are influenced by the number of popular scientific journals, newspapers, and books an individual reads or reviews. For example, Howard-Jones et al. (2009) concluded that the average number of neuromyths was lower among those who read newspapers than among those who do not, but this difference proved statistically insignificant. Similarly, while the prevalence of neuromyths was lower among those reading scientific journals than among those who did not, this difference was also insignificant. Again, no significant difference was observed in the average occurrence of neuromyths among teachers according to the number of books they read, and Dekker, Lee, Howard-Jones, and Jolles (2012) found that, like exposure to popular science publications or scientific journals, factors such as gender and age failed to account for neuromyths. In a study of neuroscience literacy, Herculano-Houzel (2002) concluded that, although there was some relationship between participants’ exposure to scientific journals at university and the number of correct answers they gave, these reading habits had no such effect among high school students, although reading newspapers was found to increase mean correct scores by 9%. The existence of neuromyths in the educational field has been highlighted in a number of studies (e.g., Ansari & Coch, 2006; Geake, 2008; Goswami, 2006; Pasquinelli, 2012; Tardif & Doudin, 2011). Although there has been little research on neuromyths among teachers (Dekker et al., 2012; Howard-Jones et al., 2009), there is some evidence that they commonly share three such misconceptions, related to visual, auditory, and kinesthetic (VAK) learning styles, the role of hemispheric dominance in learning; and the need for short exercises to maintain integration between left and right hemispheres (the so-called “Brain Gym” method). As these neuromyths may differ across cultures, more research is needed to identify and prevent their adoption in particular countries and regions.

• That learning styles reflect different dominances, informing the use of VAK and dominant forms of perception in education. • That regular and plentiful intake of water improves children’s brain function and test results. • That IQ is distributed across various types of multi-intelligence (e.g., Della Sala, 2007; Howard-Jones et al., 2009). These neuromyths are examined in more detail below. We Use Only 10% of Our Brain The idea that we use only 10% of our brain’s capacity is the most common neuromyth (Wanjek, 2002). The myth is based on unproven parapsychological claims about the unused potential of the human mind, or on neuroanatomical evidence relating to glia–neuron or white matter–gray matter ratios (Della Sala, 2007; Lilienfeld, Lynn, Ruscio, & Beyerstein, 2011). However, science has failed to confirm any such unused region; in patients who experience severe brain trauma, for instance, each region of the brain has been shown to have a specific function (e.g., Organisation for Economic Cooperation and Development, 2007).

VAK Learning Styles Individual variations in academic abilities and proficiencies have generated particular interest in idiosyncratic learning styles. Although the evidence linking learning styles to VAK channels has proved inadequate, this approach has been widely adopted by educators (Dunn, Dunn, & Price, 1989) in determining a child’s dominant learning style and educating them accordingly (Geake, 2008). According to this model, visual learners should be shown diagrams, colorful pictures, and material that appeal to the eye to help them to learn and to retain information. Similarly, auditory learners favor sounds, and kinesthetic learners move and act upon what they learn; by following these principles, learning outcomes are said to improve (Rato, Abreu, & Castro-Caldas, 2013). Because a student’s preferred learning style may not be immediately clear, some schools attempt to label students in the classroom. However, the VAK method creates dilemmas for teachers, such as “what should teachers do with these students when V and K learners are in music class, A and K learners are in painting class, and V and A learners are in handicraft application class?” (Geake, 2008). Kayser Types of Neuromyth According to the Organisation for Economic Cooperation, (2007) noted that the brain will also see when it hears and and Development (2002), the following are the most promi- touches, that it will hear when it sees, and that individuals are mainly visual data processors. That being so, it curnent neuromyths: rently is not possible to define clear boundaries between • That humans use only 10% of their brain. individual learning styles; indeed, there is no evidence of • That either the left or right cerebral hemisphere is dom- any educational advantage of teaching based on preferred inant. learning style. As Howard-Jones (2008) pointed out, neither


213

Misconceptions Regarding the Brain

neuroscience nor any other science affirms the educational hyponatremia or water poisoning (e.g., Boetzkes et al., 2010; merits of VAK-based learning over other learning styles. Miyamoto et al., 2012). Hemispheric Dominance Another common neuromyth is that individuals predominantly use either the left or right hemisphere of the brain. This is based on a misinterpretation of laterality studies; Goswami (2004) stated that the reference to right- and left-brain learning processes in Organisation for Economic Cooperation, and Development (OECD) reports was one of a number of troubling neuromyths. From a historical perspective, studies highlighting anomalies of information processing in split-brain patients were the original source of these misconceptions (Geake, 2008). Subsequently, Singh and O’Boyle (2004) showed that the normal brain was not composed of two separately operating hemispheres but that the different cognitive characteristics of the left and right brain were very well-integrated, and that major conflicts between them were very rare. For instance, creative thinking, which supposedly reflects right brain dominance, actually requires the integration of characteristics of both hemispheres; these do not operate independently or in isolation, and creative individuals need to use both hemispheres in developing practical solutions to real problems (Geake, 2008). Another neuromyth related to hemispheric dominance is that grammar is processed in the left hemisphere while emotional processing occurs in the right. However, language researchers have rejected the idea that linguistic processes occur only in the left hemisphere in all humans (Thierry, Giraud, & Price, 2003). Walsh, Pascual-Leone, and Kosslyn (2003) insisted that human brain functions and behaviors may best be explained by the functional connectivity between cerebral structures rather than by localization. Plentiful and Regular Water Consumption Improves Brain Function Drinking plenty of water to enhance the learning process has been advocated by some brain-based learning programs. However, the evidence for this view was overgeneralized, and the ensuing neuromyth suggests that if a child does not drink enough water, they should be encouraged to drink more, as this will promote learning. In general, drinking water is beneficial, as it maintains hydration, but these findings have been overinterpreted (e.g., Howard-Jones, 2010). Howard-Jones et al. (2009) concluded that the advice to drink six to eight glasses of water a day to prevent brain shrinkage was not supported by neuroscience. Indeed, the evidence suggests that eliminating water from the body will constrain brain functions and decrease cognitive performance, and that there is no positive or direct relationship between enriched learning and water consumption (Rato et al., 2013). Excessive liquid consumption may even be harmful, leading in some cases to

214

Purpose of the Present Study According to Goswami (2006), the emergence of neuromyths can be explained by a lack of communication between educators and neuroscientists, which complicates the process of data transmission between the two fields. A better understanding of preservice teachers’ opinions and misconceptions about the brain can contribute to professional development by developing teachers’ critical awareness. The present study was designed to help preservice teachers by highlighting these misconceptions and showing how neuroscience can inform theory in both educational sciences and practices. The key objective was to identify common neuromyths among preservice teachers.

METHOD

Research Design The survey method was selected as the most appropriate approach. Items compiled from a literature review of previous studies were translated into Turkish. The resulting statements were checked by experts, and a 59-assertion neuromyth questionnaire was constructed, with three response options for each assertion (yes, no, or don’t know) to capture the participant’s views. Participants The study participants were preservice classroom teachers (primary school), preservice math teachers (secondary school), and preservice science teachers (secondary school). These departments were selected to investigate the effect of courses dealing with neuroscience (such as biology) on the development of neuromyths. A review of the university educational program found that the biology course was provided efficiently in the science program and at lower levels than in the class teaching program. Although there was no biology or biology-related content in the math teaching program, it was considered appropriate to include these teachers, as departmental educational programs are thought to influence neuromyths. In total, 2,932 preservice teachers from six state universities in different cities participated in the study. The participants ranged in age between 17 and 36 (X = 19.95 ± 1.69); of these, 79% were female (n = 2327) and 21% were male (n = 605). Table 1 summarizes the distribution of participants according to department, gender, grade level, and mean age and standard deviations. Fourth-grade preservice teachers are the largest group (n = 1344); in terms of department, preservice classroom teachers predominate (n = 1279). The



1.243 1.27 1.142 1.344 1.693 18.57 19.69 20.61 21.73 19.95 .083 894 .195 818 .230 651 .195 569 .099 2,932 18.98 20.40 21.03 22.31 20.67 50 39 28 39 156 .083 .089 .105 .103 .048 18.26 19.61 20.46 21.48 19.95 213 186 133 139 671 .139 .157 .134 .183 .077 18.69 19.78 21.07 22.15 20.42 76 60 82 44 262 .067 .072 .078 .096 .039 18.86 19.71 20.60 21.61 20.20 .156 325 .179 285 .197 246 .188 161 .050 1,017 18.36 20.41 20.84 22.88 20.62 61 46 38 42 187 .094 .086 .109 .101 .049 169 202 124 144 639 Total

First Second Third Fourth Class level

18.29 19.41 20.28 21.47 19.86

X X X X X N Department

Female

ss

N

Male

ss

N

X

ss

N

Male Gender Gender

Female

Preservice classroom teacher Preservice mathematics teachers

Table 1 Descriptive Statistics for Participants by Department, Gender, Grade Level, and Mean Age

ss

N

Female

ss

N

X

Male Gender

Preservice science teachers

ss

N

Total

ss


mean age of preservice math teachers is 19.86 ± .049 for females and 20.62 ± .05 for males. The mean age of preservice classroom teachers is 20.2 ± .039 for females and 20.42 ± .077 for males. Finally, the mean age of preservice science teachers is 19.95 ± .048 for females and 20.67 ± .099 for males.

