At YouTube School with Prof. Facebook: Students’ Attitudes towards Learning English through Social Media

Introduction

If you are one of the social media members, you might get familiar with English Vocabulary, ESL Team, Dictionary.com, VOA Learning English, BBC Learning English or Learn English-British Council which are some of the sources for learning English provided on Facebook, YouTube, Twitter, etc. and which anyone can access by using only a fingertip. According to the various English teaching network sites, it indicates that the technologies have resulted in educational paradigm shift which creates new parameters such as collaboration, personalization, and user-generated content (Allam & Elyas, 2016). This signifies the coherence between the present circumstance and Vygotsky’s concept of “the dominant role of social experience in human development” (Vygotsky, 1978, p. 22). His socio-cultural theory emphasized that the social interaction of language learners impact the cognitive development which supports individuals learning (Vygotsky, 1978). Therefore, it is not surprising that there have been big loads of research focusing on the co-construction of knowledge from both inside and outside classrooms through social media networks as resources for the collaborative learning (Gamble & Wilkins, 2014) and most of the results turned positive. It is inevitable that our students who were born as digital natives surrounded by tools of digital ages (Prensky, 2001) consider social media networks as an integral part of their language learning process. Buzzetto-More (2013) stressed that online learning is self-directed and adjustable learning approach which students are able to concentrate on their needs, interests, abilities, learning styles and ambitions. Furthermore, students have a chance to create and participate in-depth learning through interaction, collaboration and critical thinking (Liburd & Christensen, 2013).

In Thailand, Thailand ICT Nation Plan II (IT 2010) set the goal to change the country to become “knowledge base society” so e-education has been driven as one of the plan’s ultimate goals which is a strategy to strengthen and enhance teaching and learning skills by improving the quality of electronic teaching materials (Suktrisul, 2007). However,                e-education or e-learning system produced by universities seems unsuccessful enough due to the limitation of accessibility and attractiveness of designs and contents (Boondao, Komlayut & Punnakan, 2009, Muangkeow, 2007). There are some studies indicating that social media is more interesting among teachers and students. For instance, the study of Seechaliao (2015) found that more than 70 percent of teachers adopted social media to use in their courses while Facebook, Twitter and YouTube positively affected university students’ learning as the results of the studies of Kitchakarn (2016), Tananuraksakul (2015), and Tantarangsee (2016). The reason why social media sites are more popular than e-learning system provided by universities can be explained by Technology Acceptance Model (TAM) which consists of ease of use, perceived usefulness, and attitudes towards using (Davis, 1989). Therefore, this study was conducted to explore the attitudes of Thai university students who were studying in private and government universities towards using social media for English language learning which resulted from the differences of genders, majors, and types of universities in order to propose an exact implementation of innovative language teaching pedagogy.

Constructivism: an approach for teaching and learning with interaction

Harasim (2012) summarized that constructivism is one of the epistemological perspectives on learning theories which believes that “knowledge is created to fit with reality” (p.14) and it is not fixed and absolute information transmitted to students by teachers as same as behaviorism and cognitivism which are objectivist epistemology. The best-known “social constructivism” of Vygotsky (1978) focused on child’s acquisition of new knowledge through contacts and interactions with people which are driven by social and cultural influences (Turuk, 2008). Vygotsky explained the phenomena of learning construction through an interaction as follows

Every function in the child’s cultural development appears twice: first, on the social level, and later, on the individual level; first, between people (interpsychological) and then inside the child (intrapsychological). This applies equally to voluntary attention, to logical memory, and to the formation of concepts. All the higher functions originate as actual relationships between individuals.(Vygotsky, 1978, p.57)

 

Vygotsky (1978) proposed the notion of Zone of Proximal Development (ZPD) for the purpose of clarifying the zone between a child’s actual development and potential development. ZPD can be scaffolded through social interaction by mediators such as languages, peers, or collaborative tasks which a child internalizes and co-constructs the new knowledge from social interaction and communication to reach his/her potential development and improve cognitive conceptual (Turuk, 2008, Zainuddin, Abdullah & Downe, 2011). When learning in the ZPD with interaction and collaboration with peers or teachers results in the social plane or interpsychological level, cognitive plane or intrapsychological level will be incorporated within the child (Liu & Matthews, 2005, Shabani, 2016). Tapscott (1998) pointed out that this approach can replace one-way instruction with construction and discovery of knowledge which encourage learners to have intellectual and rationality.

