Scholarly article on topic 'A model of using social media for collaborative learning to enhance learners’ performance on learning'

A model of using social media for collaborative learning to enhance learners’ performance on learning Academic research paper on "Computer and information sciences"

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Abstract of research paper on Computer and information sciences, author of scientific article — Waleed Mugahed Al-Rahmi, Akram M. Zeki

Abstract Social media has been always described as the channel through which knowledge is transmitted between communities and learners. This social media has been utilized by colleges in a way to encourage collaborative learning and social interaction. This study explores the use of social media in the process of collaborative learning through learning Quran and Hadith. Through this investigation, different factors enhancing collaborative learning in learning Quran and Hadith in the context of using social media are going to be examined. 340 respondents participated in this study. The structural equation modeling (SEM) was used to analyze the data obtained. Upon analysis and structural model validities, the study resulted in a model used for measuring the influences of the different variables. The study reported direct and indirect significant impacts of these variables on collaborative learning through the use of social media which might lead to a better performance by learners.

Academic research paper on topic "A model of using social media for collaborative learning to enhance learners’ performance on learning"

Journal of King Saud University - Computer and Information Sciences (2016) xxx, xxx-xxx

King Saud University

Journal of King Saud University -Computer and Information Sciences

www.ksu.edu.sa www.sciencedirect.com

Journal of

King 5aud University -

Computer and Information Sciences

A model of using social media for collaborative learning to enhance learners' performance on learning

Waleed Mugahed Al-Rahmi *, Akram M. Zeki

7 Faculty of Information and Communication Technology, International Islamic University Malaysia, P.O Box 10, 50728

8 Kuala Lumpur, Malaysia

9 Received 6 August 2016; accepted 16 September 2016

KEYWORDS

Social media usage; Collaborative learning; Higher education and learners' performance

Abstract Social media has been always described as the channel through which knowledge is transmitted between communities and learners. This social media has been utilized by colleges in a way to encourage collaborative learning and social interaction. This study explores the use of social media in the process of collaborative learning through learning Quran and Hadith. Through this investigation, different factors enhancing collaborative learning in learning Quran and Hadith in the context of using social media are going to be examined. 340 respondents participated in this study. The structural equation modeling (SEM) was used to analyze the data obtained. Upon analysis and structural model validities, the study resulted in a model used for measuring the influences of the different variables. The study reported direct and indirect significant impacts of these variables on collaborative learning through the use of social media which might lead to a better performance by learners.

© 2016 Production and hosting by Elsevier B.V. on behalf of King Saud University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

19 1. Introduction

20 In a comparison between the internet used today called as Web

21 2.0 and the one we used before called 1.0, it is reported that the

22 former is better than the latter in terms of interactivity (Kaplan

Corresponding author. E-mail addresses: Waleed.alrahmi@yahoo.com (W.M. Al-Rahmi), akramzeki@iium.edu.my (A.M. Zeki). Peer review under responsibility of King Saud University.

and Haenlein, 2010). These researchers also add that the inter- 23

net of these days provide many interactive items like Face- 24

book, Blogs and YouTube. According to Bercovici (2010), 25

students use social media in general for the purpose of interac- 26 tive engagement in the social environment. Recently, Higher 27 education is shifting attention to the use of social media in 28 teaching and learning after highlighting research community 29

in the traditional view. Anderson (2012) mentions some condi- 30

tions under which the use of social media can lead to active 31

collaborative learning in higher education. These conditions 32

are represented by the active collaborative learning and the 33

motivation of cognitive skills reflection and metacognition. 34 Some researchers like Larusson and Alterman (2009) and 35

Ertmer et al. (2011) reported the positive influence of social 36

http://dx.doi.org/10.1016/jjksuci.2016.09.002

1319-1578 © 2016 Production and hosting by Elsevier B.V. on behalf of King Saud University.

