The Impact of the 5E Learning Model Improved with Concept Maps on Motivation Lütfiye V aroğlu* 1 , Ayhan Yilmaz 2 and Şenol Şen 2 • The examination of students’ motivation towards lessons is an impor - tant aspect of educational studies. The constructivist approach signifi - cantly impacts the improvement of students’ motivation. The present study aims to examine the use of the 5E learning model with concept maps to support students’ motivation and compare the 5E approach and the classical approach to teaching chemistry in terms of motiva - tional dimensions. The main subject of this study is an assessment of students’ motivation using the 5E learning model, which promotes student-centred teaching. The study was conducted with 100 8th-grade lower secondary school students who attended a school in the Turk - ish Republic of Northern Cyprus (TRNC) during the spring semester of the 2018/19 school year. The study was conducted with two randomly selected groups: experimental (EG) and control (CG). The lessons of the EG were taught using the 5E Learning Model Improved with Con - cept Maps, while lessons of the CG were conducted using the current, conventional teaching method. The Motivated Strategies for Learning Questionnaire (MSLQ) was applied as a data collection tool in the study. Descriptive statistics and Multivariate Analysis of Variance (MANOV A) were used in data analysis. As a result, it was determined that the EG students’ motivation scores showed a significant difference from the CG students’ motivation scores. Furthermore, a significant difference was established between the EG and CG students’ intrinsic goal orientation and test anxiety post-test scores. Although the EG students’ averages for other sub-dimensions were higher than the CG students’ averages, no significant difference was found between the groups. Keywords: concept maps, motivation, lower secondary school students, 5E learning model 1 *Corresponding Author. Graduate School of Educational Sciences, Hacettepe University, Ankara, Turkey; lutfiyevaroglu@gmail.com. 2 Department of Mathematics and Science Education, Hacettepe University, Ankara, Turkey. DOI: https://doi.org/10.26529/cepsj.1504 Published on-line as Recently Accepted Paper: September 2023 c e p s Journal the impact of the 5e learning model improved with concept maps on motivation 2 Vpliv učnega modela 5 E, izboljšanega s konceptualnimi modeli, na motivacijo Lütfiye V aroğlu, Ayhan Yılmaz in Şenol Şen • Preučevanje motivacije učencev za pouk je pomemben vidik pedago- Preučevanje motivacije učencev za pouk je pomemben vidik pedago - ških študij. Konstruktivistični pristop pomembno vpliva na izboljšanje motivacije pri učencih. Namen te študije je preučiti uporabo učnega modela 5 E s konceptualnimi modeli za podporo motivacije pri učen - cih ter primerjati pristop 5 E in klasični pristop k poučevanju kemije z vidika motivacijskih razsežnosti. Glavni predmet te študije je ocena motivacije pri učencih z uporabo učnega modela 5 E, ki spodbuja po - učevanje, osredinjeno na učence. Študija je bila izvedena s 100 učenci zadnjega triletja osnovne šole (8. in 9. razreda), ki so obiskovali šolo v turški republiki Severni Ciper v spomladanskem semestru šolskega leta 2018/19. Študija je bila izvedena z dvema naključno izbranima skupina - ma: eksperimentalno (ES) in kontrolno (KS). Pouk ES je potekal po uč - nem modelu 5 E, izboljšanem s konceptualnimi modeli, pouk KS pa po zdajšnji, tj. običajni metodi poučevanja. Kot orodje za zbiranje podatkov je bil v študiji uporabljen vprašalnik motivacijskih prepričanj in učnih strategij (MSLQ). Pri analizi podatkov sta bili uporabljeni opisna stati - stika in multivariatna analiza variance (MANOVA). Na podlagi analize je bilo ugotovljeno, da se rezultati motivacije učencev ES pomembno razlikujejo od rezultatov motivacije učencev KS. Poleg tega je bila ugoto - vljena pomembna razlika med rezultatom notranje ciljne usmerjenosti in testne anksioznosti učencev ES in KS po opravljenem testu. Čeprav so bila povprečja učencev ES za druge poddimenzije višja od povprečij učencev KS, med skupinama ni bila ugotovljena pomembna razlika. Ključne besede: konceptualni modeli, motivacija, učenci zadnjega triletja osnovne šole, učni model 5 E c e p s Journal 3 Introduction Motivation is one of the main factors influencing whether students are willing to learn about a subject or solve a problem (Akbaba, 2006). Motivation affects an individual’s performance (Kian et al., 2014). Motivation is a complex process in which purposive action is initiated and continued (Schunk et al., 2008; Sharaabi-Naor et al., 2014). Akbaba (2006) states that motivation is one of the sources that determine student behaviours at school and, accordingly, affects the speed