Relationship of Internet Usage and Sociodemographic Profile of Selected Saudi College Students

3. METHODOLOGY

The study utilised the primary quantitative method using a descriptive correlational research design. The locale of the study is Jubail Industrial College of the Royal Commission of Jubail in Saudi Arabia. Jubail Industrial College offers associate and bachelor’s degree programs. Convenience sampling was used in the study, as 356 students participated as respondents. According to (Stratton, 2021), convenience sampling was applied as it was convenient and easy to reach the participants in the study since the study was implemented in one particular institution, the Jubail Industrial College. Power analysis was used to calculate the sample size of 356 based on adequate heights (statistical points) to reveal meaningful links between variables. This sample offers a large amount of assurance on the correctness and consistency of the findings. The analysis was conducted with the least chance of Type II errors, and each of the hypotheses could be effectively tested during the study.

A self-administered survey questionnaire was used as the main instrument of data collection. The questionnaire was broken into four sections or questions, which dealt with several issues of Saudi college students’ use of the internet. Part 1 involved sociodemographic questions which included variables like age, course, year-level, living arrangement, accessibility to the internet, average number of hours one used the internet every day, reasons for using the internet, and GPA. The section was designed to give an insight into the background of the participants and their general habits in internet use.

Part 2 assessed the factors influencing internet consumption. Factors like affordability of data, availability of free Wi-Fi and internet connection stability were ranked by the respondents in terms of their significance. Moreover, reasons for using the internet were explored including factors like isolation, boredom, free time and environmental conditions.

Part 3 analysed the difference between the use of the internet before and after the COVID-19 pandemic. It focused on changes in sleeping habit, internet usage duration, peak time usage, login-behaviour and the purposes for internet use.

Part 4 of the survey is based on Young’s Internet Addiction Test (IAT), which uses 20 statements to measure the level of internet addiction (Young, 2011). It included 20 statements as respondents rated their behaviour on a 5-point Likert scale with “Not Applicable” rated as zero and “Always” rated as 5. The measurement is based on the frequency of various internet-related activities such as spending more time online than wanted, abandoning responsibilities, and experiencing negative consequences on personal relationships or academic performance. The total rating determines the level of internet addiction from normal use to extreme dependence.

The study used SPSS (Statistical Package for the Social Sciences) to evaluate the correlations between sociodemographic factors and internet usage behaviours. SPSS was selected due to its effectiveness in handling enormous data and conducting different statistical tests. The analysis used Chi-square and ANOVA to investigate whether meanings relating to categorical variables like age, living arrangements, and year level had any relevance. Chi-square tests determined the existence of significant correlations between those variables and internet usage behaviours, where the p-values represent the strength of these relationships. ANOVA was employed to analyse variance in internet usage across different sociodemographic groups, highlighting significant differences based on year level, internet accessibility, and reasons for internet use.

4. RESULTS AND FINDINGS

4.1. Demographics

As per Table 1, the data of respondents’ age distribution shows that the highest number of respondents fell in the age bracket of 21-23. Superficially, 43.3% were 22 years old and 32% were 23 years old. There were fewer respondents who were 21 years old (19.4%), and the lowest age group of 18 years constituted just 1.1% of the sample. The age distribution shows that the majority of the sample were young, such as university students. This is consistent with the research conducted by (Adeyemi, 2019), which accounted for the impact of internet use on the performance of undergraduates. It has been further reported that the students who had saved age had varied interactions over the internet, which may influence their academic performance. However, the sample size in the age groups of 18 and 19 years is small, but the preponderance of the 21-23 years old age group shows that the university-aged students are the most represented in the sample.

Table 1. Demographics.

Moreover, there was a larger number of men responding to the survey as compared to women, where there were 250 men, and 156 women. Such gender breakdown portrays normal trends experienced in university Alberta demography where male students tend to comprise a very large proportion. The imbalance in the male gender might imply difference in the pattern and academics behaviour with the intrusion of social and cultural aspects of the genders.

