The effect of Animated Pedagogical agents on motivation of students learning

International Journal of Basic Sciences & Applied Research. Vol., 3 (SP), 179-189, 2014 Available online at http://www.isicenter.org ISSN 2147-3749 2014 The effect of Animated Pedagogical agents on motivation of students learning Zeynab Esmaeili Bejdani 1*, Khadijeh Aliabadi 2, Mohammad Reza Nili 3 1 Graduate student in Educational Technology, Allameh Tabatabai University of Tehran 2 Assistant Professor in Educational Technology, Allameh Tabatabai University of Tehran 3 Assistant Professor in Educational Technology, Allameh Tabatabai University of Tehran * Corresponding Author Email: esmaeili_zeynab@yahoo.com Abstract Multimedia technologies, there are new achievements, and development of Animated Pedagogical agents in multimedia, where, in order to attract learners to learn. This study was conducted to evaluate the effectiveness of animated Pedagogical agents in multimedia-based learning drive. The study sample consisted of female students in third, fourth district of Tehran. A sample of size n=60, the Nabovat Middle School, was selected as a convenience sample. Of the seven third grades, the school, the 30-member class, was selected at random and tested, and controlled, random. One group was exposed to the media, the animated Pedagogical agents, and other groups, were exposed to multimedia and animation training without an factor. Before and after the training, the learning motivation questionnaire, the Chin and Shi (2005), was used for students. Data analysis was performed using analysis of ANCOVA. The results of this study showed that multimedia-based educational animated factor, more effective, and motivate student learning, as compared to multimedia platforms without dynamic educational and motivational component of learning, just out, self-efficacy, and learning strategies were higher. Keywords: Multimedia, Animated pedagogical agents, Learning, Learning motives Introduction With the advent of new technologies, the education system is more efficient, than ever, to meet the need of training. Rather, studies show that the use of new technologies in traditional education, leading to increased effectiveness in learning (Damanz, 2003). Today, education as an essential component of the education system, not the exception, developments, and achievements of the arrival of new technologies, because education is the most basic needs of these developments. Computer, as an example of these technologies, is used in various ways, in education. Computer assisted instruction, computer-managed instruction and computer-based training, are examples of the use of computers in teaching and learning process (Noruzi & Razavi, 2011). With the accelerated development of new computer technologies and the unique charm of computers, for all people and particular adolescents, the design and production of multimedia learning environments, which leads to increased learning, find has acceptance. On the other hand, nowadays, e-learning, is the capacity of the extraordinary, the prospects for development of the education system, in the opinion of some experts, is an important technology which could be supported, a new approach, the teaching and learning (Zarei & Movahhed, 2005). Since a set of multimedia technologies, are employed in creating a learning experience, so in the end, you should proceed to, enrich the field of multimedia. Because, multimedia, and enhance learning is that people learn, only 20 percent of what they see, and 30 percent of what they hear, and 50 percent, from what I can see and hear, but, if what you see and hear, they do coincide, their learning will increase to 80 percent. Multimedia by providing a dynamic experience, allowing them to increase the speed of learning of basic skills (Razavi, 2011), and of course, Woo, in this paper the design of multimedia learning environments using elements of training, in 2009, admitted to the affair. Communication, using words and images, which lead to the spread of learning, called Multimedia Learning (Razavi, 2004). In fact, multimedia training, including the media, that due to their multi-sensory nature, can be compatible with a variety of learning styles, easily, and provide learning easy and lasting with various forms of interaction (Sharp, 1999). The main advantage of multimedia, as compared to other forms of education is flexible, in terms of information and quick access, provide feedback, and the purpose of using multimedia is to help the learning of learners, and enhance their literacy (Razavi, 2011). In the end, the richer the media, should be the criteria and principles of design and production of multimedia, well-respected, so, enjoy making our students, the better the advantages and benefits of this achievement, and students, address the issues of learning and teaching principles, with much interest, and thereby, meaningful learning achieved, in compliance with effective learning. "Research on the use of 179

