UNIVERZA V LJUBLJANI FAKULTETA ZA DRUŽBENE VEDE
Internet skills among different groups of proxy internet users:
comparison between Slovenia and the United Kingdom Internetne veščine med različnimi skupinami posrednih uporabnikov interneta: primerjava med Slovenijo in Veliko
Britanijo Diplomsko delo
UNIVERZA V LJUBLJANI FAKULTETA ZA DRUŽBENE VEDE
Mentorica: doc. dr. Darja Grošelj Somentorica: prof. dr. Bianca C. Reisdorf
Internet skills among different groups of proxy internet users:
comparison between Slovenia and the United Kingdom Internetne veščine med različnimi skupinami posrednih uporabnikov interneta: primerjava med Slovenijo in Veliko
Britanijo Diplomsko delo
Zahvala doc. dr. Darji Grošelj, za vse nasvete, strokovno svetovanje in čas, ki mi ga je posvetila pri pisanju diplomskega dela.
Zahvaljujem se tudi družini in prijateljem za pomoč in spodbudo med študijem.
Internetne veščine med različnimi skupinami posrednih uporabnikov interneta:
primerjava med Slovenijo in Veliko Britanijo
Kljub vse večji razširjenosti internetnih tehnologij in spletnih storitev se še vedno soočamo z neenakomerno porazdelitvijo internetnih veščin med različnimi skupinami posameznikov.
Nekateri posamezniki poskušajo nadoknaditi lastno pomanjkanje internetnih veščin s posredno rabo interneta, ko prosijo nekoga drugega, da v njihovem imenu izvede dejavnost na spletu. V diplomskem delu smo primerjali internetne veščine med štirimi skupinami uporabnikov interneta, ki na različne načine sodelujejo v posredni rabi interneta (internetni posredniki in posredni uporabniki; samo internetni posredniki; samo posredni uporabniki; ne sodelujejo v posredni rabi). Te skupine smo primerjali med internetnimi uporabniki v Sloveniji in v Veliki Britaniji. V empirični študiji smo analizirali podatke ankete Slovensko javno mnenje (2018) in ankete Dostop in uporaba interneta (2019). Rezultati kažejo, da imajo uporabniki interneta, ki sodelujejo v posredni rabi interneta kot ponudniki ali prejemniki, različne ravni internetnih veščin. Medtem ko imajo ponudniki posredne rabe višje ravni internetnih veščin, imajo prejemniki posredne rabe nižje ravni internetnih veščin. To se je pokazalo tako pri uporabnikih interneta v Sloveniji kot tudi med uporabniki interneta v Veliki Britaniji. Ugotovili smo tudi, da obstajajo opazne razlike v stopnjah internetnih veščin med slovenskimi in britanskimi uporabniki interneta glede na njihov način sodelovanja v posredni rabi interneta.
Ključne besede: posredna raba interneta, internetne veščine, Slovenija, Velika Britanija, digitalne neenakosti.
Internet skills among different groups of proxy internet users: comparison between Slovenia and the United Kingdom
Despite the growing ubiquity of internet technologies and online services, we still face an unequal distribution of internet skills among different groups of individuals. Some individuals try to compensate for their own lack of internet skills through proxy internet use (PIU), where they ask someone else to perform an online activity on their behalf. In this thesis, we compared internet skills of four groups of internet users engaged in proxy internet use (as both proxy users and users-by-proxy, only proxy users, only users-by-proxy, or not engaged). We have compared these groups among Slovenian and the British internet users. In the empirical study, we analysed data from the Slovenian Public Opinion Survey (2018) and the Internet Access and Use survey (2019). The results show that internet users who are involved in PIU as providers or receivers have different levels of internet skills. In particular, those who are providing PIU have higher levels of internet skills while receivers of PIU have lower levels of internet skills. This has been shown among internet users in Slovenia as well as internet users in the UK. We also found that there are noticeable differences in levels of internet skills between Slovenian and UK internet users considering their involvement in proxy internet use.
Key words: proxy internet use, internet skills, Slovenia, United Kingdom, digital inequality.
1 Introduction ... 7
2 Proxy internet use ... 10
2.1 Factors and characteristics of users-by-proxy ... 12
2.2 Factors and characteristics of proxy users... 13
3 Internet skills ... 16
3.1 Forms and typology of internet skills ... 17
3.2 Studies of internet skills in Slovenia and the United Kingdom ... 20
4 Research Framework ... 23
5 Empirical study ... 24
5.1 Data ... 24
5.2 Sample ... 24
5.3 Measurement instruments ... 26
5.3.1 Internet skills ... 26
5.3.2 Proxy internet use ... 27
5.3.3 Demographics ... 28
6 Results ... 29
6.1 Descriptive statistics: internet skills ... 29
6.2 Descriptive statistics: proxy internet use ... 32
6.3 One-way ANOVA for different groups of PIU among Slovenian and UK internet users ... 36
6.4 Multiple linear regression... 42
7 Conclusion ... 45
8 Literature ... 49
6 Content of tables
Table 3.1 Digital Economy and Society Index (DESI) ranking for the UK and Slovenia ... 21
Table 5.1 Sociodemographic characteristics of full sample and sample of internet users for Slovenia and the UK ... 26
Table 6.1 Descriptive statistics for internet skills in Slovenian sample ... 30
Table 6.2 Descriptive statistics for internet skills in UK sample ... 31
Table 6.4 Descriptive statistics for variable proxy internet use – proxy user ... 32
Table 6.5 Number of activities performed by proxy users for Slovenia and the UK ... 33
Table 6.6 Descriptive statistics for variable proxy internet use – users-by-proxy ... 34
Table 6.7 Number of activities received by proxy internet use (user-by-proxy) in Slovenia and the UK ... 34
Table 6.8 Frequency table for proxy users, users by proxy, and combination of PU and UBP ... 36
Table 6.9 Descriptive statistics of mean values among Slovenian internet users ... 37
Table 6.10 ANOVA test performed among groups of PIU in Slovenia ... 38
Table 6.11 Multiple Comparisons for groups of PIU among Slovenian internet users ... 39
Table 6.12 Descriptive statistics of mean values among British internet users ... 40
Table 6.13 ANOVA test performed among groups of PIU in the UK ... 41
Table 6.14 Multiple Comparisons for groups of PIU among British internet users ... 42
Table 6.15 Regression model 1 – influence of internet skills on the extent of proxy user engagement ... 43
Table 6.16 Regression model 2 – influence of internet skills on the extent of user-by-proxy engagement ... 44
Content of figures Table 3.1 Digital Economy and Society Index (DESI) ranking for the UK and Slovenia ... 21
7 1 Introduction
Since engagement with the internet is becoming a necessity in everyday life, individuals who do not have digital devices, access to the internet or internet skills are more and more disadvantaged (Blank et. al., 2020). While some scholars argue that the non-hierarchical nature of the internet and the increase of user-friendly software contribute to the reduction of different forms of inequality, many scholars (Witte and Mannon, 2010; Robinson et. al., 2020; van Dijk, 2020; Warschauer, 2004) claim that the internet represents a medium that is consequential for some forms of inequality.