of reaching goals in educational environments. The literature suggests that various teaching methods, models, and strategies employed in chemistry lessons can enhance student motivation (Demircioğlu et al., 2019; Kutu & Sözbilir, 2011; Tosun & Taşkesenligil, 2012). Demircioğlu et al. (2019) reported that teaching based on the REACT strategy (which has five steps: relating, experiencing, applying, cooperating, and trans - ferring), which is based on a context-based learning approach, positively affects the motivation of 10 th -grade students regarding chemistry lessons. Many studies have investigated the motivation of students at various ed - ucational levels, including secondary school and university, towards chemistry courses (Austin et al., 2018; Cetin-Dindar & Geban, 2015; Gunes et al., 2020; Şen & Yılmaz, 2014; Tosun, 2013). Tosun et al. (2013) noted that the Problem-Based Learning (PBL) approach was found to increase the motivation of undergradu - ate students in chemistry lessons. Similarly, Korkut and Oren (2018) found that the use of science stories supported by concept cartoons increased 7 th -grade students’ motivation. Moreover, the motivation of secondary school students has been discussed in various studies conducted on other branches of science education, such as physics and biology (Aydin, 2016; Snetinová et al., 2018). Concept maps are graphical tools used to organise and reflect informa - tion. They consist of boxes representing concepts and lines connecting these concepts to illustrate their relationships (Novak, 1990). Studies on chemistry education have highlighted the use of concept maps in classrooms (Aguiar & Correia, 2016; Singh & Moono, 2015; Talbert et al., 2020). Kilic and Cakmak (2013) stated that concept maps were one of the most effective tools to support meaningful learning. Additionally, concept maps have been used as evaluation tools to identify misconceptions and as teaching materials in science education studies (Austin & Shore, 1995; Bulut et al., 2021; Ries et al., 2022; Sari & Bay - ram, 2018). According to the studies in the literature, the concept maps have positive effects on students’ academic achievement, motivation, logical think - ing, and problem-solving skills (Abd El-Hay et al., 2018; Bektuzun & Y el; 2019; Kara & Kefeli, 2018; Ozgun & Y alcin, 2019). Moreover, studies revealed that the the impact of the 5e learning model improved with concept maps on motivation 4 use of concept maps with various strategies, methods, and techniques increases students’ motivation throughout the course (Chen et al., 2016; Kostova & Ra - doynovska, 2010; Keraro et al., 2007). Atkin and Karplus (1962) introduced the learning cycle model with three phases (i.e., exploration, invention, and discovery). In contrast, the 5E learning model proposed by Bybee et al. (2006) comprises five steps: 1) engage - ment, 2) exploration, 3) explanation, 4) elaboration, and 5) evaluation. The 5E learning model, based on the constructivist approach, enables students to use their knowledge and skills actively and improves students’ motivation (Pirci & Torun, 2020). Furthermore, several studies in the literature stated that the 5E learning model enhanced learning motivation in science classes (Guven et al., 2022; Putra et al., 2018; Rizki et al., 2023). Studies have also demonstrated that the 5E learning model, as an application of constructivist learning theory, posi - tively affects students’ motivation, attitude, and success (Demir & Emre, 2020; Putra et al., 2018; Yalcin Altun et al., 2010). In this context, recent studies have also explored the use of the 5E learning model in conjunction with different techniques, methods, and strategies (Bagci & Y alin, 2018; Koc & Sarikaya, 2020; Utami & Subali, 2020). Additionally, the incorporation of concept maps has been shown to contribute positively to students’ achievement, attitude, logical thinking, and motivation (Akgunduz & Bal, 2013; Chawla & Singh, 2015; Chiou, 2015; Çömek et al., 2016; Kara & Kefeli, 2018). This study builds on these findings to investigate the utilisation of the 5E learning model with concept maps to support students’ motivation and com - pare the 5E approach with the classical approach to teaching chemistry in terms of motivational dimensions. Pintrich et al. (1991) developed the Motivated Strategies for Learning Questionnaire (MSLQ) to assess students’ motivation with six sub-dimension: 1) intrinsic goal orientation, 2) extrinsic goal orientation, 3) task value, 4) con - trol of learning beliefs, 5) self-efficacy for learning and performance, and 6) test anxiety. Effective self-regulative learning characteristics, such as intrinsic goal orientation and self-efficacy, positively affect success (Chyung et