Additional Analysis

The analyses described above were directed at testing the model, in order to assess the validity of the research hypotheses. As is frequently the case in empirical work of this nature, the previous analyses raised further questions concerning the reasons of for the use of new technologies in learning and teaching EFL in Saudi Arabia. The following analysis of data addresses these emergent issues and contributes to the discussion and the implications of the study.

To assess mobile devices’ ownership in the two samples, the participants were asked to specify what devices they currently own. Table 39 indicates that the Smart Phone was the most popular device and was owned by 81.4% of students and 79.7% of instructors. Faculty were more likely than students to own a cell phone and electronic dictionary, but were less likely to possess a tablet/ipad than students.

Table 40: Descriptive Statistics for Owing Mobile Devices

Owing Mobile Devices Frequency Percentage

Students Survey Cell Phone 294 33.8 Smart Phone 708 81.4 Electronic Dictionary 95 10.9 Tablet/iPad 347 39.9 e-Reader/Kindle 3 0.3

Don’t have any 18 2.1

Faculty Survey Cell Phone 38 59.4 Smart Phone 51 79.7 Electronic Dictionary 14 21.9 Tablet/iPad 18 28.1 e-Reader/Kindle 1 1.6

Don’t have any 0 0

As the smart phone was the most popular mobile device used by the participants, it is worth examining how frequently they use this device, more especially to access the internet (see Table 41). As can be seen from the table, the proportion of faculty using their smart phones more than five times each day was higher (70.3%) than that of students (61.7%). Moreover, a greater proportion of this group of staff making the heaviest use of their smart phones were also more likely to access the internet (62.5%) than the comparable group of students (48.6%). So, in essence, staff were more likely than students to use their smart phones, and were also more likely to use their smart phones to access the internet.

Table 41:Descriptive Statistics for Smart Phone

Frequency of using Smart

Phone No. (%) of General Usage No. (%) of Accessing Internet Students Survey

More than 5 times per day 537 (61.7%) 423 (48.6%)

2-5 times per day 117 (13.4%) 149 (17.1%)

Once a day 27 (3.1%) 54 (6.2%)

4-6 times per week 7 (0.8%) 22 (2.5%)

2-3 times per week 10 (1.1%) 26 (3%)

Once a week 3 (0.3%) 18 (2.1%)

2-3 times per month 4 (0.5%) 8 (0.9%)

Once a month 3 (0.3%) 7 (0.8%)

N/A 162 (18.6%) 163 (18.7%)

Faculty Survey

More than 5 times per day 45 (70.3%) 40 (62.5%)

2-5 times per day 4 (6.3%) 6 (9.4%)

Once a day 2 (3.1%) 2 (3.1%)

4-6 times per week 0 (0%) 1 (1.6%)

2-3 times per week 0 (0%) 0 (0%)

Once a week 0 (0%) 1 (1.6%)

2-3 times per month 0 (0%) 0 (0%)

Once a month 0 (0%) 0 (0%)

N/A 13 (20.3%) 13 (20.3%)

Besides reporting the Use Behaviour of mobile technologies in learning and teaching EFL as part of the research model, participants were also asked to indicate how frequent they use their mobile devices for a list of common possible usages, and these frequencies are reported in Table 42 below.

Table 42:Use Behaviour of Mobile Technologies in General

Usage

Frequency No. (%)

Very

Frequently Frequently Occasionally Rarely Never

Students Survey

Phone calls 348 (40%) 359 (41.3%) 109 (12.5%) 30 (3.4%) 24 (2.8%)

Video-conversation 57 (6.6%) 64 (7.4%) 204 (23.4%) 269 (30.9%) 276 (31.7%)

Sending & receiving text

messages 203 (23.3%) 193 (22.2%) 280 (32.2%) 150 (17.2%) 44 (5.1%)

Accessing the internet 401 (46.1%) 254 (29.2%) 100 (11.5%) 53 (6.1%) 62 (7.1%)

Sending & receiving e-mails 188 (21.6%) 145 (16.7%) 245 (28.2%) 147 (16.9%) 145 (16.7%)

Scheduling appointments 88 (10.1%) 86 (9.9%) 206 (23.7%) 207 (23.8%) 283 (32.5%)

Banking 79 (9.1%) 90 (10.3%) 186 (21.4%) 167 (19.2%) 348 (40%)

Playing non-academic games 153 (17.6%) 139 (16%) 195 (22.4%) 188 (21.6%) 195 (22.4%)

Reading or editing documents 74 (8.5%) 84 (9.7%) 198 (22.8%) 200 (23%) 314 (36.1%)

