Background of research and attitudes towards statistics

This chapter includes a brief overview of the theoretical background of attitudes concept and research on statistics achievement and attitudes toward statistics. The chapter besides presents descriptions of instruments designed to mensurate statistics attitudes. Overall, this chapter provides background and context for understanding the function of attitudes in larning statistics.

Definition of Attitudes and Attitudes toward Statisticss

The construct of attitude was used to depict the spacial orientation or seeable place of physical objects such as statues or pictures. It derived from the Latin word ‘aptus ‘ which on the one manus refers to the “ fittingness ” or “ adaptedness ” and on the other manus refers to the “ aptitude ” that connotes a subjective or mental province of readying for action ( Allport, 1935 ; Breckler & A ; Wiggins, 1989 ) . As the concept of attitude had no globally accepted definition in psychological science for a long period of clip, there had been a small understanding on the significance of attitudes ( Pratkanis, 1989 ) . However, the starting point for the definition of attitude was accepted as Gordon W. Allport ‘s ( 1935, p.810 ) definition of attitude ( Bordens & A ; Horowitz, 2002 ) . He stated that “ attitude is a mental and nervous province of preparedness, organized thorough experience, exercising a directive or dynamic influence upon the person ‘s response to all objects and state of affairss with which it is related ” ( Allport, 1935 ) . Presently, attitude is defined as “ a temperament to react, favourably or unfavourably to an object, individual, establishment or an event ” ( Ajzen, 2005, p.3 ) p.3, or as “ erudite cognitive, affectional and behavioural sensitivities to react positively or negatively to certain objects, state of affairss, establishments, constructs or individuals ” ( Aiken, 2002, p.3 ) ( Aiken, 2002 ; Ajzen, 1988 ) . Taken together, attitudes toward statistics can be conceptualized as a multidimensional concept that refers to the learned cognitive, affectional and behavioural sensitivities to react positively or negatively to the field of statistics, statistics classs, statistics stuffs and statistics teachers. In this thesis survey, pupils ‘ attitudes toward statistics were assumed to be dwelling of the undermentioned dimensions: cognitive competency, trouble, affect, value, involvement and attempt.

Theoretical Background of Attitudes

Attitudes have been accepted to impact behaviour for a long clip ( Holland, 2007 ) . Therefore several theories attempted to explicate the function of attitudes on human behaviour. These theories included learning theories, the theories of sound action and planned behaviour, self-efficacy and self finding theories, involvement theories, and anticipation value theory ( Alderman, 2008 ; Bagozzi, 1992 ) .

Theories of Learning

Learning is defined as permanent alterations in persons ‘ behaviour or cognition which consequence from experience ( Hergenhahn & A ; Olson, 2005 ; Mayer, 2008 ) . Harmonizing to Schunk ( 2008 ) larning involves geting and modifying cognition, accomplishments, schemes, beliefs, attitudes and behaviours. This definition promotes the thought that larning non merely deals with the cognitive dimensions such as accomplishments and cognition but besides trades with the affectional dimensions such as beliefs and attitudes.

A acquisition theory is a “ systematic incorporate mentality in respect to the nature of the procedure whereby people relate to their environments in such a manner as to heighten their ability to utilize both themselves and their environments in a most effectual manner ” ( Bigge & A ; Shermis, 2004 ) ( p.3 ) . Learning theories besides serve as Bridgess between research and educational patterns ( Bandura & A ; Schunk, 1981 ) . Therefore, a acquisition theory is a systematic model that aims to explicate the nature of the acquisition procedure and reassign research findings into recommendations for educational pattern.

The 20th century larning theories can be classified into two wide households: Behavioral Learning Theories and Cognitive Learning Theories ( Bigge & A ; Shermis, 2004 ) . These theories explain the function of attitudes on human larning from different point of positions. Behavioral larning theories explain larning as comparatively lasting alteration in discernible behaviours ; whereas cognitivists define larning as a comparatively lasting and internal alteration in mental associations which can non easy be observed ( Pritchard, 2008 ) . Although behavioural larning theories do non deny the affectional dimension of larning, their justification is inexplicit. They propose that the behaviours that have been reinforced or rewarded in the hereafter are likely to be repeated. This posit that persons ‘ preparedness and willingness should be ensured before they learn. In a different manner, cognitive theories explicitly emphasize the function of attitudes on larning. In cognitive acquisition theories non merely pupils ‘ larning factual information but besides their developing new attitudes is of import. For illustration, cognitive theories such as Bandura ‘s societal cognitive theory contends that pupils ‘ ends, outlooks and competency are the of import factors act uponing their public presentation and developmental position ( Bandura & A ; Schunk, 1981 ) .

In drumhead, the two wide groups of larning theories deal otherwise with the position of attitudes in larning. However, both of them emphasized the significance and the demand of holding temperaments to react positively to the procedure of acquisition.

The Theory of Reasoned Action and Planned Behavior

The theory of reasoned action asserts that the immediate cause of a behaviour is behavioural purpose. Harmonizing to this theory, attitude toward the behaviour and subjective norm ( societal influence ) are the two determiners of behavioural purpose. The theory was modified with an extra forecaster variable: sensed behavioural control. New theory was named as the theory of planned behaviour ( Bohner & A ; Wanke, 2002 ) .

Attitude

Subjective norm

Purpose

Behavior

Perceived behavioural control

Figure 2.1. Theory of Planned Behavior ( Ajzen, 1988 )

Like the theory of sound action, the theory of planned behaviour asserts that a individual ‘s purpose is the most of import determiner of action. In this theory, non merely attitude toward behaviour and the subjective norm but besides the sensed behavioural control is the determiner of the purposes. The theory besides posits that, in bend, attitude toward behaviour is determined by the individual ‘s rating of the results associated with the behaviour and by the strength of these associations ( Ajzen, 1988 ) .