al., 2010). In - trinsic motivation provides satisfaction derived from the task itself, whereas ex - trinsic motivation is driven by external factors, such as rewards or punishments based on task performance (Lin et al., 2003). The task value relates to the beliefs about the importance of the task (Pintrich, 1999). The control of beliefs reflects students’ ideas regarding their level of control over their own learning (Pin - trich & Garcia, 1993). Test anxiety encompasses worry and emotional distress related to exams and negatively affects the students (Pintrich & Garcia, 1993). Therefore, when examining motivation in the context of chemistry education, c e p s Journal 5 it is important to consider components such as task value, self-efficacy, and test anxiety, as they have been studied extensively (Karpudewan et al., 2015; Lynch & Trujillo, 2011; Zusho et al., 2003). Güngör Seyhan (2020) found that high school students’ motivation in chemistry lessons predicted their attitudes towards the subject, as well as their self-efficacy and self-regulatory learning strategies. Studies consistently show a significant relationship between students’ motivation, achievement, and per - formance in chemistry courses (Eskicioglu & Alpat, 2017; Ferrell et al., 2016). Accordingly, Zusho et al. (2003) emphasised that self-efficacy and task value, as the components of motivation, were the best predictors of students’ success in chemistry courses. Concordantly, in studies on mathematics and science edu - cation, a positive and significant relationship between students’ motivation and their achievement, attitude, metacognitive awareness, and scientific creativity levels has been observed (Atay, 2014; Azizoğlu & Çetin, 2009; Çeliker et al., 2015; Yıldırım & Kansız, 2018). Moreover, the meta-analysis study conducted by Alkan and Bayri (2017) revealed a statistically significant and positive relation - ship between motivation and achievement towards science. Thus, it is crucial to investigate the impact of the 5E Learning Model Improved with Concept Maps on motivation within the context of the chemistry courses. This study aims to examine the influence of the 5E Learning Model Im - proved with Concept Maps on the motivation of secondary school students. In accordance with this purpose, we aimed to investigate the use of the 5E learning model with concept maps that support students’ motivation and to compare the 5E approach with the classical approach to teaching chemistry in terms of motivational dimensions. The findings from this study will provide important evidence regarding the effect of learning environments on students’ motivation. In line with this purpose of the study, the answer to the following question was investigated. 1. ‘Is there a significant difference between experimental (EG) and control groups (CG) students’ motivation (intrinsic goal orientation (IGO1), ex - trinsic goal orientation (EGO2), task value (TV3), control of learning beliefs (CLB4), self-efficacy for learning and performance (SELP5), test anxiety (TA6)) according to the teaching method?’ the impact of the 5e learning model improved with concept maps on motivation 6 Method This section describes the study participants, data collection tool, re - search design, the application process, the implementation of concept maps to steps of the 5E learning model and the data analysis employed. Participants The purposive sampling method was used for sample selection. In this direction, a secondary school that admitted students through an examination and provided a similar educational background was selected. The research was carried out with 100 students in the 8 th grade and aged 13 and 14 during the sec - ond semester of the 2018/19 academic year. The study was performed with two experimental groups (EG (female: 22, male: 28)) and two control groups (CG (female: 21, male: 29)), which were selected randomly. All participants volun - tarily took part in the research. The study was approved by the Ethical Committee of Hacettepe Uni - versity. Additionally, the presented study was verified by the TRNC National Education Ministry. Instrument The Motivated Strategies for Learning Questionnaire (MSLQ) was used as the data collection tool for the study. Motivated Strategies for Learning Questionnaire (MSLQ): The MSLQ is an assessment tool developed by Pintrich et al. (1991) to investigate students’ motivational orientation and use of various learning strategies. The question - naire was adapted to Turkish by different researchers (Altun & Erden, 2006; Büyüköztürk et al., 2004; Karadeniz et al., 2008; Sungur, 2004). The seven- point Likert scale comprises two basic components as motivation and learning strategies. The sub-dimensions of the scale