Introduction to Gender Differences in Computer and Information Literacy

Gebhardt, Eveline; Thomson, Sue; Ainley, John; Hillman, Kylie

doi:10.1007/978-3-030-26203-7_1

Cited by 20 publications

(13 citation statements)

References 28 publications

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“…In addition, a recently published meta-analysis on gender and attitudes towards ICT found a small but significant positive effect, suggesting that male participants hold more favourable attitudes (Cai et al 2016). In contrast, a study by Gebhardt et al (2019) found gender differences only in country-level analyses. Thus, it would be meaningful to explore whether this holds true for the German pre-service teacher sample in comparison to other countries.…”

Section: Discussionmentioning

confidence: 95%

“…However, the topic of gender differences appears to be complex, as empirical research has yielded mixed evidence on the impact of gender on ICT-related constructs (Hatlevik and Arnseth 2012;Siddiq et al 2015). With respect to ICT self-efficacy, the ICILS reported that male teachers showed higher ICT self-efficacy than female teachers (Gebhardt et al 2019). Additionally, a higher percentage of female than male teachers reported using ICT in their instruction.…”

Section: Gender Differences and Ictmentioning

confidence: 99%

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“Do You Think You Have What it Takes?” – Exploring Predictors of Pre-Service Teachers’ Prospective ICT Use

Pozas

2021

Tech Know Learn

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Despite extensive efforts to support teachers with the integration of information and communication technologies (ICT) into their classroom practice, current research reports that teachers face immense challenges when integrating ICT into their teaching. This issue has become even more relevant with the rapid spread of the COVID-19 virus, forcing schools around the world to close for an indefinite period of time and thus to offer remote digital learning solutions. Against this background, this study focused on examining the predictors of pre-service teachers’ prospective ICT use and investigated the heterogeneous results of previous research related to ICT use and gender. Following the ‘will, skill, tool’ framework, the study examined relevant factors of pre-service teachers’ (N = 103) prospective ICT use for teaching and learning processes by means of multiple regression analyses. The analyses included pre-service teachers’ background characteristics, ICT profiles (attitudes and self-efficacy), digital competencies and use of digital tools in order to explore their role in future in-class use of ICT. They also show that there are no gender differences in pre-service teachers’ prospective ICT integration. However, male pre-service teachers hold more positive attitudes towards ICT use than their female counterparts. Additionally, the findings reveal that the two strongest predictors of pre-service teachers’ future ICT use are their attitudes and perceived competency to teach and implement technology in their teaching practices. Finally, the results provide important information about teachers’ training needs. Implications of the results and further research are discussed.

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Section: Discussionmentioning

confidence: 95%

Section: Gender Differences and Ictmentioning

confidence: 99%

“Do You Think You Have What it Takes?” – Exploring Predictors of Pre-Service Teachers’ Prospective ICT Use

Pozas

2021

Tech Know Learn

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“…In turn, other studies found that female students had on average a higher skill level than boys (ACARA 2015; Aesaert and van Braak 2015;Fraillon et al 2014Fraillon et al , 2019Gebhardt et al 2019;Thomson 2015). In Australia, for instance, it was observed that girls in sixth and tenth grade classes displayed a higher computer and information literacy than boys (ACARA 2015(ACARA , 2018.…”

Section: Fig 1 Icils 2013 Framework Modelmentioning

confidence: 91%

The relationship between differences in students’ computer and information literacy and response times: an analysis of IEA-ICILS data