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

JKSUCI 272 26 September 2016

2 W.M. Al-Rahmi, A.M. Zeki

37 media on the process of learning leading to a better level of

38 performance. For example, Junco et al. (2011) examined the

39 use of Twitter and Blogs while Novak et al. (2012) investigated

40 the use of several types of social media. They all agreed that

41 these tools play a positive role in enhancing the performance

42 of learners and encourage active collaborative learning at the

43 level of higher education. Much of the research done in the

44 area of social media adopts the model called TAM. From

45 the perspective of other studies, social media is reported to

46 use either utilitarian or hedonic technologies based on corre-

47 sponding TAM foundations. The hedonic nature of social

48 media is confirmed through literature such as Al-Rahmi

49 et al. (2014), Sledgianowski and Kulviwat (2008), and Hu

50 et al. (2011) which reports positive influences of perceived

51 enjoyment and perceived ease of use on social media adoption

52 behavior. On the other hand, the utilitarian nature of social

53 media is still vague (Ernst et al., 2013; Al-Rahmi et al.,

54 2015). On the light of this, the current study is considered a dis-

55 tinguished effort since it explores TAM factors influencing col-

56 laborative learning to learn Quran and Hadith in the context

57 of social media use. At the level of Malaysian higher educa-

58 tion, the current study attempts to examine the impact collab-

59 orative learning has on the learners' performance through the

60 use of social media. While the second part of the current study

61 deals with the research model and verifies the different

62 hypotheses, the third part is designed to explain the methodol-

63 ogy applied as well as the process of data collection. The last

64 two part of the study involve illustrating the findings and pro-

65 viding a summary of the main points and results respectively.

66 2. Social media use in higher education

67 Recently, the interest of higher education has shifted from the

68 concentration on knowledge skills into highlighting long-

69 learning in terms of skills (Junco, 2012). One type of these

70 skills that receive special attention by employers is the collab-

71 oration skills. The topic of active collaborative learning has

72 received much attention by researchers and scholars. For

73 example, Dillenbourg et al. (1995) described this type of learn-

74 ing as the situation whereby two or more learners engage in the

75 process of learning new knowledge. Several social media tools

76 studied such as MySpace, Facebook and Twitter are tools that

77 could be used for educational purposes. The current study is

78 using the general term of social media for sweeping

79 generalization.

80 Through the use of social media in the context of learning,

81 high school students will have positive tendencies to appreciate

82 creative work, support toward peer alumni, and have mutual

83 support with the school. Through literature, several factors

84 in relation with higher education were examined. For example,

85 faculty use was examined by Al-Rahmi et al. (2014), Ajjan and

86 Hartshorne (2008), Chen and Bryer (2012), and Roblyer et al.

87 (2010) while student engagement was examined by Junco et al.