are modular that can be used indi - vidually or together in accordance with the purpose of the study (Büyüköztürk et al., 2004). The motivation dimension of the scale consists of 31 items that evaluate students’ beliefs about the purpose and value, beliefs about their ability to succeed and concerns about the tests within the course (Pintrich et al., 1991). For the evaluation of the scale, it is stated that the score obtained by the student from each factor indicates the characteristic of the relevant factor at such a high or low level (Büyüköztürk et al., 2004; Pintrich et al., 1991). In this study, the motivation dimension utilised the IGO1, EGO2, TA3, TV4, CLB5, and SELP6 c e p s Journal 7 sub-dimensions. The scale was adapted for the chemistry course by Şen (2015). The scale adapted by Şen (2015) was used in the study. For validity and reli - ability analysis, the scale was administered to 334 secondary school students. Confirmatory Factor Analysis was performed to examine the scale’s construct validity, and Cronbach’s alpha internal consistency coefficients were calculated for each sub-dimension to determine reliability. Karadeniz et al. (2008) report - ed that the corrected total item correlation values for the motivation dimension of the scale include 6 factors, ranging between .15 and .58. Table 1 presents the Cronbach’s alpha coefficients calculated within the context of this study regard - ing the motivation dimension of the scale, along with the values calculated for the original scale (Pintrich et al., 1991), and the adapted scale (Büyüköztürk et al., 2004). Table 1 Cronbach’s Alpha Coefficients for Motivation Dimension Sub-dimension Current Scale Original Scale Adapted Scale IGO1 .61 .74 .59 EGO2 .75 .62 .63 TV3 .88 .90 .80 CLB4 .65 .68 .52 SELP5 .93 .93 .86 TA6 .66 .80 .69 O’Rourke et al. (2005) stated that Cronbach’s Alpha values below 0.70 may be sufficient and that social scientists sometimes report values below 0.60. Therefore, it was decided that Cronbach’s Alpha values were sufficient for reliability. In this study, “fit statistics were calculated for the six factors specified in the motivation dimension. As a consequence of the analysis, it was found that the fit indices ( NNFI = .95, NFI = .92, CFI = .96, RMSEA = .075), especially chi-square/df = (947/422) = 2.24” (Varoglu, 2021; pp. 44). Garver and Mentzer (1999) suggested using NNFI, CFI and RMSEA values to determine model-data fit. Considering the results of the analysis, it is revealed that the RMSEA value is less than .08, the CFI value is greater than .90, the NFI and NNFI values are also greater than .90., and the model is fitted with the data (Schermelleh-Engel et al., 2003). the impact of the 5e learning model improved with concept maps on motivation 8 Research design This present study examined the impact of the 5E Learning Model Im - proved with Concept Maps on motivation among 8 th -grade students. In this context, the study was performed with two experimental (EG) and two control groups (CG) with a non-equivalent control group design, a quantitative re - search method. The EG consisted of 50 students, with 26 students in one group and 24 in the other. Similarly, the CG comprised 50 students, with 25 students in each group. Application process This study aimed to examine the impact of the 5E Learning Model Im - proved with Concept Maps on the motivation of 8 th -grade students within the context of the periodic table, which is an essential topic in a chemistry course. In the study, we worked with two experimental and two control groups. In the teaching method applied to the experimental group, concept maps were system - atically used in the exploration (2 nd step), explanation (3 rd step) and evaluation (5 th step) steps of the 5E model; therefore, the 5E Learning Model was improved. Simultaneously, the control group received lessons with the existing teaching method. MSLQ was applied as a pre-test to both EG and CG students in the first week of the application. Then, the EG students were provided information about the concept maps to ensure they could prepare them. Considering that each student would have an idea about ‘water’, the concept map application was made and ensured that the students could easily create concept maps and establish crosslinks. In contrast, none of the constructivist activity was done with CG, which only received information about water. The lessons of the EG students were conducted with the 5E Learning Model Improved with Concept Maps, while CG students continued with the current teaching method, which did not include constructivist activities. The current teaching model for CG followed a conventional teacher-centred approach in which the teacher used a textbook with direct