The extent to which individuals are digitally included or excluded from the digital environment has been researched in the field of the digital divide which was first conceptualized to consider only physical access to the internet, i.e., whether internet access exists or not. However, more and more research has been conducted where studies of the digital divide paid more attention to the social, cultural and psychological backgrounds of individuals. Therefore, multidimensional definitions of the digital divide have occurred that led to the conceptualization of digital inequalities research. In particular, DiMaggio and Hargittai (2001) have distinguished five dimensions that can create a digital divide: technical means (the possession of hardware and software), the autonomy of use (the freedom to use the internet for preferred activities), use patterns (different types of uses), social support networks (the possibility to obtain help and encouragement to use the internet) and skills (the abilities to use the internet). Van Dijk (2020) in his book explains that there are four dimensions of access to ICTs. The first one is motivation and attitude because the first stage to access and adoption of ICT technologies is psychological. “Human needs, motives, attitudes, expectancies, gratifications, and intentions drive the decision to purchase a computer or other digital medium and to connect to a network such as the internet” (van Dijk, 2020, p.56). The second dimension is physical access defined by van Dijk as “the opportunity to use digital media by obtaining them privately in homes or publicly in collective settings” (van Dijk, 2020, p.74). The third dimension of access by van Dijk (2020) is digital skills or “the individual ability to operate and use digital media” (p.92), which will be discussed in more detail further in this study. Lastly, we have usage access or the lack of significant usage opportunities (ibid.).
In particular, many digital divide and social inequality studies documented the immense importance of internet skills for digital engagement. In the last decade, the focus of research on the digital divide has partially shifted from physical access to differences in internet skills and their effect on social inequality. Therefore, early studies on the social impact of information communication technologies (ICT) were primarily focused on the difference between individuals who had access to the internet and computer and those who did not. However, as research developed the focus started shifting to questions regarding internet use and internet skills (Hargittai and Hsieh, 2013).
Internet use has been interpreted as individual use of the internet, which is defined in terms of the amount of use, variety of different uses, and types of use (Blank and Grošelj, 2014). In research literature, internet use is often discussed through the prism of active uses, that is, the main focus is on what an individual does on the internet for themselves. However, it often happens that internet users turn to others for assistance because of certain limitations in their abilities to use the internet. This phenomenon is represented by the concept of proxy internet use (PIU), which is defined by Grošelj et al. (2019) as “an activity where internet non-users ask internet users to perform online activities on their behalf, which is a strategy for obtaining (indirect) internet access” (p.2). There is a significant share of individuals who “might well be involved in proxy internet use – either as a proxy user or someone dependent on such a proxy user” (Selwyn et al. 2016, p.7). A proxy user is an individual who performs activities on the internet for someone else while the individual who receives the assistance is called user-by- proxy. Empirical research shows that 40% of non-users in Slovenia have been engaged in proxy internet use (Grošelj et al., 2019). A similar result on proxy internet use among non-users has been shown in the Netherlands (van Deursen in Helsper, 2015) as well as in the United Kingdom (Ofcom, 2018).
While most of the studies performed on PIU to date focus on non-users of the internet, more researchers are realizing that internet users may also be involved in PIU not only as proxy users but also as users-by-proxy. For example, some internet users may provide and receive assistance using the internet at the same time, while other internet users may only receive assistance from others. This thesis will focus on internet users engaged in PIU, as proxy users or users-by-proxy. There are multiple factors that shape engagement in different forms of PIU among internet users and internet skills represent an important factor.
Despite the growing ubiquity of internet technologies and online services, we still face an unequal distribution of internet skills among different groups of individuals. This applies to countries such as Slovenia, which is a country with an average rate of internet skills, as well as to digitally and informationally more advanced countries such as the United Kingdom. The 2019 report on the Digital Economy and Society Index (DESI) shows that Slovenia ranks 15th among EU countries and is below the EU average. The share of the population in Slovenia with a minimum of basic digital skills is 54%, and 30% of the population has advanced digital skills.
The UK, on the other hand, ranks 6th and is above the EU average. They account for 71% of the population with at least basic digital skills, which is 14 percentage points more than the EU average. In addition, the proportion of users with advanced skills is also relatively high at 46%, while in the EU the average is 31% (European Commission, 2019).
The phenomenon of proxy internet use is interesting in connection to internet skills because it establishes complex relationships between internet users in terms of receiving and providing proxy internet use. In this thesis, we would like to compare the internet skills of different groups of internet users, namely: (1) a group of individuals who accept assistance in using the internet but do not offer it to other individuals; (2) a group of individuals who do not accept help but offer it to other people; (3) a group that receives and offers assistance in using the internet; (4) a group that neither accepts nor offers assistance in using the internet. At the same time, we will compare the four groups of internet users in Slovenia and the United Kingdom to find out how the cultural context co-shapes the relationship between internet skills and proxy internet use. Based on the model of the compound and sequential digital inequalities (van Deursen et.
al., 2017), we assume that individuals who lack internet skills will also lack the use of the internet and would therefore be more likely to receive rather than provide proxy internet use.
We wonder if such a connection exists in Slovenia and Great Britain, where internet users are expected to vary considerably in terms of the level of internet skills.
10 2 Proxy internet use
Regardless of their individual circumstances, non-users are in an increasingly unfavourable position in a digital age where many of the activities and services they rely on are now online.
