Upper-Basic Schoolteachers’ Beliefs about Their Students’ Awareness of Digital Citizenship

Abstract

Students’ awareness of digital citizenship (DC) is a growing topic in educational technology. Teachers’ beliefs regarding this awareness are a primary factor to influence this awareness. The current research aimed to verify the level of upper-basic schoolteachers’ beliefs about their students’ awareness of DC. It also intended to verify whether this level is significantly different due to teachers’ gender, discipline, academic qualification, and experience. The present research followed random sampling and the sample for the present research consisted of 153 teachers. The teachers were upper-basic schoolteachers that teach Arabic language, mathematics, and technology. The data were collected using a DC questionnaire, while the analysis was done using statistical exams, specifically one-sample t-test, independent-sample t-test, and ANOVA. The research results indicated that the mean score of schoolteachers’ beliefs about their students’ awareness of Cyberbullying, Digital Privacy, and Digital Netiquette was significantly higher than the good DC beliefs score, while the mean score of schoolteachers’ beliefs about their students’ awareness of Digital Identity and Digital Footprint was significantly higher than the normal DC beliefs score. In addition, the results indicated no significant differences in teachers’ beliefs about the awareness of DC’s components due to gender, academic qualification, or years of experience. Moreover, there are no significant differences in teachers’ beliefs about students’ DC’s awareness due to the discipline, except for Digital Privacy.

1. Introduction

Electronic and digital learning has drawn researchers’ interest for three decades now. Researchers have focused on the different aspects of electronic and digital learning, specifically the cognitive aspect [1], the social aspect [2], the affective aspect [3], the behavioral aspect [4], and the meta-aspect [5]. The researchers’ interest in electronic and digital learning has resulted in their interest in the phenomenon of DC.

In addition to the above, DC has drawn researchers’ interest due to its influences on students’ attitudes, beliefs, and behavior in digital learning environments [6,7,8,9]. For example, Ribble [10] says that a digital citizen addresses the characteristics of understanding several cultural and social issues related to technology. These issues and practices are related to exhibiting a positive approach to technology’s use in supporting collaboration, building communities, and maintaining work and education norms. Though research on DC has been published for more than 15 years [11], DC research in schools is still in its beginnings, which points at the need for studies that investigate this field of research. The present study investigates two issues: The level of teachers’ beliefs about their students’ awareness of DC components and whether this level is influenced by background variables, specifically gender, discipline, academic qualification, and years of experience.

1.1. Theoretical Framework

We live in an era in which technological developments are accelerating, and the internet that serves social relations is undergoing one such development. This leads to the great attention that should be paid by educators in order to achieve their educational goals through paying attention to their students’ DC as protecting them from the risks that may be caused by misuse and lack of awareness of internet uses. This attention could benefit from the availability of different programs at schools aiming to support the students’ and teachers’ awareness of safe technological usage to protect themselves, their rights, and the materials they use. This falls under the umbrella of DC education in schools. This concept refers to the social responsibility of everyone about rules, standards, principles, ideas, and rights while using technological tools and applications [12]. Curran [13] introduces DC as the use of appropriate, evolving, and permanent technology while reserving the responsibility of the users. Therefore, a digital citizen should defend his right, all digital rights, for everyone to work with digital tools. In addition, according to Trust [14], the digital citizen should respect the privacy of users’ digital sources, treat those who communicate with them electronically with sympathy and respect, use critical thinking when using all internet resources, stay away from unreliable sources and not share them, support and develop the goals of social life using technology, maintain his and others’ mental, physical, and emotional health by using digital sources deliberately and for the benefit of others, appreciate and know that the digital world is evolving, so we have to keep pace with the modernity of digital development.

The internet serves the achieving of different goals, including obtaining information, generating content, and interacting. This is especially true in the last years with teachers’ need to lead educational practices in the classroom. This led to the advancement of the DC notion that researchers suggested includes different components. Ribble [15] introduced five essential elements of DC: Identity, Footprint, Cyberbullying, Privacy, and Netiquette.