instruction methods. The same subjects were taught with EG. In this context, the formation of ions is based on the concepts of anion and cation and chemical bonding in relation to the subject of the periodic table presented by the teacher. The study was completed by applying the MSLQ as a post-test to both the EG and CG students. c e p s Journal 9 Implementation of concept maps to 2 nd , 3 rd , and 5 th steps of 5e learning model This section explains the activities prepared regarding the periodic table by the 5E Learning Model Improved with Concept Maps with examples. First, we state that the students were informed about the 5E Learning Model and concept maps prior to the application. Doing so ensured that the students were ready to use the concept maps by making applications related to them. Engagement Step: To engage the attention of the students to the peri - odic table, an activity of preparing identity cards for the elements was carried out. The students were prompted with the question, ‘What kind of information should be included if an identity card were to be prepared for an element?’ . This activity aimed to shift the students’ focus towards the elements in the periodic table and encourage them to think about the essential information related to each element that should be included on the identity cards. Exploration Step: In this step, students were encouraged to work to - gether while the teacher took on a passive role. The students were divided into two groups (with 13 students in each group in EG1 and 12 students in each group in EG2) to support working together. The groups were provided with fill-in-the-blank type questions related to the periodic table. These questions required the students to make comments by using the periodic table. For ex - ample, it asked the groups to indicate the elements arranged by their atomic number using the periodic table. The students were asked to write down these answers, which were the concepts involved in the periodic table. In favour of these fill-in-the-blank-type questions, the students noted down the concepts related to the periodic table, such as group, period, atomic number, and metal or non-metal. Next, the students create a concept map by establishing a rela - tionship between these concepts. Explanation Step: In this step, the teacher took an active role and used a concept map to provide explanations. Figure 1 shows a concept map prepared and used by the teacher. the impact of the 5e learning model improved with concept maps on motivation 10 Figure 1 An example of a concept map is prepared for the explanation step (Varoglu, 2021). Elaboration Step: An activity is prepared so that what the students have learned is taken one step further and applied. The students were divided into groups of three or four, and a team tournament was held. The students an - swered the questions by using the periodic table, which was on the board. In this way, students were asked to apply and interpret what they had learned on the periodic table for other elements. For example, the groups were asked to classify the element boron as a metal, non-metal, or semi-metal, write two met - als and two non-metals in the second period, and indicate whether hydrogen is a metal or a non-metal. Evaluation Step: Concept maps were used to evaluate students’ learning in this step. In this context, the students created a concept map from scratch related to the concepts they had learned. Additionally, to support this step, a puzzle and a structured grid were prepared about the concepts applied. The application began with the used of the pre-tests and was completed in about one month with the use of the post-tests, focusing on the topic of the periodic table. Throughout this period, it was thought that the teaching model applied to the experimental group, which is an application of the constructiv - ist approach, would affect the students’ motivation components towards the chemistry lesson. atoms chemical bonds covalent H 2 O cation Na + ions ionic NaCl anion Cl – chemical by sharing electrons has + charge can gain or lose electron(s) by transferring electrons has – charge example example example example c e p s Journal 11 Data analysis The quantitative data acquired from the study were analysed with sta - tistical analysis by using the IBM SPSS Statistics 20 software. The descriptive statistics (mean, standard deviation, minimum, maximum, skewness and kur - tosis) were examined. Inferential statistics were used after the necessary as - sumptions were provided. Multivariate Analysis of Variance (MANOV A) anal - ysis was used to determine the scores of students that acquired the Motivational Strategies for Learning Questionnaire (MSLQ). Results Table 2 shows the descriptive