I will compose some research support here!

Self Efficacy and Self Determination Theories

Bandura ( 1986 ) defined self efficaciousness as persons ‘ beliefs about their public presentation capablenesss in a peculiar sphere. Self efficaciousness theory assumes that persons ‘ judgement of their efficaciousness is a map of the undertaking, situational features runing at the clip, their past experience and anterior beliefs about the undertaking, and their current beliefs and feelings as they work on the undertaking. This theory was supported with some surveies that ego efficaciousness is related to the pupils ‘ existent accomplishment in schoolroom ( Pinrich, 2003 ) ( Pintrich, 1999 ) . Similarly, self-determination theory postulates that an apprehension of human motive requires the consideration of psychological demands for competency, liberty and relatedness ( Deci, Vallerand, Pelletier, & A ; Ryan, 1991 ) . Like self-efficacy theory, the ego finding theory concerns with advancing in pupils ‘ assurance in their ain capacities. This theory besides focuses on the involvement and valuing of instruction. Therefore, the theory of self finding stress three human demands: the demands for competency, relatedness and ego finding ( Deci, Vallerand, Pelletier, & A ; Ryan, 1991 ) .

I will compose research support for this theory here!

Interest Theories

Hidi ( 1990 ) argued that involvement is cardinal to finding how we select and persist in treating certain types of information in penchant to others ( Hidi, 1990 ) . Interest is besides assumed to be a map of personal features which is slightly stable over clip ( Pintrich, 2003 ) .

Dewey ( 1969 ) asserted that involvement had three stages: active stage, nonsubjective stage, and emotional stage. He argued that, foremost, to be interested in any affair is to be actively concerned with it ; secondly, involvement does non stop merely in itself but it attaches itself to an object ; and thirdly, involvement has an emotional or appreciative side.

I will compose more about the theory and research support here!

Expectancy Value Theory of Motivation

Motivation was derived from the Latin verb “ movere ” which means “ to travel ” . It was defined as the procedure whereby end directed activity is come into action and sustained ( Pintrich, Schunk, & A ; Meece, 2008 ) and as a status that direct and stimulate behaviour ( Barbara, Geoffrey, & A ; Willem, 2009 ) . Systematically, Alderman ( 2008 ) argued that motive has three maps: activating or triping behaviour, directing behaviour and modulating the continuity of behaviour. Expectancy value theory is one of the most comprehensive theories that explain these three maps of motive.

Expectancy value theory proposes that persons ‘ anticipations for success and the subjective value they attach for wining are of import determiners of persons ‘ motive to execute different accomplishment undertakings ; their picks of which undertakings to prosecute, and their continuity and public presentation ( Atkinson, 1957 ; Denissen, Zarrett, & A ; Eccles, 2007 ; Eccles, 1994 ; Wigfield & A ; Eccles, 2000, , 2002 ) . In other words, theoreticians argue that persons select the undertakings for which they have the highest outlooks for success and to which they attach the greatest subjective undertaking value ( Denissen, Zarrett, & A ; Eccles, 2007 ) . Eccles and her co-workers developed a theoretical account based on anticipation value theory ( Eccles, 1994 ; Wigfield & A ; Eccles, 2000, , 2002 ) . Eccles and co-workers ‘ theoretical account attempted to explicate persons ‘ motive, accomplishment related picks and public presentation ( Figure 2.2. ) .

Figure 2.2. Eccles ‘ and Colleagues ‘ Expectancy-Value Model of Achievement Motivation, Figure taken from Wigfield & A ; Eccles, 2000 ; p.69.

As seen in Figure 2.2. , in this theoretical account, public presentation, continuity, and pick of accomplishment undertakings ( such as class registrations and occupational pick ) are most straight predicted by two variables: anticipations for success and the value attached to the assorted achievement-related options. In bend, anticipations for success and subjective values are influenced by other accomplishment related beliefs ( achievement ends, self-schemata, and undertaking specific beliefs ) . These beliefs are influenced by persons ‘ readings of old public presentation, their readings of other ‘s attitudes and outlooks of them, and their memories of similar undertakings. The theoretical account besides links these beliefs to assorted other contextual and cultural influences such as cultural norms, experiences, aptitudes, personal beliefs and attitudes.

Measures of Attitude toward Statisticss

“ It will be conceded at the beginning that an attitude is a complex matter which can non be entirely described by any individual numerical index ” ( Thurstone, 1928 ) p.530

Although attitudes were routinely represented by a individual numerical index ; societal scientists have long recognized that this pattern is deficient to capture all relevant belongingss of attitudes ( Fabrigar, MacDonald, & A ; Wegener, 2005 ) . As antecedently mentioned, attitude is a conjectural concept which is unaccessible to direct observation and must be inferred from mensurable responses ( Ajzen, 1988 ) . Furthermore, attitudes should be formed through cognitive, affectional and behavioural procedures and expressed through cognitive, affectional and behavioural responses ( Eagly & A ; Chaiken, 2005 ) . Therefore, it can be argued that an instrument developed to mensurate statistics attitudes should reflect the multidimensionality of attitudes and include cognitive, affectional and behavioural responses. Additionally, the instrument should besides include “ fine-tunes ” subscales with an acceptable factorial construction ( Gal & A ; Ginsburg, 1994 ) .

