Computers & Education 75 (2014) 1–18

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Computers & Education

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The effects of UZWEBMAT on the probability unitachievement of Turkish eleventh grade students and thereasons for such effects

Özcan Özyurt a,*, Hacer Özyurt a, Bülent Güven b, Adnan Baki b

a Software Engineering Department, Faculty of Technology, Karadeniz Technical University, Of, Trabzon, TurkeybDepartment of Science and Mathematics Education, Karadeniz Technical University, Akçaabat, Trabzon, Turkey

a r t i c l e i n f o

Article history:Received 28 September 2013Received in revised form5 February 2014Accepted 6 February 2014Available online 19 February 2014

Keywords:Evaluation of CAL systemsImproving classroom teachingInteractive learning environmentsMultimedia/hypermedia systemsTeaching/learning strategies

* Corresponding author. Tel.: þ90 4627717250 848E-mail addresses: oozyurt@ktu.edu.tr (Ö. Özyurt),

http://dx.doi.org/10.1016/j.compedu.2014.02.0050360-1315/� 2014 Elsevier Ltd. All rights reserved.

a b s t r a c t

This study aimed at determining the effects of UZWEBMAT (Turkish abbreviation of Adaptive andINtelligent WEB based MAThematics teaching–learning system) on the probability unit academicachievement of students and the underlying reasons for these effects. The study was conducted in anAnatolian High School located in a district of Trabzon province, Turkey in the fall semester of the aca-demic year 2011–2012. The research sample consisted of 106 eleventh grade students and 2 mathematicsteachers. Semi-experimental method was used in the study. Pre-Probability Unit Achievement Test (pre-PUAT), Post-Probability Unit Achievement Test (post-PUAT), Scale for Evaluation of the UZWEBMAT byStudents (SEUS), Student Interview Form (SIF), and Teacher Interview Form (TIF) were used for collectingdata. Research results indicated that there was a statistically significant difference in favor of theexperimental group (EG) students between the academic achievement of the EG students and that of thecontrol group (CG) students. In addition, male EG students were found to be more successful than femaleEG students. However, no statistically significant relationship was found between the learning styles andthe academic achievements of the EG students with different learning styles (visual–auditory–kines-thetic). In addition, no statistically significant relationship was detected between the genders and theacademic achievements of the EG students having different learning styles. It was concluded that thehigher achievement of the EG students resulted from the fact that they received education in accordancewith their learning styles via UZWEBMAT, the learning objects included in UZWEBMAT had appropriatestructural characteristics, students enjoyed learning in that environment, and students had continuousinterest in the lesson.

� 2014 Elsevier Ltd. All rights reserved.

1. Introduction

The advantages brought by technological advancements have led to many changes and innovations in the field of education. The mostimportant change is the frequent use of computers in educational activities. As a result, such concepts as computer-based learning,computer-based education, computer-assisted learning, and computer-assisted education have arisen (Baki, 2002; Brown, 2007; Handal &Herrington, 2003). Improvements in information technologies have led to a differentiation and a variation in computer-assisted learning.These environments have caused the emergence of phenomenon called “ubiquitous learning”. In the most general sense, this phenomenonis referred to as electronic learning. It is also called with such different names as e-learning, web-based learning, web-based teaching, web-based education, and virtual learning environment (Kainnen, 2009). Today, the advantages brought by web-based teaching are frequentlyused for mathematics learning, too (Baki & Güveli, 2008; Crippen & Earl, 2007; Handal & Herrington, 2003; Sitzmann, Kraiger, Stewart, &Wisher, 2006). Although Web-Based Learning Environments (WBLEs) bring along many advantages to education generally and to math-ematics education specifically, how these environments should be designed has been a matter of dispute.

In the WBLE, all students are collected in the “same virtual classroom” environment (Twigg, 2003). However, this is not in absoluteharmony with the real life. This is because; everyone has unique characteristics in real life. In this respect, the use of personalized/

5.hacerozyurt@ktu.edu.tr (H. Özyurt), bguven@ktu.edu.tr (B. Güven), abaki@ktu.edu.tr (A. Baki).

Ö. Özyurt et al. / Computers & Education 75 (2014) 1–182

individualized learning materials gains importance in the WBLEs. One of the most important problems in the WBLEs is that students havedifferent learning profiles, different preliminary knowledge, different expectations, and different learning abilities (Inan, Flores, & Grant,2010; Twigg, 2003). Traditional web-based learning environments may prevent many students from keeping their learning processesunder control, and yield negative results in terms of learning motivations and strategies (Berge, 2002; Brusilovsky & Peylo, 2003; Capuano,Gaeta, Micarelli, & Sangineto, 2003; Graf, Kinshuk, & Liu, 2009; Yükselturk & Inan, 2006). These advantages and limitations of the WBLEscause these environments to be criticized in terms of content and presentation (Brusilovsky, 2001). This has led to the emergence andextension of Adaptive and Intelligent Web Based Educational Systems (AIWBESs) as a new approach. AIWBESs offer an individualizedenvironment including different learning strategies and sources, solution supports, and interfaces to students by taking into account theirindividual differences (Brown, 2007; Brown, Brailsford, Fisher, Moore, & Ashman, 2006; Brusilovsky & Peylo, 2003; Inan et al., 2010;Kainnen, 2009; Karampiperis & Sampson, 2005; Mustafa & Sharif, 2011).

The characteristics to be used for individualizing the WBLEs have become an important research subject. Many studies have concludedthat learning styles are one of the most important parameters that can be used for designing AIWBESs and adapting content (Brown, 2007;Brown, Cristea, Stewart, & Brailsford, 2005; Demirbas & Demirkan, 2007; Kainnen, 2009; Karampiperis & Sampson, 2005; Latham, Crockett,McLean, Edmonds, & O’Shea, 2010; Liegle & Janicki, 2006; Manochehr, 2006; Papanikolaou, Mabbott, Bull, & Grigoriadou, 2006). Theliterature contains many studies showing that learning style-based learning/e-learning environments have a positive effect on the academicachievement of students (Aydıntan, Sahin, & Uysal, 2012; Bachari, Abelwahed, & Adnani, 2011; Bozkurt & Aydo�gdu, 2009; Busato, Prins,Elshout, & Hamaker, 1999; Corso et al., 2001; Hsieh, Jang, Hwang, & Chen, 2011; Kraus, Reed, & Fitzgerald, 2001; Lim, Lee, & Richard,2006; Mustafa & Sharif, 2011; Siadaty & Taghiyareh, 2007). In addition, those e-learning environments where a particular learning styleis used are more efficient and satisfying for students, and reduce learning time (Bajraktarevic, Hall, & Fullick, 2003; Graf & Kinshuk, 2007;Manochehr, 2006; Mustafa & Sharif, 2011; Papanikolaou, Grigoriadou, Kornilakis, & Magoulas, 2003; Popescu, 2010; Sangineto, Capuano,Gaeta, & Micarelli, 2008; Triantafillou, Pomportsis, & Demetriadis, 2003; Wang, 2008).

2. Related works

This section deals with the learning style-based AIWBESs reviewed within this scope of this study. 39 studies were reviewed. Table 1provides the distribution of these studies by learning styles, assessment types, and levels.

As is seen in Table 1, the frequencies and percentages of studies based on learning styles are as follows: Felder–Silverman (n ¼ 19,f ¼ 48.72%), Dunn & Dunn (n ¼ 1, f ¼ 2.56%), Honey & Mumford (n ¼ 2, f ¼ 5.13%), Jackson (n ¼ 1, f ¼ 2.56%), Keefe (n ¼ 1, f ¼ 2.56%), Kolb(n¼ 4, f¼ 10.26%), Mixed (n¼ 1, f¼ 2.56%), Myers–Briggs Type Indicator (n¼ 1, f¼ 2.56%), Witkin & Goodenough (n¼ 2, f¼ 5.13%), and VAK/VARK and VARK adaptive (n ¼ 7, f ¼ 17.95%). The frequencies and percentages of studies by levels are as follows: primary education (n ¼ 1,f¼ 2.56%), secondary education (n¼ 2, f¼ 5.13%), and university (n¼ 28, f¼ 71.79%). Some of the studies reviewed do notmention any level(n ¼ 8, f ¼ 20.51%). These studies were presented as a framework.