multimedia learning, have a past, more than twenty years, and two of these tools include: tutoring intelligent systems, and educational factors" (Aschroder & Adisop 2012). In other words, Animated Pedagogical agents, there is an emerging topic in the field of multimedia. The history of Pedagogical agents is, at the same time, the emergence of e-learning, the emergence of e- learning, researchers have been trying to raise the efficiency of learning, learners, and increase their motivation during learning. With a great deal of research that has been done in this area, researchers are using, and emotional characteristics of successful teachers, to have paid to the design of training, which are virtual, and on-screen character. These factors can maintain learners' attention during training, orally, and by means of speech, or might affect the use of gesture and glance. Nonverbal learning and educational factors are more attractive to learners, for example, of training, you can understand, user participation, using a moving screen, the way they look at the screen, provide feedback, and convey emotions (Atinson, 2002). Nowadays, Animated Pedagogical agents are designed to develop an intelligent training system (Aschrvdr & Adisop, 20012). Animated Pedagogical agents, a real character, which is designed to facilitate and enhance learning, and are used in educational programs, including training, education or skills. Educational animated factors, with tremendous potential to support learning, because, well, the simulation capabilities of a learning environment, the actual class (Wu, 2008). In fact, the Pedagogical agents are real characters, they appear as presenters on the screen, and are, the user, through multimedia learning environment (Klerbot & Hidik, 2011). Pedagogical agents have the ability to display many roles in multimedia learning environments, such as placement, frame, coaching, modeling, testing building. However, educational factors often are, in the role of a trainer or a coach (Aschroder & Adisop 2012. p 43). Use Pedagogical agents in multimedia learning environment could lead to the adoption of higher learning, because it simulates the human interaction, face-to-face (Gharebaghi, 2010). This study to determine the effectiveness of Animated Pedagogical agents platforms, the students' motivation to learn, investigate, question assumptions. The beneficial effects of Animated Pedagogical agents, it can be noted that the role of motivational factors in learning. The findings suggest that, despite feelings of educational animated factor can be used in the optimization of motivation, and student learning (Kim et al., 2007). Motivation is a process whereby the activity is purposeful, persistent and irritating (Biabangard, 2005). In other words, motivation is a particular need or desire that counts, specific cause of a particular behavior (Seif, 2008). "This, in theory, motivation, and student learning studies show that self-efficacy, personal goals to the tasks, the working and learning environment, and impact on motivating student learning. Use a combination of learning oriented structure, and motivational theory, we find that "self-esteem, values, knowledge, learning, learning strategies, the purpose of personal education and learning environment are important motivational factors that are motivating students to learn science it "(Toan et al., 2005)." learning motivation can be defined as the enthusiasm for the learner, the learning content of the curriculum "(Cheg & Ho, 2001). Findings of research show, an animated Pedagogical agents is regarded as social members, similar to humans, needs to be effective communication and interaction with the learners, the environment. Therefore, animated instruction factor, produces results more definitively, to increase the learning group (Woo, 2008. p 203). using a Animated learning platforms for providing training, similar to teaching the teacher in the classroom, but an animated educational factor is similar to a the real teacher, and cannot exist alone, therefore, is required in a system, learning occurs as a backup, to launch the educational system (Woo, 2008). The general hypothesis Animated Pedagogical agents in multimedia, impact on learning motivation. Partial hypotheses Animated Pedagogical agents in multimedia, and impact on self-efficacy. Animated Pedagogical agents in multimedia impact on learning strategies. Animated Pedagogical agents in multimedia have impact on the value of learning. Animated Pedagogical agents in multimedia, and impact on, the goal of learning performance. Animated Pedagogical agents in multimedia, and impact on, the goal of learning success. An animated Pedagogical agent in multimedia