Data Collection The study used a neuromyth data collection form comprising 59 challenging statements related to neuromyths, based on issues identified in the literature review (e.g., Dekker et al., 2012; Herculano-Houzel, 2002; Howard-Jones et al., 2009; Karakus, Howard-Jones, & Jay, 2015) (see Table 2). The original form comprised 75 assertions, reduced to 59 on the basis of expert reviews and a pilot study. The original statements were in English; because the study was to be conducted in Turkey, these were translated into Turkish, and their validity was checked following translation from source to target language. Translation from English to Turkish was carried out by three experts (educational instructors) with relevant content knowledge and proficiency in English, eliminating any need for back-translation into the source language. The resulting neuromyth form was analyzed for Turkish language conformity by two experts in Turkish language and literature. Some adjustments were made to ensure content integrity. To check item equivalences, the form was subsequently administered to five graduate students, each of whom was asked the meaning of each item. Following translation of the form, 30 English Teaching department students attending the fourth grade in the Faculty of Education of a state university participated in linguistic equivalence studies based on the bilingual design method (Hambleton & Bollwark, 1991). The results confirmed a high level of relationship between scores on both forms, and administration of the form to the study participants then commenced. Previous studies that informed the selection of items on the neuromyth form are listed in Table 2. Items were categorized as either educational or general assertions; the first 25 items are educational, and those between 26 and 59 are general. The educational neuromyths (i.e., the first 25 items) were originally identified by the Organisation for Economic Cooperation, and Development (2002). In categorizing these as educational assertions, the inclusion of word objects such as learning, mental, academic, and success was taken into account; all other items fell into the category of general assertions. Two experts (with educational doctorates) assisted in performing this categorization. The final shape of the neuromyth form as produced by the researchers reflected the views of these two experts, whose level of consensus was calculated as .96 (Miles &

215


Table 2 Studies Informing the Selection of Items on the Neuromyth Form No. Cited from articles

No.

Cited from articles

No.

Cited from articles

1

Dekker et al., 2012; Howard-Jones et al., 2009; Karakus et al., 2015

10

Dekker et al., 2012; Howard-Jones et al., 2009; Karakus et al., 2015

19

2

Dekker et al., 2012; Howard-Jones et al., 2009; Karakus et al., 2015 Dekker et al., 2012; Karakus et al., 2015

11

Dekker et al., 2012; Howard-Jones et al., 2009; Karakus et al., 2015 Howard-Jones et al., 2009

20

Dekker et al., 2012; Howard-Jones et al., 2009; Karakus et al., 2015 Dekker et al., 2012; Howard-Jones et al., 2009; Karakus et al., 2015 Dekker et al., 2012; Howard-Jones et al., 2009; Karakus et al., 2015 Dekker et al., 2012; Howard-Jones et al., 2009; Karakus et al., 2015 Dekker et al., 2012; Howard-Jones et al., 2009; Karakus et al., 2015

13

Howard-Jones et al., 2009; Karakus et al., 2015 Dekker et al., 2012; Howard-Jones et al., 2009 Dekker et al., 2012; Howard-Jones et al., 2009 Howard-Jones et al., 2009

22

17

Herculano-Houzel, 2002; Howard-Jones et al., 2009

26

Dekker et al., 2012; Howard-Jones et al., 2009; Karakus et al., 2015 Howard-Jones et al., 2009 Herculano-Houzel, 2002; Howard-Jones et al., 2009 Dekker et al., 2012; Herculano-Houzel, 2002; Howard-Jones et al., 2009; Karakus et al., 2015 Dekker et al., 2012; Herculano-Houzel, 2002; Howard-Jones et al., 2009 Dekker et al., 2012; Howard-Jones et al., 2009 Dekker et al., 2012 Dekker et al., 2012; Herculano-Houzel, 2002 Dekker et al., 2012 Dekker et al., 2012 Herculano-Houzel, 2002 Herculano-Houzel, 2002

18

27

37 38

Herculano-Houzel, 2002; Howard-Jones et al., 2009 Dekker et al., 2012 Dekker et al., 2012

Dekker et al., 2012; Herculano-Houzel, 2002; Howard-Jones et al., 2009 Herculano-Houzel, 2002; Howard-Jones et al., 2009 Herculano-Houzel, 2002; Howard-Jones et al., 2009 Herculano-Houzel, 2002; Howard-Jones et al., 2009 Herculano-Houzel, 2002; Howard-Jones et al., 2009 Herculano-Houzel, 2002; Howard-Jones et al., 2009 Dekker et al., 2012; Howard-Jones et al., 2009 Dekker et al., 2012; Herculano-Houzel, 2002; Howard-Jones et al., 2009 Howard-Jones et al., 2009

46 47

Herculano-Houzel, 2002 Herculano-Houzel, 2002

39

Dekker et al., 2012

48

Herculano-Houzel, 2002

40

Dekker et al., 2012

49


41

Dekker et al., 2012

50


42 43

Dekker et al., 2012 Dekker et al., 2012

51 52

Herculano-Houzel, 2002 Herculano-Houzel, 2002

44 45 56 59

Herculano-Houzel, 2002 Herculano-Houzel, 2002 Herculano-Houzel, 2002 Herculano-Houzel, 2002

53 54 57

Herculano-Houzel, 2002 Herculano-Houzel, 2002 Herculano-Houzel, 2002

3 4 5 6 7 8

9 28 29 30

31 32 33 34 35 36 55 58

12

14 15 16

21

23 24 25

Huberman, 1994). When the assertions were discordant, categorization was completed by consensus. Aside from the assertions related to neuromyths, participants were also asked to provide personal information, including their age, gender, grade level, department, annual book-reading habits, and consumption of popular scientific journals and daily newspapers. All participants were volunteers, and they were informed that their data would remain confidential.

1, correct answers were scored 2, and don’t know responses were scored 0. Because the concept of neuromyth related to incorrect responses, the analysis focused on these. Using descriptive statistics, responses to each item were recorded as percentages and frequencies, and educational and general neuromyth scores were calculated for each participant. One-way analysis of variance (ANOVA) was used to examine how neuromyth scores differed by department, grade level, and exposure to books, popular scientific journals, and newspapers. A separate independent-samples (groups) t-test was used to identify any difference in neuData Analysis The data were analyzed using a number of statistical romyth scores by gender. If the number of books read methods. Initially, participants’ responses were rescored within the year was between 0 and 10, this was coded according to the answer key; incorrect answers were scored 1; between 11 and 20 was coded 2; between 21 and 30

216



was coded 3; and 31 or more was coded 4. Journal and newspaper-reading habits were encoded as follows: 0, I never read; 1, I sometimes read; and 2, I always read. Where differences occurred, Tukey, LSD, and Tamhane T2 tests were applied to identify the relevant groups. Eta-squared scores were used in comparisons to determine effect sizes. According to Cohen (1988), η2 = .01–.06 is considered a “small” impact; η2 = .06–.14 is regarded as a “moderate” impact; and η2 = .14 or above is considered a “great” impact.