The architectures, structures, and characteristics of the systems developed were given in 12 studies out of the reviewed 39 studies. Theliterature contains no study evaluating these systems. There are studies evaluating other 27 systems. These studies are divided into fourcategories based on the mode of evaluation: (1) the studies in which only academic achievements are compared (n ¼ 8, f ¼ 29.63%), (2) thestudies inwhich only the views of students are collected (n¼ 13, f ¼ 48.15%), (3) the studies inwhich the views of students and teachers areevaluated together (n ¼ 1, f ¼ 3.70%), and (4) the studies in which both academic achievements are compared and the views of students arecollected (n ¼ 5, f ¼ 18.52%). There are 13 studies in which academic achievements are compared. In 9 of these studies, a significant dif-ference was found in favor of EG students. In other 4 of 13 studies, no statistically significant difference was found between groups.

The evaluation of the studies by subjects shows that these systems are developed for learning and teaching of various subjects (manysubjects of computer sciences in particular). The evaluation of the studies based on levels and subjects indicates that there are a limitednumber of studies in the field of mathematics. As a matter of fact, only 1 study was found to deal with mathematics at secondary educationlevel. The title of this study is TSAL (Tseng, Chu, Hwang, & Tsai, 2008). In this sense, there is a lack of these kinds of studies in the field ofmathematics and at high school level in particular. Thus, it is necessary to make widespread the innovative learning environments thatcorrespond to today’s educational mentality at primary education and secondary education levels. In this respect, the design, imple-mentation, and evaluation of AIWBESs generally for all subjects at primary education and secondary education levels and specifically forvarious subjects of mathematics course may make important contributions to the literature. Furthermore, although the literature containsmany studies investigating the effects of these learning environments on the academic achievement of students, there is no study examiningthe reasons underlying such effects in detail. Therefore, the present study addressed the factors influential on the academic achievement ofstudents as well as the reasons underlying their learning performances. These factors are important for understanding the learning per-formances of students better.

The subjects of probability unit – the subjects most difficult to learn and teach in the mathematics course –were chosen to make up thecontent of the present study. The literature contains many studies focusing on the difficulties encountered when learning and teaching theprobability unit (Fast, 2001; Gürbüz, 2007; Gürbüz & Birgin, 2012; Kafoussi, 2004; Memnun, 2008; Munisamy & Doraisamy, 1998). Some ofthese difficulties are as follows: subjects are generally covered in teacher-centered environments (Gürbüz, 2007), there are not appropriateteaching materials, students have misconceptions on these subjects (Fast, 2001; Gürbüz, 2007; Gürbüz & Birgin, 2012; Manage & Scariano,2010), students have negative attitudes toward the subject of probability (Memnun, 2008), and some of teachers do not/cannot use effectiveand efficient teaching techniques when teaching this subject (Gürbüz, 2007; Memnun, 2008).

It is significant to integrate the AIWBES developed in this study to traditional classroom environment, and investigate whether it brings asolution to the problems encountered in learning and teaching the related subjects. The principal characteristic of the AIWBES developed isthat it takes into consideration the individual differences of students, presents the most suitable content to them and such content areprepared with the intention of enabling students to learn by discovery. In addition, it differs from traditional web-based environments inthat the activities making up the content of the system concretize abstract concepts by establishing a connectionwith the daily life, it adaptsitself depending on the learning performances of students, etc. All in all, the system developed provides an individualized learning envi-ronment which is quite difficult to be obtained in the traditional classroom environment. TraditionalWBLEs fail to create individual learning

Table 1The classification of the systems and studies reviewed in the present study.

Systems and studies Learning styles Evaluations Levels

Felder–Silverman

Dunn &Dunn

Honey &Mumford

Jackson Keefe Kolb Mixed Myers–Briggs typeindicator

Witkin &Goodenough

VAK/VARK andVARK adaptive

Opinionsof students

Opinionsof teachers

Academicachievement

Elementaryeducation

Secondaryeducation

Highereducation

Undeclared

ADAPTAPlan (Baldiriset al., 2008)

U U

AES-CS (Triantafillouet al., 2003)

U U U

AES-LS (Mustafa &Sharif, 2011)

U U U U

AHA! (Stash, Cristea,& De Bra, 2004)

U U

(Akkoyunlu &Soylu, 2008)

U U U U

APeLS (Conlan,Hockemeyer,Wade, &Albert, 2002)

U U U

Arthur (Gilbert& Han, 1999)

U U U

(Bousbia, Rebai,Labat,& Balla, 2010)

U U U

CIMEL-ITS (Parvez &Blank, 2007)

U U

CS383 (Carver,Howard,& Lane, 1999)

U U

DEUS (Brownet al., 2007)

U U U

Diogene (Sanginetoet al., 2008)

U U U

<e-aula> (Sancho,Martinez,& Fernandez-Manjon, 2005)

U U

EDUCA (Cabada,Estrada,& García, 2011)

U U U

eTeacher (Schiaffino,Garcia,& Amandi, 2008)

U U U

ILASH (Bajraktarevicet al., 2003)

U U U

iLearn (Peter, Bacon,& Dastbaz, 2010)

U U

iMANIC (Stern, 2001) U U U

INSPIRE (Papanikolaouet al., 2003)

U U U

iWeaver(Wolf, 2007)

U U U

IWT (Capuanoet al., 2003)

U U

(Kinshuk, Liu,& Graf, 2009)

U U U

(Ku & Chang, 2011) U U U

(continued on next page)

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Table 1 (continued )

Systems and studies Learning styles Evaluations Levels

Felder–Silverman

Dunn &Dunn

Honey &Mumford

Jackson Keefe Kolb Mixed Myers–Briggs typeindicator

Witkin &Goodenough

VAK/VARK andVARK adaptive

Opinionsof students

Opinionsof teachers

Academicachievement

Elementaryeducation

Secondaryeducation

Highereducation

Undeclared

LearnFit (Bachariet al., 2011)

U U U

Lecomps (Sterbini &Temperini, 2009)

U U

(Liegle & Janicki, 2006) U U U

MAS-PLANG(Pena, Marzo,& de la Rosa, 2004)

U U

MOT (Stashet al., 2004)

U U

OPAL (Conlanet al., 2002)

U U

OSCAR (Lathamet al., 2010)

U U U

(Own, 2006) U U U U

PALS2 (Siadaty& Taghiyareh, 2007)

U U U

SACS (Wang, Wang,& Huang, 2008)

U U U U

TANGOW (Carro, Pulido,& Rodriguez, 1999)

U U

TSAL (Tseng et al., 2008) U U U

(U�gur, Akkoyunlu, &Kurbano�glu, 2011)

U U U

WELSA (Popescu, 2010) U U U U

WHURLE (Brownet al., 2006)

U U U U

3DE (Corso et al., 2001) U U U

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Ö. Özyurt et al. / Computers & Education 75 (2014) 1–18 5

environments (Brusilovsky, 2001; Brusilovsky & Peylo, 2003; Graf et al., 2009; Inan et al., 2010). The infrastructure of this study is the newtrend to create WBLEs as individual learning environments based on various factors such as individual learning differences, learning needs,and learning levels of students (Brown, 2007; Brown et al., 2005; Kainnen, 2009; Latham et al., 2010; Twigg, 2003). Thus, an innovative e-learning environment that can be used instead of traditional classroom environments may be created. Since these environments can beregarded as an alternative to traditional classroom environments, the impacts of traditional classroom environments and these new en-vironments on student learning may be investigated. As a result of their, in this study, an adaptive intelligent web-based learning envi-ronment called UZWEBMAT aimed at teaching the subjects of the probability unit covered in the 11th grade mathematics course wasdesigned, implemented, and evaluated. It is thought that this study will provide important contributions to this field in terms of the use andbecomingwidespread of innovative e-learning environments inmathematics education. And it is also expected that results of this studywillboth fill a gap in this field and will lighten the following studies.

