Chapter 4.5
Computer Attitudes and CompetenciesamongPrimary and Secondary Schools Students
Martina Meelissen
University of Twente
Enschede, The Netherlands
Abstract:This chapter provides an overview of research from the last 15 years on attitudes and competencies regarding computer use by primary and secondary school students. For many scholars in this field, the low participation of women in computer related training courses and professions, has been the reason to focus mainly on the ‘gender gap’ in computing and on gender differences in computer attitudes especially. However, despite the numerous studies on this subject, consensus about explanations for these gender differences in computer attitudes is still lacking. Three main theories will be discussed: socialisation, gender specific behaviour and the influence of teaching. Compared to computer attitude studies, the availability of studies and theories on students’ computer competencies is much more limited. Students’ own assessment of their abilities in general computer use has received more attention in this field of research, although this subject is also often addressed from a gender perspective.
Keywords: Computer attitudes; Computer competencies; Gender differences; Primary education; Secondary education
Introduction
Research on students’ use of information technology often results from concerns about the so called ‘digital divide’. The digital divide refers to differences in computer use, attitudes and competencies with regard to gender, age, ethnicity or social economic status (Broos & Roe, 2006). In most western countries the participation of females in IT professional careers and pathways is not only low but is also still falling (Anderson, Lankhear, Timms & Courtney, in press). Therefore, in the last thirty years, the most frequently reported socio-demographic parameter of the digital divide has been gender. One of the main topics in this field is girls’ and boys’ attitudes toward information technology (which is mostly referred to as ‘computer attitudes’). In the United States in particular, differences between female and male students in attitudes toward computers has been the subject of many studies since the 1980s (Volman, 1994). At first, the interest for computer attitudes was mainly directed to being one of the influencing factors explaining gender differences in computer use and in computer competencies. During the last twenty years, computer attitudes have become the main focus of study by itself. Nowadays, the number of studies on the ‘gender gap’ in computer attitudes, exceeds the number of studies on computer competencies and abilities by large (Imhof, Vollmeyer & Beierlein, 2007; Kay, 2006). Studies on computer attitudes, competencies or use among students with different cultural or social economic backgrounds are also still scarce, although the differences between these groups seem to be substantial as well (Volman, Van Eck, Heemskerk & Kuiper, 2005).
This chapter provides an overview of the main research results of studies on (gender) differences in computer attitudes (including computer anxiety) and studies on (gender) differences in computer competencies during the last fifteen years (see for summaries of earlier studies e.g. Volman, 1994). Although the majority of studies are conducted among university and college students or among adults, the main focus in this chapter will be on students in primary and secondary education.
The first and major part of this chapter is directed to studies on computer attitudes. Despite the large interest of researchers for students’ computer attitudes, the results of these studies are often inconclusive or sometimes contrasting. Therefore, the benefits as well as the limitations of these studies will be discussed in the first section. An overview of the main results and outcomes is provided in section 2. Section 3 focuses on research on student’ computer competencies, including their own perceived competencies. The last section (4) summarizes the main results and addresses possibilities for future research in this field.
Measuring Computer Attitudes
As stated before, despite the large number of studies on students’ computer attitudes, the results of these studies are often inconclusive or even in contrast to each other. For example, although the majority of studies show less positive computer attitudes of girls compared to that of boys, the difference is often very small or negligible (Meelissen, 2005; Whitley, 1997). Furthermore, some studies show no gender differences in computer attitudes at all or find more positive attitudes among girls compared to those of boys (King, Bond & Blandford, 2002; North & Noyes, 2002; Whitley, 1997). One of the explanations could be related to the measuring of the construct ‘computer attitudes’ in those studies. The research literature on attitudes toward computers shows a large variation in the use of computer attitudes scales (Christensen & Knezek, 2000; Dryburgh, 2000; Durndell, Haag & Laithwaite, 2000). In general, the operationalization of computer attitudes is based on the attitude theory of Fishbein and Azjen (1975), in which three aspects are distinguished. The first aspect is the affective aspect and refers to someone’s feelings about the subject. In terms of computer attitudes, the affective aspect can be measured by statements about liking computers or enjoyment in computer use. The perceived relevance of computers could be an operationalization of the cognitive aspect of attitudes or on other words, someone’s perceptions and opinions about the subject. The last aspect refers to the behaviour toward the subject. In computer attitudes research, this aspect can be measured by instruments measuring computer anxiety or self-confidence in computer use.