RESULTS

The analysis in Table 3 confirms that neuromyths about the brain are prevalent among preservice teachers, and that participants had no knowledge about some of the assertions on the form. This applies in particular to general assertions (no comment) when compared with educational assertions. More than 60% accepted the following neuromyths: “Individuals learn better when they receive information in their preferred learning style” (97.6%); “Differences in hemispheric dominance (left brain, right brain) can help explain individual differences among learners” (78.5%); “Omega 3 supplements do not enhance the mental capacity of children in the general population” (63.3%); and “There are no critical periods in childhood after which you cannot learn some things, just sensitive periods when it’s easier” (70.1%). The teachers also displayed a striking lack of knowledge (i.e., don’t know) in the case of the following assertions: “It has been scientifically proven that fatty acid supplements (omega-3 and omega-6) have a positive effect on academic achievement” (43.9%); and “Exercises that rehearse co-ordination of motor perception skills can improve literacy skills” (38.7%). Among general assertions, the following neuromyths were also common: “Memory is stored in the brain much like as in a computer. That is, each memory goes into a tiny piece of the brain” (79.3%); “Emotional brain processes interrupt those brain processes involved with reasoning” (43.3%); “Children must acquire their native language before a second language is learned. If they do not do so, neither language will be fully acquired” (49.2%); “The left and right hemisphere of the brain always work together” (48.8%); and “When a brain region is damaged, other parts of the brain can take up its function” (53.2%). The participating teachers were also ill-informed about the following general assertions: “The brains of boys and girls develop at the same rate” (49.2%); “Brain development has finished by the time children reach secondary school” (46.7%); and “Learning is not because of the addition of new cells to the brain” (35.5%). The most prevalent neuromyth was “When we sleep, the brain enters into rest” (52.8%).


Results by Department and Grade Level In Table 4, the data show that teachers’ mean neuromyth scores for general assertions were higher than for educational assertions. In each of the three departments, neuromyths involving educational assertions were higher at the first grade level, declining in the midclasses, and increasing again in the senior grade; this was also the case for general assertions. For preservice science teachers, mean neuromyth scores for both educational and general assertions were higher than for the other two departments (Table 5). A comparison of neuromyth scores by grade level and department found no significant difference between preservice classroom teachers by grade level for educational and general assertions (F[3, 1275] = 2.337; p > .05, F[3, 1275] = 2.070; p > .05). For math and science departments, a significant difference was found (F[3, 822] = 4.50; p < .05, F[3, 823] = 26.509; p < .05) between mean neuromyth scores for educational assertions by grade level. In the mathematics department, these differences were between first and third grade levels and between third and fourth grade levels and between the first and third, first and fourth, second and fourth, and third and fourth grade levels in the science department. Mean neuromyth scores for general assertions showed a significant difference between grade levels in the mathematics and science departments (F[3, 822] = 7.667; p < .05, F[3, 823] = 24.932; p < .05). The source of this difference was found to be the third grade in the mathematics department and the fourth grade in the science department. In the mathematics department, class level was moderately effective as a predictor of differences in neuromyth scores for educational and general assertions (η2 = .016, η2 = .027); in the science department, grade level was found to be effective at a higher level (η2 = .088, η2 = .083).

The Effect of Book Reading The analysis in Table 6 shows that increased book reading among preservice teachers in the mathematics department reduced neuromyths in both the educational and general categories in the third grade, but these increased again in the fourth grade. The same was found for preservice science teachers. In contrast, general neuromyths among preservice classroom teachers were seen to decline. Table 7 data analysis reveals no significant difference in educational and general neuromyth scores between preservice teachers in different departments by book-reading level. Tables 8 and 9 compare departments on the basis of the neuromyth category by book-reading level. Preservice science teachers who never read believed most of the educational and general neuromyths (Table 8); the same was found for those reading the most books. For other book-reading levels, some variance was found across departments.

217


Table 3 Responses of Preservice Teachers to the Neuromyth Test A.N.

C.

Assertions

1

Educational neuroscience assertions

Individuals learn better when they receive information in their preferred learning style (e.g., auditory, visual, kinesthetic). Environments that are rich in stimulus improve the brains of preschool children. It has been scientifically proven that fatty acid supplements (omega-3 and omega-6) have a positive effect on academic achievement. Differences in hemispheric dominance (left brain, right brain) can help explain individual differences among learners. Exercises that rehearse co-ordination of motor perception skills can improve literacy skills. Extended rehearsal of some mental processes can change the shape and structure of some parts of the brain. Learning problems associated with developmental differences in brain function cannot be remediated by education. Individual learners show preferences for the mode in which they receive information (e.g., visual, auditory, kinesthetic). Children are less attentive after consuming sugary drinks and/or snacks. Omega-3 supplements do not enhance the mental capacity of children in the general population. There are no critical periods in childhood after which you cannot learn some things, just sensitive periods when it’s easier. Vigorous exercise can improve mental function. To learn how to do something, it is necessary to pay attention to it. Learning occurs through modification of the brain’s neural connections. Learning is not because of the addition of new cells to the brain. Children must acquire their native language before a second language is learned. If they do not do so neither language will be fully acquired. The left and right hemisphere of the brain always work together. Brain development has finished by the time children reach secondary school. There are critical periods in childhood after which certain things can no longer be learned Information is stored in the brain in a network of cells distributed throughout the brain. Academic achievement can be affected by skipping breakfast. There are sensitive periods in childhood when it is easier to learn things. Any brain region can perform any function. Mental effort raises oxygen consumption by the brain. Knowing our brain, we can understand better how our thoughts, our reasoning, and our memories work. Short bouts of co-ordination exercises can improve integration of left and right hemispheric brain function. Regular drinking of caffeinated drinks reduces alertness. Production of new connections in the brain can continue into old age. Drinking less than six to eight glasses of water a day can cause the brain to shrink. One’s environment can influence hormone production and, in turn, personality.

2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

17 18 19 20 21 22 23 24 25 26 27 28 29 30

218

General neuroscience assertions

C

I

DK

A

97.6

1.1

1.3

I

81.3

7.3

11.4

C

51.9

4.2

43.9

I

78.5

5.5

16

I

49.6

11.7

38.7

I

49.8

15.4

34.8

C

18.9

59.4

21.7

I

86.8

4.6

8.7

C

41

23

35.9

I

11.5

63.3

25.2

C

12

70.1

17.9

C

79.9 91.6 62.9

7.8 4.4 9.7

12.3 4 27.5

C C C

34.9 49.2

29.6 23.1

35.5 27.7

C I

20 19.9

48.8 33.4

31.2 46.7

C I

39.5

41.6

18.9

I

73.1

7.6

19.3

C

60.5 89.4

20.7 4.5

18.8 6.1

C C

29 66,5 74.6

45.9 7.9 7.6

25.1 25.6 17.8

I C C

66.7

3.2

30.1

I

29.4 69 16.2

47.8 11.6 35.3

22.8 19.4 48.5

C C I

58.1

14.5

27.5

C



Table 3 continued A.N.

C.

31 32 33 34 35

36 37

38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59

Assertions Performance in activities such as playing the piano improves as a function of hours spent practicing. Hormones influence the body’s internal state, and not their personality. Memory is stored in the brain much like as in a computer. That is, each memory goes into a tiny piece of the brain. Memory is stored in networks of cells distributed throughout the brain. Keeping a phone number in memory until dialing, recalling recent events and distant experiences, all use the same memory system. When we sleep, the brain shuts down. Brain activity depends entirely on the external environment: with no senses stimulated, we do not see, hear, or feel anything. Emotional brain processes interrupt those brain processes involved with reasoning. Cognitive abilities are inherited and cannot be modified by the environment or by life experience. We mostly only use 10% of our brains. We use our brains 24 hr a day. Boys have bigger brains than girls. When a brain region is damaged, other parts of the brain can take up its function. The brains of boys and girls develop at the same rate. Normal development of the human brain involves the birth and death of brain cells. Mental capacity is hereditary and cannot be changed by the environment or experience. The brain is the body organ that consumes the most oxygen. The human brain stops growing at the end of adolescence. People who lost sight at an early age hear better than people with normal vision. The electroencephalogram gives a measure of the development of each brain region. In the majority of right-handed people, speech is a specialty of the left brain hemisphere. Dreaming is important to learning because during this sleep phase we consolidate what we learn. Dreaming occurs any time during sleep. When we sleep, the brain enters into rest. Language is inborn; even if raised in solitary, human beings will speak. Drugs such as cocaine are addictive and affect the mind because they alter the chemical balance of the brain. There is no single “real world”; each of us creates his own real world from the experience of the world. The brain works like a computer, that is, with data collection, processing, and exit of decisions. With more knowledge about our brain, we can improve our quality of life.

C

I

DK.

A

65.2

22.4

12.3

C

17.8

65.7

16.4

I

79.3

7.2

13.5

I

61.4

8.4

30.2

C

34.8

33.9

31.3

I

12.4 30.5

75.9 49.8

11.7 19.7

I I

43.3

27.4

29.3

I

20

58.6

21.5

I

42.2 6. 20.8 14.5

26.6 18.4 41.9 53.2

31.2 19.6 37.2 32.4

I C C C

18.5 69.4

32.3 6.5

49.2 24

I C

21.4

63

15.6

I

49.3 18.1 60.6

9.9 40.4 11.1

40.8 41.5 28.3

C I C

19.5

8.2

72.3

I

43.7

7.6

48.6

C

50.3

21.2

28.4

C

61.7 52.8 26.3

21.7 27.6 45.6

16.6 19.6 28

I I I

83.4

6.6

10

C

75.5

8.9

15.6

C

83.7

6.4

9.8

C

80.6

5.5

13.9

C

A = correct answer; A.N. = assertion number; C. = category; C = correct; I = incorrect; DK = I don’t know.