Early Statisticss Attitudes Instruments

Get downing in 1980s, many instruments were developed to mensurate pupils ‘ attitudes toward statistics. These instruments included Statistics Attitudes Survey ( Roberts & A ; Bilderback, 1980 ) , Atittudes Toward Statistics ( Wise, 1985 ) , Multi-factorial Scale of Attitudes Toward Statistics ( Auzmendi, 1991 ) , and Students Attitudes Toward Statistics ( Sutarso, 1992 ) . These instruments are presented in Table 2.1 along with their constituents and internal consistence values.

Table 2.1.

Some Examples of the Attitude toward Statistics Measures

Attitude toward Statistics Instruments

Components

Croanbach alpha

Special air service: Statisticss Attitudes Survey

( Roberts & A ; Bilderback, 1980 )

One constituent

.90-.95

Astatine: Attitudes Toward Statisticss: ( Wise, 1985 )

Course, Field

1. .90

2. .92

MSATS: Multi-factorial Scale of Attitudes Toward Statistics

( Auzmendi, 1991 )

Motivation, Enjoyment, Anxiety, Confidence, Usefulness

.60- .87

STATS: Students Attitudes toward Statisticss ( Sutarso, 1992 )

Students ‘ involvement and future pertinence, Relationship and impact of the teacher, Attitude toward statistical tools, Self-confidence, Parental influence, Initiative and excess attempt in larning statistics

.86

( for overall graduated table )

In a reappraisal of attitudes toward statistics instruments, the most used instruments were Statistics Attitudes Survey ( Roberts & A ; Bilderback, 1980 ) , Attitudes toward Statistics ( Wise 1985 ) and Survey of Attitudes toward Statistics ( SATS, Schau et al. , 1995 ) . Equally far as is known, Statistics Attitudes Survey ( SAS ) was the first instrument developed to mensurate attitudes toward statistics. It is a uni-dimensional, five-point Likert-type graduated table with 33 points. The dependability coefficients were reported as runing from.90 to.93 when the instrument was administered to three samples of alumnus pupils taking introductory statistics classs ( Roberts & A ; Bilderback, 1980 ; Roberts & A ; Reese, 1987 ; Roberts & A ; Saxe, 1982 ) . Although SAS has been used widely, some jobs have been reported about the Statistics Attitude Survey. Some of these jobs can be listed as followers: the instruments ‘ being one dimensional assumes that attitudes are uni-dimensional ‘ some points step pupils ‘ cognition of statistics instead than their attitudes, and the instrument is non suited for the disposal at the beginning of a statistics class ( Gal & A ; Ginsburg, 1994 ; Rhoads & A ; Hubele, 2000 ; Schau, 2003 ; Waters, Martelli, Zakrajsek, & A ; Popovich, 1988 ; Wise, 1985 ) .

Five old ages after the development of SAS, Wise ( 1985 ) developed his Attitudes toward Statisticss ( ATS ) graduated table. Like SAS, this instrument had a five-point Likert-type graduated table. It consisted of 29 points with two constituents: attitudes toward statistics class and attitude toward statistics field. Wise ( 1985 ) reported dependability coefficients as.92 for field and.90 for class subscales, which indicated that he had extremely dependable tonss when the instrument was administered to his sample of 92 introductory instruction statistics pupils. Although Wise ( 1985 ) developed his instrument to work out the jobs voiced for SAS, his instrument was besides criticized in recent surveies. Some of these surveies argued that the field and class constituents of ATS did non cover attitudes toward statistics concept and this two constituent construction had non been validated suitably ( Gal & A ; Ginsburg, 1994 ; Schau, 2003 ; Schau, Stevens, Dauphinee, & A ; DelVecchio, 1995 ) .

In drumhead, the early statistics attitude instruments along with the largely used 1s had high internal consistence values in several surveies. However, these instruments were non conclusive in footings of their subscales. As it was mentioned before, there has been no consensus on the definition of attitudes in societal psychological science. Consequently, there exists no consistence on the constituents of the instruments that attempt to mensurate pupils ‘ attitudes toward statistics. This indicated that development of early statistics attitude steps were non based on solid theoretical backgrounds. This point is really of import to advert since it caused several jobs in understanding research on attitudes toward statistics as it made it hard to compare research surveies with different steps holding different constituents. Therefore, there existed a demand for the development of a new instrument which would hold a strong theoretical background and good defined constituents with an acceptable factorial construction.

Survey of Attitudes toward Statistics-36A© ( SATS-36A© )

Schau, et Al. ( 1995 ) suggested that a statistics attitude study should hold several features. Some of these features were that the graduated table should include the most of import dimensions of attitudes, it should be applicable to different statistics classs, pupils ‘ input should be taken in the study development procedure, and content cogency and construction of the study should be supported through confirmatory analysis techniques. They argued that none of the bing statistics attitude studies had all of these features. Therefore, Survey of Attitudes toward StatisticsA© ( SATSA© ) was developed to include these properties.

Survey of Attitudes toward StatisticsA© has a seven-point response graduated table ( 1=strongly disagree, 4= neither disagree nor agree, 7= strongly agree ) in which higher tonss corresponds to positive attitudes. The study is available in pre and station versions to mensurate attitude toward statistics at the beginning and at the terminal of the class. The study was ab initio developed with 28 points measuring four constituents: Affect, Value, Cognitive Competence and Difficulty. More late, two other constituents: Attempt and Interest were added to the instrument based on Eccles ‘ anticipation value theory ( Schau, 2003 ) . Hence, the current Survey of Attitudes toward Statistics -36A© ( SATS-36A© ) outputs six constituents with 36 points. In add-on to the 36 points, SATS-36A© includes points that buttocks other concepts such as pupils ‘ features and old accomplishment in mathematics and statistics.