88 (2012) and Al-Rahmi and Othman (2013). Moreover, the rela-

89 tion with academic achievement was also explored by Junco

90 (2012), Junco et al. (2011) and Al-Rahmi and Othman

91 (2013). In their study, Yang et al. (2011) found that interactive

92 blogs play a significant role in the peer interaction among stu-

93 dents leading to a better academic achievement. In another

94 study, it was reported that the college students were negatively

95 influenced by the time spent on Facebook and it negatively

affected their performance. It also has a weak relation with 96

the time provided for class preparation. The transformation 97

of personal learning environments to be a new pedagogical 98

approach is one of the most potential benefits of social media 99

and this transformation aims to improve self-regulated learn- 100

ing (Dabbagh and Kitsantas, 2011). Through this transforma- 101

tion, students will be provided the advantage of having control 102

over their learning activities. Flickr, Wikis and Blogs are exam- 103

ples of web based tools that can be utilized for the purpose of 104

improving learning environments. 105

3. Research model 106

Constructivism Theory and Technology Acceptance Model 107

(TAM) are the main grounds from which the research model 108

is originated. The former theory highlights and proposes that 109

interaction among learners and their instructors is an impor- 110

tant stage in reaching engagement and active collaborative 111

learning (Vygotsky, 1978; Carlile et al., 2004). The latter model 112

mentioned above is also utilized in this research as it highlights 113

the topic of new technology adoption being strongly influenced 114

by perceived usefulness and ease of use. Much of the research 115

in this field uses TAM, which was developed by Davis (1989), 116

as a theoretical model. The reason why TAM is heavily used is 117

because it determines the future of any computer technology in 118

terms of acceptance or rejection. See Fig. 1. 119

3.1. Perceived usefulness 120

As proposed by the TAM model, the use of IT tools among 121

users heavily depends on their perceived usefulness (Davis, 122

1989; Venkatesh and Davis, 2000; Venkatesh et al., 2003). In 123

one of the studies done in this area, Jackson et al. (1997) 124

reported that there is no relation among perceived usefulness 125

and attitude and social media. Moreover, usefulness was found 126

to have a negative relation with the use of information system 127

(IS) (Venkatesh and Davis, 2000). Other researchers also 128

reported that there is no indication of the perceived 129

usefulness-actual use relationship (Szajna, 1996; Lucas and 130

Spitler, 1999; Bajaj and Nidumolu, 1998). An example for that 131

would be that mentioned by Lucas and Spitler (1999) that the 132

problem was with the researchers' variables that were not sig- 133

nificant while studying the model (Venkatesh and Davis, 134

2000). Considering the above discussion, the researcher pro- 135

poses the following hypotheses: 136

H1: There is a significant relationship between perceived 137

usefulness and social media use. 138

H2: There is a significant relationship between perceived 139

usefulness and collaborative learning. 140

3.2. Perceived enjoyment 142

The adoption of a self-service technology can be strongly influ- 143

enced by the perceived enjoyment as reported by Curran and 144

Meuter (2007). Perceived enjoyment was also found to have 145

a positive impact on the users' choices of surfing the internet 146

(Eighmey and McCord, 1998). Users' attitude and intention 147

of using social media are mainly determined by the level of 148

enjoyment they experience while using social media (Curran 149

Social media for collaborative learning to enhance learners' performance

Figure 1 The research model with hypotheses.

and Lennon, 2011). In the context of technology use and adoption, the term of perceived enjoyment (PE) has been described as the level whereby any activity is deemed to be enjoyable regardless of other things like performance consequences as a result of the system use (Davis and Warshaw, 1992). The idea that social media has provided its learners with a high level of enjoyment and a great deal of interaction with their peer is still under questioning. Considering the above discussion, the researcher proposes the following hypothesis:

H3: There is a significant relationship between perceived

enjoyment and social media use (Figs. 2 and 3).

H4: There is a significant relationship between perceived

enjoyment and collaborative learning.

3.3. Perceived ease of use

It is suggested by the TAM that certain components like perceived usefulness, behavioral attitude, intention and actual use are highly influenced by perceived ease (Davis, 1989; Mathieson, 1991; Moore and Benbasat, 1991). Looking at the relation between perceived ease of use and perceived usefulness, Davis (1989) has reported that former might mediate the latter and this view is the opposite to the view by Venkatesh and Davis (2000) who argue that the former is a parallel and direct determinant of use. While talking of UTAUT, effort expectancy is used to capture the concepts of perceived use (TAM/TAM2), complexity and ease of use. It refers to the level of ease related to the system use (Venkatesh and Davis, 2000).This relationship between perceived ease of use-perceived usefulness was rejected as reported in some studies by Chau and Hu (2002), Bajaj and Nidumolu (1998), and Hu et al. (1999). Opposing TAM view and the finding of Venkatesh and Davis (2000) and Chau and Hu (2002) reported that there was no relation of influence among perceived ease, perceived usefulness or attitude (Venkatesh and Davis, 2000). Considering the above discussion, the researcher proposes the following hypothesis:

H5: There is a significant relationship between perceived 186

ease of use and social media use. 187

H6: There is a significant relationship between perceived 188

ease of use and collaborative learning. 189

200 201 202

210 211

H7: There is a significant relationship between social media 212 use and collaborative learning. 213

H8: There is a significant relationship between social media 214 use and students' satisfaction. 215

The participation in learning participation is said to be 218 increased through the use of social media. Thus, as the interest 219

3.4. Social media use

One of the main forces influencing the development of technology utilization models is the Social media use for active collaborative learning and engagement (Venkatesh et al., 2003; Davis, 1989). Moreover, both terms of perceived ease of use and perceived usefulness are known as the most crucial post-adoption perceptions. These perception have an exceptional role in increasing the level of satisfaction and future social media use (Venkatesh and Bala, 2008; Pelling and White, 2009). In support of this, Moon and Kim (2001) observed that those who positively interact with the web system and possess higher behavior to use it are the individuals who feel comfortable with ease while using this system. Social media is seen as a channel for transmitting information and knowledge between communities and learners. An example of that is Facebook application that can be used in several ways for the purpose of communication during interaction among students (Mack and Head, 2007). In the study by Brady et al. (2010), it was reported that the use of social media among students has increased between the years of 2007 and 2007. A decrease in the gap between older and younger students in terms of using social media was also detected. Considering the above discussion, the researcher proposes the following hypotheses:

3.5. Collaborative learning

W.M. Al-Rahmi, A.M. Zeki

fe22) fe23) fe24) fe2£

Figure 2 Results of the proposed model (path).

220 on active collaborative learning increased, the attention of

221 scholars and researchers started to move toward social media

222 (Ractham and Firpo, 2011). Through the online social envi-

223 ronment, students become more able to communicate with

224 their peers solving problems or organize social events in a col-

225 laborative way (Anderson et al., 2010). For the social media to

226 achieve collaborative learning in higher education there are

227 vital condition that should be provided. These conditions are

228 represented by the creation of active collaborative learning

and the motivation of cognitive skills reflection and metacog- 229

nition (Anderson, 2012). Some researchers like Larusson and 230

Alterman (2009) and Ertmer et al. (2011) reported that the 231

use of social media by students in doing their assignments 232

was of a positive impact on the level of learning. In a study 233

done on the active collaborative learning exercises in a wiki, 234

Zhu (2012) and Lund (2008) maintained that it has a positive 235

impact on students who became more able to do activities like 236

discussing their writing with peers and send as well as receive 237

Social media for collaborative learning to enhance learners' performance

i22) fe23) fe24) fe25) fe26) (e27

Figure 3 Results of the proposed model (hypotheses estimate).

238 feedback before publishing their final work. It is remarkable to

239 mention that this tool 'wiki' can be used as an indication of

240 sharing knowledge within the learning group. In terms of

241 knowledge, Janssen et al. (2010) put forward that collaborative

242 learning is far more important when learners are equipped with

243 cognitive ability. Considering the above discussion, the

244 researcher proposes the following hypothesis:

245 H9: There is a significant relationship between collaborative

246 learning and learners' performance.

3.6. Students' satisfaction 248

There is a need to research the area of interaction among stu- 249

dents online and highlight the factor if there are cultural differ- 250 ences and their influence through online engagement between 251

learners from different cultures (Kim, 2011). This is true 252 because learners' from certain cultures might have a different 253 understanding of the educational interventions in the context 254

of another culture. Several researchers like Santhanam et al. 255

(2008), So and Brush (2008) and Wu et al. (2010) focused on students' satisfaction within active collaborative learning atmosphere. When talking about user's adoption and satisfaction of technologies, two significant variables should be mentioned namely Perceived usefulness and perceived ease of use due to the observation that they are indicators of users' satisfaction with websites (Greenhow et al., 2009) as well as computers (Davis, 1989). According to Chai and Fan (2016) the Mobile Inverted Constructivism (MIC) is more acceptable to the digital natives. Moreover, technology success is found to be determined by the concept of entertainment which is related to the adoption and satisfaction levels of IS systems in the context of technology use (Kim et al., 2009). Therefore, it is recommended by Chang and Wang (2008) that online courses should be equipped by all sorts of interaction in order to reach a better learning and fulfil the students' satisfaction. Considering the above discussion, the researcher proposes the following hypothesis:

H10: There is a significant relationship between students'

satisfaction and learners' performance.