3. Material and method

This section focuses on the material and research methodology employed in the study in detail.

3.1. Material

UZWEBMAT was designed as an individualized and innovative AIWBES based on VAK (Visual–Auditory–Kinesthetic) learning style. Thecontent of UZWEBMAT is the subjects of permutation, combination, binominal expansion, and probability, which are among the secondaryeducation 11th grade mathematics subjects. Other details such as the reason for the selection of the VAK learning style for UZWEBMAT, thelearning styles scale employed, the manner of implementation of this scale, and the ways of determining the learning styles of students canbe found in the literature (Özyurt, Özyurt, & Baki, 2013). Beside this, such details about general structural and innovative features ofUZWEBMAT and the difference between UZWEBMAT and traditional WBLEs and how it provides individual learning environment forstudents can be obtained from published study. Because of the fact that a comprehensive study on UZWEBMAT has been already published,the features of this study have not been mentioned in this study. In order to understand this study completely and make the sense ofstatistical analysis it will be useful to inspect the UZWEBMAT from literature comprehensively.

3.2. Experimental design

Semi-experimental method was used in the study. This is because; it is not possible to select EG and CG students absolutely randomly inschool environments. Classes are determined by the administrations of institutions beforehand. Thus, the preliminarily formed classes aretreated as EG and CG (Çepni, 2007). At the end of the study, qualitative and quantitative data were collected from EG students in order toanswer research questions. In addition, qualitative data were collected from teachers.

3.3. Purpose and research questions

The main purpose of this study was to investigate the effects of UZWEBMAT developed for the learning and teaching of the probabilityunit on the achievement of students in the probability unit. Another purpose of this study was to reveal the factors affecting the learningperformances of students. This study made an attempt to answer the following research questions:

1. Does UZWEBMAT have any effect on cognitive learning?a) Does UZWEBMAT have any effect on the academic achievement of students in the probability unit?b) Is there any statistically significant difference between the academic achievements of students with different learning styles who

use UZWEBMAT?c) Is there any statistically significant difference between the academic achievements of male and female students who use

UZWEBMAT?d) Is there any statistically significant difference between the academic achievements of male and female students with different

learning styles who use UZWEBMAT?2. How does UZWEBMAT affect the learning performances of students?

3.4. Sample

This study was carried out in an Anatolian High School located in Trabzon, Turkey in the 2011–2012 academic year. The research sampleconsisted of 106 eleventh grade students and 2 mathematics teachers. The sections 11-A, 11-B, 11-C, and 11-D of the above-mentioned

Table 2The distribution of the EG students by learning styles and gender.

Gender Visual Auditory Kinesthetic N

f % f % f %

Male 6 17.6 15 44.1 13 38.3 34Female 11 55.0 6 30.0 3 15.0 20N 17 21 16 54

f: Frequency.

Ö. Özyurt et al. / Computers & Education 75 (2014) 1–186

school were selected to constitute the research sample. Students from 11-B (n¼ 26) and 11-D (n¼ 28) were selected as EG students (n¼ 54),and students from 11-A (n ¼ 26) and 11-C (n ¼ 26) were selected as CG students (n ¼ 52). The numbers and percentages of EG students(n¼ 54) based on learning styles were as follows: visual (n¼ 17; 31.5%), auditory (n¼ 21, 38.9%), and kinesthetic (n¼ 16, 29.6%). 34 of the EGstudents were male, and 20 were male. Table 2 presents the distribution of the EG students by learning styles and gender.

Each one of 2mathematics teachers included in the study had one EG section and one CG section (i.e. the first teacher taught 11-A and 11-B, and the second teacher taught 11-C and 11-D). In this way, teachers had an opportunity to make a better comparison of the learningperformances of the EG students and the CG students.

3.5. Procedure

Each one of the two sections included in the EG was taught via UZWEBMAT in the computer laboratory for 6 weeks. The study lasted for24 h (4 h a week). Each one of the EG students worked individually on a computer, thereby receiving an individual education. The CGstudents continued to be taught by a teacher in the classroom environment according to the traditional method.

The EG students received education via UZWEBMAT under the supervision of researcher and course teachers. Any student who logged inUZWEBMAT progressed in that environment based on his/her performance. All operations of the student were recorded in the database. Thestudent who logged out the system at the end of the course hour could continue fromwhere s/he had left when s/he logged in the system inthe next course hour. This procedure continued for 24 course hours in this way. In that process, teacher and researcher did not lecture on therelated subject and did not directly intervene in.

3.6. Data collection tools

Pre-Probability Unit Achievement Test (pre-PUAT), Post-Probability Unit Achievement Test (post-PUAT), Scale for Evaluation of theUZWEBMAT by Students (SEUS), Student Interview Form (SIF), and Teacher Interview Form (TIF) were used for data collection in the presentstudy. Data about the academic achievement of students were collected through pre-PUAT and post-PUAT. Qualitative and quantitative datawere collected from students via SEUS and SIF respectively. Similarly, qualitative data were collected from teachers via TIF. While data aboutthe first research problemwere collected via pre-PUAT and post-PUAT, data about the second research problemwere collected via SEUS, SIF,and TIF.

At the beginning of the study, pre-PUATwas administered to the EG students and the CG students. At the end of the study, post-PUATwasadministered to students from both groups. In addition, 54 EG students were asked to fill in SEUS at the end of the study. 28 students wererandomly selected from the EG, and qualitative data were collected from these students via SIF. Finally, qualitative data were collected fromtwo teachers through TIF.

Pre-PUAT, post-PUATand SEUSwere developed by the researcher. The validity and reliability studies of these toolswere conducted by theresearcher (Özyurt, 2013; Özyurt et al., 2013). SIF and TIF were developed by the researcher, too (Özyurt, 2013). The Pre-PUATconsisted of 26questions, and the post-PUAT consisted of 18 questions. The related subjects are covered in the secondary education 8th grade and 11thgrade mathematics curricula in Turkey respectively. Prior to implementation, a pre-PUAT was carried out to determine whether theachievement levels of EG and CG students were equal. Therefore, the questions of that test were prepared at the 8th grade level. After theimplementation, a post-PUAT was performed in order to compare the achievement levels of EG and CG students. Thus, the questions of thattest were prepared at the 11th grade level.

3.7. Data analysis

The quantitative data collected from students via pre-PUAT, post-PUAT, and SEUS were analyzed through SPSS 16.0 program. Thequalitative data collected from students and teachers via SIF and TIF were subjected to content analysis.

The pre-PUAT and post-PUAT scores of the EG students and the CG students were compared through independent t-test. The pre-PUAT and post-PUAT scores of the EG students with different learning styles were analyzed through Kruskal–Wallis test. The pre-PUATand post-PUAT scores of male students and female students were subjected to Mann Whitney U-Test in order to compare theachievements of the EG students by gender. Finally, the pre-PUAT and post-PUAT scores of male students and female students from eachstyle (visual-male, visual-female; auditory-male, auditory-female; kinesthetic-male, kinesthetic-female) were subjected to MannWhitney U-Test.

The quantitative data collected from students via SEUS were subjected to descriptive analysis. Each item in SEUS contained five choices:“I strongly disagree”, “I disagree”, “I am neutral”, “I agree”, and “I strongly agree”. Semantically positive items in the scalewere scored from 1to 5 (i.e. 1–2–3–4–5). Similarly, semantically negative items were reversed and scored from 5 to 1 (i.e. 5–4–3–2–1). The answers given bystudents to each item were subjected to calculation whereby the average and frequency values of each item were obtained.