(Selwyn et al., 2016). Besides non-users, it is also important to address limited use of the internet, i.e., individuals who are online but make limited use of the internet, which often results in their disadvantage. To make up for their non-use or limited use of the internet, these individuals engage in proxy internet use which in short represents a situation that involves two parties, where one individual might not use the internet directly, but rather rely on someone else—usually from their social network—to go online for them (Grošelj et. al. 2020; Morris et al., 2007). Most performed activities in proxy internet use are sending emails, buying products, searching for information, or using government services. (Selwyn et al. 2016).
Although the nature of PIU is limited, its prevalence is widely acknowledged. According to a population-based survey, around 40% of internet non-users in various countries report engaging in PIU (Ofcom, 2018; Blank and Reisdorf., 2012; Selwyn et al., 2016). Those who use the internet for someone else tend to engage in activities that are perceived as important or risky by users-by-proxy (Blank, 2013; Dolničar, Grošelj, Filipovič Hrast, Vehovar, &
Studies conducted among non-users show that non-users over 65 years of age are less likely to engage in PIU (Dolničar et al.,2018; van Deursen & Helsper, 2015). These studies also found that women and non-users with a positive attitude towards the internet were more likely to participate in PIU. Dolničar et al. (2018) focused their study on the characteristics of social support networks and how they affected people’s chances of engaging in PIU. They found that having (grand) children in their social networks is linked to higher levels of PIU. There are various reasons why people use PIU. Three qualitative studies provided insight into the context of online non-user. One of these revealed that non-users consider PIU to be convenient and efficient, while those who reject the PIU claim that it makes them feel stigmatized and burdensome (Blank and Reisdorf, 2012).
In the 2005 Oxford Internet Survey (OxIS), Dutton (2005) researched the use of the internet in the UK, where he analysed, among others, a sample of 709 non-users and 167 ex-users. He found that PIU is more likely to be used by ex-users (34%) than non-users (15%), which means
that those who had some experience with the use of the internet are more likely to take advantage of indirect use of the internet. Also, ex-users (52%) are more likely than non-users (43%) to know someone to assist them (Dutton, 2005, p. 6).
To date, most studies have examined PIU concerning internet non-users, but some more recent research suggests that people who engage in PIU are not exclusively non-users. They can be also internet users who, for various reasons, cannot or do not want to perform certain activities online so they turn to others to assist them in those activities(Selwyn et al., 2016). Selwyn et.
al. (2016) state that individuals who are supported by proxies are rarely absolute non-users, except for some cases of physical incapability. Most of the individuals covered in their research used to make the internet in a certain way, usually using only smartphones and Apps. A study conducted by Petrovčič et. al. (2021) examined how proxy use and use-by proxy interfere in the effects of internet skills on internet use and outcomes among internet users, so this study explored users-by-proxy who are also internet users.
In this thesis, we will focus both on proxy users and users-by-proxy in two samples of internet users. It is also really important to note that users-by-proxy are not only non-users. Instead, there is a significant amount of users-by-proxy who are internet users with possible limitations in the use of the internet. Since PIU research among internet users is understudied, it will be interesting to see what differences will occur in individuals who engage in different roles simultaneously. Proxy internet use among internet users is a complex phenomenon because all individuals are engaged in some use of the internet. Therefore, we can distinguish four groups of PIU: (1) a group of individuals who accept assistance in using the internet but do not offer it to other individuals; (2) a group of individuals who do not accept assistance but offer it to other people; (3) a group that receives and offers assistance in using the internet; (4) a group that neither accepts nor offers assistance in using the internet. Furthermore, we will firstly elaborate on factors and characteristics of users-by-proxy and see what previous research was conducted on them. After that, we will deal with those who give assistance to others (proxy users) and their characteristics.
2.1 Factors and characteristics of users-by-proxy
Previous studies were mostly examining individuals who are on the receiving end of PIU, also referred to as users-by-proxy. In this chapter, we will elaborate more on their characteristics.
Based on Blank’s (2013) research in the UK, 70% of non-users say they could access the internet by proxy internet use, whereas only about 20% of non-users engage a proxy user.
About 50% of non-users aged from 25 to 44 activated a proxy user while the percentage of individuals aged 45 and more is from 20% to 30%. Gender and employment status do not play an important role in use-by-proxy because around 30% of both men and women activate proxy internet use. As expected, family members and friends most commonly enable internet access to non-users. These are usually children and grandchildren since they account for 60% of proxy internet users reported by non-users (Blank’s, 2013). Friemel (2016) reported that 44% of individuals in Switzerland who do not use the internet personally use it with someone else’s assistance. As mentioned earlier, most common types of PIU include "instrumental or functional activities, such as online banking or shopping, information seeking and interacting with government services online" (Grošelj et al., 2019, p. 215).
In a quantitative study conducted by Grošelj et al. (2019), they found that in Slovenia one of the most common reasons for individuals not to engage in internet use is lack of access. In such cases, non-users are not prone to activating PIU. On the other hand, individuals who lack internet skills are more prone to activate PIU.
“Since access barriers were measured with statements that reflect a general availability of internet access, this result indicates that non-users who live in technology-poor households or neighbourhoods may have difficulties finding a proxy user. In contrast, non-users who indicated that a lack of skills kept them offline were more likely to activate PIU, which suggests that “non-users who are more aware of their deficiency in skills might be more aware of online opportunities” (Grošelj et al., 2019, p. 220).
In a different study, Grošelj et al. (2019) also found that 86% of individuals who are not users of the internet had someone to perform certain online activities on their behalf, 46.7% of which engaged in PIU. The use of the internet among users-by-proxy is very limited in terms of the extent and consequences of the internet use and covers many different social groups. First of all, some do not use the internet at all for various reasons. These include, in particular, people with physical or mental disabilities and people who are otherwise socially excluded (e.g., the homeless). In addition, groups in institutionalized environment (e.g., persons actively
participating in the armed forces, prisoners, and patients in guarded hospitals) should also be considered (Selwyn et al., 2016, p. 6). On the other hand, there are limited internet users, who use the internet to a limited extent in terms of occasional visits to certain websites or the use of e-mail (Selwyn, 2016, p. 11) mainly due to the difficulties they face. These vary according to the type of activity and the level of self-confidence in using the internet. The most common problem is lack of knowledge (low level of internet skills) or uncertainty (Hunsaker et al., 2020, p. 5). Disinterest, mistrust, concern, confusion, and/or lack of assistance from others also occur, especially among older internet users (Hunsaker et al., 2020, pp. 7-8). According to van Deursen et. al. (2014), it is also important to note that internet users with lower levels of operational internet skills turn to others for support – usually friends and family.