statistics of the pre-test scores for motiva - tion sub-dimensions of both the EG and CG students. The fact that the kurtosis and skewness values of the students’ pre-test scores are between +2 and -2 in - dicates that the scores comply with the normal distribution (George & Mallery, 2003). Table 2 revealed that the scores of the students in the EG and CG were close to each other. Before the analysis, the assumptions of the MANOV A anal - ysis were verified as having been met. Table 2 Descriptive Statistics for Pre-Test Scores (Mean (M), standard deviation (SD), sample size (N), skewness, kurtosis, minimum and maximum values) Sub-dimension Group Mean df N Skewness Kurtosis Min. Max. IGO1 EG 19.48 4.32 50 -.717 -.011 8 27 CG 18.86 4.15 50 -.312 .004 8 28 Total 19.17 4.22 100 -.506 -.129 8 28 EGO2 EG 18.62 5.80 50 -.939 .472 4 28 CG 20.50 4.92 50 -.377 -.312 9 28 Total 19.56 5.44 100 -.772 .506 4 28 TV3 EG 28.76 9.16 50 -.696 -.510 10 42 CG 30.88 8.18 50 -1.148 .953 7 42 Total 29.82 8.70 100 -.896 -.001 7 42 CLB4 EG 21.78 4.16 50 -.709 .204 10 28 CG 20.96 4.29 50 -.615 -.252 11 28 Total 21.37 4.22 100 -.649 -.099 10 28 SELP5 EG 35.74 12.71 50 -.595 .337 8 54 CG 38.52 10.04 50 -.741 .503 10 55 Total 37.13 11.48 100 -.717 .029 8 55 TA6 EG 18.58 7.42 50 .329 -.626 6 35 CG 19.40 5.93 50 -.086 -.838 7 30 Total 18.99 6.69 100 .147 -.657 6 35 Note: EG=experimental group, CG=control group the impact of the 5e learning model improved with concept maps on motivation 12 The findings of the MANOVA analysis performed on the scores for the sub-dimensions indicated in Table 3 reveal that there is a significant difference in the pre-test scores between the EG and CG students (( Ʌ) = .849, F (6, 93) = 2.748, p < .05) (Varoglu, 2021; p.81). According to this result, the scores to be obtained from the linear component consisting of the pre-test scores of the students indicate a difference when compared to the experimental and control groups. However, when the sub-dimensions were examined one by one, it was seen that the pre-test results were very close to each other. The Table of Tests of Between Subjects Effects shows that the sub-dimensions did not make a signifi - cant difference (Varoglu, 2021). Table 3 reflects the results of the analysis. Table 3 T ests of Between-Subjects Effects for Motivation Pre-T est Scores by Sub-Dimensions Source Dependent Variable Sum of Squares df Mean Square F sig. Partial Eta Squared Group IGO1 9.610 1 9.610 .536 .466 .005 EGO2 88.360 1 88.360 3.053 .084 .030 TV3 112.360 1 112.360 1.491 .225 .015 CLB4 16.810 1 16.810 .942 .334 .010 SELP5 193.210 1 193.210 1.472 .228 .015 TA6 16.810 1 16.810 .373 .543 .004 The results obtained as an outcome of the descriptive statistics of the post-test scores are given in Table 4. To test the properties of the data for the normal distribution, skewness and kurtosis values were inspected. The fact that the skewness and kurtosis coefficients, which provide information about the symmetry and peak of the distribution, are between +2 and -2 is a sufficient parameter for the normal distribution (George & Mallery, 2003; Perry et al., 2017). Recent studies have pointed out that larger kurtosis and skewness values can be accepted for the normal distribution (Iyer et al., 2017; Orcan, 2020). Kallner (2018) reported that the kurtosis value is an expression of the sharpness of the distribution, and the kurtosis can take up to three values as a normal distribution. c e p s Journal 13 Table 4 Descriptive Statistics for Post-Test Scores (Mean (M), standard deviation (SD), sample size (N), skewness, kurtosis, minimum and maximum values) Sub-dimension Group Mean SD N Skewness Kurtosis Min. Max. IGO1 EG 23.20 2.92 50 -.421 -.631 17 28 CG 20.96 2.99 50 -.366 .027 14 27 Total 22.08 3.15 100 -.337 -.288 14 28 EGO2 EG 19.20 4.16 50 .052 -.417 9 27 CG 21.08 3.86 50 -.350 -.740 13 28 Total 20.14 4.10 100 -.165 -.673 9 28 TV3 EG 33.70 5.44 50 -.845 .367 20 42 CG 31.70 5.92 50 -1.344 2.264 12 41 Total 32.70 5.75 100 -1.105 1.555 12 42 CLB4 EG 18.60 3.81 50 -.499 -.029 9 25 CG 19.12 3.63 50 -.401 .022 9 26 Total 18.86 3.71 100 -.453 -.037 9 26 SELP5 EG 42.10 8.95 50 -.826 .030 21 54 CG 38.76 8.93 50 -.620 .480 15 53 Total 40.43 9.05 100 .241 .094 15 54 TA6 EG 15.90 5.72 50 .450 -.697 7 28 CG 20.34 5.28 50 -.054 -.402 9 31 Total 18.12 5.91 100 .101 -.797 7 31 Note: EG=experimental group, CG=control group In the comparison of post-test scores, MANOVA analysis was per - formed based on the fact that there was no significant difference between the pre-test scores. The results of the MANOVA analysis performed on the scores for the sub-dimensions are given in Table 5. The results of the MANOV A analy - sis on the scores for the sub-dimensions reveal that there is a