The qualitative data collected from students and teachers via SIF and TIF were analyzed through content analysis. The data obtainedthrough interviews were transcribed and presented to each participant for them to check whether what they told was understood correctly.By this means, respondent validation was ensured. The data obtained through interviews were coded by three different experts simulta-neously in order to ensure coding validity. The relations among the outputs of experts were examined, and final codes were formed inaccordance with the consensus of those three experts.

Table 3T-test results regarding the pre-PUAT scores of the EG students and the CG students.

Group N X sd df t p

Control 52 63.54 12.98 104 .32 .745Experimental 54 64.35 12.73

Table 4T-test results regarding the post-PUAT scores of the EG students and the CG students.

Group N X sd df t p

Control 52 57.71 15.22 104 3.01 .003Experimental 54 66.15 13.53

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4. Findings

This section presents the findings obtained through the analysis of the data collected in the present study with regard to researchquestions.

4.1. Findings concerning the effects of UZWEBMAT on learning the probability unit

This section presents the findings concerning the effects of UZWEBMAT on the cognitive learning of students in detail.

4.1.1. The comparison of the pre-PUAT and post-PUAT scores of the experimental group and the control groupThe pre-PUAT and post-PUAT scores of the EG students and the CG students were compared. Since the pre-PUAT scores obtained by the

EG students and the CG students displayed a normal distribution, independent t-test was used for comparing those data. Table 3 shows thepre-PUAT t-test results of two groups.

As is seen in Table 3, no statistically significant difference was found between the pre-test scores of groups through t-test [t (104) ¼ .32,p > .05]. Since the post-PUAT scores obtained by the EG students and the CG students displayed a normal distribution, independent t-testwas used for comparison. Table 4 shows the result of t-test comparing the post-PUAT achievement scores of two groups.

As is seen in Table 4, a statistically significant difference in favor of the EG was found between the post-test scores of groups through t-test [t(104) ¼ 3.01, p < .05].

4.1.2. The comparison of the pre-PUAT and post-PUAT scores of students with different learning styles who received education via UZWEBMATThe pre-PUAT and post-PUAT scores of the EG students with different learning styles were compared.Firstly, the pre-PUAT achievement scores of students with three different learning styles (visual–auditory–kinesthetic) were compared.

All three groups consisted of less than 30 students. Thus, Kruskal Wallis – a non-parametric test – was used. Table 5 shows the result ofKruskal Wallis test that compared the pre-PUAT scores of three different groups.

As is seen in Table 5, no statistically significant difference was found between the pre-PUAT scores of students by their learning styles[c2(2) ¼ .088, p > .05]. Table 6 shows the result of Kruskal Wallis test that compared the post-PUAT scores of three different groups.

As is seen in Table 6, no statistically significant difference was found between the post-PUAT scores of students by their learning styles[c2(2) ¼ 2.55, p > .05].

4.1.3. The comparison of the pre-PUAT and post-PUAT scores of male and female students learning via UZWEBMATThe pre-PUAT and post-PUAT scores of male and female EG students were compared through Mann Whitney U-Test. Table 7 shows the

result of Mann Whitney U-Test test that compared pre-PUAT achievement scores.As is seen in Table 7, no statistically significant difference was found between the pre-test achievement scores of students by their

learning styles throughMannWhitney U-Test [U¼ 307.500, p> .05]. Table 8 shows the result of MannWhitney U-Test test that was used forinvestigating whether there was any statistically significant difference between post-PUAT achievement scores.

As is seen in Table 8, a statistically significant difference in favor of male students was found between the post-PUAT scores of groupsthrough Mann Whitney U-Test [U ¼ 199.00, p < .05].

4.1.4. The comparison of the pre-PUAT and post-PUAT scores of male and female students with different learning styles receiving education viaUZWEBMAT

Since each group made up by male and females’ students from each style consisted of less than 30 students, Mann Whitney U-Test – anon-parametric test – was used for comparing pre-PUAT and post-PUAT scores.

Firstly, the pre-PUAT and post-PUAT scores of male and female students with a visual learning style were compared. Table 9 shows theresult of Mann Whitney U-Test comparing the pre-PUAT scores of male and female students with a visual learning style.

As is seen in Table 9, no statistically significant difference was found between the pre-test achievement scores of male and femalestudents with a visual learning style through Mann Whitney U-Test [U ¼ 31.00, p > .05]. Table 10 shows the result of Mann Whitney U-Testcomparing the post-PUAT achievement scores of male and female students with a visual learning style.

As is seen in Table 10, no statistically significant difference was found between the post-PUAT achievement scores of male and femalestudents with a visual learning style through Mann Whitney U-Test [U ¼ 25.50, p > .05].

Table 5The result of Kruskal–Wallis test comparing the pre-PUAT scores of the EG students with different learning styles.

Learning style N Mean rank df c2 p

Visual 17 26.76 2 .088 .957Auditory 21 27.43Kinesthetic 16 28.38

Table 6The result of Kruskal–Wallis test comparing the post-PUAT scores of the EG students with different learning styles.

Learning style N Mean rank df c2 p

Visual 17 25.35 2 2.55 .279Auditory 21 25.29Kinesthetic 16 32.69

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Secondly, the pre-PUAT and post-PUAT scores of male and female students with an auditory learning style were compared. Table 11shows the result of Mann Whitney U-Test comparing the pre-PUAT scores of male and female students with an auditory learning style.

As is seen in Table 11, no statistically significant difference was found between the pre-PUAT achievement scores of male and femalestudents with an auditory learning style through Mann Whitney U-Test [U ¼ 41.50, p > .05]. Table 12 shows the result of Mann Whitney U-Test comparing the post-PUAT scores of male and female students with an auditory learning style.

As is seen in Table 12, no statistically significant difference was found between the post-PUAT achievement scores of groups throughMann Whitney U-Test [U ¼ 21.50, p > .05].

Lastly, the pre-PUAT and post-PUAT scores of male and female students with a kinesthetic learning style were compared. Table 13 showsthe result of Mann Whitney U-Test comparing the pre-PUAT scores of male and female students with a kinesthetic learning style.

As is seen in Table 13, no statistically significant difference was found between the pre-PUAT scores of groups through MannWhitney U-Test [U ¼ 13.50, p > .05]. Table 14 shows the result of Mann Whitney U-Test comparing the post-PUAT achievement scores of male andfemale students with a kinesthetic learning style.

As is seen in Table 14, no statistically significant difference was found between the post-PUAT scores of groups throughMannWhitney U-Test [U ¼ 6.50, p > .05].

4.2. Findings concerning the effects of UZWEBMAT on learning performance from the points of view of students

SEUS and SIF were used for collecting data from the students who used UZWEBMAT in regard to their opinions about the role of thatsystem in learning relevant subjects. This section presents the quantitative and qualitative data collected from students via SEUS and SIF.

4.2.1. The findings obtained through SEUSA Likert-type scale was used for receiving the opinions of students using UZWEBMAT about their learning as well as their self-

evaluations. Each item of 13-item SEUS contained five choices: “I strongly disagree”, “I disagree”, “I am neutral”, “I agree”, and “Istrongly agree”. The items of that scale were scored from 1 to 5 (i.e. 1–2–3–4–5). The average and the frequency values of each item werefound based on the answers given by students. Table 15 presents the findings obtained from the EG students (n ¼ 54).

The average of the twelfth item of the scale, “Learning with UZWEBMAT was boring” was found to be 1.91. Since this item wassemantically negative, the scores related to the item were reversed. Then, the average value of the item was found to be 4.09. The seconditem was found to be the item with the highest average value (4.2). That item was followed by the fourth, eight, and tenth items (4.1)respectively.