219


Table 4 Descriptive Statistics for Neuromyth Form Scores of Preservice Teachers by Department and Grade Level Department

Grade level

Category

N

Mean

Standard deviation

Standard error

Preservice mathematics teachers

First

Education General Education General Education General Education General Education General Education General Education General Education General Education General Education General Education General Education General Education General Education General Education General

230 230 248 248 162 162 186 186 826 826 263 263 225 225 161 161 178 178 827 827 401 401 345 345 328 328 205 205 1,279 1,279

5.73 9.72 5.27 9.12 5.02 8.15 5.70 9.40 5.45 9.16 5.67 9.04 5.52 8.98 5.00 8.47 7.36 11.51 5.86 9.44 5.45 9.18 5.23 8.95 5.65 9.04 5.68 9.64 5.48 9.16

2.123 3.171 2.302 3.441 2.329 3.265 2.278 3.255 2.268 3.331 2.297 3.120 2.256 3.668 2.419 3.565 3.594 4.431 2.762 3.824 2.286 3.173 2.304 3.356 2.461 3.484 2.593 3.193 2.392 3.312

.140 .209 .146 .218 .183 .256 .167 .238 .078 .115 .141 .192 .150 .244 190 .281 .269 .332 .096 .133 .114 .158 .124 .180 .135 .192 .181 .223 .066 .092

Second Third Fourth Total Preservice science teachers

First Second Third Fourth Total

Preservice classroom teachers

First Second Third Fourth Total

Levene statistic

df1

df2

Sig.

Education

.530

3

822

.662

General

.561

3

822

.641

Education

18.175

3

823

.000

General

11.119

3

823

.000

Education

1.640

3

1,275

.178

General

.388

3

1,275

.762

Table 5 Comparison of Neuromyth Scores by Grade Level and Department Department

Category


Education

General Preservice science teachers

Education

General Preservice classroom teachers

Education

General

220

Between groups Within groups Total Between groups Within groups Total Between groups Within groups Total Between groups Within groups Total Between groups Within groups Total Between groups Within groups Total

Sum of squares

df

Mean square

F

Sig.

Effect size (η2 )

68.580 4,175.885 4,244.465 249.242 8,907.703 9,156.944 555.422 5,747.946 6,303.369 1,006.611 11,075.955 12,082.566 39.993 7,273.396 7,313.389 67.964 13,955.534 14,023.498

3 822 825 3 822 825 3 823 826 3 823 826 3 1,275 1,278 3 1,275 1,278

22.860 5.080

4.500

.004

.016

83.081 10.837

7.667

.000

.027

185.141 6.984

26.509

.000

.088

335.537 13.458

24.932

.000

.083

13.331 5.705

2.337

.072

—

22.655 10.946

2.070

.102

—



Table 6 Descriptive Statistics for Book-Reading Status by Department and Neuromyth Category Category Preservice mathematics teacher

Education

General

Preservice science teacher

Education

General

Preservice classroom teacher

Education

General

Book-reading level

N

Mean

Standard deviation

Standard error

Levene statistic

df1

df2

Sig.

1 2 3 4 Total 1 2 3 4 Total 1 2 3 4 Total 1 2 3 4 Total 1 2 3 4 Total 1 2 3 4 Total

643 142 23 18 826 643 142 23 18 826 663 118 29 17 827 663 118 29 17 827 908 256 73 42 1,279 908 256 73 42 1,279

5.44 5.57 4.86 5.27 5.45 9.18 9.08 8.95 9.33 9.16 5.97 5.47 5.17 5.52 5.86 9.54 8.94 9.20 9.76 9.44 5.49 5.46 5.57 5.14 5.48 9.24 8.99 8.97 8.80 9.16

2.29 2.12 2.13 2.49 2.26 3.30 3.49 3.53 2.78 3.33 2.86 2.31 2.12 2.15 2.76 3.89 3.50 3.38 3.94 3.82 2.43 2.26 2.33 2.23 2.39 3.33 3.25 3.34 3.18 3.31

.090 .178 .445 .587 .078 .130 .293 .737 .656 .115 .111 .213 .394 .522 .096 .151 .322 .628 .956 .133 .081 .141 .273 .345 .066 .110 .203 .392 .491 .092

.524

3

822

.666

.482

3

822

.695

2.10

3

823

.099

.703

3

823

.550

1.439

3

1,275

.230

.232

3

1,275

.874

Table 7 Comparison of Neuromyth Scores Among Preservice Teachers by Book Reading Department

Category


Education


Education


Education

General



Sum of squares

df

Mean square

F

Sig.

10.342 4,234.123 4,244.465 2.772 9,154.173 9,156.944 41.958 6,261.411 6,303.369 38.363 12,044.203 12,082.566 5.678 7,307.711 7,313.389 20.420 14,003.078 14,023.498

3 822 825 3 822 825 3 823 826 3 823 826 3 1,275 1,278 3 1,275 1,278

3.447 5.151

.669

.571

.924 11.136

.083

.969

13.986 7.608

1.838

.139

12.788 14.635

.874

.454

1.893 5.732

.330

.804

6.807 10.983

.620

.602

221


Table 8 Neuromyth Scores by Book-Reading Level and Department

Book level

Category

Department

1

Education

Math teacher Science teacher Classroom teacher Total Math teacher Science teacher Classroom teacher Total Math teacher Science teacher Classroom teacher Total Math teacher Science teacher Classroom teacher Total Math teacher Science teacher Classroom teacher Total Math teacher Science teacher Classroom teacher Total Math teacher Science teacher Classroom teacher Total Math teacher Science teacher Classroom teacher Total

General

2

Education

General

3

Education

General

4

Education

General

N

Mean

Standard deviation

Standard error

Levene statistic

df1

df2

Sig.

643 663 908 2,214 643 663 908 2,214 142 118 256 516 142 118 256 516 23 29 73 125 23 29 73 125 18 17 42 77 18 17 42 77

5.44 5.97 5.49 5.62 9.18 9.54 9.24 9.31 5.57 5.47 5.46 5.49 9.08 8.94 8.99 9.00 4.86 5.17 5.57 5.35 8.95 9.20 8.97 9.02 5.27 5.52 5.14 5.25 9.33 9.76 8.80 9.14

2.298 2.864 2.439 2.545 3.307 3.894 3.333 3.505 2.125 2.319 2.266 2.236 3.495 3.500 3.252 3.371 2.138 2.122 2.338 2.254 3.535 3.384 3.349 3.366 2.492 2.154 2.236 2.256 2.786 3.945 3.187 3.263

.090 .111 .080 .054 .130 .151 .110 .074 .178 .213 .141 .098 .293 .322 .203 .148 .445 .394 .273 .201 .737 .628 .392 .301 .587 .522 .345 .257 .656 .956 .491 .371

8.152

2

2,211

.000

13.020

2

2,211

.000

.200

2

513

.819

.616

2

513

.540

.039

2

122

.962

.004

2

122

.996

.493

2

74

.613

.846

2

74

.433

In relation to educational neuromyths, Table 9 reports a significant difference between departments among participants who rarely read books (Level 1) (F[2, 2211] = 9.067; p < .05). In the educational category, reading books at a lower level rarely influenced the difference among departments (η2 = .008). Other levels of book reading did not result in differences among departments. When the source of the difference seen in the level of rare book reading (Level 1) was examined (Tamhane T2 test result), it was found that it was seen among the preservice teachers Science and Mathematics, and Science and Class teachers. The Effect of Reading Popular Scientific Journals The analysis in Table 10 shows that, among mathematics and preservice science teachers, reading popular scientific journals increases educational neuromyths while reducing those in the general category. For preservice classroom teachers, however, both educational and general neuromyth scores were found to decline.

