Learning technology with beginner-friendly software: design students' on attitude towards software alternatives

When teachers introduce a new type of technology, they often choose a beginner-friendly software option. The aim of the current study was to investigate whether and how design students' perception towards a beginner-friendly software influences their perception, attitude, and intention to learn other more advanced software. Based on the Technology Acceptance Model, we proposed and tested correlations between students' perception towards beginner-friendly software and their perceptions of other software in the same category. To introduce computational tools for conducting big-data research, we developed a beginner-friendly software called Onion, which allows design students to use computational tools such as data retrieval from social media and artificial-intelligence-based object recognition through a graphical user interface. We conducted two introductory workshops, and captured students' perception towards Onion and their perception and intention to learn more advanced computational tools with a questionnaire. The results indicated that learners' perceived usefulness of the beginner-friendly software has strong and positive correlations with their perceived usefulness and learning intention of other software alternatives. This suggests that introducing new technologies with beginner-friendly software can influence learners' perception towards and intention to learn other similar but less beginner-friendly software packages. Theoretical and practical implications are discussed.