Figure1: Zone of Proximal Development (ZPD) between child’s current development and potential development (Adopted from Zainuddin, Abdullah & Downe, 2011)

Swain (2000) pointed out that collaborative learning increases potential of learners to develop ZPD such as interactions between teachers and students and pair work or group activities until knowledge is mutually constructed. After that students will be able to be self-regulated and their performances are automated. Therefore, to develop ZPD needs interactions in collaborative learning as a prerequisite for engaging in self-regulation (Vygotsky, 1978). This stimulates students to become active rather than passive which entails the learners as the center of learning (Ally, 2004).

Unlike behaviorism, cognitivism, and social constructivism which considered learning as an individual pursuit, the Internet Revolution and Knowledge Age of the 21^st century have introduced a new mindset for active learning called Online Collaborative Learning Theory emphasizing knowledge-building process which inducts learners from all ages to build online knowledge communities in formal and informal setting (Harasim, 2012). Similarly, Scardamalia & Bereiter (2006) agreed that the traditional educational practice which emphasized on knowledge transmission has been being replaced by newer constructivist methods. Knowledge building is refashioning education and initiating students into a knowledge creating culture (Scardamalia & Bereiter, 2006).

One important advantage of knowledge building as an educational approach is that it provides a straightforward way to address the contemporary emphasis on knowledge creation and innovation. These lie outside the scope of most constructivist approaches, whereas they are at the heart of knowledge building (Scardamalia & Bereiter, 2006, p. 99).

 

Ally (2004) explained two kinds of online learning; synchronous and asynchronous online learning. Synchronous online learning is a learning method which students can access online materials anytime and provide teachers and students multiple ways of real-time interactions and collaboration at specific hours whereas asynchronous online learning allows students to participate in online classes based on their own schedule with no specific class hours (Er, Özden & Arifoglu, 2009). In synchronous online learning, students will feel involved with the classes and receive instant feedbacks and educational experiences in real-time communication while asynchronous online learning provides students their own pace to form their thought without worrying about time.

The Integration of Technology Acceptance Model and Technology Task Fit

Technology Acceptance Model (TAM) and Technology Task Fit (TTF) are often referred and considered to use as a framework in studies of language learning through technology; therefore, this study integrated TAM and TTF as a theoretical guideline for the questionnaire as the suggestion of Dishaw and Strong (1999) in order to provide a stronger model to study behaviors of university students in learning English through technology like Facebook, YouTube, Line, Twitter and so on. The integration of the two models is widely employed in many studies. For instance, the research of Madini and Alshaikhi (2017) on visual reality learning in English for Specific Purpose combined TAM and TTF as their conceptual framework whereas Ajayi, Iahad, Ahmad and Yusof (2017) applied the combination of the models including Behavioral Attitude as factors influencing the flipped learning.

 

Technology Acceptance Model (TAM)

Technology Acceptance Model (TAM) was developed by Davis in 1989 in a purpose to measure IT users’ attitudes towards using IT based on two variables: perceived usefulness and perceived ease of use. Perceived of usefulness is “the degree to which a person believes that using a particular system would enhance his or her job performance” while perceived ease of use means “the degree to which a person believes that using a particular system would be free of effort” (Davis, 1989, p.320).

Perceived usefulness and perceived ease of use influence attitudes. If the attitude is high and positive, it results in higher behavioral intention, the degree of a person’s desire and readiness to use new information technology. Perceived usefulness and perceived ease of use can directly affect behavioral intention and affect each other in the same direction as well (Davis, 1989). However, there are external variables (e.g. personal variables of users, user participation in design, system characteristics, and nature of the implementation process) which can indirectly impact personal internal beliefs and attitudes (Tsai, 2012, Venkantesh & Davis, 1996).