First, the “Digital Identity”, or internet identity, is defined as a collective identity that the internet user determines in digital communities. It can also be defined as a representation that an individual builds for himself [16]. Digital Identity is investing in society and changing behavior by taking advantage of digital transformation and technical development to serve the user and prove his identity in a documented manner. Technological communication and these means can provide services more efficiently, support the administrative reform process, and constantly strive to achieve general user satisfaction and ensure the efficiency of the services provided. This era is a result of this tremendous development, and one of the principles of Digital Identity is to ensure its use anywhere and at any time, and the possibility of accessing all services in an elaborate manner through the use of modern advertising means, such as websites and mobile applications and the adaptation of electronic devices and the use of their features as tools to protect information security such as facial recognition.

Second, A “Digital Footprint” is a record of your activities online, including the websites visited during one’s online activity, emails sent during this activity, and information provided by the user or by others. Users can create their Digital Footprints actively or passively, allowing anyone to track their internet activities and devices, whereas Camacho et al. [17] talk about Digital Footprint as when a user intentionally shares information about himself or herself. A user’s active Digital Footprint becomes their inactive digital fingerprint if he or she logs on using a registered username or profile. When information about a user is collected without his or her knowledge, a passive digital fingerprint is created.

Third, “Cyberbullying” is when bullying happens through the application of digital tools. Engaging technology in education leads to an increase in the occurrence of Cyberbullying through social media applications. In a literature review authored by Martin et al. [18], they report that frequent internet and digital device use may expose children to Cyberbullying or other safety concerns. Parents and children need to be educated about online safety precautions, such as reporting inappropriate content and blocking strangers, in order to ensure digital safety. Parents should also have regular conversations with their children about digital usage and online interactions.

Fourth, Digital Privacy is the digital media users’ right to privacy [19]. Gülsoy [19] considers both the loss of control and intrusion as Digital Privacy components, where this concern of control and intrusion is associated with personal information related to users’ online activities. Leatham [20] says that past studies that addressed Digital Privacy point to the need for more research in this field and adds that when viewed in light of the vulnerability of children and adolescents, controlling access to personally identifiable information is an important issue.

Fifth, Digital Netiquette addresses the rules, whether formal or informal, that are relevant when engaging in online communication [21]. According to Kryder [22], when online disagreements arise, it is important to be both kind and critical. As far as Digital Netiquette was concerned, socioeconomic status and parental involvement were significantly related [23]. Similarly, Xing and Wang [12] found that teenagers who had more interaction with their parents demonstrated higher levels of Digital Netiquette.

1.2. Literature Review

Soler-Costa et al. [24], applying systemic review, found that the papers studied could be categorized into two categories. The first category is related to the accurate use of email, where the studies showed that this use is presented through guidelines. The second category is related to digital trends, such as Cyberbullying. In the educational context, the studies showed that university students lack a basic understanding of Netiquette. Here, when the guidelines are provided, the quality of students’ discussion improves.

Abdullatif and Gameil [25] found that undergraduate students had a low level of knowledge and expertise of DC, where a great part of the participants addressed DC through ethical practices. In addition, the authors found that the participants showed several concerns regarding security and safety related to digital resources, digital information accuracy, understanding laws and consequences associated with the use of internet resources, taking responsibility for inappropriate behavior, and restricting the time and duration of daily use of digital resources.

“Netiquette behavior” has the most negative social consequences associated with Cyberbullying. Akinsola et al. [26] examined the effect of Cyberbullying on social media platforms on Digital Netiquette and users’ privacy. The study results showed significant differences in Digital Netiquette and users’ privacy due to social media use. According to Dienlin and Trepte [27], despite stating that privacy concerns are important to them, people tend to disclose information in a manner that is incompatible with those concerns.

Li’s [28] study found that male students are more likely to engage in Cyberbullying than females. Kansu and Öksüz [29] found that among preservice classroom teachers, gender significantly influenced their DC levels. Arouri and Hamaidi [30] found that students’ perceptions of the employed Netiquette ways were not influenced by background variables, such as gender, specialization, or content level. Abdullatif and Gameil [25] found that the participants’ knowledge and skills of DC components varied significantly depending on their academic major. Choi et al. [31] found that the background variables (work experience, social networking use in the class, and self-efficacy in the use of internet) affected teachers’ beliefs about DC significantly.