General average related to SEUS was found to be 3.88. According to Yenilmez (2008), score ranges can be categorized as follows in orderto improve the statistical clarity of scales: ‘I strongly disagree’ (1–1.79), ‘I disagree’ (1.80–2.59), ‘I am neutral’ (2.60–3.39), ‘I agree’ (3.40–4.19), and ‘I strongly agree’ (4.20–5). That categorization and the average score obtained in SEUS showed that students had the opinion, “Iagree” in regard to UZWEBMAT in general. The data obtained through SEUS were categorized in terms of male and female students, too.General average related to SEUS was found to be 3.88. While the average of female students (3.69) was found to be below the generalaverage, the average of male students (4.00) was found to be above the general average.

4.2.2. The findings obtained through interviewsAn interview was conducted with randomly selected 28 EG students in order to examine in detail the opinions and attitudes of the EG

students concerning UZWEBMAT. Those students were coded as follows: Std1, Std2,., Std28. Interview data were organized in such a waythat they would clearly reveal the factors influential on the learning performances of students. Table 16 gives the themes and sub-themesrevealing the role of UZWEBMAT.

Details concerning the themes and sub-themes given in Table 16 are as follows:Sub-themes concerning the theme of “Learning style-based learning” were found to be “entertainment” and “facilitating under-

standing”. Student views about each sub-theme are provided below.

Student views about the sub-theme of “entertainment”

Std1 : .I liked receiving education in accordance with my learning style.

Std19 : .It was more enjoyable than classroom environment.

Student views about the sub-theme of “facilitating understanding”

Table 7The result of Mann Whitney U-test comparing the pre-PUAT scores of male and female EG students.

Group N Mean rank Sum of ranks U p

Male 34 28.46 967.50 307.500 .55Female 20 25.88 517.60

Table 8The result of Mann Whitney U-test comparing the post-PUAT scores of male and female EG students.

Group N Mean rank Sum of ranks U p

Male 34 31.65 1076.00 199.00 .01Female 20 20.45 409.00

Ö. Özyurt et al. / Computers & Education 75 (2014) 1–18 9

Std3 : Since content was suitable for me, I was better at solving questions and I was able to understand the subjects better.

Std20 : Visuality yielded better results for me, I understood better.

Only one sub-theme was found concerning the theme of “Directing to a different content”. It was “bringing a new perspective”. Studentviews about that sub-theme are provided below.

Student views about the sub-theme of “bringing a new perspective”

Std9 : .Yes, it had a very positive effect. I saw different solutions thanks to the presentation of activities in different ways. After I solved aquestion, I was able to solve other questions depending on the solution of that question. When I missed something auditory, it directed me tovisual content. Diversity came about because I learnt visually, too.

Std14 :.When I failed in an activity in visual content, it directed me to auditory content where I saw different solutions of the questions in thesame activity. After I completed that activity, I was brought back to visual content. Thus, I had a chance to look at the case from a differentperspective.

Sub-themes concerning the theme of “Learning through activities” were found to “comprehend the logic”, “detailing”, “discovery”,“permanence, “repeatability”, and “link with the daily life”. Student views about each sub-theme are provided below.

Student views about the sub-theme of “comprehending the logic”

Std3 : .After I read questions, I started to think over questions. This is because; the system gave us the logic firstly, and provided informationboxes later. As a result, I started to reason, find the relations among numbers, and understand the logic of question. Later on, I did not needformulas anymore.

Std9 : ...Firstly, we carried out the activities. Then, UZWEBMAT gave information boxes. I saw that I could understand the information providedby information boxes thanks to what we had done during the activities. If information had been given firstly, I would have proceeded by roteand I would have used the information in exactly the same way. However, in that case, I learnt by myself. I had already inferred the meaningsbefore they were provided by the information boxes.

Student views about the sub-theme of “detailing”

Std5 : ...We may not have dealt with such details in the classroom environment. We entered into details during the activities, which yieldedbetter results.

Student views about the sub-theme of “discovery”

Std7 : ...For example, if you incorrectly answer a question twice, the system gives you tips about how the question can be solved besides the logicof that question. This enables you to discover the relations.

Std12 : .It does not give us information and formulas directly. It requests us to reach them by ourselves through the examples it gives.Eventually, it shows us the related information. Thanks to that structure, I was able to understand the subject and obtained formulas by myself.In this way, I discovered and understood better.

Student views about the sub-theme of “permanence”

Std1 : ...What I learnt via that system remained in mymind more, because wemade more effort individually and tips were givenwhenwe failedin activities. We solved questions thanks to these tips. In this way, what I learnt remained in my mind more, and I did not forget them. I couldhave forgotten more easily if the lecture had been in the classroom.

Std4 : ...This structure became well-established after a while. I think formulas will not be forgotten anymore because they were not givendirectly by rote. We learnt them by ourselves.

Student views about the sub-theme of “repeatability”

Std8 : .I was able to listen to the same activities and repeat them several times. Thus, I understood and learnt better. It was good for me.Sometimes, I leave some subjects uncompleted at school, or I may be lost in thought or be in a bad condition. Even so, I may find the sameeducational conditions and repeat subjects at home when I feel myself better.

Table 9The result of Mann Whitney U-test comparing the pre-PUAT scores of male and female students with a visual learning style.

Group N Mean rank Sum of ranks U P

Male 6 8.67 52.00 31.00 .84Female 11 9.18 101.00

Table 10The result of Mann Whitney U-Test comparing the post-PUAT scores of male and female students with a visual learning style.

Group N Mean rank Sum of ranks U p

Male 6 10.25 61.50 25.50 .44Female 11 8.32 91.50

Ö. Özyurt et al. / Computers & Education 75 (2014) 1–1810

Std17 : .I had a chance to go back and revise the points I had not understood. I think it was good.

Student views about the sub-theme of “link with the daily life”

Std13 : .Cases from daily life were used, too. It was positive. When our teacher lectured us different subjects, we asked ourselves for whatpurpose we would use them. However, that system firstly indicated us how we should use what we learnt, and then taught us the details ofsubjects.

Sub-themes concerning the theme of “Activity structure” were found to be “comprehending the logic”, “discovery”, “increasingmotivation”, and “progressing in content”. Student views about each sub-theme are provided below.

Student views about the sub-theme of “Comprehending the logic”

Std8 : .I solved problems with simpler examples or smaller numbers. By this means, I understood the solution logics of problems. Then, Iadopted the same ways in other questions with bigger numbers. Thus, I was able to reach true results and complete activities correctly.

Std17 :.Initially, activities presented difficult questions. When we failed in these questions, the system directed us to easier questions where itmade us grasp the fundamental point and taught how to solve other questions. It was really beneficial...

Student views about the sub-theme of “discovery”

Std15 : .When I failed in a question in an activity, the system directed me to a simpler question where it showed me the logic of the questionand how to solve it. In this way, I was able to understand the essential point by interpreting.

Std16 : .When I failed in a question in an activity, the system showed me how to solve the question by giving tips, which helped me andenabled me to reach the result by myself.

Student views about the sub-theme of “increasing motivation”

Std9 : .When I failed in something, it warned me by saying, “thing again”, which motivated me.

Std26 : .When you fail, it gives you examples thanks to which you get the point and conduct the activities more enthusiastically.

Student views about the sub-theme of “progressing in content”

Std6 :.For example, you can pass to the next question by accidentally skipping a question or taking a wild guess. However, questions becomemore difficult later. You have to solve the question; otherwise the system does not allow you to progress. Therefore, you have to understand thesubject. You cannot go on without learning. The system does not allow you to pass without understanding, which is really nice. When you fail ina question, it presents you a simpler question where you learn the logic of the question as well as how to solve the question. Then, you can solvedifficult questions gradually.

Std25 :.When teacher lectures, you have some deficiencies in any case. However, this system ensures complete learning. The systemmakes usovercome the activity by giving us examples. We cannot go on unless we understand the activity. In this respect, we must learn compulsorily.However, in the case of lecture by teacher, we can go on even if we do not understand. This system is better for our understanding.