222

Reading popular scientific journals influences the development of neuromyths in preservice teachers (Table 11). Specifically, journal reading is associated with a significant difference in educational neuromyth scores among preservice mathematics and science teachers, but no difference was observed in the case of preservice classroom teachers. Separately, reading journals was found to have a low level of effect size on educational assertions for preservice mathematics and science teachers (η2 = .007, η2 = .025). For general neuromyths, a significant difference was observed for science and preservice classroom teachers, but there was no difference for preservice mathematics teachers. Reading journals was found to have a low level of effect on general assertions (η2 = .02, η2 = .006). For preservice science teachers, differences in educational neuromyths favor those who always read as compared to those who sometimes read, and favor those who never read when compared with those who sometimes read. For preservice classroom teachers, however, the differences favor those who



Table 9 Comparison of Neuromyth Scores by Department and Book Reading Book level 1

Education General

2

Education General

3

Education General

4

Education General

Sum of squares

df

Mean square

F

Sig.

Effect size (η2 )

116.638 14,221.704 14,338.341 48.992 27,146.582 27,195.574 1.029 2,575.970 2,576.998 1.275 5,853.677 5,854.952 9.930 620.582 630.512 1.268 1,403.660 1,404.928 1.816 384.989 386.805 11.894 797.535 809.429

2 2,211 2,213 2 2,211 2,213 2 513 515 2 513 515 2 122 124 2 122 124 2 74 76 2 74 76

58.319 6.432

9.067

.000

.008

24.496 12.278

1.995

.136

—

.514 5.021

.102

.903

—

.637 11.411

.056

.946

—

4.965 5.087

.976

.380

—

.634 11.505

.055

.946

—

.908 5.203

.175

.840

—

5.947 10.778

.552

.578

—

Between groups Within groups Total Between groups Within groups Total Between groups Within groups Total Between groups Within groups Total Between groups Within groups Total Between groups Within groups Total Between groups Within groups Total Between groups Within groups Total

Table 10 Neuromyth Scores by Level of Exposure to Popular Scientific Journals and by Department Department

Category

Scale


Education

Never Sometimes Always Total Never Sometimes Always Total Never Sometimes Always Total Never Sometimes Always Total Never Sometimes Always Total Never Sometimes Always Total

General


Education

General


Education

General


N

Mean

Standard deviation

Standard error

Levene statistic

df1

df2

Sig.

53 49 724 826 53 49 724 826 53 92 682 827 53 92 682 827 62 69 1,148 1,279 62 69 1,148 1,279

4.81 5.89 5.46 5.45 9.22 10.26 9.08 9.16 4.94 6.97 5.78 5.86 9.35 10.97 9.24 9.44 6.09 5.81 5.43 5.48 9.46 10.21 9.08 9.16

1.881 2.671 2.257 2.268 3.079 3.219 3.347 3.331 2.413 3.331 2.662 2.762 4.420 4.092 3.695 3.824 2.653 2.579 2.361 2.392 3.687 3.338 3.280 3.312

.258 .381 .083 .078 .423 .459 .124 .115 .331 .347 .101 .096 .607 .426 .141 .133 .336 .310 .069 .066 .468 .401 .096 .092

2.444

2

823

.087

.489

2

823

.613

3.993

2

824

.019

2.171

2

824

.115

.518

2

1,276

.596

.906

2

1,276

.404

223


Table 11 Comparison of Neuromyth Scores by Exposure to Popular Scientific Journals Department

Category


Education

General


Education

General


Education

General


Sum of squares

df

Mean square

F

Sig.

Effect size (η2 )

31.657 4,212.807 4,244.465 63.768 9,093.177 9,156.944 162.987 6,140.382 6,303.369 242.796 11,839.770 12,082.566 33.993 7,279.395 7,313.389 90.020 13,933.478 14,023.498

2 823 825 2 823 825 2 824 826 2 824 826 2 1,276 1,278 2 1,276 1,278

15.829 5.119

3.092

.046

.007

31.884 11.049

2.886

.056

—

81.493 7.452

10.936

.000

.025

121.398 14.369

8.449

.000

.02

16.997 5.705

2.979

.051

—

45.010 10.920

4.122

.016

.006

always read when compared with those who sometimes read. The analyses reported in Table 12 found that the educational and general neuromyth scores of the preservice classroom teachers who never read any journals proved to be higher than those of the other departments, whereas in those who sometimes or always read journals, the educational and general neuromyth scores of the preservice science teachers proved to be high. The analysis in Table 13 shows a significant difference in educational neuromyth scores among departments according to popular scientific journal reading level; no significant difference was observed for general neuromyths. Differing journal reading level had differential effects on educational neuromyths; reading no journal at all had a moderate effect (η2 = .06) on the neuromyth score difference among departments; reading journals from time to time had a moderate effect (η2 = .035); and reading journals all the time had a lower level of effect (η2 = .004). Educational neuromyths among preservice teachers who never read journals were highest among preservice classroom teachers; for those reading journals occasionally, and for those who always read journals, prevalence was highest among preservice science teachers.

The Effect of Newspaper Reading Neuromyth scores are influenced by newspaper reading and department attended (Table 14). Among preservice mathematics teachers, as newspaper-reading level increased, educational neuromyths appeared to increase while general

224

neuromyths declined. The neuromyth scores of preservice teachers in the other two departments were also seen to vary with newspaper reading. The scores of preservice classroom teachers were found to decline as newspaper reading increased only for general neuromyths. Educational and general neuromyth scores for the departments in question are seen to vary according to newspaper-reading levels (Table 15). While newspaper reading made no difference to the neuromyths of preservice math teachers, it accounted for a significant difference in educational neuromyths in the department of science teaching and in general neuromyths in the department of classroom teaching. Reading newspapers was found to have a low level of effect (η2 = .009) on the development of educational neuromyths among preservice science teachers, and again at a lower level (η2 = .007) on the development of general neuromyths among preservice classroom teachers. The observed difference in educational neuromyths in science favored those who always read newspapers as compared to those who read newspapers occasionally. The analysis in Table 16 shows that among preservice teachers who never read newspapers, educational neuromyths are lowest among preservice mathematics teachers while general neuromyths are lowest among preservice science teachers. Among those who always read the newspaper, neuromyths in both educational and general categories are lowest among preservice classroom teachers. It can also be seen that among those who always read the newspaper, neuromyths are highest among preservice science teachers. Total scores for educational neuromyths indicate that these are higher among those who never read the newspaper than



Table 12 Neuromyth Scores of Preservice Teachers by Journal Reading

Magazines category Never

Education

General

Sometimes

Education

General

Always

Education

General

Mathematics Science Classroom Total Mathematics Science Classroom Total Mathematics Science Classroom Total Mathematics Science Classroom Total Mathematics Science Classroom Total Mathematics Science Classroom Total

N

Mean

Standard deviation

Standard error

Levene statistic

df1

df2

Sig.

53 53 62 168 53 53 62 168 49 92 69 210 49 92 69 210 724 682 1,148 2,554 724 682 1,148 2,554

4.81 4.94 6.09 5.32 9.22 9.35 9.46 9.35 5.89 6.97 5.81 6.34 10.26 10.97 10.21 10.56 5.46 5.78 5.43 5.53 9.08 9.24 9.08 9.12

1.881 2.413 2.653 2.416 3.079 4.420 3.687 3.743 2.671 3.331 2.579 2.992 3.219 4.092 3.338 3.665 2.257 2.662 2.361 2.421 3.347 3.695 3.280 3.414

.258 .331 .336 .186 .423 .607 .468 .288 .381 .347 .310 .206 .459 .426 .401 .252 .083 .101 .069 .047 .124 .141 .096 .067

.838

2

165

.435

3.374

2

165

.037

1.777

2

207

.172

3.057

2

207

.049

4.824

2

2,551

.008

7.872

2

2,551

.000

Table 13 Comparison of Neuromyth Scores of Preservice Teachers by Journal Reading by Department

Magazine Never

Education General

Sometimes

Education General

Always

Education General



Sum of squares

df

58.631 916.363 974.994 1.664 2,338.907 2,340.571 66.317 1,804.997 1,871.314 28.449 2,779.247 2,807.695 59.889 14,911.225 14,971.114 13.606 29,748.270 29,761.876

2 165 167 2 165 167 2 207 209 2 207 209 2 2,551 2,553 2 2,551 2,553

Mean square

F

Sig.

Effect size (η2 )

29.316 5.554

5.279

.006

.06

.832 14.175

.059

.943

—

33.159 8.720

3.803

.024

.035

14.224 13.426

1.059

.349

—

29.944 5.845

5.123

.006

.004

6.803 11.661

.583

.558

—

225


Table 14 Neuromyth Scores of Preservice Teachers by Newspaper Reading

N

Mean

Standard deviation

Standard error

Levene statistic

df1

df2

Sig.

