The Impact of Mobile Learning Applications on the Lecturer’s Role and Development of Learner’s Motivation towards Learning: Empirical Study at the Faculties Physical Education-Libya

The purpose of the present research was to validate a stated model for mobile applications as one of the modern teaching methods in the learning process with specific focus on its effectiveness on the teacher’s role and development of Libyan learners’ motivation towards learning. To achieve this research aim, the researcher used a descriptive approach as a quantitative research design that utilizes a Structural Equation Modeling (SEM) Method in order to evaluate the main hypotheses of the research. The study sample consisted of 450 participants (lecturers at the Faculties Physical Education-Libya). The conclusion of the resulting study showed the presence of a weak or low correlation linking mobile learning applications and the development of students' motivation towards learning (.16). However, the study showed that the impact of mobile learning applications on the teacher’s role was (.63). Moreover, the study found that the teacher's role has a higher level of significant influence or impact than mobile learning applications on the development of students 'motivation towards learning (86). The results also revealed that there is an indirect impact of mobile applications through the teacher’s role which was higher than its direct impact on the development of students' motivation towards learning.


Introduction
Nowadays, the world is witnessing a rapidly growing development in various fields, particularly, in the area of technology.Technology in its multiple and various forms has become an essential requirement of this modern age where the technical progress or advancement is penetrating all fields including education that has been given its adequate share of this advancement.Increasing the social interaction through mobile phone applications has become a unique demand for learning styles since applications provide learners with the opportunities to interact and share content, flexibility as well as self-learning.Therefore, curriculum and syllabus designers are required to give more attention to mobile phone applications to support student learning: both individually and collaboratively or in groups (Baird & Fisher, 2005).learning process were very satisfied since mobile applications led them to develop their desires or interests for learning, and therefore, the researcher recommended such mobile applications for those new students in the next year.
In a study by (Motivalla, 2007), the students found that mobile applications as a free and a good means for classroom interaction, a tool for discussing courses with peers as well as with teachers and a useful tool for learning.It also provided them with the opportunity to access from anywhere, and it is convenient to use, and effective in providing personal content.In general, the results of the same study revealed that the students were satisfied with mobile applications to learning.
Mobile devices promote and facilitate cooperation and interaction among students since they are a means to discover, collect, discuss and share, that is, as a means to self-reflection, which improves the learning environment.This is even emphasized by the Social Constructivism or Social Constructivist Theory, which is has a close connection to learning strategies (Lan & Tsai, 2011).The main reason behind the current investigation of mobile learning applications in the Libyan learning context reported in this study is that the researchers observed the proliferation of smart phones among university students.They just come to university, being expected to have already used such mobiles at the university and their daily lives.Thus, the study aims to analyze the impact of using such mobile technologies in Libyan universities by analyzing the causal relationships between the benefits of mobile learning applications and the development of students' motivation towards learning.In order to achieve this, several research questions were asked: 1).Do smart phone applications impact the development of students' motivation towards learning at Tripoli University?
2).What is the relationship between the mobile learning applications and the lecturer's part in the acquisition of knowledge?
3).Does the lecturer's role, within the modern technologies, have any impact on the development of students' motivation towards learning at Tripoli University? 4).Do mobile learning applications in the presence of the lecturer have any impact on the development of students' motivation towards learning at Tripoli University?

Research Objectives
The current study seeks to test the construct validity of a proposed model for learning motivations by testing the causal relationships among mobile learning applications, students' initiative towards education and the role of the lecturer in the learning process.

Research Hypotheses
Following the results of previous studies, including (Baird & Fisher, 2005), (Jackson, 2012), (Hall & Huey, 2013), this study seeks to analyze the following hypotheses:  Mobile learning applications have a direct impact on the students' motivation towards learning. There is a relationship of direct impact between mobile learning applications and the lecturer's part in the acquisition of knowledge. There exists a direct impact between the lecturer's part in the acquisition of knowledge and the development of students' motivation towards learning. There is a relationship of indirect impact between mobile learning applications and the development of students' motivation towards learning through the lecturer.

The Research Model
Because the study focuses on impact of mobile learning applications on the teacher's part in the acquisition of knowledge and the development of students' motivation towards learning, the researchers relied on a previous study (Hasan Mahdi, 2014) in determining the dimensions of the independent factor, the study of (Hall & Huey, 2013) in determining the dimensions of the mediating factor and the study of (Eldawei, 2013) in determining the dimensions of the dependent variable.As shown in Figure 1.

Study Population and Sample
The study population consists of faculty members or teaching staff at the faculties physical education-Libyan Universities, a number of (N= 1573) lecturer.However, due to the great area of these faculties, the sample size was set to 1:5 according to the number of items of the questionnaire (N= 88 items) (Ssekaran, 2003).Therefore, the sample size was (440), and based on this, 450 questionnaires were distributed to the participants, but only (N= 404) questionnaires were valid for the analysis, thus representing or accounting for (89%) of the overall number of the questionnaires distributed to the participants.