2. Materials and Methods

The research methodology is quantitative and follows the descriptive method. Descriptive studies are conducted to address the current state of a statistical phenomenon.

2.1. Study Population and Sample

The sampling method was random. The population of the research is the upper-basic schoolteachers that teach Arabic language, mathematics, and technology in the West Bank in Palestine in the academic year (2021/2022). The questionnaire for the present research was distributed to 236 teachers. The upper-basic schoolteachers that teach Arabic language, mathematics, and technology were requested to participate in the research by filling out a Google form of the DC questionnaire. Researchers pointed to the advantages and disadvantages of online surveys and questionnaires. It has been found that respondents prefer to complete survey questionnaires online because they can answer at their own pace and at their convenience [32]. A paper-based survey is cumbersome to construct and may involve multiple question types and manual skip logic. With online surveys, however, video or audio clips can be included as well [33]. Researchers also pointed to the disadvantages of online questionnaires. Ball [33] said that a pitfall of online surveys is the accumulation of biased or non-representative responses since those without internet access cannot participate in them. Ball [33] also mentioned that in the case of a survey that respondents share with their friends and colleagues with similar interests and perspectives, some views may become overrepresented. In the present research, we tried to overcome the disadvantages of online questionnaires by not putting the questionnaire on social media sites. In addition, all the participants in our case have internet access. Moreover, we combined online and paper administration of the questionnaire so that the questionnaire reached different participants.

One hundred fifty-three teachers filled the Google form. Afterwards, an attempt was made to ask Arabic language, mathematics, and technology, who did not participate electronically, to fill out a paper form of the questionnaire. In this way, we got an additional 83 responses.

Table 1. Participants according to background variables.

Variable	Category	Frequency	Percentage
Gender	male	94	39.8
	female	142	60.2
Years of experience	less than 7 years old	65	27.5
	7–15 years old	93	39.4
	more than 15 years	78	33.1
Academic qualification	diploma	16	6.8
	Bachelor	157	66.5
	Master	59	25
	PhD	4	1.7
Discipline	Arabic language	109	46.2
	Math	95	40.3
	Technology	32	13.6

describes the participants’ frequency according to the background variables.

2.2. Data Collecting Tool

The questionnaire adopted here included two sections. The first section collected demographic information, specifically gender, academic qualification, and years of experience. The second part included DC items adopted from Martin et al. [21]. The questionnaire consisted of 24 items partitioned into five components. The first component is Cyberbullying and consists of 2 items (e.g., “my students know the importance of having a clue when someone claims he was bullied”). The second component is ‘Digital Netiquette’ and consists of 6 items (e.g., ‘My students know they need the permission of the person before putting the person’s photo online’). The third component is the Digital Footprint component and consists of 4 items (e.g., ‘I believe my students are aware that they are legally responsible for their posts online’). The fourth component is Digital Privacy and consists of 8 items (e.g., ‘my students know how to create a password for their online account that is difficult for others to guess’). The last component of DC is a Digital Identity and consists of 4 items (e.g., my students know that their online activities can also impact their face-to-face identity’). The scale is a 5-point Likert-type scale: (1): “I strongly disagree”, (2): “I disagree”, (3): “Neutral”, (4): “I agree”, (5): “I strongly agree”. Item 6 in the digital internet component and item 4 in the Digital Footprint component were inversely stated.

2.3. Instrument Validity and Reliability

After translating questionnaire items from English to Arabic language, the instrument was assessed by 6 expert teachers, two of each of the disciplines in the upper-stage: Arabic language, mathematics, and technology, to take their opinions regarding the clarity of the questionnaire items. As a result of their suggestions, changes were made to clarify some items.

For each component of the scale, Cronbach’s alpha reliability coefficients were calculated. The reliability coefficient for the total scale was found to be 0.893, while it was 0.798, 0.814, 0.809, 0.881, and 0.755 for the Digital Identity, Digital Footprint, Cyberbullying, Digital Privacy, and Digital Netiquette, respectively. Thus, the scale is reliable as Cronbach’s alpha reliability coefficients are higher than the value (0.70) [34,35].

2.4. Statistical Assumptions

The test for data normality was not performed as the number of respondents, which is 236, exceeded 30 or 40 [36]. In the case of the present number of participants, the normality assumption’s violation would not lead to major complications in handling the parametric tests [37].