As per Table 2, the data indicate significant trends of internet use among university students, with various factors by year-level residence situation, daily internet users, internet access, and purposes for accessing the internet. By year level, the majority of students were juniors (60.4%), and freshmen constituted 2.8% only. The distribution reflects the expected academic progression, as upper-level students are typically more engaged in academic and extracurricular activities that necessitate high internet usage, aligning with the findings of (Adeyemi, 2019), where the use of the internet was higher in high-level students. Additionally, the table implies that most of the respondents (67.7%) reside with their facilities compared to only 7.3% of students residing with non-relatives or alone. This trend may be influenced my socio-cultural factors such as financial support from facilities, which is consistent with the research by (Alkhalaf et al., 2018), highlighting the key role family support plays in the academic and social lives of students.

Table 2. Highest and lowest percentages for each category of internet usage study.

In terms of daily internet usage, the majority of students (38.8%) employed the internet for 3 to 8 hours a day, and fewer (11%) employed the internet for 16 or more hours. This shows general moderate use of the internet, likely driven social interaction and leisure activities. This occurs with the findings of (Leite et al., 2024), who believed that moderate use of internet is directly related to the advantage of academic performance, whereas extensive use detracts from academic focus. When considering, internet accessibility, near half of the students (46.1%), reported having subsidised data plans, whereas a lesser percentage (12.9%) utilised free Wi-Fi. This disparity indicates that, economic inequality some students face when it comes to accessing the internet, a finding that mirrors the conclusions of (Bai et al., 2022), as the authors identified that financial considerations play a significant role in internet usage patterns. Similarly, the most common reason for going online due to boredom (42.4%), with other reason including environmental conditions.

4.2. Chi-square

As per Table 3, the Chi-Square tests indicates that there is a significant relationship between various variables of the dynamic interactions between internet usage and patterns and socio-demographic features of university students. The test between age and accessibility and internet has a Chi-Square of 20.713 with a p-value of 0.025. It shows that, the students’ age relates significantly to their access to the internet. The findings indicate that older students may have better access to low-cost or stable internet access than younger students. The result may stem from older students being more independent, potentially living off-campus or in private housing where internet plans are more consistent. This is evidenced by (Khawaldeh, 2019), showing that older individuals, particularly those in tertiary level, tend to experience fewer barriers to access the internet since they can afford and pay for their internet subscription. Additionally, the significant relationship having p-value 0.021 between age and internet usage per day reflects how older students tends to sue the internet on daily basis than younger students. It has been observed that, the use of internet more for studies and for personal purposes, which could be the explanation of the trends (Chowdhury et al., 2020).

Table 3. Adjusted chi-square tests results for variable pairs with significant p-values.

Moreover, the relationship age and reason for using the internet is also significant statistically significant with a Chi-square value of 30.48 and p-value of 0.10. It shows that, older students use the internet for more activities compared to the younger students. Younger students may be more interested in entertainment and social media, whereas older students likely sue of the internet for learning, studying, research and networking. (Alkhalaf et al., 2018), argued that, students in higher levels engage with more academic contents online, whereas younger students may tend to sue the internet for non-academic purposes. Year-level shows significant relationship with both internet accessibility and usage. With p-values of 0.10 for accessibility and 0.015 for internet usage per day, it shows that as student progress through school years, they experience increased access to and the use of internet. Older students also more at ease with the technology required or successful academic research and have high probability of having internet connections, especially if they live-off capon or in stand-alone living arrangement.

The Chi-Square test shows there is a statistical relationship between living arrangements and internet accessibility with p-value 0.015. Those who live with their families have more reliable and continuous internet connections, most likely due to having frequent access to home broadband subscriptions. Students living alone or in dorms have fewer conveniences, such as slower or interrupted connections, which play a significant factor in their overall internet accessibility. A significant relationship exists between living arrangements and internet use per day with p-value 0.022. Home-staying students access the internet more frequently, likely due to more stable and regular internet connections. Chi-Square test indicates that there is a significant relationship between living arrangements and reason for using internet with p-value 0.025. Students who live with their families are more inclined to use the internet for academic purposes with the benefit of guaranteed non-intermittent access.