Survey of Attitudes toward Statistics has been used in a figure of surveies that involved samples with different educational degrees, big leagues and nationalities ( Barkatsas, Gialamas, & A ; Bechrakis, 2009 ; Chiesi & A ; Primi, 2008 ; Tempelaar, Loeff, & A ; Gijselaers, 2007 ; Verhoeven, 2009 ) . Consequences of these surveies showed that the SATSA© has good psychometric belongingss.

The six-factor construction of the SATSA© has been validated with maximal likelihood confirmatory factor analysis techniques in some of these surveies The consequences demonstrated a really good tantrum of the informations to the hypothesized six-factor theoretical account ( Tempelaar, Loeff, & A ; Gijselaers, 2007 ; Verhoeven, 2009 ) .

The internal consistences of the subscales have been estimated in current surveies. These surveies showed that the six constituents in SATSA© exhibit largely high internal consistences. Cronbach ‘s alpha values normally vary from.80-.82 for Affect, .77-.85 for Cognitive Competence, .78-.88 for Value, and.68-.79 for Difficulty, .80 to.90 for Interest, .76 to.80 for Effort ( Carnell, 2008 ; Tempelaar, Loeff, & A ; Gijselaers, 2007 ; Verhoeven, 2009 ) . The Croanbach alpha values that are calculated in selected surveies were presented in Table 2.2.

Table 2.2.

Comparison of Croanbach Alpha Values of SATS-36A© Subscales in Different Surveies

Tempelaar et al. , 2007

Carnell, 2008

Verhoven, 2009

Affect

.82

.81

.80-.82

Cognitive Competence

.78

.85

.77-.82

Value

.78

.88

.78-.82

Trouble

.68

.79

.71-.75

Interest

.80

.90

.83-.84

Attempt

.76

.79

.80

In this thesis survey, SATS-36A© was used for several grounds. First, SATSA© is a widely used and the most current instrument developed to measure attitudes toward statistics. Second, psychometric belongingss of the instrument is extensively documented and supported by collateral analysis techniques. Third, the coevals of the subscales was based on a strong theoretical background. Fourth, it has been used across different cultural contexts.

Research on Attitudes toward Statisticss

Although attitudes toward statistics has non been a great concern for research workers in field for a long period of clip, there have been some involvement on the relationship between pupils ‘ attitudes and accomplishment in statistics, the alteration in pupils ‘ attitudes over clip and factors impacting pupils ‘ attitudes toward statistics.

Correlation between Achievement and Attitudes toward Statisticss

Several surveies have been conducted to analyze the correlatives of attitudes toward statistics. Some of the early surveies investigated the relationship between attitudes toward statistics and statistics accomplishment. In 1954, Bendig and Hughes conducted a survey with two samples of 50 and 71 pupils. They reported that attitudes toward statistics accounted for four to five per centum of variableness in pupils ‘ statistics achievement ( Bendig & A ; Hughes ) . Twenty-four old ages after, Feinberg and Halperin ( 1978 ) supported their findings with a sample of 278 pupils enrolled in introductory statistics classs. They found that class public presentation was positively correlated with pupils ‘ attitude toward quantitative topics and negatively correlated with state-trait anxiousness ( Feinberg & A ; Halperin, 1978 ) . Taken together, these early surveies demonstrated the being of positive correlativities between attitude toward statistics and statistics accomplishment.

The correlational surveies on pupils ‘ attitudes toward statistics were accelerated during the past 20 old ages. These surveies can be examined in two groups. The first group of these surveies investigated the correlativity of attitudes toward statistics and statistics accomplishment ; nevertheless, the 2nd group examined the correlativity of the accomplishment and statistics or trial anxiousness.

The recent research that focused on the relationship between attitudes toward statistics classs and accomplishment in statistics largely resulted in statistically important and positive correlativities. For illustration, Perney and Ravid ( 1990 ) found that 60 eight maestro grade instruction pupils ‘ class public presentation was significantly correlated with old attitudes toward statistics as a class, but non with attitudes toward statistics as a field ( Perney & A ; Ravid, 1990 ) . Likewise, Vanhoof et Al. ( 2006 ) reported positive correlativities between attitudes toward statistics as a class and short term statistics exam consequences when they collected informations from 72 educational pupils in Belgium ( Vanhoof et al. , 2006 ) . At the same twelvemonth in United States, Lawless and Kulikowich ( 2006 ) collected informations from 267 pupils from three university systems. They found positive and statistically important relationship between pupils ‘ involvement in statistics and their statistics cognition ( Lawless & A ; Kulikowich, 2006 ) .

The 2nd group of current correlational surveies investigated the correlativity between statistics achievement and anxiousness as being one of the dimensions of attitudes toward statistics. In 1996, Fitzgerald and Jurs collected informations from 109 alumnus pupils. They found important correlativities between statistics achievement and statistics test anxiousness ( Fitzgerald, 1997 ) . Two old ages subsequently, Schutz et Al. ( 1998 ) supported their findings. They collected informations from 94 alumnus pupils and reported a important correlativity between statistics public presentation and trial anxiousness ( Schutz, Drogosz, White, & A ; Distefano, 1998 ) .

In drumhead, all of these consequences combined from early and resent literature confirm the hypothesis that attitudes toward statistics correlatives to statistics accomplishment.