The homogeneity of variance test resulted in insignificant Levene’s statistics for each of the background variables, which proved that the scores of teachers’ beliefs are homogenous for each of these variables [37].

The outliers’ assumption was tested using boxplots [38], which showed some upper and lower outliers. No extreme outliers were detected, so we did not remove observations.

2.5. Data Analysis

SPSS 26.00 was used to perform the statistical exams. To examine the level of DC beliefs, the mean score of each component was compared with critical scores: The “good DC beliefs score” and the “normal DC beliefs score.” The good DC beliefs score was computed by dividing 4 (4 units between 1, the smallest score given for any item, and 5, the greatest score given for the item) by 5 that represented 5 levels, getting 0.80. Thus, we obtained the points related to the DC beliefs intervals presented in Figure 1. The two middle points (2.6 and 3.4) represented the “normal DC beliefs score” and the “good DC beliefs score” respectively. Moreover, the point 4.2 represented the “very good DC beliefs score.” Our use of these critical scores and the associated one sample t-test follows other educational studies [39].

The scores of teachers’ DC beliefs were homogenous across the research sample partitioned according to the background variables. The independent sample t-test was carried out to find out whether the differences in teachers’ DC beliefs due to gender and due to the academic qualification variable were significant. Moreover, the ANOVA test was carried out to find out whether the difference in teachers’ DC beliefs due to years of experience was significant.

3. Results

3.1. The Level of Upper-Basic School Teachers’ Beliefs about Their Students’ Awareness of DC

The first question investigated the level of upper-basic schoolteachers’ beliefs about their students’ awareness of DC. The investigation was done by carrying out a one-sample t-test, which enabled the comparison of the mean score of the DC component with the normal level (2.6) and the good level (3.4).

Table 2. The level of upper-basic schoolteachers’ beliefs about students’ awareness of DC.

	N	Mean	SD	T2.6	p	t3.4	p
Cyberbullying	236	3.84	0.65	29.06	0.000	10.26	0.000
Digital Privacy	236	3.54	0.66	21.87	0.000	3.32	0.001
Digital Identity	236	3.30	0.75	14.48	0.000	−2.02	0.044
Digital Netiquette	236	3.63	0.56	28.22	0.000	6.21	0.000
Digital Footprint	236	3.05	0.57	12.24	0.000	−9.38	0.000

gives the outcome of the computations.

Table 2 shows that the mean score of schoolteachers’ beliefs about their students’ awareness of Cyberbullying, Digital Privacy, and Digital Netiquette was significantly more than the good DC beliefs score (p < 0.05), while the mean score of schoolteachers’ beliefs about their students’ awareness of Digital Identity and Digital Footprint is significantly more than the normal DC beliefs score (p < 0.05).

3.2. Differences According to Background Variables

The second research question verified whether there was significant difference in upper-basic schoolteachers’ beliefs about their students’ awareness of DC due to gender, discipline, academic qualifications, and years of experience.

3.2.1. Differences According to Gender

The independent-sample t-test was used to verify the difference in the participating teachers’ beliefs about their students’ awareness of DC due to gender.

Table 3. Means, standard deviations and independent-sample t-test of the DC according to gender (N = 94 for males and N = 142 for females).

	Gender	Mean	SD	t	p
Cyberbullying	male	3.86	0.68	0.372	0.710
	female	3.82	0.64
Digital Privacy	male	3.48	0.65	−1.112	0.267
	female	3.58	0.67
Digital Identity	male	3.26	0.74	−0.647	0.518
	female	3.33	0.75
Digital Netiquette	male	3.65	0.54	0.440	0.660
	female	3.61	0.57
Digital Footprint	male	3.07	0.54	0.414	0.680
	female	3.04	0.59

describes the results of the computations.

The results indicate that there are no statistically significant differences between males and females in their beliefs about their students’ awareness of the components of DC.

3.2.2. Differences According to Discipline

The one-way ANOVA test was used to investigate the significance of the differences in the average ranks of teachers’ beliefs about their students’ awareness of DC according to the discipline.

Table 4. Means, standard deviations and F values for the five DC components according to discipline.

