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Home-PC usage and achievement in English
Computers & Education 49 (2007) 1112–1121 www.elsevier.com/locate/compedu
Home-PC usage and achievement in English Folkvard Nævdal Bergen College (HiB), Faculty of Education, Postboks 7030, N-5020 Bergen, Norway
Abstract This article investigates the relation between home computer use and performance in English at school. The sample consists of 656 tenth-class students (age 15–16) in upper-secondary schools in Bergen, Norway. Data collection took place in the spring of 2002 and was administrated by the county education office. After correcting for gender, subject interest, reading disabilities and different PC activity categories, it was still possible to predict performance in English on a significant level from the total time spent in front of the PC-screen. Both boys and girls who seldom used home computers achieved low scores in English. However, of those students who spent two or more hours per day in front of the screen, girls performed very well in English while boys failed to show similar performance gains. Moreover, youths who were classified as poor readers benefited more from using home computers than those who were more competent readers. Ó 2006 Elsevier Ltd. All rights reserved. Keywords: PC-usage; Home-PC; School achievement; Leisure time; Youth; Language
1. Introduction In Scandinavia, personal computers are no longer exclusive toys or tools for those who are privileged. Almost every Norwegian home now has a modern PC and about eighty to ninety percent of homes have some kind of connection to the Internet. English is, in some variant, the dominant language of computers and Internet sites in the western world. In Norway, English (UK) is a core school subject and regarded as the first foreign language.
E-mail address: [email protected]. 0360-1315/$ - see front matter Ó 2006 Elsevier Ltd. All rights reserved. doi:10.1016/j.compedu.2006.01.003
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The hypothesis in this study was that use of a home computer strengthens an individual’s general competence in English, even when account is taken of reading difficulties, interest in English as school subject, different ways of using PCs and gender. Mumtaz (2001) claims that in Great Britain, and probably in most other western countries, computers in homes and leisure clubs are more technologically advanced and offer a greater range of activities than those found in the normal classroom. The gap between leisure and school equipment and engagement is growing, according to Mumtaz (2001). Facer, Sutherland, Furlong, and Furlong (2001) concluded that children and youthes do not use computers primarily in the pursuit of learning, but rather to achieve practical objectives and construct peer-group identities. The question addressed in this study is how home computer usage, regardless of the intentions, impacts on adolescents’ competence in English. Instructions, messages and Internet texts are generally in some variant of the English language. PC users are forced into this language by necessity if they want to master the most elementary dialogue with their computers or to understand the information they seek, even from Norwegian firms like airline companies, hotels, etc. If this kind of experience increases the general competence in English, we would expect that it would also strengthen the performance in English as evaluated by the teacher. Those who spend much of their leisure time in front of a computer, therefore, should perform better in English than those who do not use home computers to any great extent. While all kinds of PC activities will not have the same effect on school performance (Sutherland, Facer, Furlong, & Furlong, 2000), even ‘‘the players’’ have to deal with instructions, initials, words and statements in English if they wish to become an advanced player. Net-chatting and extended text reading in English are expected to have an even greater affect. It is important to study whether girls and boys have the same benefit from using home computers because of the gender differences in activity preferences and time spent on computer-based activities (Bimber, 2000; Naevdal, 2004; Orleans & Laney, 2000). While it is evident that pupils with reading disabilities tend to avoid computers (Leino, 2003), those who do not may benefit significantly. Through computer activities they may increase their reading experience, being motivated to search for information and interpret instructions on the screen; they might otherwise avoid all reading activities. In general, research on children’s and youths’ use of technology in domestic settings is a growing field (Facer et al., 2001; Levingstone, 2003). Most of these studies describe social interaction between family members and also peers; they have focused on processes, activity categories, functions and consequences. (Orleans & Laney, 2000; Wartella & Jennings, 2000) However, few studies have examined the link between home computer usage and school achievement. One of the studies from USA (Attewell & Battle, 1999) indicates a connection between most school subjects and home-PC usage, also after correcting for socio-economic status (SES) and ethnic classifications. Relevant to mention here, they found a significant connection between home computer use and achievement in mathematics and reading. This connection was found to be stronger in high-level SES groups. Boys benefited more from home computer use than girls, and ethnic minorities benefited least. In a review article, Subrahmanyam, Greenfield, Karut, and Gross (2001) refer to studies that have identified relations between computer use at home and achievement in science and art. In a Scandinavian sample of secondary school students, Leino (2003) found a positive relation between PC-usage and grades achieved in academic school subjects. He claimed that this relationship might be explained by the individual’s level of literacy. Poor readers/writers did not
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do as well in most school subjects, and they used computers infrequently because this required reading/writing ability. In another study, Naevdal (2004) found that only school-relevant PC activities like information seeking and doing lessons predicted general school achievement; playing and chatting did not. The use children and youth made of computers ranged from solely for entertainment to advanced technical programming, communication and educational activities. Playing games is obviously the dominant activity among teens. However, boys and girls differ with regard to the content of their PC activities and the time spent on these. Girls use computers less frequently than boys (Durndell & Thompson, 1997; Martin, 1998; Naevdal, 2002). Boys use computers as entertainment (games and net surfing) and experiment with the computer’s functions and with programming. Most girls are more practically and socially oriented, looking upon the home-PC as a tool, not a toy. They use it to communicate by e-post and in chat rooms on the Net (Mumtaz, 2001), as well as to search for information related to their homework or to do their lessons. (Befring, 1995; Jackson, Ervin, Gardner & Schmitt, 2001; Naevdal, 2002; Nordli, 1998). In contrast to Attewell and Battle’s (1999) findings, official statistics reveal that Norwegian girls are higher achievers in most school subjects than boys, with the exception of math and science (Læringssenteret, 2002). This difference may be due to changes that have taken place since the 1980s, or to differences between Norway and USA. The hypothesis of the present study is that pupils’ use of home computers improves their ability in English, even when allowance is made for differences in reading ability, interest in English as a school subject, preferences in PC-activities and gender. The hypothesis also postulates that gender has no affect on the benefits accrued from PC use; and that those with reading disabilities benefit more from PC use than normal readers.
