Dr Ioulia Televantou is a researcher in quantitative social science, with a special interest in the application of advance quantitative techniques in large-scale, empirical driven research, seeking to assess peer effects and contextual influences on cognitive and affective domains in childhood and adolescence. I earned a 1st class honours in Pure Mathematics (University of Cyprus). I then went to Oxford where I completed an MSc in Applied Statistics – a degree with a focus on applications of Statistics using R programming language – and a second MSc in Educational Research Methodology. During my doctorate studies (Oxford University Department of Education, 2009-2014), I worked under the supervision of Herbert W. Marsh (Professor at Australian Catholic University, Emeritus Professor at Australian Catholic University and founder of the International SELF Research Centre). My research has so far received several awards and grants, among others, the 2015 Bruce Choppin Memorial award and the 2017 AERA travel award grant. In addition, it has been published in major scientific journals (SESI, Journal of Educational Psychology, Learning & Instruction) and it has attracted funding from major funding bodies (e.g. the Economic Social Research Council, UK and the Research Promotion Foundation, Cyprus). As well as doing research, I very much enjoy teaching Research Methodology and Quantitative Methods courses to both undergraduate and postgraduate students in Education, Psychology, and allied fields. I have extensive experience in teaching Distance Learning – as well as conventional courses.
Among other measures taken to cease the spread of coronavirus pandemic, higher education institutions have been forced to switch their mode of assessing students’ learning (e.g., final exams) from face-to-face to online. However, not all students are equal in terms of the skills required to navigate computerized educational spaces optimally – and this is especially the case for people form older generations (e.g. in continuous education programs). This may have serious consequences on the validity of the scores of students in online assessments. For instance, computer self-efficacy, a judgment of one’s ability to complete a task with the use of a computer is an important predictor of the extent to which learners feel anxiety when engaging in technology-supported learning environments and may also be related to their academic self-efficacy and academic performance in such environments.
Our study, aims in investigating whether mature university students’ computer self-efficacy and computer anxiety levels have an impact on their academic outcomes in an e-learning environment (academic self-efficacy and academic performance). The findings that we present are based on online survey of a convenient sample of ~ seventy adults studying for a graduate degree in Special Education at a private University in Cyprus.
All students denoted that they had access to at least one desktop or laptop computer, with three or more years of experience in using the corresponding device. Lower computer self-efficacy predicted lower academic self-efficacy (r= .505, p < .001) and higher computer anxiety (r = -.432, p < .01), while higher computer anxiety predicted lower academic self-efficacy (r = -.423, p < .01).
Although being only tentative, our findings provide insights on how digital inequalities among university students may lead to achievement gaps, the latter being related more to students’ computer self-efficacy and anxiety, rather than to students’ actual academic merit.