Due to such reasons, there is a need for support or assistance whereupon users-by-proxy turn to proxy users for assistance. Therefore, internet users with a higher level of internet skills and different types of internet use (Reisdorf et al., 2020, p. 4), who are, consequently, more competent and confident users, assist users-by-proxy, such as technical knowledge of the internet and internet devices, and at the same time, usually represent their network of social support (Dolničar et al., 2018, p. 308). This type of assistance from the networks of social support can be represented with “weak” or “strong ties”.
“The connections and networks that people have with others, and the support and assistance that can be accessed through these connections. In this sense, some individuals’ internet access and use are reliant on help and resources provided through their ‘weak ties’, such as work colleagues or neighbours. Others might rely on their ‘strong ties’ with well-resourced and knowledgeable others, such as close friends and family members” (Morris et al., 2007, p.6).
In their study, Petrovčič et. al. (2021) also confirmed how proxy use and use-by proxy interfere in the effects of internet skills on internet use and outcomes among internet users. Accordingly, the lack of creative internet skills increases the likelihood of being a user-by proxy. They also confirmed that internet users’ engagement in use-by-proxy had no significant effects neither on their internet uses nor on their outcomes.
2.2 Factors and characteristics of proxy users
Less research has been done on individuals who are providing proxy use and are named proxy users. Proxy users or individuals going online on behalf of others are usually family members,
tutors, individuals acting in a professional capacity or social workers who usually use computers and the internet regularly (Blank, 2013; Dolničar, 2018). Solidarity and support can be observed in everyday life. For example, younger family members provide PIU for older adults such as parents and grandparents by teaching them basic information communication technologies (ICT). On the other hand, parents teach their younger family members about problems with personal information and privacy online (Taipale, 2019).
Proxy internet use is situation-specific, which means that proxy users do use the internet on someone’s behalf on a weekly or even monthly basis rather than every day. Additionally, proxy users do not usually support someone else who tries to use the internet but the activity of using the internet for someone else. It is not uncommon for proxy users to use the internet independently from the individual they assist. For example, they perform online services under the guise of the person they assist and without their involvement. For that reason, most of the people remain dependent on their proxy users to perform important online activities, while only a fraction of them learns and can repeat the activity performed by their proxy, thus acquiring some internet skills (Selwyn, 2016).
PIU has also been predominantly researched in health-related information seeking. In those studies, researchers have identified that proxy users “have looked for information related to the health conditions of others” (Selwyn et al. 2016, p.7). In that respect, individuals without access to the internet are real users of online health information. For example, one of ten respondents in Massey's (2016) research state that the internet is their primary information source regarding health-related queries, even though they are not users of the internet. Another study has shown that one of five respondents who is not an internet user has family members or friends who have conducted a health-related topic search online (Ayantunde et al. 2007).
Reisdorf et al. (2020) researched if any particular type of internet skill or internet use, namely, economic, personal, cultural or social one is connected with providing proxy internet use to others. The type, scope and level of internet skills are important in proxy use for many reasons.
Proxy internet use is often based on completing complex activities which can lead to significant consequences for individuals being assisted since activities performed by proxy users are very often based on the internet banking or government services as well as social media. Their findings suggest that “those who reported high operational skills were also more likely to provide PIU” (Reisdorf et al., 2020, p.14). They also suggest that operational skills are more
important for PIU than other types of skills, which was also confirmed by Selwyn's (2016) qualitative study. In their study, Reisdorf et al. (2020) also analysed how socio-demographic factors impact PIU and they concluded that only education was positively associated with the provision of PIU. This was not surprising since previous research conducted by Hargittai (2006), and van Deursen (2014) showed that there is a strong correlation between education and internet skills.
According to Reisdorf et. al. (2020), proxy internet use is mostly provided in segments, is limited in time and is only triggered when needed. Furthermore, this means that individuals providing help need to act immediately and efficiently, having no time to learn processes they must perform (Selwyn et al., 2016). For that reason, the scope and type of skills may represent an indispensable factor regarding who provides proxy internet use and who is not. Based on Hargittai and Shafer (2006), women tend to think that their internet skills are lower as opposed to men, even if testing shows that their skills are the same. This makes men more likely to perform as proxy users (Reisdorf et al., 2020) even though women are, for example, more supportive and caring which could potentially represent them as proxy internet users(Reevy and Maslach, 2001).
When it comes to internet users 41% of them reported helping someone go online in the last year. These individuals are usually younger (between 14 and 34), have higher education and higher incomes (Blank, 2013). Petrovčič et. al. (2021) also confirmed: "that internet users with a higher level of very basic (i.e., operational) and very advanced (i.e., creative) types of internet skills were more likely to engage in proxy use” (p.7).
As described in the two previous chapters, levels of internet skills are very important when it comes to determining whether people act as proxy users or not. It is also interesting to see what level and which type of internet skills are predominant in users-by-proxy because we concluded, according to Selwyn et al. (2016), that users-by-proxy are not complete non-users.
Instead, they are online but make limited use of the internet. Therefore, the next segment of this paper defines internet skills and explains different typologies of internet skills, focusing on the typology used in our empirical research.
16 3 Internet skills
The use of the internet is based on the interaction of users with advanced interfaces, providing them with access to content and services on the World Wide Web (Green, 2020, pp. 111-112).
At the same time, active use of the internet requires users to have specific knowledge and a set of different skills enabling them to search for information, perform transactions, establish and/or maintain interpersonal communication with other users (van Deursen and van Dijk, 2014, p. 509). These skills are grouped within the concept of internet skills. With the fast implication of digital technology into society, internet skills are the only of many concepts that have occurred in the research of the internet. According to van Deursen et al. (2016), internet skills should be distinguished from computer skills, as they require a wide range of knowledge and competence. For instance, when individuals have to practice communication online or create content, these activities require a broader knowledge than just opening an application.