Pretest-Posttest Design Studies on Attitudes toward Statisticss

There are a limited figure of pretest-posttest design surveies on attitudes toward statistics. One group of these surveies investigated the alteration in pupils ‘ attitudes toward statistics before and after taking a statistics class ( Evans, 2007 ; Limpscomb, Hotard, Shelley, & A ; Baldwin, 2002 ; Sizemore & A ; Lewandowski, 2009 ) ; whereas, the other group of the surveies investigated the alterations in pupils ‘ attitudes toward statistics when a untraditional instructional method is presented in statistics classs ( Neter & A ; Chervany, 1973 ; Rhoads & A ; Hubele, 2000 ; Sciutto, 1995 ) . See Table 2.1. for some illustrations of pretest-posttest design surveies on attitudes toward statistics.

Table 2.1.

Selected Pretest-Posttest Design Studies on Students ‘ Attitudes toward Statisticss

Survey

Findingss

Neter & A ; Chervany, 1973

No alteration in pupils ‘ attitudes toward statistics over the semester taking a computing machine assisted statistics class

Sciutto, 1995

Students centered instructional methods decreased pupils ‘ anxiousness toward statistics and increased pupils ‘ degree of involvement in statistics

Stork, 2003

Student generated informations increased pupils sensed competency in statistics

Rhoads & A ; Hubele, 2000

No alteration in pupils ‘ attitudes toward statistics over the semester in a computing machine integrated statistics class

Limpscomb et al. , 2002

Students ‘ cognitive competency and impact toward statistics increased but the value of statistics and trouble of statistics subscales did non alteration over the semester

Evans, 2007

No alteration in pupils ‘ attitudes toward statistics over the semester

Sizemore & A ; Lewandowski, 2009

No alteration between pupils ‘ attitudes toward statistics from the beginning to the terminal of a statistics class, but a diminution in pupils ‘ tonss on the sensed public-service corporation of research and statistics

In a research article by Evans ( 2007 ) , no alteration from 115 pupils ‘ pre attitudes toward statistics to post attitudes toward statistics was reported. This is supported by Sizemore and Lewandowski ( 2009 ) who reported no alteration between 92 undergraduate psychological science pupils ‘ attitudes toward statistics from the beginning to the terminal of a statistics class, but a diminution in pupils ‘ tonss on the sensed public-service corporation of research and statistics. Contrarily, in a survey with 97 sophomore degree bussiness pupils, Limpscomb et Al ( 2002 ) found that pupils ‘ cognitive competency and impact toward statistics increased from pre-test to post trial. But they supported antecedently mentioned surveies in a manner that pupils ‘ tonss of the value of statistics and trouble of statistics subscales did non alteration from the beginning to the terminal of the semester. Take together, these consequences indicated that taking an introductory statistics class was non ever an effectual manner to increase positive attitudes toward statistics. Therefore, research workers in the field tested the function of utilizing different instructional methods in statistics classs on pupils ‘ attitudes toward statistics.

In an early survey by Neter and Chervany ( 1973 ) the consequence of utilizing computing machines on pupils ‘ attitudes toward statistics was investigated. The consequences indicated that there were no alteration in pupils ‘ attitudes toward statistics after taking a computing machine assisted statistics class ( Neter & A ; Chervany, 1973 ) . Similarly, Rhoads and Hubele ( 2000 ) reported that, in general, pupils ‘ attitudes toward the field of statistics and class of statistics did non alteration over the semester in a computing machine integrated statistics class with 63 undergraduate technology pupils ( Rhoads & A ; Hubele, 2000 ) . It can be argued that utilizing computing machines in statistics classs are non entirely an effectual manner to increase pupils ‘ positive attitudes toward statistics. Hence, Scuitto ( 1995 ) investigated the function of utilizing pupil centered methods in an introductory degree statistics class on 17 undergraduate psychological science pupils ‘ involvement and anxiousness degrees. These methods included individualized category illustrations and student-generated informations sets. He concluded that these methods decreased pupils ‘ anxiousness toward statistics and increased pupils ‘ degree of involvement in statistics ( Sciutto, 1995 ) . Similarly, Stork ( 2003 ) concluded that working with their ain informations enhanced pupils ‘ perceived competency in her class with 80 undergraduate concern pupils ( Stork, 2003 ) .

In drumhead ; although, research showed assortment of findings, there besides seems to be a general understanding on the stableness of pupils ‘ attitudes toward statistics before and after taking statistics classs. Current literature reappraisal besides demonstrated that experimental surveies which investigate the effects of untraditional instructional methods on pupils ‘ attitudes toward statistics are needed. For this intent, a literature reappraisal on experimental design surveies were presented in the following subdivision.

Experimental Studies on Attitudes toward Statisticss

A little figure of experimental surveies have investigated the effects of assorted instructional methods on pupils ‘ attitudes toward statistics. Some of these methods included on-line direction, undertaking based direction and pupil centered direction. One of these surveies was conducted by Suanpang, Petocz and Kalceff ( 2004 ) . The focal point of the survey was to look into the consequence of on-line direction on pupils ‘ attitudes toward statistics. The sample consisted of 112 online and 118 traditional group pupils enrolled in Business Statistics categories. Consequences revealed that pupils ‘ attitudes toward statistics tonss ( measured by affect, value, cognitive competency, and easiness subscales ) in the online group had increased while the traditional group remained in the same degree in footings of affect, cognitive competency and value and they even scored lower in footings of the relaxation of statistics ( Suanpang, Petocz, & A ; Kalceff, 2004 ) . The consequence indicated that on-line direction helped pupils to hold more positive attitudes toward statistics. With a similar attack, Wiberg ( 2009 ) revised a statistics class for psychological science pupils and investigated the difference between traditional ( n=20 ) and revised class ( n=24 ) pupils ‘ attitudes toward statistics. The revised class included a class web page, computing machine based assignments, and a job based learning techniques based on pupil centered acquisition. She reported that pupils in the revised group showed significantly higher cognitive competency in statistics, and value and impact toward statistics ; whereas pupils attitudes toward the relaxation of the statistics is about the same in two groups ( Wiberg, 2009 ) . Perversely to the antecedently mentioned experimental surveies, Carnell ( 2008 ) did non happen important difference between experimental group ( n=24 ) and control group ( n=18 ) pupils ‘ attitudes toward statistics when she investigated the consequence of utilizing pupil informations aggregation undertakings ( Carnell, 2008 ) . However, she pointed out the possible presence of several confusing variables. She besides argued that this one survey did non happen any average difference did non intend that undertakings do non heighten attitudes. Therefore, more surveies needed to be done in order to understand the effects of utilizing undertakings on pupils ‘ attitudes toward statistics.