		N	Mean	SD	F	p
Cyberbullying	Arabic language	109	3.89	0.66	0.69	0.504
	Math	95	3.78	0.67
	Technology	32	3.81	0.56
Digital Privacy	Arabic language	109	3.62	0.629
	Math	95	3.41	0.67	3.328	0.038
	Technology	32	3.69	0.70
Digital Identity	Arabic language	109	3.39	0.72
	Math	95	3.17	0.82	2.609	0.076
	Technology	32	3.41	0.53
Digital Netiquette	Arabic language	109	3.64	0.59
	Math	95	3.61	0.52	0.108	0.897
	Technology	32	3.65	0.56
Digital Footprint	Arabic language	109	3.06	0.59
	Math	95	3.02	0.55	0.440	0.644
	Technology	32	3.13	0.57

shows the results of the computations.

Table 4 indicates no significant differences in teachers’ beliefs about their students’ awareness of DC due to the discipline, except for Digital Privacy (F = 3.33, p = 0.04). We carried out LSD post-hoc analysis of electronic privacy to verify the pairwise differences.

Table 5. Pairwise comparisons between teachers’ beliefs about their students’ awareness of Digital Privacy according to the discipline.

Discipline	Discipline	Mean Difference	p
Mathematics	Technology	−0.28	0.04
Mathematics	Arabic language	−0.20	0.03
Technology	Arabic language	0.07	0.58

shows the pairwise comparisons.

Table 5 shows that there were significant differences in teachers’ beliefs about their students’ Digital Privacy in favor of technology and Arabic language teachers, between mathematics teachers and technology teachers, as well as between mathematics teachers and Arabic language teachers.

3.2.3. Differences According to Academic Qualification

The independent sample t-test was used to verify the difference in the participating teachers’ beliefs about their students’ awareness of DC due to academic qualification.

Table 6. Means, standard deviations, and t values of the five DC domains according to academic qualification (N = 157 for Bachelor, and 59 for Master).

	Qualification	N	Mean	SD	t	p
Cyberbullying	Bachelor	157	3.81	0.62	−0.93	0.36
	master	59	3.90	0.74
Digital Privacy	Bachelor	157	3.52	0.65	0.15	0.88
	master	59	3.51	0.73
Digital Identity	Bachelor	157	3.26	0.72	−0.497	0.620
	master	59	3.32	0.81
Digital Netiquette	Bachelor	157	3.62	0.55	0.421	0.674
	master	59	3.59	0.59
Digital Footprint	Bachelor	157	2.99	0.56	−1.34	0.18
	master	59	3.11	0.57

shows the computations.

Table 6 shows that there were no statistically significant differences in the participating teachers’ beliefs about their students’ awareness of DC components due to academic qualification.

3.2.4. Differences According to Years of Experience

The one-way ANOVA test was used to investigate the significance of the differences in the participating teachers’ beliefs about their students’ awareness of DC due to years of experience. The results are shown in

Table 7. Means, standard deviations, and F values of the five DC domains according to years of experience.

		N	Mean	SD	F	p
Cyberbullying	less than 7 years old	65	3.8846	0.59140	0.26	0.77
	7–15 years old	93	3.8280	0.61897
	more than 15 years	78	3.8077	0.74394
Digital Privacy	less than 7 years old	65	3.4942	0.63601	0.51	0.60
	7–15 years old	93	3.5954	0.67702
	more than 15 years	78	3.5208	0.66980
Digital Identity	less than 7 years old	65	3.3115	0.75134	0.02	0.98
	7–15 years old	93	3.2903	0.69479
	more than 15 years	78	3.3077	0.80373
Digital Footprint	less than 7 years old	65	3.6359	0.54318	0.08	0.92
	7–15 years old	93	3.6075	0.50936
	more than 15 years	78	3.6389	0.62903
Digital Netiquette	less than 7 years old	65	3.0000	0.57791	0.395	0.67
	7–15 years old	93	3.0780	0.54296
	more than 15 years	78	3.0673	0.59445

.

Table 7 shows no significant differences in the participating teachers’ beliefs about their students’ awareness of DC components due to years of experience.