significant differ - ence between the post-test scores of the EG and CG students (( Ʌ) = .700, F (6, 93) = 6.629, p < .05) (Varoglu, 2021; pp. 83). Bonferroni adjustment is required to determine a more reliable signifi - cance level to reduce the probability of a Type 1 error rate (Tabachnick et al., 2007). Since the number of dependent variables in the study was 6, the value of .05 was divided by 6, and the value of .0083 was obtained; this value was accept - ed as the new significance level. Table 5 shows the Analysis of Variance Table. the impact of the 5e learning model improved with concept maps on motivation 14 Table 5 Tests of Between-Subjects Effects for Motivation Post-Test Scores by Sub-Dimensions Source Dependent Variable Sum of Squares df Mean Square F sig. Partial Eta Squared Group IGO1 125.440 1 125.440 14.362 .000 .128 EGO2 88.360 1 88.360 5.482 .021 .053 TV3 100.000 1 100.000 3.092 .082 .031 CLB4 6.760 1 6.760 .488 .486 .005 SELP5 278.890 1 278.890 3.489 .065 .034 TA6 492.840 1 492.840 16.264 .000 .142 Table 5 shows that the students’ intrinsic goal orientation (IGO1) and test anxiety (TA6) post-test scores show a significant difference ( p < .008) be- tween the EG and CG groups. As a result, when the pre-test scores of experimental and control group students were examined, it was concluded that there was no significant differ - ence between the scores. In addition, the post-test scores show that the internal goal regulation scores showed a significant difference in favour of the experi - mental group, and the test anxiety scores showed a significant difference in fa - vour of the control group. Discussion & Conclusion The question ‘Is there a significant difference between EG and CG stu - dents’ motivation (IGO1, EGO2, TV3, CLB4, SELP5, TA6) according to the teaching method?’ takes place in the scope of the research problem; the moti - vations of the students of the experimental and control groups were examined using statistical methods. MANOVA analysis was used to determine whether there was a significant difference between the motivation pre-test scores of the experimental and control group students. The results of the MANOVA analysis performed on the scores for the IGO1, EGO2, TV3, CLB4, SELP5 and TA6 sub-dimensions revealed that there was a significant difference between the post-test scores of the experimental and control group students (( Ʌ) = .700, F (6, 93) = 6.629, p < .05) (Varoglu, 2021). In the present study, the 5E Learning Model was implemented with the support of concept maps. It was concluded that the motivation of the ex - perimental group students for the chemistry lesson was higher in the IGO1 c e p s Journal 15 sub-dimension. The TA6 sub-dimension was lower than the control group students. The literature revealed that learning activities prepared with the 5E Learning Model (Aktaş, 2013; Cetin-Dindar & Geban, 2017; Cheng et al., 2015; İlter & Ünal, 2014) and concept maps (Kara & Kefeli, 2018; Keraro et al., 2007) increase the motivation of the students towards the lesson in different courses, such as social studies, science, biology, and chemistry. Moreover, it has been determined that the context-based teaching method supported by the 5E learn - ing model increased student motivation and conceptual understanding in sci - ence lessons (Derman & Badeli, 2017). Similarly, it is stated in the literature that the simulation and animation-supported 5E model increases the success and motivation of students in science lessons (Derman & Badeli, 2017; Öner & Y aman, 2020). Based on the results, although the mean scores of EGO2, TV3, CLB4 and SELP5 were higher for the experimental group students than the control group students, there was no significant difference between the two groups. In addi - tion, there were significant differences in the IGO1 and TA6 scores between the experimental and control group students. Pintrich et al. (1991) state that there is a negative relationship between test anxiety and academic performance. Ac - cording to the results, the experimental group students had higher IGO1 mean scores, and the control group had higher TA6 scores. Studies show that intrinsic goal orientation is associated with success as one of the academic outcomes (Pintrich & Schrauben, 1992; Sungur & Gungoren, 2009). Otherwise, the in - trinsic goal orientation encourages students to have a more advanced cognitive structure by focusing on learning (Pintrich & Schrauben, 1992) Considering the results obtained from this study and the findings from the studies conducted in the literature in general, it can be stated that the 5E Learning Model, which is supported by using different techniques, positively affects the success, attitude, and motivation of the students in