Although TAM has been developed and modified in various versions (Chutter, 2009), Dishaw & Strong (1999) commented that TAM lacks task focus for understanding IT utilization. Therefore, they proposed that there should be the integration between TAM and TTF models so that it can provide a stronger model to explore the actual IT utilization.

 

Task Technology Fit (TTF)

Goodhue & Thompson (1995) suggested TTF due to the fact that he believed “the technology must be utilized, and the technology must be a good fit with the tasks it supports.” (p. 213), therefore; TTF was developed to explain how technology leads to performance impacts and how user satisfaction is assessed. In other words, if tasks are assigned to apply in an appropriate technology, the convergence of the personal needs and benefits of users and functionality of the technology can increase performance impact, utilization, and user satisfaction. Accordingly, TTF plays the role as a predictor of user performance (Huang & Chuan, 2016). The explanatory variables directly influencing technology use and individual performance consists of Technology Characteristics, Task Characteristics, and Individual Abilities (Gebauer, Shaw & Gribbins, 2005).

Dishaw & Strong (1999) claimed that some TTF models consider individual performance as outcomes and Individual Abilities or tool experience of users can directly affect Utilization or actual tool use. Therefore, Task-Technology Fit can occur depending on the correspondence of technology functionality, task requirement, and individual abilities (Gebauer, Shaw & Gribbins, 2005). McCarthy & McCarthy (2014) explored students’ perception of social media through TTF and tested ease of use, usefulness, and right information as components of individual characteristics and reliability, accessibility, and compatibility as components of task characteristics. Additionally, technology characteristics were assumed as “the characteristics of any given system are the same for all who use the system” (Goodhue & Thompson, 1995, p. 222) which Bass (2010) determined personalization, mobility and collaboration in order to investigate employees’ satisfaction and productivity of using ICT tools in workplace. Nevertheless, there are precursors of Utilization such as attitudes towards use, habit, facilitating conditions, and social norms which might indirectly affect performance impacts (Huang & Chuan, 2016).

 

 

 

 

 

 

 

 

 

 

TAM

Task technology fit

Tool experience

——————————————————————————————————

TTF

	Tool characteristics
			Task characteristics

 

 

 

Figure 2: The diagram showing the integration of TAM and TTF models (Adopted from Dishaw & Strong, 1999)

The diagram illustrates the incorporated models of TAM and TTF which was employed in this study. The integrated model was used as the framework to create the questionnaire which comprised the items concerning perceived usefulness and perceived ease of use from TAM model influencing users’ attitudes and behavioral intention. The attitudes and behavioral intention will reflect the actual tool use. In addition, TTF results from perceived usefulness and perceived ease of use; thereby, the items in the questionnaire also focused on  task characteristics and technology characteristics which manifest the actual tool use as same as TAM model. Tool experience or individual abilities were included in demographic section.

 

 

 

 

 

Foreign researches in using social network sites for language learning

The use of social network sites (SNs) as tools for language learning is extensively worldwide. A lot of studies in the past decade explore the effectiveness and users’ attitude towards these SNs, including the studies of Denker et al. (2018), Labib & Mostafa (2015), Sim Monica & Pop Annamria (2014), and Park & Lee (2013).

Nowadays, technologies and social network sites play a role as teacher assistants in learning process. Social network sites such as Facebook or Twitter become the channels for communicate in learning and teaching language in classrooms. According to Technology Acceptance Model (TAM), perceived usefulness and perceived ease of use of that technology impact individuals’ motive to use technology.  Denker et al. (2018) investigate students’ attitude and their motivations to use Twitter in order to communicate with the teacher. They found that online communication attitudes shape student motivation to communicate with their teacher.

Based on TAM, Labib & Mostafa (2015) also study the effect of using SNs in collaborative learning among undergraduate and post-graduate students in Egypt. The results showed that the students’ intention in using SNs in educational purposes is weaker than using SNs in entertainment and socialization. They also found that 90% of the undergraduate students used Twitter whereas it was used only 21% of the post graduate students. Facebook and YouTube were used by 49% and 50%of the undergraduate students, and 51% and 50% by the post graduate students.