2. Method The present study is part of a more comprehensive study that measures a wide variety of issues related to adolescents’ living conditions in Bergen, the second largest city in Norway. Ideally, the sample should represent all youth in the 10th class (15–16 years old) in the city of Bergen. The sample was drawn from inner city as well as suburban and rural schools within the city boundary (10 schools). Data collection took place in the spring of 2002 (April), when the students started the very last session of their last semester in upper-secondary school. Parental permission was required and standard procedures developed to ensure anonymity. Data collection was administrated by the county education office in Bergen. None of the selected schools refused to participate. Questionnaires were sent to 930 pupils in the selected schools. The students were given two hours to fill in the anonymous questionnaire which contained general questions related to individual characteristics, family life, school, and leisure time; and specific questions about access to a home computer, Internet and different equipment and applications. They were also asked about computer-related activities and preferences, as will be described below. Of the sample of 930 pupils, 656 participated in the study. The Norwegian Data Inspectorate demands positive (opt in) permission from the parents. Positive permission was not obtained for 152 students. Thus these were excluded from participation. In addition, we missed students because some classes were difficult to organize on the day of data collection (excursions, etc.)
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and some students were randomly absent. Seventy one percent of the sample participated; 329 girls and 327 boys completed the questionnaires in full. The information obtained from the questionnaires can be summed up as follows. Of the sample pupils, just three percent did not have a modern computer at home. Ten percent had little knowledge of computers, equipment and the possibilities of home computer. Seventy percent knew that they had a multimedia computer at home, and eighty-six percent had access to Internet at least via an ordinary phone line. The time spent working on the PC was named ‘‘PC-time’’. PC-time was rated according to the following scale: (i) never or very seldom, (ii) sporadic or less than five hours per week, (iii) almost daily, less than two hours and (iv) daily, two hours or more. The last category was named ‘‘Super users’’. School achievement in English was established based on the formal grade the pupils reported having received in English at the end of the first semester in 10th class; they were rated on a scale of 1–6 with 6 being the highest score. To establish individual interest in English, the participants were asked to indicate how much they liked English as school subject on a scale from 1 through 5. In order to establish reading ability, the participants were asked if they had difficulties in reading and writing compared with the norm in the class, and to indicate the extent of the problem on the following scale: (i) Not at all, (ii) slight, (iii) problematic, (iv) very problematic. In all, 80 students reported reduced reading/writing ability, thirty-two girls and forty-eight boys. Just 5 boys reported reading disabilities at the highest level. The students were asked how often they used the computer to: (i) do lessons, (ii) experiment with programming, (iii) search for themes, (iv) chat on the net, (v) play music, (vi) play games, (vii) just surf on the net and (viii) send mail and messages to friends. The ranking scale was: (i) never, (ii) sometimes, (iii) often, (iv) very often and (v) almost all the time. The eight computer-activities were factorized (Principal Comp., Varimax rotated, resulting in three activity-factors that explained 66% of the variance: (fac. I) Entertainment and technology (playing, surfing and experimenting, (fac. II) Communication (e-post and chatting) and (fac. III) Information seeking and text-handling. The factor scores are used as variables in the analysis model. In the following text, and in the tables and figures, these factors are named (I) Toy activities (playing, surfing and experimenting with programming), (II) Tool 1 activities (Communication) and (III) Tool 2 activities (Education related). The statistical analysis was carried out using the SPSS-programme. (George & Mallery, 2001). The research questions and data were suitable for multivariate regression analysis. The main analysis was modeled as hierarchical regression in two steps. The first step includes the variables that are not related to computer activities. The second step adds PC-time and the three computeractivity factors. R2 changes are given. Regarding the hypothesis about interaction, these effects will be tested by variance analysis and illustrated on a graph. Curved linearity is of particular interest.
3. Results Table 1 below provides a statistical description of the mean achievement in English in each of the four user categories. The language competence was found to be best in the group that used home computers daily and moderately, less than two hours.