has impact on stimulating learning environments. To study the purpose of research, learning motivation questionnaire, with 35 items, 5-point Likert scale, which was designed by Toan, Chin or Shi in 2005, was used. Learning Motivation Questionnaire components include: (Toan et al., 2005). Self-efficacy: it refers to, the students believe in their abilities to perform learning tasks. Active learning strategies: it refers to the active role of students in the use of strategies to construct new knowledge based on previous understanding. Valuable learning valuable than learning science, allows students to problem-solving skills, experience, research activities, self-motivator, a way of thinking, and to find the relationship between science and everyday life gained. If they can understand, this is an important value; they are motivated to learn science. The objective function: it refers to the goals of the students, learning science, competing with other students and the teacher's attention. The goal of success: it refers to the satisfaction of the students, to increase competency, and success in learning science. The Triggers of the learning environment: the classroom, the learning environment of students, such as curriculum, teacher education, and the interaction affects the motivation of students in learning science. 180

Look on, doing research on the determinants of education This Dansors and Atikson (2007), The science of learning through multimedia, indicate that the student's learning environment based on computer, learns best, content, time, file also exist along with offering texts on the display. In addition, the combination of narration with the visual presence of an animated instruction factor may also encourage students to in-depth information processing, most of the time, or narrative text appears on the screen itself Shop (Gharebaghi, 2010), the impact of Animated Pedagogical agents, in the role of educator and expert on learning, facilitating learning and motivation to learn science, noted that animated learning coaches factor more than expert educational animated factors affect the learning, facilitating learning, and motivation to learn science. Ilmaz et al (2012), The effect of education as a social model, to learn, to remember, and attitudes of learners in four experimental situations (like a human cartoon character, user interface, combined with sound user interface, along with writing) concluded that students who were exposed to factor similar to human learning on academic achievement, to remember, and attitudes gained better results than the other groups News. Experimental study, titled "The Impact of Pedagogical agents on facilitating learning, and motivate learners, with an emphasis on sound and appearance of the training" was conducted by Domag (2010). This study was sought to answer this question, factors on how things should be, in terms of sound and appearance, to enhance learning and motivation of learners. The results showed that the mere existence of the training, not increase, learning and motivation, and if the training is desirable, in terms of appearance, learning increases, as well as, learning will not take place, if both signs the sound and appearance, both are bad. The results showed significant impact of noise and the appearance of factors on learning. The purpose of this Biler and Kim (2009), the effects of different types of learning (process or behavior, attitude or practice), direct gesture symbols (no, no) and facial (no, no), the perception learners, the social reputation of the school. In this study, the effects of education, and non-verbal behavior of the factor (gestures and facial expressions), were studied. Participants in this study were 136 college students who engaged in learning, teaching in two different environments, with different factors, such as gestures and facial expressions. Results showed those facial expressions and gestures, the factor influences on perception and learning, as well as verbal interactions. An experimental study was conducted, titled "The Role of simulation training through the Pedagogical agents." This study was designed to demonstrate the empirical validity of three distinct roles of education (undergraduate, motivating, and coaching) for university students, and the research environment, based on a "collaborative training of multiple intelligent coaches." The role of educational factors, was made by the image, animation, collisions, sound, text, software Perez 4, and was run by Microsoft factor software. Through two controlled experiments, three of the credibility finding was based on the understanding of students (n = 78), and in particular its real impact on a person's motivation and learning. The results showed that the role of this factor does not perceive, not just react to the student than the intended