50 224 552 826 50 224 552 826 60 211 556 827 60 211 556 827 64 300 915 1,279 64 300 915 1,279

5.36 5.44 5.46 5.45 9.74 9.12 9.13 9.16 5.63 6.33 5.71 5.86 9.53 9.91 9.26 9.44 5.68 5.74 5.38 5.48 9.96 9.50 8.99 9.16

2.173 2.387 2.230 2.268 3.250 3.291 3.356 3.331 2.583 3.035 2.654 2.762 3.877 3.962 3.756 3.824 2.335 2.300 2.420 2.392 2.782 3.460 3.283 3.312

.307 .159 .094 .078 .459 .219 .142 .115 .333 .208 .112 .096 .500 .272 .159 .133 .291 .132 .080 .066 .347 .199 .108 .092

.782

2

823

.458

.177

2

823

.838

3.011

2

824

.050

.142

2

824

.867

.863

2

1,276

.422

1.470

2

1,276

.230

Department Preservice mathematics teachers

Education

General


Education

General


Education

General

Never Sometimes Always Total Never Sometimes Always Total Never Sometimes Always Total Never Sometimes Always Total Never Sometimes Always Total Never Sometimes Always Total

Table 15 Comparison of Neuromyth Scores by Newspaper Reading

Department Preservice mathematics teachers

Education


Education


Education

General

226


Sum of squares

df

.465 4,244.000 4,244.465 17.470 9,139.474 9,156,944 62.796 6,240.573 6,303.369 66.817 12,015.749 12,082.566 31.333 7,282.056 7,313.389 101.588 13,921.910 14,023.498

2 823 825 2 823 825 2 824 826 2 824 826 2 1,276 1,278 2 1,276 1,278

Mean square

F

Sig.

Effect size (η2 )

.232 5.157

.045

.956

—

8.735 11.105

.787

.456

—

31.398 7.574

4.146

.016

.009

33.408 14.582

2.291

.102

—

15.666 5.707

2.745

.065

—

50.794 10.911

4.655

.010

.007



Table 16 Neuromyth Scores by Newspaper Reading

Newspaper Never

Education

General

Sometimes

Education

General

Always

Education

General

Mathematics Science Classroom Total Mathematics Science Classroom Total Mathematics Science Classroom Total Mathematics Science Classroom Total Mathematics Science Classroom Total Mathematics Science Classroom Total

N

Mean

Standard deviation

Standard error

Levene statistic

df1

df2

Sig.

50 60 64 174 50 60 64 174 224 211 300 735 224 211 300 735 552 556 915 2,023 552 556 915 2,023

5.36 5.63 5.68 5.57 9.74 9.53 9.96 9.75 5.44 6.33 5.74 5.82 9.12 9.91 9.50 9.50 5.46 5.71 5.38 5.49 9.13 9.26 8.99 9.10

2,173 2,583 2.335 2.370 3.250 3.877 2.782 3.312 2.387 3.035 2.300 2.577 3.291 3.962 3.460 3.571 2.230 2.654 2.420 2.440 3.356 3.756 3.283 3.439

.307 .333 .291 .179 .459 .500 .347 .251 .159 .208 .132 .095 .219 .272 .199 .131 .094 .112 .080 .054 .142 .159 .108 .076

1.725

2

171

.181

2.760

2

171

.066

8.324

2

732

.000

3.529

2

732

.030

3.347

2

2,020

.035

8.630

2

2,020

.000

among those who always read it, but lower than among those who sometimes read. Total scores for general neuromyths show that these decline as newspaper reading increases. The analysis in Table 17 shows no significant difference in general neuromyth scores across departments by newspaper-reading level. However, with the exception of those who never read newspapers, there was a significant difference among departments in educational neuromyths between those who sometimes read and those who always read newspapers. While reading the newspaper occasionally had a moderate effect (η2 = .018) on educational neuromyth scores, it had a lower effect (η2 = .003) than reading the newspaper all the time. However, educational neuromyths were more prevalent among preservice science teachers who read newspapers occasionally.

The Effect of Gender For the purpose of examining whether or not the genders of the preservice teachers had affected their neuromyth scores, the data were subjected to the independent-samples (groups) t-test; the results are presented in Table 18. Educational neuromyths differed significantly by gender, with males scoring better overall (Table 18). However, there was no significant gender difference in relation to general


neuromyths. The results indicate differences between males and females in respect of educational neuromyths. The analysis in Table 19 shows a significant gender difference between the mathematics and science departments in educational neuromyths, with males scoring better in both departments. While there was a significant gender difference in general neuromyths in the science department, this difference was insignificant in the mathematics department. In the department of classroom teaching, neuromyth scores did not differ by gender in either category.

DISCUSSION

The present findings report data analyses of the prevalence of neuromyths among preservice teachers at universities in Turkey. The study reports how these neuromyths change according to several factors. The analysis of the responses for each item shows that, as in other countries, prevalent neuromyths in Turkey include those related to learning styles, hemispheric dominance, and enhancement of mental capacity by certain nutrients. In particular, preservice teachers can be said to adopt neuromyths in the educational field. For instance, the assertion “Individuals learn better when they receive information in their preferred learning style (e.g., auditory, visual, kinesthetic)” suggests that students learn

227


Table 17 Comparison of Neuromyth Scores by Newspaper Reading Sum of squares

df

3.325 969.203 972.529 5.883 1,892.491 1,898.374 89.466 4,788.186 4,877.652 67.833 9,293.876 9,361.709 38.475 12,009.240 12,047.714 25.017 23,890.767 23,915.783

2 171 173 2 171 173 2 732 734 2 732 734 2 2,020 2,022 2 2,020 2,022

t

df

Sig. (two-tailed)

Mean difference

−3.84

2,930

.000

−.432

−1.20

2,930

.230

−.190

Newspaper Never

Education General

Sometimes

Education General

Always

Education General


Mean square

F

Sig.

Effect size (η2 )

1.663 5.668

.293

.746

—

2.941 11.067

.266

.767

—

44.733 6.541

6.839

.001

.018

33.916 12.697

2.671

.070

—

19.237 5.945

3.236

.040

.003

12.508 11.827

1.058

.347

—

Table 18 Neuromyth Scores of Preservice Teachers by Gender

Education General

Gender

N

Mean

Standard deviation

Female Male Female Male

2,327 605 2,327 605

5.49 5.92 9.20 9.39

2.40 2.70 3.38 3.77

Table 19 The Influence of Gender on Neuromyths by Department


Education


Education


Education

General

228

Gender

N

Mean

Standard deviation

t

df

Sig. (two-tailed)

Mean difference

Female

639

5.35

2.20

−2.233

824

.026

−.420

Male Female Male Female

187 639 187 671

5.77 9.14 9.23 5.69

2.45 3.20 3.72 2.60

−.318

824

.750

−.088

−3.688

825

.000

−.898

Male Female Male Female

156 671 156 1,017

6.59 9.30 10.03 5.44

3.26 3.70 4.26 2.37

−2.237

825

.026

−.758

−1.141

1,277

.254

−.189

Male Female Male

262 1,017 262

5.63 9.17 9.11

2.45 3.28 3.43

.280

1,277

.779

.064



better through their dominant learning style, and that children should be allowed to choose the style that appeals to them. However, Kayser (2007) noted that when the brain sees, it also hears and touches—for example, those who cannot see form mental spatial maps in the same way as those who can (Kriegseis, Hennighausen, Rösler, & Röder, 2006). To do this, they use auditory and tactile inputs, which are used as if they were visual. It follows that it is incorrect to sharply delineate individual learning styles, and that there is no evidence of any educational advantage in teaching or learning through the preferred learning style. The prevalence of this neuromyth among preservice teachers is likely to affect their professional development and to misdirect their teaching approach. Another prevalent neuromyth among preservice teachers is “Differences in hemispheric dominance (left brain, right brain) can help to explain individual differences among learners.” This misconception is based on clinical research on split-brain patients in the 1960s. Subsequently, the results were oversimplified to suggest that, because the left brain operated analytically and the right brain holistically, students should be taught separately in the classroom according to hemispheric dominance. In fact, all these claims were found to be wrong (Geake, 2005), as most cerebral functions involve both hemispheres. While it is true that one hemisphere may be more active during certain tasks (Karakus et al., 2015), the separation of humans into right- and left-brained is a misinterpretation, and there is no reliable evidence that hemispheric dominance is of direct relevance to teaching and learning activities. Indeed, performance and learning aspects of most daily tasks require the involvement of both hemispheres (Karakus et al., 2015). In addition, Singh and O’Boyle (2004) noted that the brain was not composed of two hemispheres operating separately, and that different cognitive characteristics in the left and the right brain were quite well-integrated. Walsh et al. (2003) further asserted that cerebral functions and behaviors could best be explained in terms of the connectivity between cerebral structures rather than by localization. Items related to nutrients and consumption of water were among the most popular behavior-related neuromyths, including “It has been scientifically proven that fatty acid supplements (omega-3 and omega-6) have a positive effect on academic achievement.” Separately, most participants answered don’t know for “Drinking water fewer than six to eight glasses a day causes the brain to shrink.” According to the Brain Gym approach, drinking water promotes learning. In fact, drinking water is considered beneficial because it maintains hydration within the body (Howard-Jones, 2008); there is also evidence that eliminating water from the body will slow down cerebral functions (Rato et al., 2013), but generalizing this information to suggest that “Drinking less