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Table 1 Statistical description of achievement in English for each of the four user levels regarding distribution, mean and standard deviation User level (4 levels)
Achievement in English (graded 1–6) Mean
Standard deviation
Confidence interval for mean (95%)
N
Never or seldom Sporadic <5 h per week Almost daily: <2 h per day Daily 2 h or more per day
3.85 4.06 4.23 3.95
0.94 0.75 0.93 0.91
3.7–4.0 3.9–4.2 4.1–4.4 3.8–4.1
136 226 197 97
Sample total
4.05
0.92
3.9–4.1
656
Table 2 below provides the summary of a hierarchical regression analysis regarding the effects of variables predicting achievement in English according the model. In Step 1, all modeled independent variables predicted achievement in English. Interest in the subject was obviously the best predictor (.46). Reading disability was found to be a hindrance ( .21). Gender showed not a strong, but a significant relationship with achievement in English. These three variables together explained 31% of the dependent’s variance. In Step 2, the four computer-related variables were added. These significantly increased the prediction power. The level in just one of the activity variables (Tool 2) was notable (.12), although not very strong. The two other activity-factors did not explicitly predict competence in English. Total time spent in front of the screen was a significant but weak indicator?? (.12). The first hypothesis that PC-time itself affected achievement in English was therefore verified. When the time was used to information seeking and text handling the profit increased. Step 2 increased the prediction power by 2% of the variance (DR2 = .02) (p < .001). This effect is quite unique and only explained by PC-related activity when the analysis is limited to the actual model. Table 2 Summary of hierarchical regression analysis for variables predicting achievement in English (N = 559) Independent variables and interactions
B
SEB
b
Step 1 (A) Gender (B) Reading disability (C) Interest in English
0.17 0.37 0.36
0.06 0.05 0.03
.09** .23** .46**
Step 2 (A) Gender (B) Reading disability (C) Interest in English (D) Communication (E) Play & technical experimentation (F) Information and text handling (G) PC-time (any activity)
0.18 0.35 0.38 0.03 0.06 0.10 0.27
0.07 0.05 0.02 0.03 0.04 0.03 0.04
.10* .21** .43** .01 .08 .12** .12**
Note: R2 = .31 for Step 1; DR2 = .02 (p < .001). Total explained variance: R2 = .33. * p < .05. ** p < .01.
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Mean: Achievement in English (1-6)
5.2 5.0 4.8 4.6 4.4 4.2 4.0
Gender
3.8
Boys
3.6 3.4 Seldom
Sporadic < 5h p.w.
Daily < 2 h.
Girls Daily 2 h. or more
PC time
Fig. 1. Graphic illustration of Achievement in English (grades) as a function of PC-time in each gender. Note: Interaction between gender and PC-time were not statistically significant at 5%-level.
The next hypothesis concerned whether there was any gender difference in the benefits accrued from the time spent in front of the computer. The linear interaction test did not verify this hypothesis, in spite of the difference between girls and boys at the super user level (see Fig. 1). Among girls there was a linear relationship between PC-time and achievement in English. Among boys, the relationship between PC-time and achievement in English was found to be curved linear where the boys’ achievement level was consistently lower than girls’ in all user categories. The boys’ achievement level was highest in the moderate user category. The linear estimation of R2 among boys was .006, but using curved linear regression (Cubic), the estimation power increased by 2% (R2 = .027). A relation between reading disability and PC-time was found (p < .02), and the result showed that those with a reading disability increased their performance in English as a function of PCtime. The slope was steeper than for normal readers. Fig. 2 below illustrates the relationship between reading disability and PC-time. To simplify the illustration, (Fig. 2) the scale for disability is reduced from four to two values, (i) normal and (ii) disabled. From Fig. 2 it is evident that the relationship between PC-time and achievement in English was obviously curved linear. The estimated linear prediction among disabled readers (n = 69) resulted in R2 = .17 (p < .000). Curved linear regression (Cubic) procedure increased the estimation effect to the extent of R2 = .22 (p < .000).
4. Discussion Generally there seemed to be a curved linear relationship between the frequency of home computer use and achievement in English. Most of the high achievers were classified as moderate users. Naevdal (2004) found that 29 out of 326 boys, but as many as 107 out of 329 girls, seldom
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Achievement in English (grade 1-6)
4.5
4.0
3.5
3.0
Reading ability 2.5 Not disabled
2.0 Never or seldom
Reduced ability Irregular < 5 h/week
Daily < 2 h/day
Daily => 2 h/day
PC-time
Fig. 2. Graphic illustration of Achievement in English as a function of PC-time, among both normal readers and those reporting reading disabilities. The interaction between reading disability and PC-time was found to be significant (p < .02).
or never used a computer after school. Both the boys and the girls in this low-user category generally performed less well at school. In the high-user category, there were 9 girls and 88 boys. These nine girls1 all performed very well at school, while the boys in this category showed great variation, but generally poorer performance than the girls. The analysis (Naevdal, 2004.) revealed that among super users the girls operated within a great many activity categories, while the boys were mainly playing games and listening to music. The girls seemed to be expanding the traditional gender role, while the boys seemed to be withdrawing from the world, including an interest in school subjects. These boys did nothing but play (games and music), surf the net and experiment with programming, building competence in a field that is not currently evaluated, directly or indirectly, as school competence. These findings, therefore, provide the background for interpreting the present study with a focus on competence in English as a consequence of home computer use. The curved linearity that is apparent in Table 1 is explained by the curved linearity among boys that surpassed the linearity among girls. The statement about linearity among girls may be questionable because of the small number of ‘‘super users’’ among the girls. It is a fact that just nine girls operated on the super user level, and that they all preformed very well in English, but the parameters in small groups like this are uncertain, in spite of the demonstrated consistency. 1 Except for two of them, these girls were located at different schools. There was no reason to believe that they even knew each other.