purpose, but, as they were designed, leading to the significant changes in they are also learning and motivation. In particular, the expert factor, who leads to increased availability of information, and motivational factors, leads to increased self-efficacy, and the instructor, leads to better learning and motivation of (Kim and Biler, 2006). Experimental study, titled " Pedagogical agents Design: The real impact of gender, race, and educational role of the" carried by Beeler and Kim (2004), the first study of an experimental study, 312 students, the randomly assigned in one of eight experimental conditions, which differed in the factors of race (white, black), gender (female, male), and images (the actual cartoon), but had the same sound, and the sound was produced by a computer (not the human voice). In the second study, 229 students were randomly assigned, in one of the 12 conditions, in which the factors were diverse, with each other, to showcase the different roles of education (undergraduate, motivating, and coaching ), as well as by race (black, white), and gender (female, male). The results, also, in general, confirms the preliminary study, it was shown that, wherever the perception factors were slightly intelligent, self-efficacy, increased to significantly. Providing motivational messages, such as the use of motivating and coaching roles, lead to increased self-efficacy, and self-regulation of students. Experimental study, titled "Effects of Pedagogical agents a separate entity," conducted by Beeler and Aberz (2003), which he proceeded to examine the question of whether having a coach, factor training, which is a combination of expertise and motivational support is more effective, or the existence of two distinct factors, one associated with expertise (expert), and the other offers motivational support (motivational). The results showed that having two separate educational factors that demonstrate, these two roles, respectively, are significantly more positive impact on the learning and perception of value. This provides preliminary evidence on the effect of training distinct personalities, and this suggests that two distinct factors that are offering different functional roles, are preferred, compared to a factor, which displays both roles. Methodology Research, according to the method of data collection, or are descriptive or experimental. This is the type of applications, including quasi-experimental designs, in fact, quasi-experimental designs, applied to pilot projects that can benefit from random assignment in it. Thus, the quasi-experimental design, two or more groups of variables is compared in terms of the independent variable, and membership groups will be determined in the normal manner, and without the involvement of the researcher. In this study, given that the classes are organized in advance, researcher, no, no, optionally, the classification and organization of the class, thus placing participants in a class, are not allowed; so random. Of the seven in the class, the grade, the school Nabovat, two classes were selected and assigned to variables, randomly. Of the sample, that is, all the female students, a student's grade, fourth grade area of Tehran, 92-93 in the second semester of study, a review of school facilities, systems, and computer equipment, the public education prophecy was selected as a convenience sample, randomly. Sample size is given in Table 1. 181

Table 1. Sample Size. Group No. Percent Sample 60 28.57% Group 1 without animated Pedagogical agents exposed 30 14.28% Group 2 exposed animated Pedagogical agents 30 14.28% A self-made multimedia educational software Educational Multimedia Builder was used during two consecutive weeks (four 80- minute sessions), to groups, to provide training. The first group of multimedia, mobile factor without animated Pedagogical agents, and second, using multimedia, with a self-made animated Pedagogical agents software Poser, were trained. In both groups, the course content was the same. Before the training, the students from both groups, pre-test learning to drive, and running, in the eighth grade geography lesson. At the end of training, motivation, learning, parallel test was performed, with the pretest. Participants Subjects were students and girls, third grade, fourth district of Tehran. These students were selected from among seven third grades, the school Nabovat to crash. Pilot project According to the study, the dependent variable is the desire to learn, we, the multi-group design with pre-test traces. Tools Learning Motivation Questionnaire was used to evaluate the students' motivation to learn. Before applying the independent variable, the pre-test questionnaire, and after the independent variable, the posttest questionnaire, were run simultaneously with the test. This questionnaire was designed by Toan, Chin and