than six to eight glasses of water a day can cause the brain to shrink” is a neuromyth (Howard-Jones et al., 2009). As to whether omega-3 supplement has a potentially positive effect, while positive results were found within the general population, no scientifically valid evidence was found in support of that argument (Howard-Jones et al., 2009). Nevertheless, most preservice teachers stated that these items were true, on the basis that nutrients like omega-3 are considered to boost children’s attention. The item “We mostly only use 10% of our brains” was deemed true by a majority of participants, aligning preservice teachers in Turkey with the findings of earlier studies elsewhere (Dekker et al., 2012; Geake, 2008; Howard-Jones et al., 2009; Karakus et al., 2015; Pasquinelli, 2012). This neuromyth is thought to result from ideas about the unused potential of the human mind (unproven parapsychological arguments) or from neuroanatomical evidence related to glia–neuron ratios or white matter–gray matter ratios (Della Sala, 2007; Lilienfeld et al., 2011). This idea originally gained momentum following a radio interview with Albert Einstein in the 1920s. Prior to World War II, at a time when some American companies advertising a home-care manual sought to persuade their customers by inventing this 10% figure, the myth achieved wide circulation (Geake, 2008). Later, toward the end of the twentieth century, it was adopted by some enthusiastic educators, which influenced educational environments. Other prevalent neuromyths among preservice teachers included “Exercises that rehearse co-ordination of motor perception skills can improve literacy skills” and “Short bouts of co-ordination exercises can improve integration of left and right hemispheric brain function.” Here, the contention was that motor perceptual abilities would improve when certain exercises were performed, stimulating certain parts of the brain (Geake, 2005). This so-called “Brain Gym” approach recommends a series of exercises to enrich academic and other learning abilities. The method is thought to have its origins in contested earlier theories such as Orton’s mixed cerebral dominance, perceptual motor training, and neurological remodeling (Tardif, Doudin, & Meylan, 2015). However, apart from their lack of theoretical infrastructure, these theories also lacked empirical validation (Tardif et al., 2015), reducing any proposed applications to the status of neuromyth. The present study also established that many preservice teachers’ neuromyths relate to the item “Children must acquire their native language before a second language is learned. If they do not do so neither language will be fully acquired.” It appears likely that this neuromyth has developed in Turkey because of the prevailing attitude to multilingualism. About 10 languages are spoken in Turkey, and although most people speak Turkish, many

229


different races and languages are represented (Karakus et al., 2015). In line with the findings of Karakus et al. (2015), about 70% of study participants were found to subscribe to the neuromyth “There are no critical periods in childhood after which you cannot learn some things, just sensitive periods when it’s easier.” Neuroscience research shows that there are periods for the learning process that are sensitive rather than critical, during which learning can be efficiently achieved. In general terms, then, the present study confirmed the prevalence of certain neuromyths among participating preservice teachers. Of these, the general misconceptions were more problematic than the educational ones. For instance, participants were found to have almost no knowledge of the assertion “The electroencephalogram gives a measure of the development of each brain region,” which fell into the category of general assertions. The fact that preservice teachers appear to lack further information may be explained by the fact that this item entails technical knowledge. Alternatively, it may be that more comments were made on the educational assertions because of participants’ sense of identity as educators. The analysis also considered whether or not the neuromyths of preservice teachers varied by department—in this case, the departments of class teaching (for primary school courses) and the departments of mathematics and science teaching (for secondary school courses). While neuroscience is more closely associated with biology, these three were considered most convenient for present purposes in terms of the integration of these concepts into classes. Although preservice math teachers do not deal explicitly with neuroscience during their university education, they engage quite intensively with such subjects in preparing for university exams. Indeed, the analysis by department revealed that the preservice science teachers recorded the highest levels of both educational and general neuromyths, followed by class teachers and preservice mathematics teachers. This striking finding may reflect the fact that neuroscience is categorized as one of the physical sciences, and that teachers involved in the subject pay more attention to neuroscience data and practices considered applicable in the educational field, so adopting these in the course of their professional development. Neuromyth scores in each department were also examined according to grade levels. Differences in both educational and general neuromyth scores among grade levels proved significant in the departments of mathematics and science. In class teaching, however, no significant difference was found in educational and general neuromyth scores among grade levels. The difference by grade level had a moderate effect size in the department of mathematics teaching, but was effective at a high level in science teaching. It was concluded that the neuromyth scores of preservice

230

mathematics teachers declined from the first grade toward the third grade but increased again in the fourth grade, which may be because preservice teachers’ practices in the senior grade involved some knowledge of neuroscience, which they applied in their classes. Similarly, neuromyths in the department of science showed a decline from the first grade toward the third grade, but a relatively higher neuromyth score was found among fourth grade preservice teachers. It also emerged that the educational neuromyth scores of preservice science teachers who had successfully completed biology courses proved higher than those who did not take such a course. The finding that the neuromyth scores of teachers in the first grade proved high may reflect the fact that they had just passed their university preparation exam (LYS), or that they had taken more biology courses. While there was also no significant difference among grade levels for math or science teachers in the fourth grade, the high mean educational neuromyth scores of preservice classroom teachers may indicate that they were exposed to certain information—related for instance to neuroscience practices integrated into education, or the use of 10% of the brain, or hemispheric dominance—reinforced by an increased tendency to believe such information during their probationary period. Sources of information such as books, popular science journals, and newspapers can also be seen to affect the neuromyth scores of preservice teachers. For example, the popular media may influence the development and prevalence of myths by popularizing neuroscience findings and suggest that these are easily applied in the classroom (Beck, 2010; Wallace, 1993). The present analysis of preservice teachers’ educational and general neuromyth scores in each department in relation to the number of books they read found no significant differences. This may be because the books read by preservice teachers are not neuroscience-related; indeed, not every book boosts the neuroscience literacy of preservice teachers. In general, the present findings align with those of Howard-Jones et al. (2009). However, it was observed that as book reading increased, educational neuromyth scores declined. The analysis of book-reading levels found that, as for the change in neuromyth scores by department, there was a significant difference only in educational neuromyth scores among those that read few books, most negatively for preservice science teachers. This effect size was at rather a small effect. In relation to reading popular scientific journals, no significant difference was found in general neuromyth scores in the department of math teaching. In the departments of science and class teaching, there were significant differences in favor of those that always read as compared to those that sometimes read. The effect size of these differences was small. While significant differences were observed in the educational neuromyth scores of preservice math



and science teachers according to journal reading level, no such difference was found among preservice classroom teachers. Interestingly, those who never read popular scientific journals subscribed to significantly fewer educational neuromyths than those who read journals sometimes or always. In other words, whereas those who followed popular scientific journals returned lower general neuromyth scores of levels, their educational neuromyth scores were at higher levels. On that basis, we may conclude that reading popular scientific journals has a positive (if small effect) effect on minimizing general neuromyths and boosting neuroscience literacy. However, those preservice teachers who read popular scientific journals may still subscribe to neuromyths if they simplify neuroscience data and practice them in the classroom without thinking critically. While there was a significant difference in educational neuromyth scores across departments according to journal reading level, no significant difference was found in general neuromyths. It can be concluded that, among those who never read journals, preservice class teachers have higher educational neuromyth scores than those in other departments. Among those who sometimes or always read, preservice science teachers have higher neuromyth scores than those in the other departments. The effect size of these differences, however, is moderate in those who never read and lower in the others. Among those who sometimes read popular scientific journals, both educational and general neuromyths were found to be at higher levels than among those who never or always read. Similarly, there were no significant differences in general neuromyth scores in the departments of mathematics and science according to newspaper-reading level, but in the department of class teaching those who constantly read newspapers were observed to have significantly lower neuromyth scores when compared to those who sometimes or never read. In relation to educational neuromyths, preservice science teachers who always read newspapers were found to have significantly lower neuromyth scores than those who sometimes read. It was concluded that these differences had small size effect size. Howard-Jones et al. (2009) found that those who read newspapers had lower neuromyth averages than those who did not, and that those who read scientific journals had lower neuromyth averages than those who did not. In line with the present findings, they concluded that the number of books read had no effect on the development of neuromyths. However, Dekker et al. (2012) concluded that reading popular scientific journals was not an effective variable on the information regarding neuroscience. In addition, Herculano-Houzel (2002) concluded that reading books, popular scientific journals, and newspapers were neuromyth-minimizing variables, which again aligns with the present results.