Research Instrument
In this regard, the current study was carried out based on the survey or questionnaire as a research instrument for collecting the necessary data because this instrument, being one of the most fitting research tools for achieving the objectives of the survey and attaining facts correlated with a specific real context.The survey used in this study consists of three main latent aspects, represented by several overt dimensions.The first aspect of the survey (the independent factor) is concerned with mobile learning applications, which consists of four dimensions (characteristics, importance possibilities, and readiness) for measuring this, and each dimension is represented by ( 8) items.
The second aspect (the mediating factor) is the lecturer's role in the learning process as a latent factor that consists of three dimensions (planning, execution and evaluation), each of which is represented by (8) items.
Concerning the third aspect of the survey (the dependent factor), it is related to the development of students' motivation towards learning, which comprises four dimensions namely; perseverance, communication, participation and achievement, and each variable is represented by (8) items.Thus, the overall number of the items is (88) items.The researcher relied on five-point-Likert Scale to measure the respondents' responses.As shown in Table 1.

Confirmatory Factor Analysis
The Structural Equation Modeling (AMOS) is for examining the research hypotheses.The model fit is determined by applying the four indices of the model goodness-of-fit: (1) The comparative fit index (CFI); (2) the minimum value of the discrepancy between the observed data and the hypothesized model divided by degrees of freedom (CMIN/DF) or normed chi-square (Marsh and Hocevar, 1985); (3) The chi-square statistics (McDonald & Marsh, 1990); (4) in addition (RMSEA) of between (0.08) to (0.10) indicates a mediocre fit (Browne & Cudeck, 1993) and would not employ a model a (RMSEA) greater than 0.1 (>0.1) (Mac Calluum et al., 1996).
The current study used two methods to decide the implication level of the incidental impact.The first method includes finding the (P) value by using the (P) value of the relationship of the independent variable and the mediating variable as well as the (P) value of the mediating variable and the dependent variable in the Sobel Test.
Here, the (P) value must be higher than (1.964).The second method is called the Sobel Test by using the specific The outcome of the goodness-of-fit of the end revision of the lecturer's part in the acquisition of knowledge model depicted that normed chi-square (CMIN/DF) was (3.392) which did not exceed (5), the (CFI) was (.961) which was higher than (90), and the RMSEA index was (.077) which was less than (.080). Figure (3) shows the adequacy of the final revised of the lecturer's part in the acquisition of knowledge model.e, the ation ircles these loadings, which were all statistically significant, ranged between (.84), which was the highest correlation between the factor of the lecturer's role in the learning process and its variable (planning) and (.69), which was the lowest estimate between the factor of mobile learning applications and its variable (readiness).For other remaining estimates, they are illustrated in Figure 5 that shows the measurement model.Moreover, Table 9 depicts the (T-value) for every relationship between the factors and its underlying variables.The results show that the value was higher than (1.964) for each relation, which was also statistically significant or the significance level (.05).Hence, considering the (T-value) was greater than (1.964), this is indicative of the statistically significant level, thus confirming of the relationship between the factors of the model and the underlying variables.

Examination of the Structural Model
As shown in Figure 6, the structural model differs from the measurement model as depicted previously in Figure ( 5).The independent factor (mobile learning applications), the dependent factor (development of students' motivation) and the mediating factor (the lecturer's role) were determined by the one headed-arrow ( ).However, in the measurement model, the relationships among these factors appeared to be independent relationships where the independent, dependent and mediating factors were not identified or determined.Moreover, the relationships among the three factors were represented by a two-headed arrow ( ).The results or output of the use of Amos show that there is a consistency between the model and the data collected, which is also confirmed through the structural model, and there is a consistency between the measurement model and the structural model established using the previous values and indices as shown in Table (8) and Figures (5,6) where the collected data of the current study was consistent with the model.The (Cmin) was (69.541), degrees of freedom ( 41), the significance level (.004) (which was statistically significant), in addition to the -Chi-square (1.696), which was less than (5), and (CFI) was (.98), and which was higher than (.90) all provide evidence confirming that the measurement model fits or has relations with the variables intended to measure in this study.The model is far from the null model (where there is a lack of such relations among the factors or variables).Furthermore, RMSEA index was (.042), which is less than (.080), which establishes the presence of the measurement model in the overall study population where the data was collected.Based on these values and indexes indicating the consistency among the structural model and the real Libyan environment, the research hypotheses were examined.

Examin
After certi the main h

Mobile
The resear students' m the output which was the path co application hypothesis was statistically significant because the T value was (12.069), which was greater than (1.964), and the significance level (.000) is less than (.05).Moreover, the path coefficient was (.86), which indicates that there is a positive direction, highlighting the evidence that the increased attention to the lecturer's part in the acquisition of knowledge leads to the development of students' motivation towards learning.
The results also show that the overall impact on the development of students' motivation was estimated (.97), which means that (97%) of the development of students' motivation towards learning was due to both mobile learning applications and the lecturer's acquisition of knowledge.This is also regarded great in terms of the impact of such underlying variables.As indicated by the results in relation to the importance of the impact, the impact of the teacher's acquisition of knowledge on the development of students' motivation towards learning was (.86), thus indicating it was even more important than mobile learning applications with an impact of (.16) and more influential on the increase of the students' interest towards education.