Shi, in 2005, with 35 items on a scale of 5 Likert), so I agree with the 5, I agree with the score 4, no idea at point 3, disagree with a score of 2, so disagree with a score of 1) and includes the following components: selfefficacy, active learning strategies, learning valuable, objective function, goal achievement, and Triggers of the learning environment. In the present study, to determine reliability, we used the method of the experts, so that the translated questionnaire, the researcher was given to a language specialist, to modify, and then approved by teachers and professors. To determine the reliability of this questionnaire, we ran it on a longer 15-member group of students to guidance from the school (with the exception of students in the sample), then the reliability of the sample was calculated using Cronbach's alpha, which the rate was 0.73. Practices implemented The present study was conducted to determine the effectiveness of instructional animated Pedagogical agents are, in multimedia-on learning motivation of third-year students in geography lessons. This research is applied, including quasiexperimental designs. In this study, given that the classes are organized in advance, the researcher has no such authority, the classification and organization of the class, thus placing participants in a class, are not allowed to so random. Of the existing classes, the classes were selected and divided into two groups randomly. The population of the study, which comprised all the female students of class 4 district of Tehran, a review of school facilities, equipment, systems, and computer training center Nabovat, were chosen as examples of available. 2 class of 30 randomly-selected from among 7 classes, and formed the sample size, desired. Each class, randomly, were exposed to an education. To provide training, educational multimedia, based on a self-made animated training, and educational factors were used in two consecutive weeks (four 80-minute sessions) for both groups. The first group was instructed. Through multi-media learning with mobile factors and the second group were taught using multimedia learning with mobile factors. Course content was the same in both groups. Before the training, the students in both the experimental group, the motivation to learn, and running, in the eighth grade geography lesson. At the end of the test, learn to drive and running, in parallel with the test. Results Researchers, by examining six factors of learning motivation questionnaire, have been looking for, confirm or reject the hypotheses: The general hypothesis Animated Pedagogical agents in multimedia have impact on learning motivation. Partial hypotheses Animated Pedagogical agents in multimedia influences on self-efficacy. Animated Pedagogical agents in multimedia, has impact on learning strategies. An animated Pedagogical agent in multimedia has impact on valuable Learning. An animated Pedagogical agent in multimedia has an impact on the goal of Learning. An animated Pedagogical agent in multimedia has impact on, the success of the Learning Objectives. An animated Pedagogical agent in multimedia has impact on stimulating learning environment. 182

Analysis of data Pre-test and post-test data analysis, the motivation for learning was performed. Descriptive findings in Table 2, and survey data, the assumptions, the covariance test in Tables 3, 4, 5, 6. Table 2. Mean and standard deviation of the variables in the two groups. Group Test Statistical Indicators Variable Factor in Multimedia Groups with animated Pedagogical Mean 126.1 agents in multimedia SD 25.03 Mean 12.27 Groups with animated Pedagogical Average adjusted 122.64 agents in multimedia SD 15.14 Group without animated Pedagogical agents in multimedia Group without animated Pedagogical agents in multimedia Mean 115.87 SD 16.33 Mean 106.4 Average adjusted 107.02 SD 21.26 According to Table 2, the mean score of animated Pedagogical agents in multimedia, with 123.27 in the posttest is more than the control group. The standard deviation of the training, the media before and is more than the control group, but this value decreased for this group than in the control group, the test behind. The statistical methods for different groups, with the control test, the analysis of variance and covariance, the assumptions necessary for the application of this method include (homogeneity of regression coefficients in groups, homogeneity of error variance in the linear the dependent variable and pre-test, the normality of the dependent variable, the data being independent from each other). The main hypotheses: the use of factor training in multimedia can increase learning. Table 3. ANOVA, regression coefficients for the two groups. Statistical indicators of resource Sum of squares df F Sig. 567.753 1 1.66 0.203 Group 565.33 1 1.65 0.204 *Pre-test group 