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As a single dependent variable in the bivariate analysis, gender was a marked contributor to competence in English, as well as for the general school performance. Girls performed better than boys in most school subjects. The picture is very consistent all over the country now (Læringssenteret, 2002). Not surprisingly, interest in English was found to be the best predictor of achievement in English. Difficulty reading was the second strongest, and negatively correlated. It is a common experience among teachers that interest in a subject can be used to predict grades, although not consistently. If girls are more interested in English than boys, this effect is included in the regression model. The inclusion of PC related activities and time spent (PC-time) further increased explanation power by 2% of the independent variance as it appeared in the hierarchical regression analysis. The use of a home computer to obtain information and to handle text documents (Tool 2) was obviously an advantage when it came to marks in English, independent of the total PC-time or of gender. These activities may be interpreted as regular school work, and work with school subjects at home usually improves school achievement. So far, these findings are very marked and expected. When adjusted for all the other independent variables, the time spent in front of the PC still had a significant impact, regardless of the content of the PC-time, gender, reading difficulties or interest in English. The hierarchical model ensured that additional explanation arise from the PCrelevant variables. The conclusion drawn from the data was that using home PCs predicted performance in English. If this usage also included school-related work like information seeking and lessons, the benefits increased. Both the unintended language exposure associated with the use of a PC and its use for systematic school work seemed to have a positive impact on competence in English. Playing, surfing and chatting did not specifically explain performance in English. The fact that those with reading disabilities seemed to profit more from computer use than ordinary readers was a surprising result. They probably practiced reading on the computer, maybe even reading English instructions and information, and thereby actually increased their reading skills. There is also a possibility that those with reading disabilities used the home computer to do their lessons. Using the computer, they would gain access to correcting programs and a variety of layouts. Thus, their school work would be much easier to do and would be presented in a much better manner. Maybe the computer simply makes the homework possible? Without a PC, the work might never have been done or it might have been presented in a form that was difficult for the teacher to evaluate. It is often stated, but as far as I know not documented, that the computer is generally a great advantage to individuals with reading/writing disabilities in performing at school. Closer analysis of the data seemed to indicate that the more disabled the pupils reported themselves to be, the greater the advantage of using home computers. As demonstrated in Fig. 2, the relation was curved linear, and the estimated effect of PC-time on achievement in English was best predicted by curved linear regression (Cubic). For those with reading disabilities, as much as 22% of the dependent variance was explained, but the achievement in English was still significantly lower than for normal readers for all PC user groups. Nevertheless, there is reason for optimism. Despite the truth of Leino’s claim (2003) that people with reading disabilities avoid the computer, this study demonstrated that those who do not, improve their achievement at school, at least in English.
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In the research field of PC use and learning, further study should focus on the actual interaction between the ordinary teaching methods in English and the use of computers at school and at home. This study gives reason for more optimism than Jackson, Fletcher, and Messer (1998) expressed in their study from the late 1980s. While the equipment standard in schools is, at least in Norway, unsatisfactory, it is nevertheless far better than just a few years ago. The general teaching methods are now, as far as the author can see, shifting from textbooks and drills, to real-life tasks utilizing, for example, the news and practical social communication. In such activities, computers can be a great advantage, and should be utilized pedagogically and integrated in all subjects. In general, the pupils’ home computers may be more up-to-date than those at school, but the range of school computer use seems to be diversifying, from drill and practice that provides relief for the teacher, towards communication, group works and personal knowledge building that actively includes the teachers. This is possible because the general technological knowledge and technical competence of teachers and pupils is now increasing as a consequence of computer experience in the private sphere. This basic technical competence is going to become necessary, common, valuable and usable at home. We seem to be moving towards a cultural standard that cannot be ignored by anyone. The computer is now a common tool that seems to have become a natural part of everyday life, integrated into our cultural concerns. Computers can be functional tools for learning, but this is dependent on the pupil’s interest in the actual subjects and reading ability. Computers should, therefore, be integrated into the learning process in a way that not only expands the fields of exercises but also increases pupil motivation, and this actually happens when the homework a pupil with a writing disability hands in is presentable.
References Attewell, P., & Battle, J. (1999). Home computers and school performance. Information Society, 15(1), 1–10. Befring, Eirik (1995). Dataspill forklart for akademikere. Nye medier – nye underholdnings-former. Hovedfagsoppgave i medievitenskap, Universitet i Oslo. Translated: PC-games explained to the graduated. New medias – new ways of entertaining. Thesis: Science of media. University of Oslo. Bimber, B. (2000). Measuring the gender gap on internet. Social Science Quarterly, 81(3), 868–875. Durndell, A., & Thompson, K. (1997). Gender and computing: a decade of change?. Computers and Education 28(1), 1–10. Facer, K., Sutherland, R., Furlong, R., & Furlong, J. (2001). What’s the point of using computers. The development of young people’s computer expertise in the home. New Media & Society, 3(2), 199–219. George, D., & Mallery, P. (2001). SPSS for Windows, step by step, a simple guide and references 10.0 update (3rd ed.). Allyn and Bacon. Jackson, L. A., Ervin, K. S., Gardner, P. D., & Schmitt, N. (2001). Gender and Internet: Women communicating and men searching. Sex Roles, 44(5–6), 363–379. Jackson, A., Fletcher, B., & Messer, D. (1998). Effects of experience on microcomputer use in primary schools: results of a secondary survey. Journal of Computer and Assisted Learning, 4(4), 214–126. Læringssenteret, www.ls.no (2002). Karakterer i grunnskolen. Translated: Grades at the end of the secondary school in Norway http://www.ls.no/utdanningsstatistikk/avgrskar/kar-grs02.html#KarGRS (Read 20.12. 2004). Leino, K. (2003). Computer usage and reading literacy. http://www.pisa.no/Dokumenter/Nordisk%20rapport/ kap6.pdf (Read 30.12.2004).