One sub-theme was found concerning the theme of “Individual learning”: “individual learning environment”. Student views about thissub-theme are provided below.

Student views about the sub-theme of “individual learning environment”

Std17 :.I think subjects are not understood in the classroom environment well because it is crowded. There is a computer for each student inUZWEBMAT. So, you study individually. Everyone can repeat and study individually any time.

Std22 : .When teacher lectures a subject, s/he cannot deal with everyone one-to-one because the classroom environment is crowded. S/helectures generally. However, the system helps us because it deals with everyone individually. As I said before, we sometimes miss some pointsbecause the teacher provides a general lecture. On the other hand, this system functions like private lesson as it provides individualizedteaching, which makes it easy for us to understand.

Table 11The result of Mann Whitney U-test comparing the pre-PUAT scores of male and female students with an auditory learning style.

Group N Mean rank Sum of ranks U p

Male 15 11.23 168.50 41.50 .78Female 6 10.42 62.50

Table 12The result of Mann Whitney U-Test comparing the post-PUAT scores of male and female students with an auditory learning style.

Group N Mean rank Sum of ranks U p

Male 15 12.57 188.50 21.50 .06Female 6 7.08 42.50

Ö. Özyurt et al. / Computers & Education 75 (2014) 1–18 11

Sub-themes concerning the theme of “Individual effort” were found to be “achievement/discovery pleasure” and “entertainment”.Student views about each sub-theme are provided below.

Student views about the sub-theme of “achievement/discovery pleasure”

Std20 : .I tried to infer formulas and made an effort for it for the first time. After I saw some formulas, I noticed that I had already obtainedthem. It was a nice discovery.

Std24 :.Since rote-learning is impossible, it is very beneficial. There is no memorization. You discover by yourself, which is more pleasurable.

Student views about the sub-theme of “entertainment”

Std3 : .I had some difficulty in the beginning, but it changed and I took pleasure towards the end.

Std12 :.In general, mathematics is not a popular and entertaining course for students. This program made mathematics quite entertaining. Iwas happy for attending the class.

4.3. The findings concerning the effects of UZWEBMAT on learning performance from the points of view of teachers

Interviews were conducted with the teachers of two classes in order to obtain an evaluation of the studies of the EG students viaUZWEBMAT, the learning environment created with UZWEBMAT and UZWEBMAT from the perspective of teachers. Each one of thoseteachers, who were coded as T1 and T2, was the teacher of both EG and CG. In this way, each teacher was able to compare his/her EGstudents with his/her CG students.

This section presents in detail the findings obtained through the interviews conducted with two teachers. Findings are firstly provided inthe form of themes and sub-themes. Then, the details of each theme and sub-theme are focused on. Table 17 gives the themes and sub-themes collected from two teachers.

The details of the findings about themes and sub-themes presented in Table 17 are as follows:One sub-theme was found concerning the theme of “Learning style-based learning”: “facilitating understanding”. This theme includes

positive views. Teacher views about this sub-theme are provided below.

Teacher views about the sub-theme of “facilitating understanding”

T1 : .The suitability of the used materials for students opens a beautiful door for students in terms of mental functions.

T2 : .Subjects are understood more easily. It was something positive for students that the method was suitable for their characteristics.

Sub-themes concerning the theme of “Activity structure” were found to be “comprehending the logic/discovery”, “progressing incontent”, and “delaying understanding”. All these sub-themes refer to positive views, but each one of them was stated by just one teacher.Teacher views about each sub-theme are provided below.

Teacher views about the sub-theme of “comprehending the logic/discovery”

T1 :.Students firstly try to put forward their own solutions. For example, when we are to prove something, we ask students to progress step bystep by inductive method. A similar structure was used in these activities, too. Here, students learn how to generalize. Since computer (thesystem) tells/shows them the points where they have made errors step by step, nice and positive results emerge.

Teacher views about the sub-theme of “progressing in content”

T2 :.Activities in books are inadequate, or students skip activities because the results are directly provided at the end of activities. In computer,however, they cannot proceed to information boxes without conducting the activities, which is really nice.

Teacher views about the sub-theme of “not delaying understanding”

T2 :.Assessment and evaluation takes place during teaching in this system. When we lecture a subject through presentation in the classroom,students ask about the points they do not understand. They may ask one more time, but after a while they start to delay learning by thinkingthat they can cope with it later on. However, the system simultaneously says to students, “Look! You did not understand, and you failed. There is

Table 13The result of Mann Whitney U-test comparing the pre-PUAT scores of male and female students with a kinesthetic learning style.

Group N Mean rank Sum of ranks U p

Male 13 8.96 116.50 13.50 .416Female 3 6.50 19.50

Table 14The result of Mann Whitney U-test comparing the post-PUAT achievement scores of male and female students with a kinesthetic learning style.

Group N Mean rank Sum of ranks U p

Male 13 9.50 123.50 6.50 .07Female 3 4.17 12.50

Ö. Özyurt et al. / Computers & Education 75 (2014) 1–1812

an easier one. There is an easier one”. In this way, students see their levels more clearly. They face facts. In the other case, however, facts aredelayed all the time. They think they can cope with them later on. However, when everything piles up, they cannot cope with them. As a resultachievement decreases. In this system, problems are not delayed, but are told to one’s face directly during activities.

Sub-themes concerning the theme of “Directing to a different content”were found to be “different perspective” (stated by two teachers)and “individual learning” (stated by one teacher). Both these sub-themes refer to positive opinions. Teacher views about each sub-theme areprovided below.

Teacher views about the sub-theme of “different perspective”

T1 : .Since students had different intelligences such as visual intelligence, auditory intelligence, and tactile intelligence, it was absolutelyuseful that students who failed in their first style saw the activity from a different perspective in their second style.

T2 : .It was absolutely useful as it introduced an alternative perspective to students.

Teacher views about the sub-theme of “individual learning”

T2 : .We cannot direct students individually in the class. We cannot say that 28 or 30 students have not understood in this style, so let’sconduct activities in another style. Some students may have not learnt while some have learnt. On the other hand, computer provides in-dividuality, which makes it easy for teachers, too. This is because; students are directed by computers individually. In fact, there are 28 teachers,not a single one.

Sub-themes concerning the theme of “Learning through activities” were found to be “student-centered education”, “individual effort”,“permanence”, and “discovery”. Teacher views about each sub-theme are provided below.

Teacher views about the sub-theme of “student-centered education”

T1 : .Student-centered education is already a system that is intended to be implemented by the Ministry of National Education. Books alsoinvolve it. It is an approach provided by the system.

Teacher views about the sub-theme of “individual effort”

T1 : .For example, I say to my students that proving a theorem is equal to solving ten questions. This is because; you infer it by yourself.Anything you infer by yourself remains in your mind. I do not remember any theorem. I remember it only if I proved it by myself. This is the wayit should be. Unfortunately, since our students study based on rote learning, they mostly resort to memorizing formulas. However, there isnothing like that in this system where students discover by themselves.

T2 : .This is because; s/he does it by himself/herself, but no one says him/her to do it in that way.

Teacher views about the sub-theme of “permanence”

T1 : .It will be permanent because students have acquired and inferred it through their own efforts.

T2 :.For example, you teach 9th grade students about the slope of a line through a simple presentation. When you ask about it 10 seconds later,the student cannot answer. However, if you tell student to draw it through an activity, s/he will not forget it until the end of the year at least.

Teacher views about the sub-theme of “discovery”

T1 : .However, there are some students who can solve questions in a probability test and make comments on them along with me, whichindicates that they have made some inferences. This is because; although I did not cover this subject in that class, they can solve the same test asthe one given to other students from the class where I lectured on the subject. I think this is a very positive result.

T2 : .What is learnt becomes permanent only if student achieves learning by discovery.

