LAUSR

The Digital Competency Profiler (DCP) is an online application for surveying the technology preferences and abilities of students in higher education. To explore the DCP as a digital-learning-readiness tool, a mixed-methods research design was developed for relating self-reported digital competencies and online-learning activity. To this end, three authentic scenarios, comprised of six tasks mapped to self-report items, were constructed. Having submitted their survey data, each of 15 participants visited the EILAB to complete a randomly-assigned scenario with a tablet. Both the performance activity and post-activity interviews were recorded digitally using a unique activity-station setup, and task artefacts were gathered as performance outcomes. Analysis was conducted in three phases. In Phase 1, both the audio-video performance data and activity artefacts were coded, assessed and scored. Exploratory correlational analyses showed a pattern of positive relationships at the task and scenario levels for two scenario groups, suggesting some predictive value for the DCP in this context. For the third group, a positive correlation was found at the scenario level, but negative correlations were found at the task level. In Phase 2, detailed case-studies were conducted, incorporating self-report data, coded performance timelines, and post-activity interviews. Several situational influencers related to problem-solving strategy, device comfort, task difficulty and motivation, beyond the purview of the DCP, were identified. In Phase 3, the findings were interpreted to position the DCP as a tool for identifying segments of students with members who, without support, will likely struggle to engage fully in technology-rich learning environments.