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Levingstone, S. (2003). Children’s use of the Internet: reflection on the emerging research agenda. New media & Society, 5(2), 147–166. Martin, Shelly (1998). Internet use in the classroom, the impact of gender. Social Science Computer Review, 16(4), 411–418. Mumtaz, Shaida (2001). Children’s enjoyment and perception of computer use in the home and the school. Computers and education, 36, 347–362. Naevdal, F. (2002). Ung i Bergen 2002. Rapport, Ungdom i skole og fritid. En beskrivelse av hverdagsforutsetninger for ˚ rstad og Ytrebygda. Bergen, Høgskolen i Bergen, 24-27. Translated: 10.klassinger i bydelene Lakseva˚g, Arna, A Young in Bergen 2002. Report, Youth in school and leisure. A description of the everyday life of the adolescents, 15–16 years old. Bergen College of Education, Bergen. Naevdal, F. (2004). Skoleprestasjoner, kjønn og bruk av PC. Tidsskrift for Ungdomsforskning, 4(1). 67–82. (Transl.: Achievement at School, gender and the use of home computers.) Journal of Youth Research, 4(1), 67–82. Nordli, Hege (1998). Fra Spice Girls til Cyber Girls. En kvalitativ studie av datafacinerte jenter i ungdomsskolen. Hovedfagsoppgave, Rapport 35, Senter for Teknologi og Samfunn. Thesis: Report nr. 35 Centre for Technology and Society, Oslo. Orleans, M., & Laney, M. C. (2000). Children’s computer use in home, isolation or sociation. Social Science of Computer Review, 18(1), 56–72. Subrahmanyam, K., Greenfield, P., Karut, R., & Gross, E. (2001). The impact of computer use on children’s and adolescents’ development. Journal of Applied Developmental Psychology, 22(1), 7–30. Sutherland, R., Facer, K., Furlong, R., & Furlong, J. (2000). A new environment for education? The computer in the home. Computers and Education, 34(3–4), 195–212. Wartella, E. A., & Jennings, N. (2000). Children and computers: new technology–old concerns. The future of children. Children and Computer Technology, 10(2), 31–43.
Home-PC usage and achievement in English Folkvard Nævdal Bergen College (HiB), Faculty of Education, Postboks 7030, N-5020 Bergen, Norway
Abstract This article investigates the relation between home computer use and performance in English at school. The sample consists of 656 tenth-class students (age 15–16) in upper-secondary schools in Bergen, Norway. Data collection took place in the spring of 2002 and was administrated by the county education office. After correcting for gender, subject interest, reading disabilities and different PC activity categories, it was still possible to predict performance in English on a significant level from the total time spent in front of the PC-screen. Both boys and girls who seldom used home computers achieved low scores in English. However, of those students who spent two or more hours per day in front of the screen, girls performed very well in English while boys failed to show similar performance gains. Moreover, youths who were classified as poor readers benefited more from using home computers than those who were more competent readers. Ó 2006 Elsevier Ltd. All rights reserved. Keywords: PC-usage; Home-PC; School achievement; Leisure time; Youth; Language
1. Introduction In Scandinavia, personal computers are no longer exclusive toys or tools for those who are privileged. Almost every Norwegian home now has a modern PC and about eighty to ninety percent of homes have some kind of connection to the Internet. English is, in some variant, the dominant language of computers and Internet sites in the western world. In Norway, English (UK) is a core school subject and regarded as the first foreign language.
E-mail address: [email protected]. 0360-1315/$ - see front matter Ó 2006 Elsevier Ltd. All rights reserved. doi:10.1016/j.compedu.2006.01.003
F. Nævdal / Computers & Education 49 (2007) 1112–1121
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The hypothesis in this study was that use of a home computer strengthens an individual’s general competence in English, even when account is taken of reading difficulties, interest in English as school subject, different ways of using PCs and gender. Mumtaz (2001) claims that in Great Britain, and probably in most other western countries, computers in homes and leisure clubs are more technologically advanced and offer a greater range of activities than those found in the normal classroom. The gap between leisure and school equipment and engagement is growing, according to Mumtaz (2001). Facer, Sutherland, Furlong, and Furlong (2001) concluded that children and youthes do not use computers primarily in the pursuit of learning, but rather to achieve practical objectives and construct peer-group identities. The question addressed in this study is how home computer usage, regardless of the intentions, impacts on adolescents’ competence in English. Instructions, messages and Internet texts are generally in some variant of the English language. PC users are forced into this language by necessity if they want to master the most elementary dialogue with their computers or to understand the information they seek, even from Norwegian firms like airline companies, hotels, etc. If this kind of experience increases the general competence in English, we would expect that it would also strengthen the performance in English as evaluated by the teacher. Those who spend much of their leisure time in front of a computer, therefore, should perform better in English than those who do not use home computers to any great extent. While all kinds of PC activities will not have the same effect on school performance (Sutherland, Facer, Furlong, & Furlong, 2000), even ‘‘the players’’ have to deal with instructions, initials, words and statements in English if they wish to become an advanced player. Net-chatting and extended text reading in English are expected to have an even greater affect. It is important to study whether girls and boys have the same benefit from using home computers because of the gender differences in activity preferences and time spent on computer-based activities (Bimber, 2000; Naevdal, 2004; Orleans & Laney, 2000). While it is evident that pupils with reading disabilities tend to avoid computers (Leino, 2003), those who do not may benefit significantly. Through computer activities they may increase their reading experience, being motivated to search for information and interpret instructions on the screen; they might otherwise avoid all reading activities. In general, research on children’s and youths’ use of technology in domestic settings is a growing field (Facer et al., 2001; Levingstone, 2003). Most of these studies describe social interaction between family members and also peers; they have focused on processes, activity categories, functions and consequences. (Orleans & Laney, 2000; Wartella & Jennings, 2000) However, few studies have examined the link between home computer usage and school achievement. One of the studies from USA (Attewell & Battle, 1999) indicates a connection between most school subjects and home-PC usage, also after correcting for socio-economic status (SES) and ethnic classifications. Relevant to mention here, they found a significant connection between home computer use and achievement in mathematics and reading. This connection was found to be stronger in high-level SES groups. Boys benefited more from home computer use than girls, and ethnic minorities benefited least. In a review article, Subrahmanyam, Greenfield, Karut, and Gross (2001) refer to studies that have identified relations between computer use at home and achievement in science and art. In a Scandinavian sample of secondary school students, Leino (2003) found a positive relation between PC-usage and grades achieved in academic school subjects. He claimed that this relationship might be explained by the individual’s level of literacy. Poor readers/writers did not