The study of Sim Monica & Pop Annamria (2014) explore the impact of social media in improving students’ vocabulary learning. In this study, the researchers used Facebook as a social media tool to present the benefits of Facebook for educational purposes. They divided the students into two groups: group A exposed to the Facebook post, group B followed the traditional teaching method.  The results showed that students with exposed to Facebook improved in vocabulary performance than the students who were taught by traditional teaching. Park & Lee (2013) also examined the use of social network for language learning (SNSLL) and their perception of ESL university students. In the study, Busuu, Livemocha, and English Café were introduced to investigate the learning tasks performance of the students. The finding demonstrated that most of the students reported positive feedback when using SNSLL. In addition, there were several factors that affect students’ satisfaction such as overall comfortable level, language proficiency levels, preferred communication modes for connecting with other, and design of the sites.

Using social network sites in learning educational purposes has a lot of benefits such as interaction, communication, and practice. Several sites were used to help in language learning beyond classroom today. Many studies attempted to investigate the attitude and factors that impact the satisfaction of the users apart from the effectiveness of the tools.

 

Social Media as a pedagogical tool in Thailand

            Regarding the rapid advancement of technology and the changing characteristics of students in 21st century, to be more familiar with technology gadgets, social media has partly or mainly been introduced in several classrooms. Apart from the use of government-support e-learning system, integration of social media in the EFL classroom hence has been conducted by educators or researchers around the world, including Thailand. This review included the implementation of Facebook, Instagram and Twitter.

Having been the most popular social media site among Thai people for decades, research studies on the use of Facebook as a learning tool have been heavily conducted. Boontham (2017); Srirat (2014) and Thongmak (2014) use Facebook groups to facilitate teaching courses for students. They found that it could promote communication, collaborative learning as well as learning achievement. Moreover, Kajornboon (2013) investigates the effects of using Facebook to assist interaction among students themselves and interaction with their teachers by assigning students to submit writing assignments on Facebook. Students thought that using Facebook to submit, give and receive feedback of their work via Facebook are effective. Kitchakarn (2016) also treats Facebook as a learning tool in her EFL classes and she investigates students’ attitudes toward the use of Facebook whether it could enhance their learning performance by using questionnaires. Similar to study of Thongmak (2014), Kitchakarn adapted model of the Technology Acceptance Modal (TAM) by Davis (1989), which was including their factors: perceived usefulness, perceived ease of use, and attitudes toward usage, to check whether they were related to the learning performance or not. The findings suggest the possibility to integrate social media in the future courses with the awareness of some distracted factors.

Boonchum (2014) implements the use of several social network services to develop her students English writing skills by allowing them to choose one of any social network services e.g. email, Facebook, Twitter and so on as a channel to submit and receive feedback from their teacher. She found that students were satisfied with this activity since they felt lesser stress and with this way, their writing skills were statistically significantly improved.
Instagram is also utilized as a learning tool in Thai EFL classroom, Chotipaktanasook (2016) explores learners’ willingness to communicate in L2 by asking her students to post pictures, and texts saying what they did during the class in English via Instagram. At the end of the course, students were asked to complete questionnaires and participate interviews. By the end of the academic year, students still report the usefulness of the social media for their education.
Lakarnchau’s study (2012) is the investigation of the use of Twitter in English writing classes. Messages posted on Twitter were analyzed. Also, the interviews were conducted and it was found that there were a few differences between high-and low- English proficiency users.
All in all, it can be obviously seen that the studies on Facebook were relatively more than other social media sites. However, from all the studies of social media as a pedagogical tool in this review indicate that the attitudes towards the implementation of the social media in EFL classes were mostly observed. This study will explore the attitudes of Thai university students toward the use of social media on the basis of the Technology Acceptance Modal (TAM) by Davis (1989), Technology Task Fit (TTF), and behavioral intention.

Research objectives:

The present study aims to investigate the relationship between two independent variables (social media and students’ factors) and attitudes toward the use of social media in their EFL classroom. The social media in this study included Youtube, Facebook, Twitter and Google+  whereas students’ factors are gender (male and female), types of university (government, private, and rajabhat), and their perspective degrees (sciences, social sciences, and arts). Hence, the hypotheses in this study included:

H1: Social media and students’ gender positively affects students’ attitudes toward the use of social media in their EFL classroom.
H2: Social media and students’ university type positively affects students’ attitudes toward the use of social media in their EFL classroom.
H3: Social media and students’ perspective degree positively affects students’ attitudes toward the use of social media in their EFL classroom.