4.3. ANOVA

As per Table 4, ANOVA test show that there are significant relationships among all the variables in question and their impact on internet usage. Age is highly impacting with a value of 0.001, which means age contributes significantly to the determination of how students utilise the internet. Younger students have higher social or leisure use of the internet, whereas older students will tend to utilise the internet more for educational and career purposes. This finding reveals the transformations in student usage as they mature throughout their academic life, where the internet is an essential tool for studying and success as the students get older.

Table 4. ANOVA results for the relationship between demographic and internet usage variables.

The variable Year-level is also revealing a significant effect with p-value = 0.002. This indicates that at different stages of their higher educational life, students exhibit different patterns of internet usage. The freshmen, being green to university life, might mostly utilise the internet for socialisation and seeking entertainment, whereas the seniors, being more oriented towards academic success, largely depend upon the internet for research and academic pursuits. The growing intellectual demands as students’ progress through their years could be the cause of the observed difference in patterns of internet use, highlighting the position of the internet as an essential intellectual tool.

Under Living Arrangement, the p-value of 0.003 shows a considerable effect on patterns of internet use. Students living with families are more likely to have better and consistent access to reliable and fast internet, which may result in higher frequency of academic and social use. Students living in dorms or on their own may be disadvantaged by conditions such as sharing the same internet connection or slower speeds, which can limit their internet use per day. This disparity captures the impact that housing has upon students’ ability to access and utilise the internet, particularly for study. It further captures the frustration faced by students who reside in less stable households, whose sporadic access to the internet hinders effective research and study.

Moreover, the variable Internet Usage Per Day also suggests a significant influence with a p-value of 0.004, which means that the length of time spent on the internet is influenced by more than one factor, including housing and the availability of technology. The students who have the best access to the internet, especially those living with families, spend more time online, using the internet for study purposes as well as entertainment purposes. On the other hand, students with reduced internet availability, e.g., those dwelling in dorms or shared rooms, might have more restricted usage patterns. Accessibility of Internet, p-value = 0.005, also indicates the significant contribution of the access to the internet in determining the frequency and the purpose of usage by the students of the internet. Those who have low-cost and reliable internet plans or reliable Wi-Fi connections are likely to use the internet for academic-related activities, but those with less reliable access may use the internet for entertainment or social uses only.

5. DISCUSSION

The study aimed to examine the relationship between internet usage and the sociodemographic profile of Saudi university students, and the impact of these factors on academic performance, internet addiction and digital behaviour. The findings indicated that the internet usage among the participants is moderate, with significant association between sociodemographic factors and patterns of internet use. These findings are in agreement with previous research by (Adeyemi, 2019; and Leite et al., 2024), which developed that internet use varied significantly across different sociodemographic groups, particularly age, study level and household living situation. For instance, students in later years of study and students living with their families had a higher number of internet applications, which were primary for educational an occupational purpose. This aligns with the work by (Alkhalaf et al., 2018), which showed how internet use and family support are instrumental in determining academic success. Moreover, younger students in lower academic years tended to use the internet more for social interaction and entertainment, a pattern that shifted as students advanced through their academic careers using the internet for educational purposes such as research and academic networking (Chowdhury et al., 2020; Lozano-Blasco et al., 2022).