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do as well in most school subjects, and they used computers infrequently because this required reading/writing ability. In another study, Naevdal (2004) found that only school-relevant PC activities like information seeking and doing lessons predicted general school achievement; playing and chatting did not. The use children and youth made of computers ranged from solely for entertainment to advanced technical programming, communication and educational activities. Playing games is obviously the dominant activity among teens. However, boys and girls differ with regard to the content of their PC activities and the time spent on these. Girls use computers less frequently than boys (Durndell & Thompson, 1997; Martin, 1998; Naevdal, 2002). Boys use computers as entertainment (games and net surfing) and experiment with the computer’s functions and with programming. Most girls are more practically and socially oriented, looking upon the home-PC as a tool, not a toy. They use it to communicate by e-post and in chat rooms on the Net (Mumtaz, 2001), as well as to search for information related to their homework or to do their lessons. (Befring, 1995; Jackson, Ervin, Gardner & Schmitt, 2001; Naevdal, 2002; Nordli, 1998). In contrast to Attewell and Battle’s (1999) findings, official statistics reveal that Norwegian girls are higher achievers in most school subjects than boys, with the exception of math and science (Læringssenteret, 2002). This difference may be due to changes that have taken place since the 1980s, or to differences between Norway and USA. The hypothesis of the present study is that pupils’ use of home computers improves their ability in English, even when allowance is made for differences in reading ability, interest in English as a school subject, preferences in PC-activities and gender. The hypothesis also postulates that gender has no affect on the benefits accrued from PC use; and that those with reading disabilities benefit more from PC use than normal readers.
2. Method The present study is part of a more comprehensive study that measures a wide variety of issues related to adolescents’ living conditions in Bergen, the second largest city in Norway. Ideally, the sample should represent all youth in the 10th class (15–16 years old) in the city of Bergen. The sample was drawn from inner city as well as suburban and rural schools within the city boundary (10 schools). Data collection took place in the spring of 2002 (April), when the students started the very last session of their last semester in upper-secondary school. Parental permission was required and standard procedures developed to ensure anonymity. Data collection was administrated by the county education office in Bergen. None of the selected schools refused to participate. Questionnaires were sent to 930 pupils in the selected schools. The students were given two hours to fill in the anonymous questionnaire which contained general questions related to individual characteristics, family life, school, and leisure time; and specific questions about access to a home computer, Internet and different equipment and applications. They were also asked about computer-related activities and preferences, as will be described below. Of the sample of 930 pupils, 656 participated in the study. The Norwegian Data Inspectorate demands positive (opt in) permission from the parents. Positive permission was not obtained for 152 students. Thus these were excluded from participation. In addition, we missed students because some classes were difficult to organize on the day of data collection (excursions, etc.)
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and some students were randomly absent. Seventy one percent of the sample participated; 329 girls and 327 boys completed the questionnaires in full. The information obtained from the questionnaires can be summed up as follows. Of the sample pupils, just three percent did not have a modern computer at home. Ten percent had little knowledge of computers, equipment and the possibilities of home computer. Seventy percent knew that they had a multimedia computer at home, and eighty-six percent had access to Internet at least via an ordinary phone line. The time spent working on the PC was named ‘‘PC-time’’. PC-time was rated according to the following scale: (i) never or very seldom, (ii) sporadic or less than five hours per week, (iii) almost daily, less than two hours and (iv) daily, two hours or more. The last category was named ‘‘Super users’’. School achievement in English was established based on the formal grade the pupils reported having received in English at the end of the first semester in 10th class; they were rated on a scale of 1–6 with 6 being the highest score. To establish individual interest in English, the participants were asked to indicate how much they liked English as school subject on a scale from 1 through 5. In order to establish reading ability, the participants were asked if they had difficulties in reading and writing compared with the norm in the class, and to indicate the extent of the problem on the following scale: (i) Not at all, (ii) slight, (iii) problematic, (iv) very problematic. In all, 80 students reported reduced reading/writing ability, thirty-two girls and forty-eight boys. Just 5 boys reported reading disabilities at the highest level. The students were asked how often they used the computer to: (i) do lessons, (ii) experiment with programming, (iii) search for themes, (iv) chat on the net, (v) play music, (vi) play games, (vii) just surf on the net and (viii) send mail and messages to friends. The ranking scale was: (i) never, (ii) sometimes, (iii) often, (iv) very often and (v) almost all the time. The eight computer-activities were factorized (Principal Comp., Varimax rotated, resulting in three activity-factors that explained 66% of the variance: (fac. I) Entertainment and technology (playing, surfing and experimenting, (fac. II) Communication (e-post and chatting) and (fac. III) Information seeking and text-handling. The factor scores are used as variables in the analysis model. In the following text, and in the tables and figures, these factors are named (I) Toy activities (playing, surfing and experimenting with programming), (II) Tool 1 activities (Communication) and (III) Tool 2 activities (Education related). The statistical analysis was carried out using the SPSS-programme. (George & Mallery, 2001). The research questions and data were suitable for multivariate regression analysis. The main analysis was modeled as hierarchical regression in two steps. The first step includes the variables that are not related to computer activities. The second step adds PC-time and the three computeractivity factors. R2 changes are given. Regarding the hypothesis about interaction, these effects will be tested by variance analysis and illustrated on a graph. Curved linearity is of particular interest.