207.962 1 0.6 0.43 Error 19167.55 56 Total 815,232 60 According to Table 3, ANOVA regression coefficients for the 0.6 F = 1 and the degrees of freedom and a significance level of 0.43 is confirmed. Table 4. F Levine test, to check the homogeneity of variances in the two groups. Variable Index df1 df F Sig. Factor in Multimedia 1 58 0.109 0.742 According to Table 4, Levine F test to assess homogeneity of variances, with F (58, 1) =0.109 and a significance level of 0.477, is confirmed. Table 5. Kolmogrov- Smirnov test to check the normality of the dependent variable. Variable Group Kolmogorov-Smirnov test Statistics df Sig. Motivation to learn Group of Educational 0.556 30 0.917 Multimedia Control group 0.9 30 0.393 According to Table 5, the dependent variable (incentive learning), for both Group, with a significance level greater than 0.05, will be confirmed. After verification of the assumptions of analysis of covariance, we assess the test the main hypothesis of this study, using analysis of covariance. The results are shown in Table 6. Table 6. Results of analysis of covariance between the tests groups, with adjustment for pretest. Statistical Indicator Sum of squares df F Sig. effect Source 387.56 1 1.140 0.29 0.020 Group 3451.553 1 10.154 0.002 0.151 183

Self-efficacy Learning Strategies Value of learning he aim of performance Th e Intl. J. Basic. Sci. Appl. Res. Vol., 3 (SP), 179-189, 2014 Error 19375.506 57 Total 815232 60 According to Table 6, after adjusting for pre-test scores, there was a significant impact of the between subjects group (0.01 P10. 154 = 1 & 57 ) F and independent variables, the effect size of 15%, explaining the variance in the dependent variable. adjusted Mean scores of the training in multimedia, suggestions, group training multimedia educational factor, had a higher Mean motivation to learn, toward the group control, did not receive the training. Descriptive Statistics This section is devoted to the study of descriptive characteristics of the two Groups, which include the pre-test and post-test mean and standard deviation. Table 7. Mean and standard deviation of variables in the two groups. Group test Statistics variable Pedagogical agents in multimedia Group pedagogical agents in multimedia Mean 533.18 SD 4.321 Mean 21.26 Average adjusted 20.87 SD 4.17 No Factor Mean 20.73 SD 3.61 Mean 18.6 Average adjusted 18.97 SD 4.94 Mean 27.76 Groups pedagogical agents in multimedia Control group Group pedagogical agents multimedia Control group Group of pedagogical agents Multimedia Control group Group of pedagogical agents Multimedia SD 5.50 Mean 26.6 Average adjusted 26.51 SD 6.95 Mean 26.33 SD 3.88 Mean 20.76 Average adjusted 20.84 SD 20.6 Mean 23.16 SD 5.03 Mean 22.2 Average adjusted 21.79 SD 4.13 Mean 19.33 SD 4.42 Mean 18.56 Average adjusted 18.96 SD 4.48 Mean 14.63 SD 10.92 Mean 14.03 Average adjusted 14.01 SD 3.06 Mean 13.16 SD 3.09 Mean 12.86 Average adjusted 12.58 SD 3.69 Mean 19.76 SD 5.09 184

Motivating of learning environments Intl. J. Basic. Sci. Appl. Res. Vol., 3 (SP), 179-189, 2014 Control group Group of pedagogical agents Multimedia Control group Mean 18.64 Average adjusted 18.45 SD 3.54 Mean 19.53 SD 3.66 Mean 16.7 Average adjusted 16.51 SD 4.57 Mean 22.2 SD 5.17 Mean 20.7 Average adjusted 20.19 SD 4.45 Mean 16.76 SD 5.32 Mean 18.93 Average adjusted 19.43 SD 4.93 The first sub-hypothesis: Animated Pedagogical agents in multimedia, self-efficacy influences. Table 8. ANOVA, regression coefficients for the two groups. Statistical indicators of resource SS df F Sig. 122 1 6.22 0.53 Group 2.3 1 0.117 0.733 Pre-test* Group 8.839 1 8.839 0.505 Error 1097.96 56 Total 815,232 60 According to Table 8 - ANOVA for regression coefficients, with 8.839 F = 1 degree of freedom and a significance level of 0.505, is confirmed. Table 9. F Levine test, to check the homogeneity of variances in the two Groups. Indicators Variable df df2 F Sig. Pedagogical agents in Multimedia 1 58 0.229 0.634 According to Table 9, Levine F test to assess homogeneity of variances, with F(58, 1)=0.229, and a significance level of 0.634, is confirmed. After verification of the assumptions of analysis of covariance, we propose to test the main hypothesis of the study, using analysis of covariance. Table 10.analysis of covariance between the test groups, with adjustment for pretest. Statistical Indicators Source SS df F Sig. Effect 114.268 1 5.885 0.018 0.094 Group 49.767 1 2.563 0.115 0.043 Error 1106.799 57 Total 25168 60 According to Table 10, after adjusting for pre-test scores, there was no significant effect, the inter-group subjects, and P<0.05 and F(57,1) =2.563 in the sense that, adjusted scores Mean, the cause of education, the media, suggests that multimedia instruction group than in the control group did not receive an education, they have higher self-efficacy Mean. The second sub-hypothesis: Animated Pedagogical agents in multimedia, the impact on learning strategies. Table 11. ANOVA, regression coefficients for the two groups. Statistical Indicators Source SS df F Sig. 55.208 1 4.513 0.038 Group 192.735 1 1.293 0.26 Pre-test *Group 109.356 1 2.55 0.115 Error 2391.789 56 Total 36683 60 185