3.7. Learners' performance

Investigating the influence of social media on learning, Helou and Rahim (2014) conducted his study in Malaysia exploring the students' opinions in this regard and concluded that they support the positive influence of social media on their performance despite the fact that they use this technology mainly for social interaction more than for academic purposes. In this connection, a significant relationship has been established between the three factors of collaborative learning, engagement and learning performance (Junco et al., 2011). Social media is integrated in the field of social science due to its advantages, flexibility and the role it plays in addressing academic and social problems. Hamid et al. (2011) maintained that the use of social media in higher education can be implemented in various ways and lead to fruitful results. For example, Madge et al. (2009) argued that through the use of this technology, educational access and interaction can be improved. Bull et al. (2008) add that it can also bridge the gap informally among students, faculty or lecturers in terms of communication. In social media various applications are seen to be used by students for the purposes of entertainment and learning. It is reported that college students use different and various applications of social media that became an essential activity in their lives used for personal and learning purposes (Cao and Hong, 2011; Dahlstrom et al., 2011). Mobile technology and the smartphone revolution have participated in this heavy use of this technology (Dahlstrom et al., 2011). Previous related literature revealed that students' engagement is positively influenced by social media due to the relation found between social networking sites and students achievement by which the former has a great influence on the latter (Brady et al., 2010; Junco et al., 2011). These researchers added this might have a positive influence on research students' performance, cognitive skill as mentioned by Alloway and Allo-way (2012) and on their skill development as mentioned by Yu et al. (2010). The potential for positive educational impact was recognized and reported in the curriculum areas of civic

W.M. Al-Rahmi, A.M. Zeki

engagement and language learning (Mahadi and Ubaidullah, 2010).

4. Research methodology and data collection

The process of data collection took place in Universiti Tekno-logi Malaysia and targeted postgraduate and undergraduate students. Being the main tool of data collection, questionnaires were distributed to assess the influence of the factors under investigation and to verify the various research hypotheses. The questionnaire involved 41 items distributed over several factors namely perceived usefulness, perceived enjoyment, perceived ease of use, social media use, collaborative learning, students' satisfaction and learning performance. It also included demographic data like gender, education level, the level of social media use on daily and weekly basis to learn Quran and Hadith. 340 respondents agreed to participate and completed the questionnaire. This number is seen acceptable as it is reported that such study requires at least 150 respondents to actively participate. Hair et al. (2010) report that 150 is acceptable for studies with seven or less constructs, modest communalities, and no unidentified constructs for structural equation modeling (SEM) technique.

5. Data analysis and results

As the questionnaires were collected, respondents were classified according to many standards: gender, education level, the use of social media. Based on gender classification, 141 male and 199 female respondents participated forming 41.5% and 58.5% respectively. According to the participants' level of education, 18 of the respondents were PhD students, 88 were Master students, 228 were Bachelor students and 6 were Diploma students with the percentages 5.3%, 25.9%, 67.1% and 1.8% respectively. In classifying the participants through their use of social media, 9.4% forming 32 respondents reported that they use social media 1-2 times a day, while 37.6% forming 128 respondents reported that they use this technology 3-4 times a day.

For the rest of participants, (22.9%) forming 78 respondents mentioned that they use it 5-6 times a day, (30.0%) with a total number of 102 reported their use of social media to be more than 6 times per day. Finally, the respondents were also classified according to their use of social media per week in learning Quran and Hadith. 6.5% of the participants with a number of 22 appeared to use social media 1-2 times a week, 10.0% forming 34 participants appeared to use social media 34 times a week, 15.9% representing 54 participants reported that they use social media 5-6 times a week, and 67.6% represented 230 respondents confirmed that they use social media more than 6 times in a week for the purpose of learning Quran and Hadith (see Table 1).

5.1. Measurement model analysis

The major tool utilized by the current study for data analysis is called the structural equation model (SEM). This technique was used along with Amos 23 and Confirmatory factor analysis (CFA). Upon analysis, the overall goodness-of-fit using fit Indices (v2, df, v2/df, RMR, IFI, TLI, CFI and RMSEA) were

JKSUCI 272 26 September 2016 ARTICLE IN PRESS No. of Pages 11

Social media for collaborative learning to enhance learners' performance 7

Table 1 Descriptive information of the sample.

Measure Value Frequency Percentage

Gender Male 141 41.5

Female 199 58.5

Total 340 100.0

Education PhD 18 5.3

Master 88 25.9

Bachelor 228 67.1

Diploma 6 1.8

Total 340 100.0

Social media used per day to 1-2 times 32 9.4

learn Quran and Hadith 3-4 times 128 37.6

5-6 times 78 22.9

More 102 30.0

than 6

Total 340 100.0

Social media used per week 1-2 times 22 6.5

to learn Quran and Hadith 3-4 times 34 10.0

5-6 times 54 15.9

More 230 67.6

than 6

Total 340 100.0

revealed. Overall model fit was accepted through the use of CFA. That was also shown through the initial confirmatory factor analysis. The goodness fit indices to measurement model all values were acceptable. Table 2 below illustrates these results of the measurement model.