Heldt

Massek

Drossel

et al. 2020

Large-scale Assess Educ

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Background Due to the increasing use of information and communication technology, computer-related skills are important for all students in order to participate in the digital age (Fraillon, J., Ainley, J., Schulz, W., Friedman, T. & Duckworth, D. (2019). Preparing for life in a digital world: IEA International Computer and Information Literacy Study 2018 International Report. Amsterdam: International Association for the Evaluation of Educational Achievement (IEA). Retrieved from https://www.iea.nl/sites/default/files/2019-11/ICILS%202019%20Digital%20final%2004112019.pdf). Educational systems play a key role in the mediation of these skills (Eickelmann. Second Handbook of Information Technology in Primary and Secondary Education. Cham: Springer, 2018). However, previous studies have shown differences in students’ computer and information literacy (CIL). Although various approaches have been used to explain these differences, process data, such as response times, have never been taken into consideration. Based on data from the IEA-study ICILS 2013 of the Czech Republic, Denmark and Germany, this secondary analysis examines to what extent response times can be used as an explanatory approach for differences in CIL also within different groups of students according to student background characteristics (gender, socioeconomic background and immigrant background). Methods First, two processing profiles using a latent profile analysis (Oberski 2016) based on response times are determined—a fast and a slow processing profile. To detect how these profiles are related to students’ CIL, also in conjunction with students’ background characteristics (socioeconomic and immigrant background), descriptive statistics are used. Results The results show that in the Czech Republic and Germany, students belonging to the fast processing profile have on average significantly higher CIL than students allocated to the slow processing profile. In Denmark, there are no significant differences. Concerning the student background characteristics in the Czech Republic, there are significant negative time-on-task effects for all groups except for students with an immigrant background and students with a high parental occupational status. There are no significant differences in Denmark. For Germany, a significant negative time-on-task effect can be found among girls. However, the other examined indicators for Germany are ambiguous. Conclusions The results show that process data can be used to explain differences in students’ CIL: In the Czech Republic and Germany, there is a correlation between response times and CIL (significant negative time-on-task effect). Further analysis should also consider other aspects of CIL (e.g. reading literacy). What becomes clear, however, is that when interpreting and explaining differences in competence, data should also be included that relates to the completion process during testing.

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“…Sex and gender differences in digital literacy [12], use [13,14] and preferences [15] of mHealth apps, as well as online health information seeking [16,17] have been previously reported. Overall, women tend to report more eHealth and mHealth usage compared to men, but this seemed to be limited to high-income countries [18].…”

Section: Introductionmentioning

confidence: 86%

An opportunity for patient-centered care: Results from a secondary analysis of sex- and gender-based data in mobile health trials for chronic medical conditions

et al. 2020

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Traditional medical practice has suffered from male bias, which can lead to sub-optimal treatment options for female patients and increase the incidence of severe side-effects in this population. Mobile health applications, mHealth apps, represent one essential component of the shift towards consumer-centered self-administered individualized health. To prevent sex-specific bias it is important that trials consider sex and gender when developing mHealth apps. We evaluated the inclusion and reporting of sex and gender at all levels in mHealth randomized controlled trials (RCTs). To this end, we conducted a secondary analysis of a large study database addressing the effectiveness of app interventions on clinical outcomes in patients with chronic medical conditions. We followed the 5 steps described in the framework by Arksey and O'Malley and the guidelines of the PRISMA-ScR. Of the 72 app-based RCTs which reported information about sex overall, 62 included individuals of both sexes. The concept of gender was not addressed in any of the studies. The consideration of sex aspects in the design, execution and reporting of mHealth RCTs was minimal or absent. To adequately address the health and preventative needs of the mHealth user population, sex and gender should be systematically included in the research, development and evaluation of mHealth applications.

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Introduction to Gender Differences in Computer and Information Literacy

Cited by 20 publications

References 28 publications

“Do You Think You Have What it Takes?” – Exploring Predictors of Pre-Service Teachers’ Prospective ICT Use

“Do You Think You Have What it Takes?” – Exploring Predictors of Pre-Service Teachers’ Prospective ICT Use

The relationship between differences in students’ computer and information literacy and response times: an analysis of IEA-ICILS data

An opportunity for patient-centered care: Results from a secondary analysis of sex- and gender-based data in mobile health trials for chronic medical conditions

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