 

 

Methodology

Sampling selection

In this study the population is Thai university students. According to Yamanae (1967) for a large or unknown population, the participants in this study should be at least 400 students. Voluntary participation technique was applied to select the data. After asking for the voluntary, 640 students from three types of university participated in this study.

 

Questionnaire Development

Questionnaire was utilized as a research instrument in this study. It was developed from Lee and Lehto, 2013 & Kitchakarn, 2016, and Sobiah, Moustafa and Ghandfoush, 2016. It consists of three parts: Part I was about personal data of respondents; Part II was the 5-rating scale items asking for the attitudes toward TAM theory (Perceived usefulness, Perceived ease of use, and Attitudes), Task-technology fit and, Behavioral intention and; Part II consisted of one open-ended question asking participants to suggest on the use of social media in EFL learning.

Before distributing questionnaire to the respondents, it was sent to three experts for content validity test (IOC) to measure the validity of the contents and the research objectives. Three experts included one assistant professor and two doctors. All of them have been teaching English in higher education institutes for more than ten years and have experienced teaching English through social media. After IOC process, one item from Part II and one item from Part III were deleted (see Appendix A). Since the participants’ first language is Thai, all items in questionnaires were translated into Thai language.

 

 

 

Data Collection

To collect data on voluntary basis, the researchers have asked lecturers from three types of higher education institutes in Thailand including government universities, Rajabhat universities (formerly teacher colleges), and private universities in Thailand to invite their students to complete the online questionnaire for one week. Online questionnaire was launched on 28 April 2018 and closed on 4 May, 2018.

 

Data Analysis

To test the hypotheses, the data gaining from the questionnaires were analyzed with two-way ANOVA in order to find the relationship among variables. There were two dependent variables: social media (X1 – Youtube, Twitter, Google+ and, Facebook) and stuents’ personal data (gender, university type and, perspective degree) whilst the independent variable was the attitude toward the use of social media in EFL classroom.

Content analysis was used to analyze open-ended question in Part III asking students for their suggestion for the use of social media in EFL learning. The answers will be categorized by the group of items in Part II of the questionnaire including TAM theory (Perceived usefulness, Perceived ease of use, and Attitudes), Task-technology fit and, Behavioral intention

 

Results

After launching the online questionnaire for one week (28 April 2018 to 4 May, 2018), 640 participants paid a visit and completed the questionnaires. Their responds in Part I can be summarized as shown in Table 1 below.

 

Table 1: Number of participants in this study divided by gender, degree, university type, preferred social media and, experience in using social media

		number of persons (n = 640)	percent
Gender	Male	138	22
	Female	502	78
Degree	Social sciences	198	31
	Sciences	80	13
	Arts	362	57
University type	Government	296	46
	Rajabhat	283	44
	Private	61	10
Social media	Youtube	382	60
	Facebook	57	9
	Google+	134	21
	others	67	10
Experience to use social media	less than 1 year	8	1
	1-5 years	108	17
	6-10 years	378	59
	more than 10 years	146	23

 

The majority of the respondents were female (502 students or 78%) while 138 respondents or 22% were male. The respondents were also divided into their perspective degrees and the number of them in each degree are as follows: 198 students or 31% were social sciences students, 80 students or 13% were sciences students and, the biggest group of students (362 students) or 57% were arts students. Also, this study separated students by their university types: government university (296 students or 46%), Rajabhat university (283 students or44%) and, private university (61 students or 10%). Responds from participants were also classified by their preferred social media for EFL learning. The most popular social media program was Youtube (382 students or 60%). The second rank went to Google+(134 students or 21%), then the lower ranks were other social media (67 students or 10%) and, Facebook (57 students or 9%), respectively. Most students have experienced using social network between 6-10 years(378 students or 59%) while some students have experienced more than 10 years (146 students or 23%). Some interesting facts are there were 108 (17%) with 1-5 years of experience and there were 8 students (1%) reported that they had experience in using social media less than one years

 

Hypothesis Tests

Two-way ANOVA was conducted to analyze the collected data and the equality of variance and honest significant difference were taken place by Levene’s Test and Tukey HSD Test respectively. There were three pairs of factors tested by Two-way ANOVA for the purpose of comparing the mean differences between groups: gender and social media, majors and social media, and genres of universities and social media.