Correlation index, a crematory factor analysis, and Composite Reliability were used for the purpose of measuring the Discriminant validity. The value of the average variance extracted (AVE) of each construct should be the same to or higher than 0.5 (Hair et al., 2010), and square root AVE of each construct should be higher than inter-construct correlations (IC) associated with that factor (Fornell and Larcker, 1998). Moreover, the constructs, items and confirmatory factor analysis results factor loading of 0.5 or greater are acceptable, Composite Reliability and Cronbach's Alpha P0.70 (Hair et al., 2010). Moreover, three criteria are used to assess the discriminant validity in the current study; correlation index among variables is less than 0.80 (Hair et al., 2010). See Tables 3 and 4.

5.2. Results of hypothesis testing

The results of the current study support the framework as well as the hypotheses proposed in terms of the directional linkage between the framework variables. The 10 hypotheses proposed in the current study were accepted and verified. Table 5 illustrates the standard errors for the structural model.

The relation between perceived usefulness and social media use in the context of learning Quran and Hadith was found to be positive and significant with (b = 0.178, p < 0.001). This finding supports H1 proposing a significant relationship between the perceived usefulness and social media use for learning Quran and Hadith. The second hypothesis that suggests significant relationship between perceived usefulness and collaborative learning in the context of learning Quran and Hadith was also confirmed. With the result of b = 0.114, p < 0.001), H3 was also confirmed as the relation between perceived enjoyment and social media use for learning Quran and Hadith was found to be significant and positive. The positive relationship between perceived enjoyment and collaborative learning in the context of learning Quran and Hadith by social media use verified and proved H4 with (b = 0.122, p < 0.001).

As for the fifth hypothesis, the relationship between the perceived ease of use and social media use for learning Quran and Hadith appeared to be positive with (b = 0.277, p < 0.001). This result proves and accepts this hypothesis. Also, the sixth hypothesis was proved and accepted as the relation between perceived ease of use and collaborative learning to learn Quran and Hadith by social media use was reported to be positive and significant with (b = 0.155, p < 0.001).

As for the seventh hypothesis, a positive significant relationship was found between social media use for learning Quran and Hadith and collaborative learning. Therefore, the hypothesis is accepted and proved with (b = 0.841, p < 0.001). Hypothesis eight suggested a positive relation between social media use and students satisfaction. As the results proved such relation, this hypothesis was accepted and proved with (b = 1.070, p < 0.001).

The ninth hypothesis that suggested a positive relation between active collaborative learning and learning performance of students was accepted and proved since the results supported such results with (b = 0.319, p < 0.001). The relation between students' satisfaction and learning performance was found to be positive and significant. This result provides support to the tenth hypothesis and therefore it was accepted with (b = 0.511, p < 0.001).

5.3. Discussion and implications

Seven factors were investigated in the current study for their influence on learners' performance to lean Quran and Hadith. This study took place in Malaysia and targeted higher education. The ten hypotheses of this study were accepted and that might contradict with other studies like Junco (2012) and Kirschner and Karpinski (2010) reporting a negative impact of social media on students' performance. Learners' skills also appeared to be developed through the use of social media in the context of learning Quran and Hadith. While consistent with the study conducted by Chai and Fan (2016) results show that in the classes where the Mobile Inverted Constructivism

Table 2 Fitness of measurement model.

Model v2 df Z2/df RMR IFI TLI CFI RMSEA

Base 1124.436 753 1.493 0.035 0.916 0.908 0.915 0.054

JKSUCI 272 26 September 2016

8 W.M. Al-Rahmi, A.M. Zeki

Table 3 Discriminant validity.

PU PE PEU SMU CL SS LP

PU 0.790

PE 0.549 0.890

PEU 0.693 0.540 0.704

SMU 0.658 0.541 0.636 0.708

CL 0.592 0.609 0.597 0.572 0.743

SS 0.609 0.451 0.632 0.651 0.583 0.723

LP 0.547 0.518 0.543 0.595 0.695 0.654 0.719

Note: PU: Perceived Usefulness; PE: Perceived Enjoyment; PEU: Perceived Ease of Use; SMU: Social Media Use; CL: Collaborative Learning;

SS: Students' Satisfaction; LP: Learners' Performance.

