Abstract:

Technologically-focussed vocations, like Engineering, require that students entering the programme have high levels of technologically literacy. But students entering South African universities have varying levels of technological literacy, with a number of them being “technologically phobic”, having implications for students’ success rates at university, as well as university lecturers who teach technical programmes to possibly adjust their teaching style. Given this, it has become increasingly necessary to determine students’ technological literacy levels before entering university. This article describes the development and validation of an instrument – the Technological Profile Inventory (TPI) – used to determine first year university students’ levels of technological literacy.
The TPI was developed from an initial study, where categories describing technological literacy were developed using phenomenography. Technological literacy was defined by two main categories, namely, how students conceive technology and how they interact with technology. Each category was defined by rigorously developed statements from the interview data of students. In total there were 41 statements. The 41 statements, together with students’ biographical information, were formatted into a questionnaire, the TPI. The questionnaire was piloted with university Engineering, Commerce and Arts students. The data were analysed to determine the validity and reliability of the TPI, in terms of its factor structure and internal consistency reliability. The factor structure aligned with the phenomenographic categories determined in the initial study, and the scales were named accordingly: Artefact, Process, Direction, Instruction, Tinkering and Engaging. All items had a factor loading of at least 0.30. The internal consistency reliability was satisfactory, suggesting that the TPI is reliable and valid and can be used with confidence by educators and researchers. Further data analysis suggested that the TPI can differentiate groups of students in terms of their technological literacy. A cohort analysis between Engineering, Commerce and Arts students, using multivariate analysis of variance (MANOVA), suggests that the instrument does collect useful data that can be used to differentiate between students from the three different faculties, which could be useful as a selection tool for university admission to technical programmes.

Keywords:

Technological literacy, phenomenography, engineering.