Often, only one or two of these aspects are measured in computer attitude studies. One of the most used instruments (or versions of this instrument) is the Computer Attitude Scale or CAS (Gressard & Loyd, 1986). In CAS three subscales are distinguished; enjoyment in computer use, computer anxiety and self-confidence in computer use. The first scale refers to the affective aspect; the other two refer to the behavioural aspect. However, computer anxiety could also be regarded as a potentially influencing factor on students’ attitudes (e.g. Durndell & Haag, 2002; King et al., 2002). The same goes for concepts such as gender stereotyped views on computers, self-efficacy or self-confidence. These concepts are used as sub-scales of computer attitudes or as potentially influencing factors on the dependent variable computer attitude (e.g. Comber, Colley, Hargreaves & Dorn, 1997; Levine & Donita-Schmidt, 1998). The large variation is discussed by Kay (1993):
“One method of developing a common language among attitudes scales is to develop a composite of the various constructs already identified. This process is hindered somewhat by a noticeable absence of theoretical justification provided by researchers in support of their constructs. In a number of studies independent constructs are identified in a post hoc fashion. Without some theoretical substance, it is difficult to pick and choose from the computer attitudes grab bag.” (Kay, 1993, p. 372).
Researchers in this field seem to pay little attention to the effects of their choice for an attitude instrument. In the research of Levine and Donita-Schmidt (1998) and Pope-Davies and Vispoel (1993) it turned out that self-confidence, which is often used as a sub-scale of computer attitudes, fits better as a subscale of computer anxiety and that anxiety and attitudes are two different concepts. Gender differences seem to be much more substantial for computer anxiety (girls are more anxious than boys) than for liking computers and relevance of computers (Charlton, 1999). On the other hand, a Scottish study among primary school children shows that gender differences only occurred in enjoyment and relevance of computer use and not in self-confidence (Todman & Dick, 1993).
There is not only variation in the operationalisation of computer attitude, but also in the actual measuring.In most cases, computer attitudes or subscales of computer attitudes are measured by presenting students with statements on computers and asking them to which extent they agree with these statements (e.g. Meelissen, 2005; Shashaani, 1994). In the study of Whitley (1996), gender differences only occurred for the negative statements (female students agreeing more with negative statements about computers than male students), while there were no differences regarding the positive statements. Therefore, Whitley (1996) emphasized that negative and positive statements in a computer attitudes scale should be well balanced. Often this is not the case.
Another possible explanation for the lack of agreement in the research literature on computer attitudes has to do with the meaning of the word “computer” in the computer attitude scales. If it is presented just as ‘computer’, the respondent could associate the computer with a variety of attractive or less attractive hardware devices, software and uses. Including a distinction in the different uses of computers in the attitude scale is not that common in the research literature (Richter, Naumann & Groeben, 2000; Van Eck, 2002). Volman (1994) measured the attitudes of Dutch secondary school students before and after a computer literacy course. Students who finished the course, no longer associated computers with playing computers games, but regarded computers mainly as an instrument for teaching and learning. According to the research of King et al., (2002), students in lower secondary education regarded computers above all as an instrument for playing games. Their attitudes changed during secondary school, as computers were used more serious for educational purposes and the use became more vocationally oriented.
Differences in associations with the word ‘computer’ could lead to differences in attitudes. In other words, the interpretation of the results of many studies is hindered by the fact that the researcher does not really know what each respondent is thinking of when he or she gives an opinion about ‘the computer’. The lack of this distinction could be a threat to the validity of the computer attitudes scale used.
Finally, in terms of generalization of the results for the research population, the eloquence of the outcomes of studies on computer attitudes is often not that strong (Dryburgh, 2000; Meelissen, 2005). Although a case study approach with in-depth interviews or lessons observations seem to be less common in this research field than a survey approach, survey instruments are frequently administered among convenience samples of students from a few classes or schools. But also in the case of larger, random samples, the possibility to generalize to the research population is often not addressed in the research design. Very few studies recognise the limitations of their sample and incorporate these limitations in the interpretation of their results (e.g. North & Noyes, 2002).
Taken into account these limitations of computer attitude studies, the main theories and research results on (gender) differences in computer attitudes are described in the next section. The section gives an overview of the main and recent publications on students’ computer attitudes in primary and secondary education. As stated before, computer attitudes are often analysed from the perspective of gender differences in computing. Therefore, a substantial part of the studies described in this article are carried out with this perspective in mind. Often, these studies do provide insight in the factors influencing computer attitudes in general as well.
In the next section, the research literature is summarised on the basis of three main topics. These are: the socialisation processes, gender-specific behaviour; and the influence of schools and teachers.