5. Discussion

This section provides a discussion of the findings concerning the learning environment createdwith UZWEBMAT. The discussion is aimedat revealing the effects of UZWEBMAT on the cognitive learning of students and as well as the reasons underlying these effects.

5.1. Discussion concerning the cognitive learning of the experimental group and the control group students

The pre-PUAT and post-PUAT scores of the EG students and the CG students were statistically compared. These comparisons demon-strated that there was no significant difference between the pre-PUAT scores of the EG and the CG students, but there was a significantdifference in favor of the EG between the post-PUAT scores of two groups.

Table 15Findings related to the answers given to SEUS.

Items X 1 Strongly disagree 2 Disagree 3 Neutral 4 Agree 5 Strongly agree

f % f % f % f % f %

Learning through appropriate content thanks toUZWEBMAT facilitated my learning

3.96 0 .0 5 9.3 8 14.8 25 46.3 16 29.6

UZWEBMAT directed me to simpler questionwhen I had difficulty in activities and providedme with solution supports when necessary.This contributed to my learning

4.2 0 .0 1 1.9 5 9.3 30 55.6 18 33.3

In the cases where I was unable to succeed inmy primary learning style, I took the samecontent in different learning styles. Thispositively influenced my learning

3.87 0 .0 3 5.6 10 18.5 32 59.3 9 16.7

Learning the related concepts and principlesvia activities involving help of UZWEBMATenabled me to understand the subject better

4.1 0 .0 1 1.9 7 13.0 30 55.6 16 29.6

I think I will not forget the information Iacquired using UZWEBMAT

3.39 4 7.4 6 11.1 19 35.2 15 27.8 10 18.5

I realized that I could learn some conceptsindependently of teacher thanks toUZWEBMAT

4.0 1 1.9 5 9.3 5 9.3 24 44.4 19 35.2

While studying with UZWEBMAT, I felt thatI had to undertake responsibility in orderto learn

3.85 1 1.9 5 9.3 5 9.3 33 61.1 10 18.5

Activities, tips and solution supports inUZWEBMAT helped me to discovermathematical relations

4.1 0 .0 1 1.9 6 11.1 31 57.4 16 29.6

UZWEBMAT enabled me to see weak andstrong aspects of myself

4.09 0 .0 2 3.7 10 18.5 23 42.6 19 35.2

UZWEBMAT was a good guide for the processof learning these subjects

4.1 0 .0 2 3.7 8 14.8 28 51.9 16 29.6

UZWEBMAT contributed to me in terms ofdeveloping more positive attitudes regardingmathematics

3.43 4 7.4 8 14.8 11 20.4 23 42.6 8 14.8

Learning with UZWEBMAT was boring 1.91 23 42.6 22 40.7 7 13.0 1 1.9 3 5.6I would like to use a system similar to

UZWEBMAT to learn other subjects ofmathematics

3.24 6 11.1 9 16.7 14 25.9 16 29.6 9 16.7

f: Frequency.

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Table 16The themes and sub-themes obtained through the interviews aimed at determining the opinions of students about UZWEBMAT.

Item Themes Sub-themes Frequency of sub-themes

1 Learning style-based learning Entertainment 2Facilitating understanding 23

2 Directing to a different content Bringing a new perspective 103 Learning via activities Comprehending the logic 17

Detailing 3Discovery 8Permanence 9Repeatability 6Link with the daily life 1

4 Activity structure Comprehending the logic 27Discovery 3Increasing motivation 4Progressing in content 3

5 Individual learning Individual learning environment 66 Individual effort Achievement/discovery pleasure 7

Entertainment 4

Ö. Özyurt et al. / Computers & Education 75 (2014) 1–1814

It may be thought that two factors play roles in the case that the EG students aremore successful than CG student in this study. The first ofthese factors isWBLE and the second one is an individualized on the basis of learning styles, adaptable and intelligent learning environment.Although there are studies in literature telling about the positive effects of web based learning environments on learning achievements ofthe students (Çepni, Tas, & Köse, 2006; Crippen & Earl, 2007; Güzeller & Akın, 2012; Nguyen & Kulm, 2005) it is also possible to talk aboutmany studies putting forward that these environments has no effect on learning achievements of the student (Alacapınar, 2003; Alonso Díaz& Blázquez Entonado, 2009; Baki & Güveli, 2008; Dell, Low, &Wilker, 2010; Larson & Sung, 2009; Lee & Rha, 2009; Lim, Kim, Chen, & Ryder,2008; Maag, 2004; Summers, Waigandt, & Whittaker, 2005). As shown by these studies, there isn’t a clear assessment on the effect oftraditionalWBLE on academical achievements of students, but even it can be said that they have no effect. Besides, asmentioned in part 1.1, apassage from traditional WBLE to innovative AIWBES is seen in our days. UZWEBMAT is also in AIWBES categories as an innovative,individualized on basis of learning styles, adaptable, intelligent e-learning environment. This situation brings the UZWEBMAT’s effects onlearning achievements of students forward. For this reason, in this study it has been thought that the second factor rather that the first oneplays role in the achievements of EG students and concentrated on it.

The existence of a statistically significant difference between the post-PUAT scores of the EG and the CG students shows that the studentsreceiving education in accordance with their individual characteristics via UZWEBMAT are more successful. The literature contains manystudies showing that learning style-based AIWBESs have a positive effect on the academic achievement of students (Bachari et al., 2011;Bajraktarevic et al., 2003; Graf & Kinshuk, 2007; Hsieh et al., 2011; Mustafa & Sharif, 2011; Own, 2006; Popescu, 2010; Siadaty &Taghiyareh, 2007; Tseng et al., 2008). According to the results about AES-LS, learnFit, PALS2, and WELSA systems that can be found inthe literature, the EG students who learn in accordance with their learning styles are more successful than CG students. These results showparallelism with the results of the present study.

The reasons underlying the higher achievement of the EG students were investigated by analyzing both the quantitative and thequalitative data collected from teachers and students. Students put forward quite positive opinions in regard to UZWEBMAT and thelearning environment created with it. It is thought that learning based on one’s learning style via UZWEBMAT, the learning objectsconstituting UZWEBMAT, and the structural characteristics of these learning objects had an effect on the higher achievement of the EGstudents. As a matter of fact, according to the first item of the scale, 75.9% of the students think that the fact that UZWEBMAT presentscontents based on their learning styles facilitates understanding. The examination of the qualitative data collected from students andteachers in regard to this item demonstrates that receiving education in accordance with one’s learning style facilitates understandingandmakes learning entertaining. Thus, it is concluded that a great majority of students are satisfied with receiving contents in accordancewith their learning styles. The literature contains studies indicating that receiving education based on learning styles increases studentsatisfaction. Mustafa and Sharif (2011); Popescu (2010); Sangineto et al. (2008); and Triantafillou et al. (2003) suggested that receivingcontent in accordance with one’s learning style was found satisfactory by students. Those systems for which students stated theirsatisfaction were AES-CS, AES-LS, Diogene, and WHURLE. It is thought that student satisfaction makes a positive contribution toachievement, too.

Table 17The themes and sub-themes obtained through the interviews aimed at determining the opinions of teachers about UZWEBMAT and the learning environment created with it.