Table 4 Item loadings on related factors.

Factor Item Standard loading Average variance extracted (AVE) Construct reliability (CR) Cronbach's Alpha

PU PU1 0.753 0.625 0.909 0.908

PU2 0.771

PU3 0.823

PU4 0.795

PU5 0.819

PU6 0.777

PE PE1 0.873 0.793 0.920 0.919

PE2 0.868

PE3 0.929

PEU PEU1 0.614 0.596 0.826 0.820

PEU2 0.500

PEU3 0.727

PEU4 0.750

PEU5 0.873

SMU SMU1 0.617 0.501 0.875 0.867

SMU2 0.606

SMU3 0.662

SMU4 0.742

SMU5 0.664

SMU6 0.607

SMU7 0.650

CL CL1 0.579 0.552 0.880 0.877

CL2 0.601

CL3 0.686

CL4 0.649

CL5 0.687

CL6 0.701

SS SS1 0.745 0.523 0.885 0.867

SS2 0.700

SS3 0.662

SS4 0.674

SS5 0.599

SS6 0.702

SS7 0.704

LP LP1 0.660 0.518 0.883 0.881

LP2 0.667

LP3 0.650

LP4 0.673

LP5 0.675

LP6 0.681

LP7 0.669

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Social media for collaborative learning to enhance learners' performance 9

Table 5 Hypotheses testing results.

H Independent Relationship Dependent Path Estimate SE C.R P Result

H1 PU ! SMU .288 .178 .064 2.790 .005 Supported

H2 PU ! CL .303 .247 .080 3.447 .000 Supported

H3 PE ! SMU .266 .114 .036 3.155 .002 Supported

H4 PE ! CL .195 .122 .044 2.764 .006 Supported

H5 PEU ! SMU .532 .277 .060 4.627 .000 Supported

H6 PEU ! CL .202 .155 .077 1.997 .046 Supported

H7 SMU ! CL .574 .841 .156 5.394 .000 Supported

H8 SMU ! SS .816 1.070 .126 8.464 .000 Supported

H9 CL ! LP .387 .319 .076 4.198 .000 Supported

H10 SS ! LP .555 .511 .097 5.293 .000 Supported

(MIC) model is applied, students are better motivated to learn and make creative achievements than those restrained by traditional classroom teaching. This study illustrated that the constructs are well represented by the indicators. Also, the measurement model proved to be acceptable through the acceptance of all goodness of fit indices. The current study also measures both convergent and discriminant validity in which the study calculated the construct reliabilities and average variance extracted values. The model was indicated to be good on the light of the values and the 10 hypotheses of the study were verified and accepted. New correlations were also added to the model and the validity of the model was confirmed by the indices and goodness of fit indices. All of these results confirm that social media has many advantages like being useful, ease to use, enjoyable, and able to satisfy the needs of the learners. This study established a model on social media use for collaborative learning to effect learners' performance.

5.4. Conclusion and future work

It is vivid that social media is heavily used by students to learn Quran and Hadith. These platforms allow students to exchange and share information with their peers (Al-rahmi et al., 2015). The major aim of the study was to explore the impact of several factors on collaborative learning and students' satisfaction which lead to a better learners' performance. TAM was the ground of the proposed model used in the current study and that involved seven constructs: perceived usefulness, perceived enjoyment, and perceived ease of use, social media use, collaborative learning, students' satisfaction and learners' performance. An online questionnaire with 41 items was used to measure these constructs and was analyzed using structural equation modeling (SEM) technique. The results highlighted that both collaborative learning and students' satisfaction have a positive influence on learners' performance in the context on learning Quran and Hadith. It is notable that the construct of students' satisfaction has the greatest influence. It also revealed the high satisfaction by students using social media enhances collaborative learning which leads to a better performance. The current study recommends that future studies include other and extra elements to assess the influence of the different factors on learners' performance through collaborative learning.

6. Uncited references

Chang and Tsai (2005) and Junco and Cotten (2012).

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