 

H1: Social media and students’ gender positively affects students’ attitudes toward the use of social media in their EFL classroom.

Genders might not affect attitudes and actual tool use of social media sites. A two-way analysis of variance tested the attitudes towards using social media (e.g. Facebook, YouTube, Google+) from students with different gender. The results in Table 2 indicated that there were not a significant main effect for genders, F(1, 628) = 0.000, p = .987, and a significant main effect for social media in learning English, F(3, 628) = 1.243, p = .293. In addition, the data did not show the significant interaction effect, F(3, 628) =0.336, p = .799, concluding that students’ gender did not influence their attitudes towards using social media in learning English language, hence H1 was rejected.

Table 2: Comparison of mean differences between genders and social media used in learning English

Dependent variables	Levene’s Test	F	Sig.	Tukey
Gender*Social media use in learning English	.940	.336	.799	.549
Gender			.987
Social media use in learning English			.293

 

Table 3: Comparison of mean differences between genders and social media used in learning English

SMuseinlearningEnglish	gender	Mean	Std. Error
Youtube	male	3.889	.073
	female	3.857	.038
Facebook	male	3.908	.181
	female	3.783	.098
Google+	male	3.702	.119
	female	3.748	.064
others	male	3.730	.168
	female	3.847	.090

 

According to Table 3 showing the comparison of mean differences between genders and social media used in learning English, attitudes of male students towards using Facebook was the highest, M = 3.908, SD = .181 whilst the most popular social network among female students is Youtube, M = 3.857, SD = .038. Interestingly found that the least popular for both male (M = 3.702, SD = .119) and female M = 3.783, SD = .098 students is Google+. However, all social media seem to gain popularity among male and female students at the high level.

 

H2: Social media and students’ university type positively affects students’ attitudes toward the use of social media in their EFL classroom.
Table 4: Comparison of mean differences between genres of universities and social media used in learning English

Dependent variables	Levene’s Test	F	Sig.	Tukey
University types*Social media use in learning English	.335	1.008	.419	.291
University types			1.455
Social media use in learning English			.718

 

Table 5: Comparison of mean differences between genres of universities and social media used in learning English

universitytype * SMuseinlearningEnglish
Dependent Variable:mean_attitude
universitytype	SMuseinlearningEnglish	Mean	Std. Error
government university	Youtube	3.923	.046
	Facebook	3.927	.158
	Google+	3.782	.101
	others	3.826	.110
Rajabhat university	Youtube	3.816	.053
	Facebook	3.635	.119
	Google+	3.720	.075
	others	3.808	.123
private university	Youtube	3.698	.121
	Facebook	4.143	.205
	Google+	3.712	.153
	others	3.869	.325

 

 

Genres of universities might not contribute attitudes and actual tool use of social media sites. A two-way analysis of variance tested the attitudes towards using social media (e.g. Facebook, YouTube, Google+) of students from government universities, Rajabhat universities, and private universities. The results indicated that there were not a significant main effect for types of universities, F(2, 628) = 1.455, p = .234, and a significant main effect for social media in learning English, F(3, 628) = .718, p = .542. In addition, the data did not show the significant interaction effect, F(6, 628) =1.008, p = .419, concluding that although students came from different universities, it did not influence their attitudes towards using social media in learning English language.

According to the graph showing the comparison of mean differences between genres of universities and social media used in learning English, attitudes of private university students towards using Facebook was higher than students’ from the others, M = 4.149, SD = .492, while Rajabhat university students had lower mean on Facebook, M = 3.635, SD = .730. And government university students tend to belong to the highest mean of attitudes towards using YouTube for learning English language, M = 3.922, SD = .609.

 

H3: Social media and students’ perspective degree positively affects students’ attitudes toward the use of social media in their EFL classroom.