Item Themes Sub-themes Frequency of sub-themes

1 Learning style-based learning Facilitating understanding 22 Activity structure Comprehending the logic/discovery 1

Progressing in content 1Not delaying understanding 1

3 Directing to a different content Different perspective 2Individual learning 1

4 Learning through activities Student-centered education 1Individual effort 2Permanence 2Discovery 2

Ö. Özyurt et al. / Computers & Education 75 (2014) 1–18 15

Other factors considered to have an effect on the higher achievement of the EG students were the learning objects constitutingUZWEBMAT, the structural characteristics of these objects, and the teaching of relevant subjects via activities. The qualitative and thequantitative data collected from students put forward important tips on this subject. The qualitative data collected from teachers supportedit, too. As a matter of fact, the items 2, 3, 4, 8, and 10 of SEUS directly demonstrate the reasons for these factors. The averages of the answersgiven to these items were found to be 4.2, 3.87, 4.1, 4.1, and 4.1 respectively. The ratios of the students delivering positive opinions (e.g. Iagree or I strongly agree) about these items were found to be 88.9%, 76%, 85.2%, 87%, and 81.5% respectively. The quantitative data obtainedthrough SEUS were supported by the qualitative data collected from students. As a matter of fact, many factors including the structuralcharacteristics of UZWEBMAT, teaching via activities, preparing an individual learning environment, requiring individual effort, pleasurebrought by such effort, and entertainment brought by such pleasure to course came to the forefront during interviews. The themes and sub-themes obtained through teacher interviews showed parallelism with student views to a large extent. As a matter of fact, similarity instudent and teacher interviews is of great importance in terms of showing the effectiveness and the efficiency of the system. The literaturecontains studies reaching similar results. Brown, Fisher, and Brailsford (2007); Busato et al. (1999); Latham et al. (2010); Own (2006);Papanikolaou et al. (2003); Popescu (2010); Sangineto et al. (2008); and Triantafillou et al. (2003) investigated the structural characteris-tics of the AEHSs based on learning styles as well as the reasons for preferring these environments. These environments contain manypositive parameters including increasing motivation, creating a sense of satisfaction among students, and providing learning pleasure. It isthought that these kinds of positive views and evaluations have an effect on the academic achievements of students.

5.2. Discussion concerning the cognitive learning of students with different learning styles learning via UZWEBMAT

The pre-PUAT and post-PUAT scores of the EG students with different leaning styles (visual–auditory–kinesthetic) were statisticallycompared. No statistically significant difference was found between the pre-PUAT scores and post-PUAT scores of students from the above-mentioned three groups. In addition, the post-PUAT score mean ranks of students from each learning style were found to be 23.35, 25.29,and 32.69 for students with visual, auditory, and kinesthetic learning styles respectively.

The fact that no difference was found among the academic achievements of students in three different groups shows that UZWEBMATachieved its goal. As a matter of fact, students received education in accordance with their learning styles in that environment. Thosestudents who learnt in accordance with their learning styles received the content that was most suitable for them. This may be an indicatorof the fact that students in each learning style achieved learning almost at the same level, thus acquired almost the same academicachievement. It is significant that although no statistically significant difference was found among groups, students with kinestheticlearning style weremore successful than students with other learning styles. The literature contains studies demonstrating that the learningenvironments that include learning objects with a high interaction level improve the academic achievements of students (Lim et al., 2006;Sedig & Liang, 2006; Wolf, 2007). In this sense, the findings of this study show parallelismwith those of the studies found in the literature.

5.3. Discussion concerning the cognitive learning of male and female students learning via UZWEBMAT

The examination of whether there was a statistically significant relationship between the academic achievements and genders of the EGstudents showed that male students in the EG were more successful than female EG students.

The quantitative data obtained through SEUS give clues about the reasons for the higher achievement of male students in comparison tofemale students. As a matter of fact, the general average related to all items in SEUS was found to be higher among male students. While thegeneral average of SEUS was found to be 3.88, the average of female students was found to be 3.69, and the average of male students wasfound to be 4.00. This is an indicator of the fact that male students hadmore positive opinions and ideas about that system. It is possible thatthis situation had an effect on the academic achievement of male students, too. The literature contains studies in which the relationshipbetween learning styles and gender is examined. Demirbas and Demirkan (2007); and Ku and Chang (2011) found that there was norelationship between the genders and the academic achievements of students learning in accordance with their learning styles, but Own(2006) reported that male students were more motivated during study in the computer environment in comparison to female students andthis affected their achievement. The results of the present study support the findings of Own (2006).

5.4. Discussion concerning the cognitive learning of male and female students with different learning styles learning via UZWEBMAT

No statistically significant difference was found between the pre-PUAT and the post-PUAT scores of male and female students in eachlearning style by gender. However, the pre-PUAT score mean ranks of each group were found to be as follows: for visual, male: 8.67, female:9.18; for auditory, male: 11.23, female: 10.42; and for kinesthetic, male: 8.96, female: 6.50. Similarly, the post-PUAT score mean ranks of eachgroup were found to be as follows: for visual, male: 10.25, female: 8.32; for auditory, male: 12.57, female: 7.08, and for kinesthetic, male:9.50, female: 4.17. In each learning style, the post-PUAT score mean ranks were found to be higher amongmale students. As it was discussedin Section 5.3, male students were found to be more successful in terms of the relationship between the post-PUAT achievement scores ofthe EG students and their genders. In this respect, the fact that the post-PUAT achievement score mean ranks of the EG male students werefound to be higher than themean ranks of female students in all three styles supports that male students aremore successful in this learningenvironment.

6. Conclusions and future works

This study investigated the effects of UZWEBMAT on the cognitive learning of students as well as the reasons underlying those effects.Semi-experimental designwas used, and an EG and a CGwere formed.While the EG students learned via UZWEBMAT, the CG students weretaught in the traditional classroom environment. At the beginning of the study, the EG students and the CG students were subjected to pre-achievement test (pre-PUAT). They were subjected to post-achievement test (post-PUAT) at the end of the study. Quantitative and quali-tative data were collected from students while only qualitative data were collected from teachers at the end of the study. Statistical analyses

Ö. Özyurt et al. / Computers & Education 75 (2014) 1–1816

indicated that EG students were more successful than CG students. In the light of the qualitative and quantitative data obtained, the factorsinfluential on the higher achievement of the EG students in comparison to the CG student are as follows: students received individualeducation in accordance with their learning environments via UZWEBMAT; UZWEBMAT and the learning objects constituting it hadappropriate structural characteristics (providing an environment for comprehending the logic and discovery, not allowing students toprogress without understanding concepts, offering an individual learning environment, establishing a link with the daily life, increasingmotivation, providing a student-centered learning environment, etc.); students learned by entertaining and without being bored in thatenvironment; students were interested in the lesson throughout the course hours and they took responsibility for their own learning; andthe system enabled students to attend the lesson actively throughout the course hours.

According to statistical analyses, there is no significant difference among the academic achievements of EG students with three differentlearning styles (visual–auditory–kinesthetic). This demonstrates the role and function of UZWEBMAT in a sense. The students receivingeducation in accordance with their learning styles received the contents most suitable for their learning styles. This may be an indicator ofthe fact that students from each learning style achieved learning at a particular level. The examination of the academic achievements of malestudents and female students in the EG shows that male students weremore successful than female students. This result may be regarded asa reflection of the opinions and thoughts of male students in regard to UZWEBMAT. As a matter of fact, male students put forward morepositive opinions about UZWEBMAT in comparison to female students. It is thought that such positive opinions affected their achievementpositively, too. No statistically significant relationship was found between the academic achievements and the genders of the EG studentswith different learning styles. On the other hand, although there isn’t any important difference statistically, when the averages are examinedit is seen that male students were more successful than female students in all three groups (visual–auditory–kinesthetic).

In this study, the dominant learning styles of the students taking the learning styles test were determined. These students were made toreceive contents in their relevant learning styles. Some different studies where the selection of learning styles is left to students may beconducted. In this way, students may be allowed to receive the content they want and they may be subjected to the learning styles test afterthey complete learning. By this means, it may be examined from different perspectives whether there is any relationship between theindividual preferences of students and their learning styles andwhat kind of an effect this situation has on students. In the present study, thecontents corresponding to learning styles were presented to students. Different studies may match learning styles with different contents,and examine the effect of this system on students.

Acknowledgments

This research was supported by The Scientific and Technological Research Council of Turkey (TUBITAK), Social Sciences and HumanitiesResearch Group (SOBAG), under Grant no. 109K543.

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