3. Results Table 1 below provides a statistical description of the mean achievement in English in each of the four user categories. The language competence was found to be best in the group that used home computers daily and moderately, less than two hours.
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Table 1 Statistical description of achievement in English for each of the four user levels regarding distribution, mean and standard deviation User level (4 levels)
Achievement in English (graded 1–6) Mean
Standard deviation
Confidence interval for mean (95%)
N
Never or seldom Sporadic <5 h per week Almost daily: <2 h per day Daily 2 h or more per day
3.85 4.06 4.23 3.95
0.94 0.75 0.93 0.91
3.7–4.0 3.9–4.2 4.1–4.4 3.8–4.1
136 226 197 97
Sample total
4.05
0.92
3.9–4.1
656
Table 2 below provides the summary of a hierarchical regression analysis regarding the effects of variables predicting achievement in English according the model. In Step 1, all modeled independent variables predicted achievement in English. Interest in the subject was obviously the best predictor (.46). Reading disability was found to be a hindrance ( .21). Gender showed not a strong, but a significant relationship with achievement in English. These three variables together explained 31% of the dependent’s variance. In Step 2, the four computer-related variables were added. These significantly increased the prediction power. The level in just one of the activity variables (Tool 2) was notable (.12), although not very strong. The two other activity-factors did not explicitly predict competence in English. Total time spent in front of the screen was a significant but weak indicator?? (.12). The first hypothesis that PC-time itself affected achievement in English was therefore verified. When the time was used to information seeking and text handling the profit increased. Step 2 increased the prediction power by 2% of the variance (DR2 = .02) (p < .001). This effect is quite unique and only explained by PC-related activity when the analysis is limited to the actual model. Table 2 Summary of hierarchical regression analysis for variables predicting achievement in English (N = 559) Independent variables and interactions
B
SEB
b
Step 1 (A) Gender (B) Reading disability (C) Interest in English
0.17 0.37 0.36
0.06 0.05 0.03
.09** .23** .46**
Step 2 (A) Gender (B) Reading disability (C) Interest in English (D) Communication (E) Play & technical experimentation (F) Information and text handling (G) PC-time (any activity)
0.18 0.35 0.38 0.03 0.06 0.10 0.27
0.07 0.05 0.02 0.03 0.04 0.03 0.04
.10* .21** .43** .01 .08 .12** .12**
Note: R2 = .31 for Step 1; DR2 = .02 (p < .001). Total explained variance: R2 = .33. * p < .05. ** p < .01.
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Mean: Achievement in English (1-6)
5.2 5.0 4.8 4.6 4.4 4.2 4.0
Gender
3.8
Boys
3.6 3.4 Seldom
Sporadic < 5h p.w.
Daily < 2 h.
Girls Daily 2 h. or more
PC time
Fig. 1. Graphic illustration of Achievement in English (grades) as a function of PC-time in each gender. Note: Interaction between gender and PC-time were not statistically significant at 5%-level.
The next hypothesis concerned whether there was any gender difference in the benefits accrued from the time spent in front of the computer. The linear interaction test did not verify this hypothesis, in spite of the difference between girls and boys at the super user level (see Fig. 1). Among girls there was a linear relationship between PC-time and achievement in English. Among boys, the relationship between PC-time and achievement in English was found to be curved linear where the boys’ achievement level was consistently lower than girls’ in all user categories. The boys’ achievement level was highest in the moderate user category. The linear estimation of R2 among boys was .006, but using curved linear regression (Cubic), the estimation power increased by 2% (R2 = .027). A relation between reading disability and PC-time was found (p < .02), and the result showed that those with a reading disability increased their performance in English as a function of PCtime. The slope was steeper than for normal readers. Fig. 2 below illustrates the relationship between reading disability and PC-time. To simplify the illustration, (Fig. 2) the scale for disability is reduced from four to two values, (i) normal and (ii) disabled. From Fig. 2 it is evident that the relationship between PC-time and achievement in English was obviously curved linear. The estimated linear prediction among disabled readers (n = 69) resulted in R2 = .17 (p < .000). Curved linear regression (Cubic) procedure increased the estimation effect to the extent of R2 = .22 (p < .000).