Analysis of how neuromyth scores differed according to the gender of preservice teachers showed that the neuromyth scores of females were lower than those of males for both educational and general assertions. This difference was significant for educational neuromyth scores but not for general assertions. The neuromyth scores of female preservice teachers may reflect their greater curiosity about neuroscience findings. Contrary to the present findings, Dekker et al. (2012) and Karakus et al. (2015) found that gender had no effect on neuromyths. However, the sampling approach used here may explain why female preservice teachers’ neuromyth scores were lower. In relation to department attended, a significant gender difference in educational neuromyth scores was observed for math and science teachers, but there was no such difference among class teachers. For general neuromyths, a significant difference between genders was found only among science teachers.

CONCLUSION

The present findings confirm the prevalence of neuromyths among preservice teachers. Neuromyth scores were found to vary by department and were generally more prevalent among preservice science teachers. It also emerged that first- and fourth-grade preservice teachers subscribed to more neuromyths. Neuromyth scores did not vary with book-reading level, but did vary with journal and newspaper-reading levels. In terms of gender differences, males exhibited more educational neuromyths than females. These results provide important guidance to limit the misapplication of brain-based ideas in the educational practices of preservice teachers. The study identified misconceptions about neuroscience as adopted by preservice teachers; future research should analyze these data in greater depth, and incorporate necessary training to assist preservice teachers in avoiding these myths. Greater access to information about the brain may not completely reduce neuromyths among preservice teachers, but further interdisciplinary studies can help to minimize these myths. It is clearly difficult to integrate neuroscience into the educational sciences, but there is reason to hope that serious advances can be made in educational neuroscience through the combined efforts of experts in both fields. REFERENCES Ansari, D., & Coch, D. (2006). Bridges over troubled waters: Education and cognitive neuroscience. Trends in Cognitive Sciences, 10(4), 146–151. Ansari, D., Coch, D., & De Smedt, B. (2011). Connecting education and cognitive neuroscience: Where will the journey take us? Educational Philosophy and Theory, 43(1), 37–42.

231


Beck, D. M. (2010). The appeal of the brain in the popular press. Perspectives on Psychological Science, 5, 762–766. Boetzkes, S., Van Hoeck, K., Verbrugghe, W., Ramet, J., Wojciechowski, M., & Jorens, P. G. (2010). Two unusual pediatric cases of dilutional hyponatremia. Pediatric Emergency Care, 26, 503–505. Coch, D., & Ansari, D. (2009). Thinking about mechanisms is crucial to connecting neuroscience and education. Cortex, 45, 546–547. Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum. Dekker, S., Lee, N. C., Howard-Jones, P., & Jolles, J. (2012). Neuromyths in education: Prevalence and predictors of misconceptions among teachers. Frontiers in Psychology, 3, 429. doi:10.3389/fpsyg.2012.00429 Della Sala, S. (2007). Tall tales about the mind and brain: Separating fact from fiction. New York, NY: Oxford University Press. Devonshire, I. M., & Dommett, E. J. (2010). Neuroscience: Viable applications in education? The Neuroscientist, 16(4), 349–356. Dunn, R. S., Dunn, K. J., & Price, G. E. (1989). Learning style inventory (LSI). Lawrence, KS: Price Systems Incorporated. Geake, J. (2005). Educational neuroscience and neuroscience education: In search of a mutual middle-way. Research Intelligence, 92, 10–13. Geake, J. (2008). Neuromythologies in education. Educational Research, 50(2), 123–133. Geake, J., & Cooper, P. (2003). Cognitive neuroscience: Implications for education? Westminster Studies in Education, 26(1), 7–20. Goswami, U. (2004). Neuroscience and education. British Journal of Educational Psychology, 74(1), 1–14. Goswami, U. (2006). Neuroscience and education: From research to practice? Nature Reviews Neuroscience, 7(5), 406–413. Goswami, U. (2008). Principles of learning, implications for teaching: A cognitive neuroscience perspective. Journal of Philosophy of Education, 42, 381–399. Hambleton, R. K., & Bollwark, J. (1991). Adapting tests for use in different cultures: Technical issues and methods. Bulletin of the International Testing Commission, 18, 3–32. Herculano-Houzel, S. (2002). Do you know your brain? A survey on public neuroscience literacy at the closing of the decade of the brain. The Neuroscientist, 8(2), 98–110. Howard-Jones, P. (2008). Philosophical challenges for researchers at the interface between neuroscience and education. Journal of Philosophy of Education, 42, 361–380. Howard-Jones, P. (2010). Introducing neuroeducational research: Neuroscience, education and the brain from contexts to practice. Abingdon, UK: Routledge. Howard-Jones, P., Franey, L., Mashmoushi, R., & Liao, Y.-C. (2009, September). The neuroscience literacy of trainee teachers. Paper presented at the British Educational Research Association Annual Conference, 1–39, University of Manchester. Jolles, J., De Groot, R. H. M., Van Benthem, J., Dekkers, H., De Glopper, C., Uijlings, H., & Wolff-Albers, A. (2005). Brain lessons. Maastricht, The Netherlands: Neuropsych Publishers. Karakus, O., Howard-Jones, P. A., & Jay, T. (2015). Primary and secondary school teachers’ knowledge and misconceptions

232

about the brain in Turkey. Procedia: Social and Behavioral Sciences, 174, 1933–1940. Kayser, C. (2007). Listening with your eyes. Scientific American Mind, 18(2), 24–29. Kriegseis, A., Hennighausen, E., Rösler, F., & Röder, B. (2006). Reduced EEG alpha activity over parieto-occipital brain areas in congenitally blind adults. Clinical Neurophysiology, 117, 1560–1573. Lilienfeld, S. O., Lynn, S. J., Ruscio, J., & Beyerstein, B. L. (2011). 50 great myths of popular psychology: Shattering widespread misconceptions about human behavior. Chichester, UK: Wiley-Blackwell. Miles, M. B., & Huberman, A. M. (1994). Qualitative data analysis: An expanded sourcebook. London, UK: Sage. Miyamoto, K., Ichikawa, J., Okuya, M., Tsuboi, T., Hirao, J. I., & Arisaka, O. (2012). Too little water or too much: Hyponatremia due to excess fluid intake. Acta Paediatrica, 101(9), e390–e391. Organisation for Economic Cooperation, and Development (2002). Understanding the brain: Towards a new learning science. Paris, France: OECD. Organisation for Economic Cooperation and Development (2007). Understanding the brain: The birth of a learning science. Paris, France: OECD. Pasquinelli, E. (2012). Neuromyths: Why do they exist and persist? Mind, Brain, and Education, 6, 89–96. Rato, J. R., Abreu, A. M., & Castro-Caldas, A. (2013). Neuromyths in education: What is fact and what is fiction for Portuguese teachers? Educational Research, 55, 441–453. Samuels, B. M. (2009). Can the differences between education and neuroscience be overcome by mind, brain, and education? Mind, Brain, and Education, 3, 45–55. Singh, H., & O’Boyle, M. W. (2004). Interhemispheric interaction during global–local processing in mathematically gifted adolescents, average-ability youth, and college students. Neuropsychology, 18(2), 371–377. Tardif, E., & Doudin, P. (2011). Neurosciences cognitives et éducation: Le début d’une collaboration. Revue des Hautes Écoles pédagogiques, 12, 95–116. Tardif, W., Doudin, P. A., & Meylan, N. (2015). Neuromyths among teachers and student teachers. Mind, Brain, and Education, 9, 50–59. Thierry, G., Giraud, A.-L., & Price, C. (2003). Hemispheric dissociation in access to the human semantic system. Neuron, 38, 499–506. Wallace, M. (1993). Discourse of derision: The role of the mass media within the education policy process. Journal of Education Policy, 8, 321–337. Walsh, V., Pascual-Leone, A., & Kosslyn, S. M. (2003). Transcranial magnetic stimulation: A neurochronometrics of mind. Cambridge, MA: MIT Press. Wanjek, C. (2002). 10 percent misconception, 90 percent misdirection: The brain at work. In C. Wanjek (Ed.), Bad medicine: Misconceptions and misuses revealed, from distance healing to vitamin O. New York, NY: Wiley.