In drumhead, the consequence of utilizing untraditional instructional methods in statistics classs on pupils ‘ attitudes toward statistics was investigated in a restricted figure of surveies. These surveies suggest that utilizing different methods in statistics direction can heighten more positive attitudes toward statistics. However, farther surveies are required in order to better understand the consequence of utilizing different instructional methods on pupils ‘ attitudes toward statistics.

Research on Attitudes toward Statistics in Turkey

A restricted figure of surveies examined pupils ‘ attitudes toward statistics in Turkey. It is extremely hard to compare and contrast these surveies. Because the research workers in those surveies developed and used different instruments mensurating different subscales, included samples from different educational degrees and big leagues, and they used different variables. A sum-up of the selected surveies that were conducted with Turkish participants were presented below.

In an experimental survey by Dogan ( 2009 ) , he compared computing machine based direction group ( n=35 ) and control group ( n=35 ) undergraduate pupils ‘ attitudes toward statistics and statistics accomplishment. He developed and administered a one dimensional, 34 point graduated table to mensurate pupils ‘ attitudes. Consequences indicated that computing machine based direction increased both pupils ‘ statistics accomplishment and pupils ‘ attitudes toward statistics ( Aldogan & A ; Aseeri, 2003 ) . Another experimental survey was conducted by YA±lmaz ( 2006 ) . In her thesis survey, she investigated the effects of real-data and reckoner supported activities on eighty four seventh graders ‘ public presentation and attitudes toward statistics. Her sample divided into three groups: reckoner and real-data based ( n=27 ) , existent informations based ( n= 29 ) , and a control group ( n=28 ) . The statistics attitude step was by the research worker that included two subscales: enjoyment and assurance in statistics. YA±lmaz ( 2006 ) reported no important differences among groups in footings of attitudes toward and accomplishment in statistics.

I will add Emmioglu, Capa-Aydin, Cobanoglu ( 2010 ) here and summarize all here

Structural Models on Achievement and Attitudes toward Statisticss

Several surveies investigated the function of multiple attitudinal variables on explicating statistics achievement utilizing Structural Equation Modeling. The consequences obtained from the literature are non comparable as different variables were used in each survey. Therefore, a sum-up of the countries that are most relevant to this thesis research, old experience, old accomplishment, and attitudes toward statistics variables, were presented below.

Equally far as is known, the first statistics attitude-achievement theoretical account was developed by Lalonde and Gardner ( 1993 ) . They conceptualized the acquisition of statistics as correspondent to the acquisition of a linguistic communication and based their theoretical account on a theory of linguistic communication larning. They reported important impact of mathematical aptitude, attitude, and attempt on pupils ‘ statistics achievement ( Lalonde & A ; Gardner, 1993 ) . Similarly, in 2002, Harlow investigated the impact of mathematical aptitude and attitudes on pupils ‘ public presentation in statistics. The attitudes variables were measured by pupils ‘ tonss on anxiousness, self-efficacy, perceived hinderances in this survey. The sample consisted of 129 quantitative methods for psychological science classs pupils. Like Lalonde and Gardner ( 1993 ) , they reported important impact of quantitative aptitudes and attitudes on public presentation in statistics. However, they did non happen a important consequence of aptitudes on pupils ‘ attitudes ( Harlow, Burkholder, & A ; Morrow, 2002 ) . In a similar attack with Lalonde and Gardner ( 1993 ) , Onwuegbuzie ( 2003 ) developed a theoretical account for foretelling statistics accomplishment which is based on a foreign linguistic communication achievement theoretical account. He included several cognitive ( analyze wonts and pupils ‘ outlooks of their public presentation in statistics scrutinies ) affective ( statistical anxiousness and research anxiousness ) and demographic variables ( figure of college-level research methodological analysis courses taken, figure of college-level statistics classs taken, and class burden ) to his theoretical account. The sample consisted of 130 alumnus pupils from a figure of instruction subjects. He found that statistics anxiousness and achievement outlook played a cardinal function in the theoretical account, interceding the relationship between statistics achievement and the undermentioned variables: research anxiousness, survey wonts, class burden, and the figure of statistics classs taken ( Onwuegbuzie, 2003 ) . Systematically, Tempelaar, et Al. ( 2007 ) reported effects of attitudes toward statistics on statistics public presentation. In this survey, they investigated the impact of statistics attitudes on statistics achievement and concluding abilities by gauging a structural equation theoretical account. This theoretical account was based on anticipation value theory. They collected informations from 842 concern and 776 economic sciences pupils in the Netherlands. They found a statistically important impact of Effort, Value, Difficulty, and Interest variables on statistical logical thinking and a statistically important impact of Cognitive Competence, Difficulty, and Effort on public presentation in statistics ( Tempelaar, Loeff, & A ; Gijselaers, 2007 ) .