4. Discussion and Conclusions

Digital learning is flourishing in schools and universities [40,41,42], where the DC of students is an important aspect of this learning. The current study aimed to verify teachers’ beliefs about their students’ awareness of DC components. The research results indicated that the level of part of the components (Digital Identity and Digital Footprint) was normal, while the level of the rest (Cyberbullying, Digital Privacy, and Digital Netiquette) was good. This indicates that the participating teachers consider part of the DC components as being aware of more than other components.

The research results could be explained by the fact that students are expected to be more aware of Cyberbullying, Digital Privacy, and Digital Netiquette. The awareness of Cyberbullying is in line with researchers’ emphasis that the use of social networking sites has recently led to an increase in awareness worldwide of Cyberbullying among young people (e.g., [43]). This is also in line Molluzzo and Lawler [44], who found that college students were aware of incidents and acts of Cyberbullying. The results on Digital Privacy are not in line with Das [45], who found that after finishing a task, 75.5% of participants fail to log off their accounts. In addition, Das [45] found that a strong password and password manager is not used by over half of the participants (53%). The results of the present research regarding Digital Netiquette are also not in line with part of the previous studies, which found that university students lack a basic understanding of Netiquette [24].

The results indicate that there are no statistically significant differences in teachers’ beliefs about students’ awareness of the components of DC between males and females. This agrees with past research that showed no significant differences in students’ perceptions or behavior regarding DC components. For example, Arouri and Hamaidi [30] found that students’ perceptions of the employed Netiquette procedures were not influenced by background variables such as gender, specialization, or study level.

The results indicate that there are significant differences in teachers’ beliefs about their students’ Digital Privacy, in favor of technology and Arabic language teachers, between mathematics teachers and technology teachers, as well as between mathematics teachers and Arabic language teachers. One reason why mathematics teachers’ beliefs regarding their students’ awareness of privacy are less than Arabic and technology teachers could be related to the teachers’ focus on some components of mathematics education more than on all the components of DC, where problem-solving and reasoning are most important to them. It is also possible that they believe that, for their students, other aspects of DC are more important than Digital Privacy. Further research, especially qualitative one, is needed in this field to verify the reasons behind teachers’ beliefs, especially mathematics teachers’ beliefs, regarding their students’ awareness of DC components.

The results indicate no significant differences in the participating teachers’ beliefs about their students’ awareness of DC due academic qualification as well as due to years of experience. The previous results do not agree with studies showing that background variables influence teachers’ and students’ perceptions and behaviors regarding DC. For example, Abdullatif and Gameil [25] found that students in different academic majors possessed varying levels of knowledge and practice of DC components. In addition, Choi et al. [31] found that teachers’ perceptions of DC were significantly affected by their years of work experience, use of social media sites for teaching, and internet self-efficacy.

5. Limitations and Recommendations

One limitation of the present research is that it was performed in a developing country. Future research should verify the issues studied in the present study in developed countries, for example, whether teachers’ beliefs about their students’ awareness of DC are significantly different due to their gender. This gender issue is important since it is expected that the gender issue affects outcomes in the different life aspects in developing countries, including teaching and learning [46].

The present research used only quantitative methodology. Future research could use qualitative methodology to show the processes that enrich students’ digital citizenship. One such research could involve interviews with teachers about their experiences concerning the processes that lead to the enrichment of students’ digital citizenship.

No component’s mean score was at the ‘very good’ level, so one recommendation of the present research is to hold workshops on DC and its components to discuss the importance of leading the students into more awareness of this issue. This recommendation is supported by researchers’ findings that teachers’ beliefs about their students’ awareness of DC are low [ex., 21], which points to the need for workshops that address students’ DC and how to strengthen it. The results are also in line with studies that found the DC’s components are influenced by participating in specific educational contexts. Lorenz et al. [47] found that in open learning contexts, students’ awareness of privacy correlates with their willingness to share and participate. The previous results show that workshops should address the educational context that cultivates students’ DC.

The present research findings should be taken in context and with limitations, where it addressed teachers’ beliefs about students’ awareness, while other studies addressed students’ behavior. More studies are needed regarding teachers’ beliefs about their students’ awareness of DC. These studies could be quantitative as well as qualitative. Future studies are needed to verify the relationship between educational technology constructs and DC. One such construct is internet literacy as part of human rights literacy [48].