Multiple different terms are used to indicate a set of basic skills needed to use a computer.
Apart from operational skills, scholars use terms such as instrumental skills, computer literacy, ICT literacy, technical competence and many more. According to Carvins' (2000) definition
“technological literacy is the ability to utilize common IT tools, including hardware, software, and internet tools like search engines” (Carvin1, 2000, as cited in van Deursen, 2010, p.59).
DiMaggio et al. (2004, p.378) defined internet skills as “the capacity to respond pragmatically and intuitively to challenges and opportunities in a manner that exploits the internet’s potential and avoids frustration” (DiMaggio et al. 2004, p.378). The definition of internet skills helps us establish the way different levels of internet skills are distributed among the population and establish the effects this distribution has on larger socio-economic factors. Many of the first classifications of internet skills treated basic skills as activities such as browsing the internet, searching for information or uploading files (Green, 2020, p. 121). However, as everyday social interactions have moved to the internet, researchers have suggested additional skills in a basic set of internet skills, such as the ability to authenticate other users, communicate with others,
1 Carvin, A. (2000). More than just access: Fitting literacy and content into the digital divide equation. EDUCAUSE Review, 35(6), 38-47.
like social networking sites, and understand and respect an online social norm. Due to constantly new definitions of the skill set, it is not surprising that some argue that precise definitions of new types of internet skills may never be achieved because their most important feature is that they change regularly (Litt, 2013, p. 614). Thus, there are several typologies of the dimension that make internet skills. Further in this thesis, we will elaborate on particular four categories, namely, operational, information-navigational, social and creative internet skills, a typology developed by van Deursen and colleagues (2016).
3.1 Forms and typology of internet skills
Previous research has mainly focused on the technicalities of internet skills, for example being able to open software like a browser (Bunz, Curry, & Voon, 2007). Besides that, research has been conducted based on online search for information, “which is mostly seen as an action via which users try to fulfil their information needs” (van Deursen, 2010, p.65). However, according to Wallace et al. (2000), there is much more to that process than just gathering information. Instead, “it encompasses posing or identifying a question or problem, exploring available information, refining the question, gathering, and evaluating information, and synthesizing and using information” (Wallace, Kupperman, Krajcik, & Soloway, 2000, p.78).
Van Deursen and van Dijk (2014) claim that the measure should as well incorporate socio- emotional and communicational skills, which are very important in the use of social media.
They expanded the scope of the communication internet skills framework by defining both content creation and communication skills. They noted that these two skills can be used to describe various aspects of online interaction, such as searching, analysing and selecting contacts.
Given all this, the most comprehensive framework and internet skills measuring instrument were developed by van Deursen and colleagues (2016) called the Internet Skills Scale (ISS).
The ISS measuring instrument is composed of four types of internet skills, two of them being medium-related and two content-related to capture the complexity of different types of engagement with the internet. The four types of internet skills are Operational, Information navigation, Social and Creative skills. As mentioned, this classification was created to acknowledge that internet skills should not only be measured at a basic technical level but take
into account the ability to use communication technologies for social purposes (van Deursen et al., 2016). Further on we will elaborate a bit more on these four types of internet skills.
Operational skills are the basic technical skills needed to manage computer and network hardware and software, for which the level of knowledge is easiest to assume and assess (van Deursen, 2010, p. 61). These abilities include, for example, knowing how to open downloaded files or how to use shortcut keys (van Deursen, 2016). Research done in this domain indicates that younger users of the internet show higher operational skills that support access to the internet (Clark2, 2001, as cited in van Deursen, 2010, p.62). The elderly population, as well as unemployed, disabled and homemakers, have shown lower operational skills. A notable part of senior citizens does not possess basic internet operation skills (Lundt & Vanderpan, 2000).
Information navigational internet skills are the second type of internet skills. Like operational skills, information navigational internet skills are medium-related and require an understanding of particular formal characteristics and techniques. For example, the internet is a medium for which an individual is required to have skills for navigating and browsing. Since every website differs from the other in the placement of photos, text, links, frames and other content, users should have skills to properly navigate different layouts on the Web. Furthermore, many websites are not user-intuitive and are developed without regard to the human factor, which makes them inaccessible for some users because it takes sophisticated navigational skills to use them properly. This issue occurs when the website is completely usable from the perspective of the developers but not for the average user (van Deursen, 2016).
Social skills include the ability to use online communication and interactions to understand and share meanings, which includes finding, evaluating, and operating online contacts, attracting attention online, and the social ability to combine knowledge and share meanings (van Deursen and Helsper, 2018, p. 235). It also involves the effective use of different messaging applications to contact people online as well as construct attractive online profiles and exchange information or opinions. Communication skills as such are becoming more prevalent in the network society (van Dijk, 2020, p. 99).
2 Clark, W. (2001). Kids and teens on the Net. Canadian Social Trends, 62, 6-10.
On the other hand, creative skills are the skills needed to create content of acceptable quality that an individual publishes or shares with others on the internet. This applies to textual, musical, video and image and multimedia content (van Deursen et. al., 2017, p. 235). Most people who contribute to the web are amateur writers, moviemakers and musicians, whose quality of work is often diverse. To be successful in the web environment, writers, video or music creators should have at least a basic knowledge of writing and creation (van Dijk, 2020, p. 99).
To sum up, the basic technical skills necessary to use the internet are referred to as operational skills. Information-navigation skills are similar to those that relate to searching for information.
Social skills are the ability to communicate and exchange meaning online. They involve the use of various online tools and techniques to gather and filter meaning and form social relationships. Creative skills are the ability to produce and distribute acceptable quality content (van Deursen et al., 2017).