In decision, there have been several structural theoretical account surveies conducted with samples changing in big leagues, nationalities and instruction degrees. Despite the differences in the samples, instruments and variables used, these surveies revealed one generalizable premise. This was that pupils ‘ old aptitude in statistics and their attitudes toward statistics are of import factors explicating their accomplishment in statistics.

Statisticss Attitudes-Achievement Structural Model

Sorge and Schau ( 2002 ) developed and tested a theoretical account interrelating undergraduate technology pupils ‘ anterior academic success, attitudes toward statistics and accomplishment degrees in introductory statistics and chance class. The theoretical account was chiefly based on Eccles and co-workers ‘ application of anticipation value theoretical account of accomplishment. The sample consisted of 264 pupils. Survey of Attitudes toward Statistics for Engineers ( SATS-EA© ) which was modified from SATSA©-28A© was used to roll up informations. The theoretical account consisted of six latent variables: Previous Success, Difficulty, Cognitive Competence, Affect, Value, and Achievement. The tried theoretical account demonstrated that Previous Success had a big entire affect on Achievement. Difficulty, Cognitive Competence and Affect had medium entire affects on Achievement and Value had no entire Affect on Achievement ( Figure 2.2. ) .

In amount, consequences indicated that both Prior Achievement and attitude toward statistics variables impact technology pupils ‘ accomplishment in introductory statistics classs ( Sorge & A ; Schau, 2002 ; Sorge, Schau, & A ; Emmioglu, 2010 ) .

Figure 2.2. Pruned Statistics Attitudes-Achievement Structural Model, Figure was Adapted from Sorge, Schau & A ; Emmioglu, 2010

This survey contributed to the field of statistics instruction by showing the complex relationships between attitudes toward statistics and statistics accomplishment. The research workers based their theoretical account on a strong theoretical background, chiefly expectancy value theory of achievement motive. Furthermore, they used an instrument, Survey of Attitudes toward StatisticsA© , which was a validated, a normally used and the most current statistics attitudes instrument at the clip of the survey. Additionally, the tried theoretical account systematically contributed to the findings of old research ( Bandalos, Finney, & A ; Geske, 2003 ; BudeA? , Imbos, Wiel, Broers, & A ; Berger, 2009 ; Nasser, 2004 ; Tempelaar, Loeff, & A ; Gijselaers, 2007 ) . However, there besides were some restrictions. First, the survey was limited with undergraduate technology pupils in a university in U.S. Secondly ; the instrument used in the survey was the earlier version of Survey of Attitudes toward Statistics. Therefore, research surveies with extra concepts, with the updated version of SATSA© and with other samples of different cultural contexts are needed. For this intent, Statistics Attitudes Model was developed and tested in this thesis survey.

Statisticss Attitudes Model

Description of Statistics Attitudes Model

The Statistics Attitudes Model was chiefly based on Eccles ‘ Expectancy-Value theory of achievement-motivation. The theoretical account included nine concepts: Previous Achievement, Student Characteristics, Statistics Outcomes, Cognitive Competence & A ; Expectancy, Affect, Value, Difficulty, Effort and Interest ( Figure 2.3. ) . The six attitudes toward statistics constituents, Cognitive Competence & A ; Expectancy, Affect, Value, Difficulty, Effort and Interest, were measured by utilizing SATS-36. Previous Achievement was measured by pupils ‘ old grade point average tonss and their old accomplishment in mathematics and statistics. Student features were measured by their big leagues, educational degree or their grades. Last, Statistics Outcomes refer to the pupils classs earned in statistics classs and their pick of taking another statistics class in the hereafter.

Student Characteristics and Difficulty were the exogenic variables of the survey since their causes were non represented in the theoretical account. However, the impacts of them on the other latent concepts were presented in the theoretical account.

The endogenous latent concepts of the survey, Previous Achievement, Cognitive Competence and Expectancy of Success, Affect, Interest, Effort and Value, were assumed to be affected by the exogenic variables of the survey and assumed to impact the result variable of the survey. Statistics Outcome was the result variable which was assumed to be affected by the six attitudes ‘ concepts and Previous Achievement and Student Characteristics variables.

Figure 2.3. Statisticss Attitude Model

Theoretical Framework for the Statistics Attitudes Model

As antecedently mentioned, several theories attempt to explicate the function of attitudes on human behaviour. As statistics attitudes theoretical account besides attempts to explicate the function of attitudes toward statistics on statistical results it is theoretically based on some of these theories: acquisition theories, the theory of reasoned action and planned behaviour, self-efficacy and self finding theories, involvement theories, and anticipation value theory. From these theories, Statistics Attitudes Model coincides with the theories of Learning, Theories of Planned Behavior, and Theories of Reasoned Action as these theories support the thought that attitudes are the determiners of human behaviour. Second, Statistics Attitudes Model is consistent with Self Efficacy and Self Determination theories. Like these theories, statistics attitude theoretical account assumes that persons ‘ judgement of their competence is a map of the perceptual experience of undertaking and their past experience and anterior beliefs about the undertaking. This premise was transferred to the statistics theoretical account in a manner that pupils ‘ cognitive competency-expectancy for success are affected by pupils ‘ perceptual experience of the trouble of statistics and their old accomplishment in statistics. Third, the theoretical account is consistent with the theory of Self Determination with respect to the function of the involvement, value and assurance on human behaviour. Fourthly, the theoretical account is supported with Interest theories as these theories focuses on the demand of Interest for explicating human behaviour. Likewise, Statistics Attitudes Model assumes that Interest has impact on Statistics Outcomes.