Students’ Computer Attitudes
The Socialisation Theory
Perceived ‘masculinity’ of computers
The rationale for research on ‘the digital divide’ between males and females is often based on females’ low participation rates in computer science courses and IT-professional careers (Anderson et al., in press). IT-professions and computers are assumed to be unattractive for females because of their ‘male image’. It is argued that this male image has a negative effect on the attitudes of girls as a result of gender differentiated socialization (e.g. Brosnan & Lee, 1998; Charlton, 1999). Children are taught by their environment (parents, other family members, peers, and in the media) what “correct” behaviour is for boys and what ‘correct’ behaviour is for girls. Knowing a lot about computing and liking computers has a different meaning for girls and boys. For example, boys with high computer interest and skills have historically received more appreciation from their environment than girls with the same skills and interest.
Some researchers have found evidence that it is not the physical attributes traditionally associated with gender (being male or female) that determine student computer attitudes. To a large extent their attitudes are determined by the gender with which the child identifies him- or herself (e.g. Brosnan & Lee, 1998; Charlton, 1999; Todman & Day, 2006). In other words, not the sex of a child but the ‘psychological gender’ is regarded as the main factor determining students’ computer attitudes. Because computers are often seen a male domain, children who identify themselves as more masculine may have more positive attitudes towards computers, as opposed to children who identify themselves as more femine.
In the 1960s, females were just as involved in the area of early computer science as males. Females played an important part in the introduction of the binary system and in the development of the computer language Cobol (COmmon Business-Oriented Language) (Corston & Colman, 1996). Female computer programmers were even preferred to male programmers because of their supposed ‘accuracy’ and ‘patience’. This changed completely during the 1970s and 1980s in most of the industrialised western countries. Computers and computer science became associated with more typically “male” areas, like mathematics, science and technology. For example in the Netherlands, the introduction of computers in secondary schools was often initiated by mathematics and science teachers. Those teachers also became responsible for the computer science lessons (Beentjes, Vooijs, & Kruse, 1995). A study carried out among secondary school females in the US, showed that negative attitudes towards mathematics are strongly related to negative attitudes towards computers and girls are less positive about mathematics than boys (Shashaani, 1995).
Not only the association of computers with mathematics and technology was responsible for the male image of computers, but the use of the first personal computers at home played a role as well. In the beginning of the 1980s almost no (user friendly) software was available, which meant that computers were predominantly used for programming and playing games (Teague & Clarke, 1995). Males spent considerably more time than females with these computers. According to Teague and Clarke, males are more interested in experimenting with new techniques, even when the practical use of that technique is not clear. For females, the direct practical use is much more important than it is for males. Furthermore, most of the computer games that were available, were more directed to the interests of boys than to the interest of girls, which emphasised the male image of computers (Charlton, 1999).
However, Charlton (1999) also argues that the male image of computers is no longer a valid explanation for gender differences in computer attitudes. Nowadays, computers are widely available, have become more user-friendly, and computer use has become much more varied. In 2003, in most western and also some non-western countries both girls and boys spend more than one hour per day playing computer games and more than half an hour per day using the Internet (Mullis, Martin, Gonzalez & Chrostowski, 2004). The variety of available computer games and intensity of gaming has increased enormously. Among English primary and lower secondary school students, playing computer games turns out to be the favourite out-of-school activity for both girls and boys (Mumtaz, 2001; Colley, 2003). In the Netherlands, primary school boys (grade 5) reported more intensive computer use outside school hours than girls did. However, although boys spent on average five hours per week, girls still spent on average three hours per week with the computer (Meelissen, 2005). Both girls and boys spent most of that time gaming.
Empirical evidence on how the image of computers is perceived by girls and boys is not widely available. In 1994, Shashaani collected data about gender stereotyped views on computing among almost 1800 American secondary school students. It turned out that only boys regarded computers as a typically male domain, while girls did not. In 1997, an English study among primary and secondary school students showed that on average, girls explicitly disagreed with gender stereotyped statements about computers and that most of the boys were neutral toward this subject (Comber et al., 1997). However, the majority of Dutch boys in grade 5 (in 1999) were convinced that boys knew more about computers than girls did (Meelissen, 2005). Furthermore, about a third of the girls agreed with them. Girls with less gender-stereotyped views on computers were expected to have more positive computer attitudes. However, gender stereotyped views on computers turned out to be unrelated to either girls’ or boys’ computer attitudes (Meelissen, 2005).
Another method for finding out if computers are (still) regarded as typically masculine, is applied in a study by Mercier, Barron and O’Conner (2006). With surveys, drawings and interviews, sixth- and eight-grade students were asked to generate representations of computer users in pictures or in words. Both girls and boys were more likely to draw a male user. Frequently, the drawing showed a boy wearing glasses and sometime the word ‘nerd’ was written under the drawing. When asked if these students saw themselves as such a ‘computer-person’, around 80% of the students disagreed. There were however, no significant gender differences.