All four types of internet skills are considered separately by researchers at the level of theoretical definitions, but they are interdependent and influence each other. Studies have also shown that a model of the compound and sequential digital exclusion is present among internet skills. We can separate the digital divide into two domains – the compound digital divide and the sequential digital divide. Compound digital exclusion is present "when a person who lacks one digital resource also lacks other digital resources of the same type” (van Deursen et. al., 2017, p.456). On the other hand, sequential digital exclusion can be seen when “a person’s digital exclusion of one type (e.g., lack of skills) leads to exclusion of a different type (e.g., low levels of internet use)” (van Deursen et. al., 2017, p.456). Figure 3.1 shows that users’ lack of rather basic technical skills (operational and information navigation internet skills) makes them unable to use other skills (social and creative) as well. The lack of these skills leads to performing not many online activities. In addition, we can see the connection between the use of the internet and the internet outcomes because individual needs to perform a particular use to produce a corresponding outcome (van Deursen et. al., 2017).
Figure 3.1 Model of the compound and sequential digital exclusion
Petrovčič et. al. (2021) research is the first to have explained the interrelationship between PIU and the three stages of the digital divide (i.e., internet skills, use, and outcome). In their paper, they situated PIU as a mediator between internet skills and internet use. They found “a notable difference between the roles of proxy use and use-by-proxy among internet users in sequential pathways from internet skills to outcomes. Unlike proxy use, which was a significant mediator of internet skills and had positive direct and indirect effects on internet uses and outcomes, use-by-proxy had no implications for internet uses and outcomes” (Petrovčič et. al., 2021, p.8).
Based on the compound and sequential model, compound digital exclusion in this paper should tell us how different types of internet skills are related. On the other hand, given that internet skills and use are related, we also expect a relationship between internet skills and PIU looking back at the sequential digital exclusion part of the model.
3.2 Studies of internet skills in Slovenia and the United Kingdom
In this chapter, we will compare digital characteristics between the United Kingdom and Slovenia and examine studies of internet skills in the two countries. First, we will compare Slovenia and the UK using the Digital Economy and Society Index (DESI), which combines different digital performance indicators of European countries and tracks the progress of EU member states over time. The report combines the following five indicators or dimensions:
connectivity, human capital, use of internet services, integration of digital technology, and digital public services (European Commission, 2019).
Table 3.1 Digital Economy and Society Index (DESI) ranking for the UK and Slovenia United Kingdom Slovenia
score rank score rank
Connectivity 63.6 10 58.5 17
Human capital 61.6 6 46.3 15
Use of internet services 67.6 5 46.6 21
Integration of digital technology 52 7 40.1 15
Digital public services 67.3 11 64.7 14
Overall score 61.9 5 50.9 16
According to the 2019 DESI report, the connectivity dimension puts the United Kingdom in 10th place among EU countries, with a score of 63.6, in comparison to Slovenia with a score of 58.5 in connectivity (17th place), which is below the EU average. The second dimension is human capital, which is the most interesting indicator in this paper since it is directly related to digital skills. The United Kingdom ranks sixth in the EU, which is above the EU average. 71%
of the British population has at least basic digital skills, and the percentage of individuals having above basic digital skills is also relatively high (46 %), which is higher than the 31%
EU average. In the second dimension – human capital, Slovenia ranks 15th with a score below the EU average. 54% of Slovenia population has at least the basic level of digital skills, while 30% have above average digital skills. Regarding the use of internet services in the UK, 94%
of the population go online at least every week, which means that only 6% never use the internet. The use of different internet services of the British population varies and is above the EU average. The downloading of music, videos and games, done by 88% of the British population, is the most popular online activity. It is followed by shopping (88 %) and online banking (78 %). Furthermore, growth has been observed in the use of social networks (74%) and reading news (72%), video on demand (53 %) and, selling online (53 %). When it comes to the use of internet services in Slovenia, like in the UK, the most popular online activity is watching music, videos, and gaming, which is performed by 84% of users. The second most popular activity is reading the news (72%), followed by the use of social networks (61%), online shopping (63%), and online banking (61%) (European Commission, 2019). Overall, the UK ranks 5th in2019 Digital Economy and Society Index (DESI), with a score of 64.9, while Slovenia is ranked 16th among 28 EU states, with an average score of 50.9 in all five dimensions.
According to a different study that used the Partnership Basic Digital Skills framework, which measures digital inclusion using with five basic digital skills – managing information, communication, transacting, problem-solving and creating – the Lloyds Bank UK Consumer Index (2018) used that framework to measure digital skills in the British population. They estimated that, in 2018, 8% of the British population lacked basic digital skills. The trend is declining but an important number of individuals still cannot do any of the five mentioned activities. Furthermore, 12% are estimated to possess only limited digital skills, which means that they lack one or multiple basic digital skills (Serafino, 2019).
We will also examine the distribution of internet skills in the elderly population, which is usually defined as persons of 60 and older. This is especially important and relevant for this paper since the elderly are usually more likely to be users-by-proxy because of different limitations such as the lack of internet skills. For example, according to the 2011 data, 76% of the British aged 75+ stated that they had never used the internet, which dropped to about 56%
in 2016 (Office for National Statistics, 2016). While we can see a decrease in the percentage of elderly nonusers, the “adoption varies considerably among the older population depending on age, income, and educational level” (Hargittai et al., 2019, p.882). Based on the research of Hargittai et al. (2019) that measured internet skills among the older population on a scale from 1 to 5, the group between 60 to 64 years old had an average score of 3.2, while the group between 75 to 85 had a significantly lower score of 2.6. The data shows that Slovenia has also a very low score, with only 27% of individuals aged between 64 and 74 using the internet, according to the 2016 study conducted by the Statistical Office of the Republic of Slovenia.
The percentage of individuals aged between 64 and 74 who have basic digital skills in Slovenia is 11%. 30% of individuals of this age (65 – 74) in Slovenia have low overall digital skills (SURS, 2016).
23 4 Research Framework
This paper focuses on levels of internet skill and proxy internet use in samples of internet users in Slovenia and the United Kingdom. We will use secondary data from two surveys, namely, the Slovenian Public Opinion Survey (2018) and the Internet Access and Use Survey (2021).
Based on prior research, we assume that proxy users possess higher levels of internet skills and perform complex activities for others or users by proxy (Selwyn et al., 2016). The analyses start with descriptive statistics to determine the distribution of variables.
This paper seeks to explore the following research questions:
Research Question 1: What are the differences in levels of internet skills among internet users according to different forms of their involvement in proxy internet use?