 

Table 6: Comparison of mean differences between genres of universities and social media used in learning English

Dependent variables				Levene’s Test		F		Sig.	Tukey
degrees*Social media use in learning English				1.041		2.216		.040	.536
degrees								.125
Social media use in learning English								.636
	Table 7: Comparison of mean differences between genders and social media used in learning English
	Dependent Variable:mean_attitude
	SMuseinlearningEnglish	degree	Mean		Std. Error
	Youtube	social sciences	3.965		.057
		sciences	3.586		.087
		arts	3.876		.045
	Facebook	social sciences	3.845		.166
		sciences	3.702		.227
		arts	3.822		.110
	Google+	social sciences	3.908		.103
		sciences	4.262		.262
		arts	3.628		.068
	others	social sciences	3.958		.151
		sciences	3.887		.194
		arts	3.737		.104

 

Table 8 : Simple Main Effect test between degree and social media use in learning English

 

Degree	Between groups		SMuseinlearningEnglish
	F	Sig.	Sig.
Social Sciences	.226	.878	.920
Sciences	2.159	.100	.185
Arts	3.132	0.26	.256

 

Table 9 : Simple Main Effect test between social media use in learning English and degree

SMuseinlearningEnglish	Between groups		Degree
	F	Sig.	Sig.
YouTube	6.982	.001	.623
Facebook	.136	.873	.852
Google+	4.533	.012	.343
Others	.707	.497	.635

 

 

A two-ways ANNOVA was used to test the attitudes towards using social media (Facebook, YouTube, Google+) and students’ degrees (social sciences,  sciences, and arts). The results showed that there were not a significant main effect for types of degrees, F(2, 628) = 2.09, p = .125, and there were not a significant main effect for social media use in learning English, F(3, 628) = .57, p = .636.

However, the interaction effect was significant, F(6,628) = 2.22, p = .04, indicating that the students degrees related with the use of social media sites. The simple main effect test between  degree and social media use in learning English showed that there was a significant for Arts, F= 3.132, p = .026. In addition, The simple main effect test between  social media use in learning English and degree showed that there was a significant for YouTube, F= 6.982, p = .001 and Google+, F = 4.533, p = .012.

Nevertheless, the Levene’s test indicated that the attitudes towards using social media sites of the students divided by their degrees are not significant, F = 1.04, p = .41. The table 7 also emphasized that the differences of the students’ mean attitude among the three degree groups towards using social media sites in learning English. The use of Youtube in learning English were found the most among the students with social sciences degree (M=3.96, S.D. = .632) and arts degree (M = 3.87, S.D. =.676), while Google+ was the most popular site in learning English for the students with sciences degree (M= 3.90, S.D. = .587).

 

Summary of suggestions

The final section of the questionnaire included an open-ended question in order to give a chance to the respondents to suggest an comment anything which was not added in the scale-questionnaire items. All the suggestions and comments are shown in frequency and separated based on kinds of universities and topics reviewed in literature.

 

 

 

Table

 10: Summary of suggestions from government universities

TOPIC	GOVERNMENT UNIVERSITIES
	positive	negative	NO COMMENT	suggestion
Perceived usefulness	20	5	0	9
perceived ease of use	36	2	0	8
Attitudes	12	1	0	17
Task-technology fit	11	6	0	16
Behavioral intention	3	0	0	10
GOOD IN OVERALL	24	0	0	0
No comment	0	0	116	0
TOTAL = 296	106	14	116	60

 

Table

 11: Summary of suggestions from Rajabhat universities

 

TOPIC	RAJABHAT UNIVERSITIES
	positive	negative	NO COMMENT	suggestion
Perceived usefulness	21	6	0	2
perceived ease of use	14	5	0	6
Attitudes	23	1	0	3
Task-technology fit	22	8	0	14
Behavioral intention	2	0	0	1
GOOD IN OVERALL	66	0	0	0
No comment	0	0	75	0
TOTAL = 269	148	20	75	26

 

 

 

 

 

 

Table

 12: Summary of suggestions from private universities

 