According to Table11, ANOVA, confirmed, to assess the regression coefficients, with F = 2.55 degree of freedom 1 and a significance level of 0.115. Table 12. Levine F test to assess the homogeneity of variances in the two groups. Indicator variable df1 df2 F Sig. Pedagogical agents in Multimedia 1 58 0.664 0.418 According to Table 12, Levine F test to assess homogeneity of variances, with F (58,1) =0.664, and a significance level of 0.418, is confirmed. After verification of the assumptions of analysis of covariance, we have to test the main hypothesis of this study, using analysis of covariance. Table 13. By analysis of covariance, the post-test, the two groups, with adjustment for pretest. Statistical indicators resource SS df F Sig. effect 17.422 1 0.397 0.531 0.007 Group 470.974 1 10.733 0.002 0.158 Error 2501.145 57 Total 36683 60 According to the above table, after adjusting for pre-test scores, there was a significant impact of the between subjects group (P 0.011 and F (57, 1) =0. 733 and independent variables, the effect size of 15%, is explained the variance of the dependent variable. adjusted Mean scores of the training in multimedia, suggests that multimedia instruction group than in the control group did not receive an education, had higher Mean learning strategies. The third sub-hypothesis: Animated Pedagogical agents in multimedia, the impact on the Value learning. Table 14. Results of analysis of covariance, the post-test, the two groups, with adjustment for pretest. Statistical indicators resource SS df F Sig. 60.611 1 3.342 0.282 Group 21.387 1 179.1 0.073 *Pre-test Group 5.478 1 0.302 0.585 Error 1015.7621 56 Total 26205 60 According to Table 14, ANOVA, regression coefficients for the F =0.302 degree of freedom 1 and a significance level of 0.585, is confirmed. Table 15. Levine F test to assess homogeneity of variances in the two groups. Indicator variable df1 df2 F Sig. Pedagogical agents in Multimedia 1 58 0.08 0.733 According to Table 15, Levine F test to assess homogeneity of variances, with 0.08 = F (58,1), and a significance level of 0.773, is confirmed. After verification of the assumptions of analysis of covariance, we propose to test the main hypothesis of this study, using analysis of covariance. Table 16. Results of analysis of covariance, the post-test, the two groups, with adjustment for pretest. Statistical indicators resource SS df F Sig. effect 56.926 1 3.177 0.08 0.053 Group 102.899 1 5.743 0.02 0.092 Error 1021.24 57 Total 26205 60 According to Table 16, after adjusting for pre-test scores, there was a significant effect of the between subjects and Group (0.01 P 5.743 = 1 and 57 (F, and the independent variables, the effect size of 15%, explain the variance in the dependent variable. adjusted Mean scores of factors in multimedia learning suggests that multimedia instruction group, had a higher Mean Value learning, compared to the control group did not receive educational factors. The fourth sub-hypothesis: Animated Pedagogical agents in multimedia, the impact on learning performance target. 186

Table 17. Results of analysis of covariance, the post-test, the two groups, with adjustment for pretest. Statistical indicators resource SS df F Sig. 2.074 1 0.174 0.678 Group 4.162 1 0.35 0.557 Pre-test *Group 0.537 1 0.045 0.833 Error 666.174 56 Total 11518 60 According to table 17: ANOVA test for regression coefficients, with F =0.045, and the degrees of freedom 1 and significant Level 0.833, confirmed. Table 18. Levine F test to assess the homogeneity of variances in the two groups. Indicator variable df1 df2 F Sig. Pedagogical agents in Multimedia 1 58 0.198 0.658 According to Table 18, Lewin F test to assess homogeneity of variances, with F(58,1) = 0.198, and a significance level of 0.658, is confirmed. After verification of the assumptions of analysis of covariance, we propose to test the main hypothesis of this study, using analysis of covariance. Table 19.analysis of covariance, the post-test, the two groups, with adjustment for pretest. Statistical indicators resource SS df F Sig. effect 2.423 1 0.207 0.651 0.004 Group 20.104 1 1.719 0.195 0.029 Error 666.711 57 Total 11518 60 According to Table 19, after adjusting for pre-test scores, there was no significant effect between the between subjects factor and group (P<0.05 and F (57,1)=0.719. That is, adjusted Mean scores of factors in multimedia learning suggest that multimedia instruction group, had a higher Mean performance than the control group did not receive the training. The fifth sub-hypothesis: Animated Pedagogical agents in multimedia, the impact on the goal of successful learning. Table 20. Results of analysis of covariance between the test groups, with adjustment for pretest. Indicator variable df1 df2 F Sig. 10.04 1 0.587 0.447 Group 0.373 1 0.022 0.883 * Pre-test Group 0.638 1 0.037 0.848 Error 958.091 56 Total 19569 60 According to Table 20, the ANOVA test for regression coefficients, with F = 0.037 and the degrees of freedom and a significance level of 1, 0.848, is confirmed. Table 21. Levine F test to check for homogeneity of variances in the two groups. Indicator variable df1 df2 F Sig. Pedagogical agents in Multimedia 1 58 1.152 0.218 According to Table 21, Lewin F test to assess homogeneity of variances, with F (58,1)=1.552 and a significance level of 0.218, is confirmed. After verification of the assumptions of analysis of covariance, we propose to test the main hypothesis of the study, using analysis of covariance. Table 22. Results of analysis of covariance between the test groups, with adjustment for pretest. Statistical indicators resource SS df F Sig. effect 13.038 1 0.775 0.382 0.013 Group 45.473 1 2.704 0.106 0.045 Error 958.829 57 Total 1018.583 60 187

According to Table 22, after adjusting for pre-test scores, there was no significant effect of the factor, between subjects and Group (0.05 <P 0.045 = 1 and 57 (F. That is, adjusted Mean scores, the cause of education, the media, suggests that multimedia instruction group than in the control group did not receive an education, had a higher Mean of success. The sixth sub-hypothesis: Animated Pedagogical agents in multimedia, the effect of motivating learning environment. Table 23. ANOVA, regression coefficients for the two groups. Statistical indicators resource SS df F Sig. 53.89 1 0.205 0.652 Group 4.087 1 2.709 0.105 * Pre-test Group 1.766 1 0.89 0.767 Error 1113.893 56 Total 24779 60 According to Table 23, ANOVA, regression coefficients for review, with 1 degree of freedom and a significance level of 0.089 F = 0.767, is confirmed. Table 24. Levine F test to assess the homogeneity of variances in the two groups. Statistical indicators resource SS df F Sig. Pedagogical agents in Multimedia 1 58 1.261 0.266 According to Table 24, Lewin F test to assess homogeneity of variances, with F (58,1)=1.261 and the significance level, 0.266 is confirmed. After verification of the assumptions of analysis of covariance, we have to test the main hypothesis of the study, using analysis of covariance. Table 25. Results of analysis of covariance between the test groups, with adjustment for pretest. Statistical indicators resource SS df F Sig. effect 54.508 1 2.785 0.101 0.047 Group 6.855 1 0.35 0.555 0.006 Error 1112.659 57 Total 24779 60 According to Table 25, after adjusting for pre-test scores, there was no significant effect of the factor Group of subjects, and (P 0.05 < and F(57, 1) = 0.35 That is, adjusted Mean scores, the cause of education, the media, suggests that multimedia instruction group than in the control group did not receive an education, not Mean of being Motivating, the better the learning environment. Conclusion Group of Multimedia Education, the pedagogical agents in multimedia, respectively, Mean motive to learn higher than the control group did not receive the training. On the one hand examination of the incentive learning, show that the mobile factor training in multimedia educational influences on self-efficacy, and learning strategies, the students, who have received the training in multimedia have, have had, the higher Mean, the Value learning the target performance goal achievement, and encouraging the learning environment. According to the obtained results, administrators and teachers can apply to improve the effectiveness of multimedia, including the deployment of animated Pedagogical agents. References Atkinson R, 2002. Optimizing Learning From Examples Using Animated Pedagogical Factors. Journal of Educational Psychology. 94:16-42. Baylor A, Ebbers S, 2003. The pedagogical factor split-persona effect: When Two Factors are better than one. Proceedings of World Conference on Educational Multimedia. 12: 459-462. Baylor AL, Kim Y, 2004. Pedagogical factor design: The impact of factor realism, gender, ethnicity, and instructional role. 7th International Conference in Intelligent Tutoring Systems. Brasil. August 30 September 3, 2004. Baylor AL, 2009. Designing nonverbal communication for pedagogical factor: When less is morecomputers in Human Behavio. 25: 450-457 Cheng EL, 2001. The influence of job and career attitudes on learning motivation and transfer. Career Development International. 1: 20-28. Clarebout G, Heidig S, 2011. Do pedagogical factors make a difference to student motivation and learning?. Journal Educational Research Review. 6: 27-54. 188

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