4. Discussion Generally there seemed to be a curved linear relationship between the frequency of home computer use and achievement in English. Most of the high achievers were classified as moderate users. Naevdal (2004) found that 29 out of 326 boys, but as many as 107 out of 329 girls, seldom
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Achievement in English (grade 1-6)
4.5
4.0
3.5
3.0
Reading ability 2.5 Not disabled
2.0 Never or seldom
Reduced ability Irregular < 5 h/week
Daily < 2 h/day
Daily => 2 h/day
PC-time
Fig. 2. Graphic illustration of Achievement in English as a function of PC-time, among both normal readers and those reporting reading disabilities. The interaction between reading disability and PC-time was found to be significant (p < .02).
or never used a computer after school. Both the boys and the girls in this low-user category generally performed less well at school. In the high-user category, there were 9 girls and 88 boys. These nine girls1 all performed very well at school, while the boys in this category showed great variation, but generally poorer performance than the girls. The analysis (Naevdal, 2004.) revealed that among super users the girls operated within a great many activity categories, while the boys were mainly playing games and listening to music. The girls seemed to be expanding the traditional gender role, while the boys seemed to be withdrawing from the world, including an interest in school subjects. These boys did nothing but play (games and music), surf the net and experiment with programming, building competence in a field that is not currently evaluated, directly or indirectly, as school competence. These findings, therefore, provide the background for interpreting the present study with a focus on competence in English as a consequence of home computer use. The curved linearity that is apparent in Table 1 is explained by the curved linearity among boys that surpassed the linearity among girls. The statement about linearity among girls may be questionable because of the small number of ‘‘super users’’ among the girls. It is a fact that just nine girls operated on the super user level, and that they all preformed very well in English, but the parameters in small groups like this are uncertain, in spite of the demonstrated consistency. 1 Except for two of them, these girls were located at different schools. There was no reason to believe that they even knew each other.
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As a single dependent variable in the bivariate analysis, gender was a marked contributor to competence in English, as well as for the general school performance. Girls performed better than boys in most school subjects. The picture is very consistent all over the country now (Læringssenteret, 2002). Not surprisingly, interest in English was found to be the best predictor of achievement in English. Difficulty reading was the second strongest, and negatively correlated. It is a common experience among teachers that interest in a subject can be used to predict grades, although not consistently. If girls are more interested in English than boys, this effect is included in the regression model. The inclusion of PC related activities and time spent (PC-time) further increased explanation power by 2% of the independent variance as it appeared in the hierarchical regression analysis. The use of a home computer to obtain information and to handle text documents (Tool 2) was obviously an advantage when it came to marks in English, independent of the total PC-time or of gender. These activities may be interpreted as regular school work, and work with school subjects at home usually improves school achievement. So far, these findings are very marked and expected. When adjusted for all the other independent variables, the time spent in front of the PC still had a significant impact, regardless of the content of the PC-time, gender, reading difficulties or interest in English. The hierarchical model ensured that additional explanation arise from the PCrelevant variables. The conclusion drawn from the data was that using home PCs predicted performance in English. If this usage also included school-related work like information seeking and lessons, the benefits increased. Both the unintended language exposure associated with the use of a PC and its use for systematic school work seemed to have a positive impact on competence in English. Playing, surfing and chatting did not specifically explain performance in English. The fact that those with reading disabilities seemed to profit more from computer use than ordinary readers was a surprising result. They probably practiced reading on the computer, maybe even reading English instructions and information, and thereby actually increased their reading skills. There is also a possibility that those with reading disabilities used the home computer to do their lessons. Using the computer, they would gain access to correcting programs and a variety of layouts. Thus, their school work would be much easier to do and would be presented in a much better manner. Maybe the computer simply makes the homework possible? Without a PC, the work might never have been done or it might have been presented in a form that was difficult for the teacher to evaluate. It is often stated, but as far as I know not documented, that the computer is generally a great advantage to individuals with reading/writing disabilities in performing at school. Closer analysis of the data seemed to indicate that the more disabled the pupils reported themselves to be, the greater the advantage of using home computers. As demonstrated in Fig. 2, the relation was curved linear, and the estimated effect of PC-time on achievement in English was best predicted by curved linear regression (Cubic). For those with reading disabilities, as much as 22% of the dependent variance was explained, but the achievement in English was still significantly lower than for normal readers for all PC user groups. Nevertheless, there is reason for optimism. Despite the truth of Leino’s claim (2003) that people with reading disabilities avoid the computer, this study demonstrated that those who do not, improve their achievement at school, at least in English.
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In the research field of PC use and learning, further study should focus on the actual interaction between the ordinary teaching methods in English and the use of computers at school and at home. This study gives reason for more optimism than Jackson, Fletcher, and Messer (1998) expressed in their study from the late 1980s. While the equipment standard in schools is, at least in Norway, unsatisfactory, it is nevertheless far better than just a few years ago. The general teaching methods are now, as far as the author can see, shifting from textbooks and drills, to real-life tasks utilizing, for example, the news and practical social communication. In such activities, computers can be a great advantage, and should be utilized pedagogically and integrated in all subjects. In general, the pupils’ home computers may be more up-to-date than those at school, but the range of school computer use seems to be diversifying, from drill and practice that provides relief for the teacher, towards communication, group works and personal knowledge building that actively includes the teachers. This is possible because the general technological knowledge and technical competence of teachers and pupils is now increasing as a consequence of computer experience in the private sphere. This basic technical competence is going to become necessary, common, valuable and usable at home. We seem to be moving towards a cultural standard that cannot be ignored by anyone. The computer is now a common tool that seems to have become a natural part of everyday life, integrated into our cultural concerns. Computers can be functional tools for learning, but this is dependent on the pupil’s interest in the actual subjects and reading ability. Computers should, therefore, be integrated into the learning process in a way that not only expands the fields of exercises but also increases pupil motivation, and this actually happens when the homework a pupil with a writing disability hands in is presentable.
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