Mobile Learning Applications and the Increase of the Students' Interest towards Education through the Lecturer's Part in the Acquisition of Knowledge
The study's hypothesis confirmed the positive and indirect effect of mobile learning applications on the interest of students' motivation towards education.In other words, there is an effect of applications used for mobile learning on the development of students' motivation towards education through the mediating factor, the teacher's role.
According to the outcome in Table 11, the value of this indirect impact (.63) was the resultant rate of multiplying the path coefficient of the relationship among mobile learning applications and the teacher's part in the acquisition of knowledge (.74) and the path coefficient of the relationship between lecturer's part in the acquisition of knowledge and the development of students' motivation towards learning (.86).The overall impact was (.79), which a result of adding the direct and indirect impact between mobile learning applications and the development of students' motivation towards learning (.63+.16 = .79).

Conclusion and Discussion of Results
The current study aimed to test the impact of the direct relationship between mobile learning applications and the development of students' motivation towards learning among Libyan students at the Faculties Physical Education-Libya on one hand and the indirect relationship between mobile learning applications and the development of students' motivation towards learning through the lecturer's part in the acquisition of knowledge on the other hand.The research also aimed to explore the effect of mobile learning applications on the teacher and the impact of the lecturer's role on the development of students' motivation towards learning.Two sets of results were obtained by the study, most important of which was that the direct effect of applications used for mobile learning on the development of students' motivation towards education was (.16), which was less than (25) (Cohen, 2002) and statistically significant.This reflects the weakness of the direct effect of mobile learning applications on the development of students' motivation towards learning.Such result collaborates or is in compliance with the outcome reported in some studies previously (Baird & Fisher, 2005) (Jonas-Dwyer et al., 2012) (Hall, 2013), (Jackson, 2012).The weak or low effect of smart phone applications as a modern means in the learning process in the Libyan business environment as found by the current study can be attributed to the poor or weak communication networks upon which smart phone applications reply on in a very large way especially because they are not available effectively, and the costs of services are high, which may not be accessible or at students' reach.However, the outcome depicted that the impact of mobile learning applications on the lecturer's role was (.54), which is a high ratio, thus indicating that smart phone applications had a positive impact on the lecturer's role in the learning process.This particular result agrees with the results of some studies like (Hasan, 20014), (Hall & Huey, 2013) (Eldawei, 2013).The results of the current study also revealed that the indirect impact of smart phone applications on the increase of students' interest towards education through the presence of the lecturer was (.63).Such result reflects the importance of having a lecturer in the learning process as a central part as well as a necessary pillar of the process.The previously mentioned result implies or underlies the importance of the lecturer's role as a mediator between modern technology applications (smart phones) and the development of students' motivation towards learning.According to the outcomes obtained in the present research, the researchers recommend that it is necessary to activate the lecturer's part in the acquisition of knowledge and it is paramount to view the lecturer as a an effective linking means in increasing the level of students' motivation to learn and acquire the skills that enable them to deal with the applications and techniques of smart phones, and software design so that they can apply them to teaching.This is because such applications have a great effect on the increase of students' motivation towards learning.In addition, the researchers recommend that future studies should be carried out on exploring or identifying the obstacles and challenges that Libyan learners face in using mobile phones or mobile learning applications in the same context or environment of the current study.

Limitations and Future Studies
Although this study provides several theoretical and practical implications, there are several limitations that would provide excellent opportunities for future contributions to this important stream of research.First, since the study focus was the faculties' physical education-in Libyan Universities the generalization of the results to other countries is limited.Future studies may test the relationship between mobile Learning Applications and development of learner's motivation towards learning in other countries in the same region.Second, cross-sectional design of the research could be another limitation.Additional research using a longitudinal methodology addresses the relationship between the mobile and development of learner's motivation towards learning through another mediator variable.

Table 3 .
Construct validity and reliability of mobile phone usage in the educational process model 6.1.3CFA of the Lecturer's Part in the Acquisition of Knowledge Questionnaire

Table 7 .
Construct validity and reliability of learners' motivation towards learning model

of the Theoretical Model by Use of the Integrated Formula of Structural Equation Modeling
After determining the statistical expectations compulsory to the analysis using Structural Equation Modeling, the sample shall be verified in terms of the identical to the sample data, then the hypotheses shall be verified in the default theoretical model.Through the Figure5which shows the scheme of default theoretical model of the study using the method of Structural Equation Modeling by (AMOS).It is shown that there is an identical between the

Table 9 .
Parameter and non-parameter estimates of the theoretical measurement model S.E.Standard Error, C.R.: Critical Ratio, P: Probability, SMC: Squared Multiple Correlations.

Table 11 .
Results of the levels of effect between the factors of the model