Faculty Survey

Phone calls 43 (67.2%) 13 (20.3%) 3 (4.7%) 4 (6.3%) 1 (1.6%)

Video-conversation 7 (10.9%) 14 (21.9%) 12 (18.8%) 14 (21.9%) 17 (26.6%)

Sending & receiving text

messages 31 (48.4%) 15 (23.4%) 9 (14.1%) 9 (14.1%) 0 (0%)

Accessing the internet 39 (60.9%) 13 (20.3%) 8 (12.5%) 4 (6.3%) 0 (0%)

Sending & receiving e-mails 40 (62.5%) 14 (21.9%) 6 (9.4%) 2 (3.1%) 2 (3.1%)

Scheduling appointments 8 (12.5%) 12 (18.8%) 16 (25%) 17 (26.6%) 11 (17.2%)

Banking 4 (6.3%) 20 (31.3%) 11 (17.2%) 15 (23.4%) 14 (21.9%)

Playing non-academic games 1 (1.6%) 8 (12.5%) 18 (28.1%) 14 (21.9%) 23 (35.9%)

Reading or editing documents 6 (9.4%) 16 (25%) 16 (25%) 17 (26.6%) 9 (14%)

*Higher score has been highlighted.

Table 42 reveals the general usage frequency of mobile technologies among students and instructors, and points to some interesting differences between the groups. 40% of students use mobile devices very frequently for phone calls and 46.1% used them very frequently for accessing the internet. However, these figures were lower than those reported for the comparable group of staff. 67% of staff used mobile devices very frequently to make phone calls, and 60.9% used them frequently to access the internet. Not surprisingly, perhaps, a considerable proportion (17.6%) of students used mobile technologies to very frequently play non-academic games, the comparable figure for staff was 1.6%. Conversely, a larger proportion of the staff reported using mobile technologies very frequently for sending and receiving text messages (48.4%) and e-mails (62.5%), than

students, for which the comparable figures were 23.3% and 21.6% respectively. Without further research, it is difficult to accurately interpret these results. However, it is possible that students no longer use e-mails or send text-messages via SMS, but rely more heavily on using Facebook or applications like WhatsApp (which is a cross-platform mobile messaging app which allows the exchange of messages without having to pay for SMS) to communicate with their friends and family.

Both students and instructors were provided with a list of services to tick if they were interested in having them on mobile devices (see Table 43). The three most requested services for students were Grades (86.25%), email (64.1%), and instant messaging with EFL staff and students (61.6%). These figures were similar to those of the staff, 87.5% of instructors chose University email as the most requested service on mobile devices, followed by instant messaging (78.1%) and reference materials (70.3%). It is perhaps, unusual to discover that nearly two-thirds of students and four-fifths of staff requested university official email to be made available on mobile devices, which may suggest that the university’s IT infrastructure is unable to supply this basic service. The remainder of the results are unsurprising, and reflect similar desires for both staff and students to make greater use of mobile devices to access academic related data and information.

Table 43:Descriptive Statistics for Required Services to be accessed on Mobile Devices

Service Frequency Percentage

Students Survey

Grades 750 86.2

University email 558 64.1

Instant messaging with EFL faculty or

students 536 61.6

Videos and audios of lectures 505 58

Admission and registration 491 56.4

Lecture slides 481 55.3

University library 439 50.5

Reference material, applications and links 383 44

Course content 362 41.6

Chat with Information Technology service 338 38.9

Course Management System 336 38.6

Educational games 306 35.2

Faculty Survey

University email 56 87.5

Instant messaging with EFL faculty or

students 50 78.1

Reference material, applications and links 45 70.3

Grades 43 67.2

Educational games 42 65.6

Course content 41 64.1

University library 40 62.5

Lecture slides 37 57.8

Videos and audio of lectures 35 54.7

Course Management System 35 54.7

Chat with Information Technology service 26 40.6

Admission and registration 24 37.5

4.8

Conclusion

This section presented the findings of the study generated by the statistical analyses of both; Students & Faculty surveys. A number of variables proved to be responsible factors for behavioural intention and use behaviour of mobile technologies in learning and teaching EFL among students and faculty. Comparing the findings of students’ survey to

those of the faculty revealed that the research model (UTAUT2) was strongly endorsed with respect to the students, with five significant factors contributing to the variance in behavioural intention and use behaviour of mobile technologies in EFL learning among students. On the other hand, only two factors contributing to the variance in behavioural intention and use behaviour of mobile technologies in EFL teaching among faculty. The impacts of some of those factors were moderated by experience or gender and in some cases by both.

In the next section, these findings are discussed in more detail and with reference to previous studies, and in the light of the objectives and purposes of the study.