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The purpose of this paper is to examine how a clinical interview protocol with failure artifact scenarios can capture changes in high school students’ explanations of troubleshooting processes in physical computing activities. The authors focus on physical computing, as finding and fixing hardware and software bugs is a highly contextual practice that involves multiple interconnected domains and skills.

This paper developed and piloted a “failure artifact scenarios” clinical interview protocol. Youth were presented with buggy physical computing projects over video calls and asked for suggestions on how to fix them without having access to the actual project or its code. Authors applied this clinical interview protocol before and after an eight-week-long physical computing (more specifically, electronic textiles) unit. They analyzed matching pre- and post-interviews from 18 students at four different schools.

The findings demonstrate how the protocol can capture change in students’ thinking about troubleshooting by eliciting students’ explanations of specificity of domain knowledge of problems, multimodality of physical computing, iterative testing of failure artifact scenarios and concreteness of troubleshooting and problem-solving processes.

Beyond tests and surveys used to assess debugging, which traditionally focus on correctness or student beliefs, the “failure artifact scenarios” clinical interview protocol reveals student troubleshooting-related thinking processes when encountering buggy projects. As an assessment tool, it may be useful to evaluate the change and development of students’ abilities over time.

This study aims to enhance our understanding of customer expectations and experiences in grocery shopping within the metaverse. It investigates factors influencing customer satisfaction and driving continued engagement with metaverse platforms, offering insights into the drivers of customer adoption and barriers to usage.

Adopting a qualitative netnographic approach, this study analysed customer reactions to Walmart’s virtual store demonstration. Data were collected from user comments on YouTube, TikTok, Twitter and Reddit. Thematic analysis was employed to identify key factors contributing to satisfaction and dissatisfaction with metaverse grocery shopping experiences.

The study reveals three major drivers shaping customer satisfaction and subsequent positive intentions toward grocery shopping in the metaverse: social, functional and hedonic stimuli. Eight critical barriers affecting the metaverse shopping experience are identified: functional, hedonic, social, financial, privacy, safety, ownership and store atmospherics concerns, including tactile, acoustic and visual elements.

The findings are derived from a qualitative analysis of customer comments on social media platforms, which may limit generalisability. Future studies could adopt a mixed-methods approach to validate these findings across broader datasets.

This work is the first research to examine customer satisfaction with grocery shopping in the metaverse. It offers valuable insights into customer expectations, adoption drivers and critical barriers, laying the groundwork for further exploration of metaverse applications in retail.