Research Question 2: Are there differences in levels of internet skills between internet users in Slovenia and the United Kingdom according to different forms of their involvement in proxy internet use?
24 5 Empirical study
The empirical study of Slovenian internet users is based on the analysis of secondary survey data collected in the period between March and June 2018 for the Slovenian Public Opinion Survey (SJM), which was conducted as part of the International Social Survey Programme (ISSP) (Grošelj, Petrovčič, Dolničar and Škafar, 2018, p.4). Using the Central Population Register of Slovenia, 2,000 citizens of Slovenia aged 18+ in March 2018 were included in the target population. 1,047 people were interviewed with the response rate of 57% (Grošelj et. al, 2018 p. 4–5). The SJM questionnaire "consisted of several thematic modules, including research on the use of new technologies and the internet, designed by researchers from the Centre for Social Informatics, FDV UL" (Grošelj and Matjašič, 2019, p. 607). The modules are internet access and use, proxy internet use, internet skills and internet use outcomes. Data for the Slovenian sample were collected by conducting a face-to-face survey.
The empirical analysis of internet users from the United Kingdom was conducted using data collected in an online panel of a web survey conducted in March and April 2019 (Grošelj, Petrovčič, & Dolničar, 2019). The questionnaire was based on the 2018 Slovenian Public Opinion Questionnaire (Grošelj et al., 2018). However, some adaptations had to be made because of study objectives and target population. The questionnaire is divided into the following four sections: frequency and scope of internet use, levels of internet use, proxy internet use, and outcomes of internet use. In the end, there is also a set of questions about the demographic characteristics of the population. The data was collected for 16 days via a web survey conducted in March and April 2019. The final sample consists of 926 respondents with the response rate of 21.2 %.
In Table 5.1, we present the socio-demographic characteristics of respondents who took part in the Slovenian Public Opinion Survey (SJM) (n = 1047). 77.9 % of respondents are internet users, which is the sample of internet users (n = 814) also presented in Table 5.1. They were defined as internet users because they responded that, in the previous three months, they had
used the internet via a computer, mobile phone, or other devices. The full sample consists of 48.6 % male and 51.4% female respondents, whereas there were 49.5% male and 50.5% female respondents among internet users. Most of the respondents in the full sample were older than 61 (32.5%), while among internet users most respondents were aged between 31 and 45 (31.7%), followed by those between 46 and 60 years of age (29.7%). The average age among internet users in Slovenia was 44.8, (Me = 44.0; SD = 15.3). In the full sample, most of the respondents had secondary education (30.8 %), while among internet users most respondents had higher education (37.8 %). Over 50% of the full sample live in a rural area, with 25.5%
living in small cities or towns. This ratio is the same among internet users.
We will now look at the sample collected in the United Kingdom. In the sample, 49.6% of respondents are male and 50.4% female. We can see that internet users in the British sample are younger than those in the Slovenian sample because we have 25.1% individuals from 18 to 30, compared to 16.2% in the Slovenian sample. There is a big difference in the category 61+
as the British sample includes 15.2% of respondents of that age, with 32.5% in the Slovenian sample. The average age of British internet users is 43.36 (Me = 43.0; SD = 14.57). Education in the UK sample had to be recoded to fit the equivalent education in Slovenia. GNVQs or equivalent was recoded into vocational school, GCSEs or equivalent and A levels / AS levels / Scottish Highers / NVQ levels / Int. Baccalaureate was recoded into high school, while Professional Qualification, Undergraduate degree or equivalent and postgraduate degree or equivalent were recoded into higher education. We can see that most of the British sample has secondary education (51.3%) which is higher compared to Slovenia (30.8%). In comparison to the Slovenian sample, more British respondents live in small cities and towns (46.6 %), while most Slovenians live in rural areas (50.6 %).
Table 5.1 Sociodemographic characteristics of full sample and sample of internet users for Slovenia and the UK
Variable Full sample Internet users Full sample / Internet
users SLO n (%) SLO n (%) UK n (%) Gender
Male 509 (48.6) 403 (49.5) 459 (49.6)
Female 538 (51.4) 411 (50.5) 467 (50.4)
18 30 170 (16.2) 170 (20.9) 232 (25.1)
31 45 261 (24.9) 258 (31.7) 278 (30.0)
46 60 276 (26.4) 242 (29.7) 275 (29.7)
Older than 61 340 (32.5) 144 (17.7) 141 (15.2)
Elementary education 117 (17.0) 65 (8.0) 49 (5.3)
Vocational education 225 (21.6) 143 (17.7) 95 (10.3)
High education 321 (30.8) 296 (36.5) 475 (51.3)
Higher education 318 (30.5) 306 (37.8) 307 (33.2)
Type of settlement
A big city 130 (12.4) 118 (14.5) 159 (17.2)
The suburbs 84 (8.0) 66 (8.1) 194 (21.0)
Small city or town 267 (25.5) 204 (25.1) 430 (46.6)
A country village 530 (50.6) 403 (49.5) 124 (13.4)
A farm or home in the country 32 (3.1) 19 (2.3) 13 (1.4)
Internet users 814 (77.9) 814 (100.0) 926 (100.0)
Interne non-user 231 (22.1)
Total 1047 (100.0) 814 (100.0) 926 (100.0)
5.3 Measurement instruments
5.3.1 Internet skills
The Internet Skill Scale (ISS) developed by van Deursen, Helsper and Eynon (2016) was used to measure internet skills. The question posed to the respondents was “Please indicate on a
scale from 1 = “Not at all true of me” to 5 = “Very true of me” how much the following statements apply to you when thinking about how you use the internet and technologies such as mobile phones (If you do not understand what the question refers to, select 6”. The scale measures these five dimensions: internet skills, operational skills, information navigation, social, creative and mobile internet skills. Mobile skills were excluded from further analysis because they are conceptually different and relate to the use of a specific device rather than general internet use (van Deursen et al., 2016; Grošelj et al., 2021). In a study conducted in 2021, Grošelj and colleagues (2021) conducted a confirmatory factor analysis on the same dataset that is used in this paper to confirm that statements shown in Table 6.1 in the Results section reflect four dimensions of internet skill.