TOPIC	PRIVATE UNIVERSITIES
	positive	negative	NO COMMENT	suggestion
Perceived usefulness	10	0	0	3
Perceived ease of use	1	0	0	2
Attitudes	2	0	0	0
Task-technology fit	0	0	0	4
Behavioral intention	0	0	0	0
GOOD IN OVERALL	0	1	0	0
No comment	0	0	38	0
TOTAL = 61	13	1	38	9

Students from all types of the universities revealed positive comments on perceived usefulness while most of the students who positively perceived ease of use of the social media came from the government universities. Social media were perceived their usefulness in terms of practicing listening and speaking and offering some kinds of knowledge which they could not experience in classrooms with flexible time such as songs or various accents of English speakers. However, there were others disagreeing since they thought that real experiences are more important and better than learning from a flat screen. One third of the students from the government universities agreed that the social media were easy to use because they are able to be accessed from everywhere and by all ages and support easily learning outside classrooms. Moreover, there could be real-time interaction, especially on Facebook, like usual classrooms. Nonetheless, those who use Facebook and YouTube found that it was not easy for them to use these types of social media due to the convenience of the system and fewer contents than their requirement.

According to the TTF, the respondents positively thought that online learning was suitable for them because they can choose convenient time. In addition, they agreed that the social media like YouTube were appropriate for listening skill although there were some complaints about the quality of video productions with regard to interesting pictures, clear sound, and useful contents which could draw their attention. Negatively, if learners do not try to practice or learn English through the social media, they are not effective educational genres for English language teaching. There was someone complaining about so many programs like on YouTube that they cannot decide which one is good and appropriate for them.

In conclusion, they suggested that the social media for English language learning should be more systematic and accessible through various channels with clear explanations/instructions. In addition, the contents should be selected circumspectly and reliably so that students can be self-directed even though there is no real interaction with instructors;   notwithstanding, language learning process/method of students might be different and learning through the social media might be pleased by students who prefer to be taught by teachers/instructors.

 

Discussion

According to the integration of TAM and TTF model, more than 70 percent of the participants have experienced the social media for more than six years (see Table 1) because they were born as digital natives as Prensky (2001) stated that they are always surrounded by digital tools. This means that they must perceive the ease of use very well as the model shows that the tool experiences of user in TTF model correspondingly affect the perceived ease of use in TAM model including the tool characteristics which they have been familiar with for many years. Their experiences with the social media make them think that it is easy to use them since they are a part of their life.

Accordingly, three forth of the participants agreed that the functions of YouTube respond to their life style in learning English. The ease of use was highly represented by 42.6 percent of all participants who strongly agreed that they can use any devices to access the social media they prefer. In fact, 382 students preferred to Youtube for EFL learning whereas Google+, the second rank was chosen by 134 students. The striking fact found in this study is the number of students implemented Facebook to learn English, that is 57 students. Most of the studies from the literature review in global and national contexts reveal that Facebook seem to be favorable tool for teachers to engage their students outside classroom. However, Yadav and Rai (2017) explore the behavior of this generation on social media usage and found that they inclined to use social media as they move on the different phases of their life cycle. The study of Boholano (2017) reveal that Youtube is in the second rank of the most popular social media for Filipino preservice teachers to their own learning and teaching. Viewing Youtube, selecting the suitable links for their own EFL learning might be a learning pace of this generation. Hence, with the popularity among students, Youtube might be a challenge tool for teachers to introduce to their own classroom.

Furthermore, more than 60 percent of them agreed that the social media they used fit their wants and needs and tasks (e.g. exercises for English listening skill on YouTube or Facebook) although there were about 30 percent disagreeing with the fit of the social media. Similarly, the model indicates that the technology fit influences the perceived usefulness which more than 60 percent of the participants recognized the social media they employ to learn English.

The results from perceived usefulness and perceived ease of use directly revealed positive attitudes towards using social media in developing their English skills and intention to employ them in the future. The results from the questionnaire created based on the integration of TAM and TTF model of  Dishaw & Strong (1999) reflect the actual use of people who apply technology in order to support their life like learning English and they also illustrate the linkage between TAM and TTF which fulfills each other and can explain the phenomenon of the social media use.

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