the course. Fur - thermore, it is thought that using the constructivist learning models will posi - tively affect students’ motivation and attitudes towards lessons by helping them learn information more easily in lessons containing abstract concepts, such as those related to chemistry. Motivation is a variable that explains an individual’s behaviour but cannot be directly observed (Korkut & Oren, 2018). Motivation will also improve students’ effective learning by supporting their active par - ticipation (Korkut & Oren, 2018). The findings determined that, except for the IGO1 and TA6 components, the motivation dimensions did not show a signifi - cant difference between the experimental and control groups. It is thought that this result may be due to reasons such as the 8 th -grade students’ difficulties in understanding the chemistry lesson because it contains abstract concepts, the the impact of the 5e learning model improved with concept maps on motivation 16 insufficient duration of the application, and their prejudices against different learning methods, techniques, and strategies. In this context, applying the 5E Learning Model Improved with Concept Maps in different topics of chemistry is recommended; different variables, such as prejudices and attitudes towards the lesson, as well as students’ motivations, should be examined in future stud - ies. From this point of view, considering the results of this study, all dimensions of motivation should be developed while preparing the activities in practice. It is thought that the findings of this study are significant in terms of the classroom environment. The study concluded that the 5E learning mod - el improved with concept maps is an effective method for increasing student motivation. The concept maps improved students’ motivation towards learn - ing chemistry by helping them visualise and organise their knowledge. Addi - tionally, the inclusion of games, puzzles, and other interesting activities within the scope of this study made learning enjoyable and heightened the interest of students in the learning environment. However, it was also observed that the students with an intrinsic goal orientation were more motivated to learn chemistry. These students were motivated by the learning process rather than external rewards such as grades. In this context, teachers must provide students opportunities to explore new concepts and offer focused feedback on their pro - gress and understanding. Another finding of the study is that the 5E learning model improved with concept maps reduces students’ test anxiety. This model enables students to develop their knowledge and skills gradually while practising in a supportive environment. To address this anxiety, teachers should establish a supportive and encouraging environment and provide opportunities for students to prac - tice their skills in preparation for exams. The main limitation of the presented study is that the students could not be selected randomly: the existing classes were used. To minimise this limita - tion, the existing classes were chosen randomly. Additionally, the study was conducted within the framework of the subject of the periodic table. It is be - lieved that the long-term application of this model to other chemistry subjects will further impact students’ motivation. Research ethics All procedures performed in studies involving human participants were in accordance with the ethical standards of Hacettepe University’s ethi - cal committee, and the committee approved the data collection procedures. The study was also conducted under the following ethical standards: Ethics c e p s Journal 17 Committee’ s Decision Date: 25.01.2019, Ethics Committee Approval Issue Num - bers: 51944218-300/00000431740. Acknowledgements This study is part of the PhD thesis entitled ‘Effect of 5E Learning Model Supported Concept Maps on Students’ Understanding of Chemical Concepts’ , Hacettepe University Institute of Graduate School of Educational Sciences, An - kara, Turkey. It was presented at the UKEK 2021 Congress. References Abd El-Hay, S. A., El Mezayen, S. E., & Ahmed, R. E. (2018). 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Her main research interests are students’ con - ceptions of science, misconceptions in chemistry and science education, and conceptual change and environmental education. Şenol Şen, currently an associated professor in the Department of Mathematics and Science Education at Hacettepe University, Ankara, Turkey. He received B.Sc., M.Sc., and Ph.D. degree from the Faculty of Education at Hacettepe University in 2009, 2011 and 2015. His research interests include self- regulated learning, chemistry education, inquiry-based learning and technol - ogy integration.