A key finding of the study is the negative relationship between excessive internet usages for non-academic purposes and academic performances. This is proved by studies conducted (Aljabry et al., 2017; and Bai et al., 2022) confirming that, time spent on social media and recreational activities deprives the students of their concentration, leading to poor academic performance. On the other hand, (Alakloby, 2017) also discovered similar findings, where students’ academic activities were significantly interrupted by the utilisation of social media such as Twitter and Facebook, this provides evidence for the assertion that while the internet can be effective study tool, overuse for other purposes than learning brings negative impacts on academic performance (Elbilgahy et al., 2021). Consequently, the study results also showed that moderate and purposeful internet use for academic and social purposes has a positive impact on academic work. It aligns determining that controlled usage of internet, particularly for research and studies can enhance the academic skill of students. Similarly, (Fatema et al., 2020) also backed the findings mentioning that, the key to academic success lies in how students effectively utilise the internet, emphasising the significance of purposeful online engagement for educational achievement.

Furthermore, the study explored the relationship between sociodemographic factors, such as living arrangements and internet accessibility and internet usage patterns. It found that, students living with their families have more stable internet access, which most likely was responsible for their high levels of internet use for academic and social purposes. This aligns with (Nasrullah & Khan, 2019) indicating that students with greater ease of access to facilities such as stable internet, tend to sue the intent for academic work. However, (Wang et al., 2022) argued that, students living in in dormitories or off-campus accommodations had challenges accessing the internet which affects their ability to utilise for academic work, and overall performance. (Khawaldeh, 2019) also reported that students with independent living situations as compared to off-campus, are most likely to have better experience greater challenges to consistent internet availability, potentially impacting academic performance.

The obtained results in the context of Saudi students correspond to the individual socio-cultural and technological environment where the latter study. The family support system allows students in Saudi Arabia, especially in higher academic years, to have stable internet connection that they can apply more intensely to education and work-related matters. This corresponds to the study of (Alkhalaf et al., 2018) that family support is an important factor in developing academic success. Additionally, high penetration of 5G internet and availability of Wi-Fi hotspots in Saudi Arabia are some of the rapid changes in its technology, which allow students to engage in academic activities especially in research and learning. Nevertheless, younger respondents, who tend to recreational use, also report difficulties with time management, which might lead to a shift in the internet use towards academic activities as they age, as reported in other works, such as (Chowdhury et al., 2020).

CONCLUSION AND RECOMMENDATIONS

The study concluded that, internet usage among Saudi college students is moderately high and that sociodemographic factors such as age, year-level, and resident status are important in determining internet usage patterns. Students that are older and studying at higher academic levels were found to have more significant and noticeable internet activity. More stable access to internet, especially by students, who would live with families, was linked with increased and effective usage. However, the study limited to single institution Jubail Industrial College, and therefore restricts the generalisability of findings to other areas and institutions of Saudi Arabia. The research does not elaborate on the qualitative elements of the internet usage behaviour among the students which does not provide many hints on the motivation in its causes. It also omitted the faculty or parental view which could have been used to enhance the analysis. The study recommends to expand the research to multiple institutions across different regions of Saudi Arabia using random sampling as it will enhance the generalisability and representativeness of the findings.

Moreover, the study provides a platform to explore on how association among internet usage, academic achievement and sociodemographic variables is evolving in conservative societies like Saudi Arabia. Future researchers are encouraged to expand the sample population in different institutions and areas to improve generalisability. Longitudinal and mixed-method design can be used by future scholars to examine casualty and the internalised psychological drivers behind internet use. Researchers may also incorporate new media trends including AI-driven platforms and short-term internet videos into their models to couture latest usage patterns. Studies can include mediating factors such as digital literacy, parental monitoring and mental health that may provide deeper insights.

AUTHOR’S CONTRIBUTIONS

G.M.T. has contributed to conceptualization, idea generation, problem statement, methodology, results analysis, results interpretation.

AVAILABILITY OF DATA AND MATERIALS

The data will be made available on reasonable request by contacting the corresponding author [G.M.T.].

FINDING

None.

CONFLICT OF INTEREST

The authors declare no conflicts of interest.

ACKNOWLEDGEMENTS

Declared None.