5.3.2 Proxy internet use
Proxy internet use has been measured with two aspects in mind, namely, provision of proxy internet use (proxy users) and receiving of proxy internet use (use-by-proxy). Provision of proxy internet use with all its attributes was measured using a set of six questions. The respondents were first asked if they had performed any of the listed eight activities on behalf of someone else in the last 12 months. If the response was affirmative for at least one activity, they were asked about the number of people they had performed online activities for, their relationship to that person, about the person’s level of experience in internet use and why they did something for those individuals. (Grošelj et. al., 2021). The received proxy internet use was measured by a set of five questions. In this segment of questions, the respondent was required to state if they had asked anyone to perform an activity online on their behalf in the last 12 months. If yes, they were asked which online activities they needed assistance for and how many people performed online activities on their behalf and how they were related to the person that usually performed activities for them. Finally, they were asked about the reasons why they had sought assistance in the use of the internet. (Grošelj et. al., 2021).Some of the questions for receiving proxy internet assistance were taken from the OxIS questionnaire (Dutton &
Blank, 2011). Other questions were developed by researchers at the Center for Social Informatics, the University of Ljubljana, based on a focus group study conducted there.
28 5.3.3 Demographics
For control in the regression models, several demographic variables were included. The first one is the gender variable represented by the value “0 – Male” and “1 – Female”. The age variable was measured by asking about the year of birth, so the current age of the respondents was taken into account when completing the questionnaire. We also included the variable ‘type of settlement’ that measured if the respondent lived in a predominantly urban or rural type of settlement. Respondents could select “A big city”, “The suburbs or outskirts of a big city”, “A small city or town”, “A county village”, “A farm or home in the country” or “Other”.
We had to recode some variables for both Slovenian and British samples. We recoded the employment status variable for the Slovenian sample by recoding the value “Performing paid work” into “1 - Employed”, while the values “Unemployed and looking for employment”, “In education”, “Vocational training”, “Permanently incapable of work”, “Retired” and “Other”
were recoded into “0 - Nonactive in employment”. In the British sample, we recoded the value
“Working Full Time (30 hours a week or more)” and “Working Part-Time (8-29 hours a week)”
into “1 - Employed" and values "Retired", "Unemployed", "Permanently sick or disabled", "In community or military service", "Undergraduate student", "Postgraduate student", "In full-time education”, “In part-time education” and “Doing housework, looking after children or other persons” into “0 – Non-active in employment”. In the British sample, we recoded the marital status variable: the value “Married” and value “Living together with a partner” were recoded into “1 - Married” and values “Single”, “Divorced, separated” and “Widowed” into value “0 - Not married”. The marital status variable was also recorded in the Slovenian sample by recoding the values “Married”, “Extramarital union” and “Living separately (is married)” to “1 - Married”, and the other values “Divorced”, “Widowed” and “Single” were recoded to “0 – Not married”.
29 6 Results
6.1 Descriptive statistics: internet skills
Table 6.1 presents descriptive statistics for internet skills items in the Slovenian sample. Items are ordered according to the four different dimensions of internet skills, namely operational, information-navigation, social, and creative skills. Reported average range is from lowest M = 2.0 to highest M = 4.6. Most items in the questionnaire were responded to by a different number of respondents. We can see that, on average, internet users in Slovenia say that they are most careful to make their comments and behaviours appropriate to the situation in which they find themselves online (M = 4.6). They also claim that they can open a new tab on their browser with an average score of M = 4.5. Further, with the same average score of M = 4.3, respondents claim that they can open a downloaded file and download/save a photo they find on the internet.
However, the lowest average score (M = 2.0) given by the respondents is for the statement “I know how to design a website.
Table 6.1 Descriptive statistics for internet skills in Slovenian sample
Statements n Avg. SD Min Max Me
I know how to open downloaded files. 804 4.3 1.3 1 5 5 I know how to download/save a photo I found online. 804 4.3 1.3 1 5 5 I know how to use shortcut keys (e.g., CTRL-C for copy,
CTRL-S for save). 810 4.1 1.4 1 5 5
I know how to open a new tab on my browser. 808 4.5 1.2 1 5 5
I know how to bookmark a website. 804 4.2 1.4 1 5 5
I find it hard to find a website I have visited before. (R) 809 4.1 1.3 1 5 5 I get tired when looking for information online. (R) 809 4.0 1.2 1 5 5 Sometimes I end up on websites without knowing how I
got there. (R)
807 3.9 1.3 1 5 4 I find the way many websites are designed confusing. (R) 806 4.3 1.0 1 5 5 Social skills
I know which information I should and shouldn’t share
online. 796 4.3 1.0 1 5 5
I know when I should and shouldn’t share information
online. 790 4.3 1.0 1 5 5
I am careful to make my comments and behaviours
appropriate to the situation I find myself in online. 759 4.6 0.8 1 5 5 Creative skills
I know how to create something new from existing online
images, music, or videos. 797 3.1 1.7 1 5 3
I know how to make basic changes to the content that
others have produced. 794 2.3 1.5 1 5 2
I know how to design a website. 808 2.0 1.4 1 5 1
I know which different types of licenses apply to online
content. 789 2.1 1.4 1 5 1
I would feel confident putting video content I have created online.
781 3.1 1.7 1 5 4 Notes: (R) indicates statements with the reverse direction of the measurement scale that were recoded. Avg. = average; SD = standard deviation; Min = minimum; Max = maximum; Me = median
Table 6.2 presents the descriptive statistics of internet skills among internet users in the UK.
The average score ranges from M = 2.3 to M = 4.6. The highest average response M = 4.6 is for the statement “I know how to open a new tab on a browser.” Respondents also claim that they know how to open downloaded files and which information they should and shouldn’t share online, for both statements the average score is M = 4.4. The lowest average score, as in the Slovenian sample, is “I know how to design a website” (M = 2.3) In general, comparing internet users in Slovenia and the UK we can see that the British sample has higher average scores on statements linked to creative skills, while the Slovenian sample has on average higher scores on information-navigation skills items. The most visible difference between Slovenia and the United Kingdom is in the statement “I know how to make basic changes to the content that others have produced.” where the Slovenian sample has a score of 2.3 in comparison to a 3.2 score in the British sample. The difference of 0.8 is noticed in the statement “I know which