Last and chiefly, Statistics Attitudes Model is based on Eccles ‘ Expectancy Value theory of achievement-motivation. In Eccles ‘ expectancy-value theoretical account, it was assumed that old accomplishment related experiences and pupil features impact pupils ‘ affective memories which in bend affect pupils subjective undertaking values attributed to the accomplishment pick. Eccles ‘ theoretical account besides assumes the impact of subjective undertaking values, self construct of abilities and perceptual experience of undertaking demands on the accomplishment related picks. Similarly, Statistics Attitude Model assumes that old accomplishment and pupil features impact pupils ‘ Affect toward statistics which in bend impact their perceptual experience of the Value of statistics. In a similar attack with Eccles ‘ theoretical account, statistics attitudes model suggests the impact of the pupils ‘ perceptual experiences of the Value of statistics, Cognitive Competence and Success Expectancy of Statistics, the perceptual experience of Difficulty of Statistics on Statistics Outcomes.

Although Eccles ‘ anticipation value theoretical account and statistics attitudes theoretical account has indispensable similarities, these two theoretical accounts have some differences. In Eccles ‘ theoretical account, the Task Demands were assessed by the trouble of the topic for a specific pupil nevertheless in this survey Difficulty was assessed by inquiring pupils about their attitudes toward the trouble of statistics as a topic for general people. Second, the concepts named as Self Concept of One ‘s Abilities and Expectation of Success were combined into one latent concept in Statistics Attitudes Model and called as Cognitive Competence-Expectancy of Success. The ground for this alteration was that Eccles and co-workers reported that these concepts can non be distinguished through empirical observation ( Denissen, Zarrett, & A ; Eccles, 2007 ; Eccles, O’Neill, & A ; Wigfield, 2005 ; Eccles & A ; Wigfield, 1995 ; Wigfield & A ; Eccles, 2000 ) . Likewise, Previous Achievement related Experiences and Interpretations of Previous Experiences were combined into one concept ( Previous Achievement ) in Statistics Attitudes theoretical account. In Statistics Attitudes Model, two dimensions of Eccles ‘ Subjective Task Value ( Attainment Value and Utility Value ) were combined into a concept called Value in Statistics Attitudes Model. In add-on, one of the Subjective Task Value dimensions which is called Cost was represented by the Effort concept in Statistics Attitudes Model since this concept was measured by the Effort constituent of the SATS-36A© . Last, Intrinsic Value dimension of the Subjective Task Value was separated and called as Interest in Statistics Attitudes Model ( Schau, Emmioglu, & A ; Ramirez, 2010 ) .

Empirical Support for the Statistics Attitudes Model

Beside the fact that Statistics Attitudes Model was based on a theoretical background, it was besides based on empirical findings. Many research surveies supported the direct effects that are proposed in Statistics Attitudes Model, These surveies are presented in Table 2.2.

Table 2.2.

Empirical Support on the Statistics Attitudes Model

Concept

Direct consequence on Construct ( Study )

Trouble

Cog. C. & A ; Expectancy ( Sorge, 2001 ) ;

Interest ( Eccles, 1983 )

Previous Accomplishment

Cognitive Competence ( Bruinsma, 2004 ; Meece, Wigfield, & A ; Eccles, 1990 ) , Affect ( Mills, 2004 ) ;

Course Outcomes ( Fitzgerald, 1997 )

Student Features

Previous Achievement ( Schram, 1996 )

Cognitive Competence and Expectancy

Affect ( Meece, Wigfield, & A ; Eccles, 1990 ; Sorge, 2001 ) ;

Interest ( Marsh, Trautwein, Ludtke, Koller, & A ; Baumert, 2005 ) ; Effort ( Greene, DeBacke, Ravindran, & A ; Krows, 1999 ) ;

Course Outcomes ( Bandura & A ; Schunk, 1981 ; Marsh, Trautwein, Ludtke, Koller, & A ; Baumert, 2005 ; Valentine, DuBois, & A ; Cooper, 2004 )

Attempt

Course Outcomes ( Cole, Bergin, & A ; Whittaker, 2008 ; Tempelaar, Loeff, & A ; Gijselaers, 2007 )

Interest

Outcomes ( Ainley, Hidi, & A ; Berndorff, 2002 ; Denissen, Zarrett, & A ; Eccles, 2007 ; Simpkins, Davis-Kean, & A ; Eccles, 2006 ) ;

Effort ( Greene, DeBacke, Ravindran, & A ; Krows, 1999 )

Affect

Value ( Meece, Wigfield, & A ; Eccles, 1990 ; Sorge, 2001 ) ; Outcomes ( Bruinsma, 2004 )

Value

Outcomes ( Meece, Wigfield, & A ; Eccles, 1990 ; Simpkins, Davis-Kean, & A ; Eccles, 2006 )

Drumhead

This chapter foremost presented the theories related to this survey. A reappraisal of old instruments used to mensurate attitudes toward statistics and research theoretical accounts on statistics accomplishment was provided along with the specific development of the SATS and achievement motive theoretical account of statistics larning.

In behavioural acquisition theory, motive is a effect of support. In Maslow ‘s human needs theory, people must fulfill their lack demands before they will be motivated to seek to fulfill their higher degree demands. Attibution theory seeks to understand people ‘s accounts for their success or failure. Expectancy theory holds that a individual ‘s motive to accomplish something depends on the merchandise of that individual ‘s appraisal of his or her opportunity of success and the value he or she places on success.