Abstract

With the proliferation of novel technology-infused learning environments, there is a need to further our understanding of their impact on learners, the learning process, and the learning outcomes for diverse student bodies in various study programs. Investigating gender differences in usage and attitudes towards different technologies is important because educational institutions, especially public ones, are seen by policy makers as structures that aim to reform societal inequalities.
The objective of this dissertation is to conduct a systematic review of the literature to establish the relationship between (a) gender and Information and Communication Technologies (ICTs) usage and (b) gender and attitudes towards the use of ICT, in the context of formal educational settings from elementary to postsecondary levels. This dissertation takes an in-depth look at ICT attitudes in learning by avoiding treating it as one indivisible construct. I subdivided the attitudinal construct into the different theoretical frameworks embedded in the literature related to technologies in pedagogical settings. These include Computer Anxiety, Negative Attitudes Towards ICT, Computer Confidence, Perceived Ease of Use of ICT, Perceived Usefulness of ICT, Perceived Satisfaction with ICT, Positive Attitudes Towards ICT, Motivation to Use ICT, Computer Self-efficacy, Intention to Use ICT, and Mixed Perceptions Towards ICT.
After a systematic literature review, I synthesized the results of 213 studies and used random-effects meta-analytic techniques to evaluate gender differences across students’ reported usage and attitudes towards ICT in learning. Findings of this dissertation reveal significant gender differences between female and male students’ reported usage of ICT and attitudes towards ICT in favor of males. Average effect sizes ranged from small to moderate. The highest average effect size belonged to the construct of Computer Confidence where male students typically reported higher confidence with computers, with .38 standard deviations above the female students. The lowest effect size belonged to the construct of Perceived Satisfaction with ICT where male students typically reported higher perceived satisfaction with ICT, with .05 standard deviations above the female students.
A number of contextual factors impacted the results of the outcomes to differing degrees. These include ‘research country’, ‘grade level of students’, ‘technology type surveyed’, ‘questionnaire used’, ‘ethnicities’, ‘subject matter’, ‘participation rate’, ‘sampling selectivity’, ‘competency’, ‘publication date’, ‘technology acceptance model’, ‘class context’, and ‘socioeconomic status’.
This dissertation concludes with educational implications and suggestions for future research investigating gender differences in students’ usage and attitudes towards ICT in learning. Considerable effort should be made by researchers to contextualize the studies as possible and as such, I recommend that gender should not be researched as a homogeneous independent variable. After all, gender is embedded in many other variables, in the same way that it is embedded in the many structures of society. Gender therefore needs to be researched with other intersecting demographics, including but not limited to participants’ home country, ethnicity, age, and socioeconomic background.

Intersectionality is a theory and a methodology that is suited to addressing the complexities of gender differences concerning the usage of and attitudes towards ICT. It imparts differences and particularities in social statuses in the hope of militating against those silent prejudices that result in social inequities. This theory allows us to inspect social demographic variables as they truly are: complex and interwoven. Adopting this theory does not mean that each study investigating gender differences needs to include all possible demographic variable interactions. However, it invites social scientists to be more comprehensive in their sampling selections and to be more aware of the complexity of social phenomena. Last but not least, intersectional methods require more than just an analysis of statistical interactions among social groups. They need to analyze the fundamental and significant impacts of these interactions.