As part of a larger research agenda to explore web development as a context for learning computational literacy skills, we investigate errors people make while writing code in HTML and CSS. We report on a lab-based study in which 20 participants were video recorded as they completed coding tasks. We have applied the skills-rules-knowledge framework to segment this data by the cognitive causes of errors they made, and present a taxonomy of these errors. Our findings demonstrate how the skills-rulesframework can be used to analyze coding errors, provide insight about the origins of these errors, and suggest ways that the design of web development tools can be improved to support learning and practice with HTML and CSS.

We examine nursing documentation on a newly implemented electronic flowsheet in medical resuscitations to identify the temporal patterns of documentation and how the recorded information supported time-critical teamwork. To determine when the information was documented, we compared timestamps from 58 flowsheet logs to those of verbal communications derived from video review. We also drew on observations of 95 resuscitations to understand the behaviors of nurse documenters. We found that only 8% of the verbal reports were documented in near real-time (one minute within the verbal report), while 42% of reports were not documented in the electronic flowsheet. In addition, 38% were documented early (before the verbal report) and 12% were documented with a delay, ranging from one to 58 minutes after the report. Our study showed that the electronic flowsheet design posed many challenges for realtime documentation, leading to paper-based workarounds and the use of free-text fields on the flowsheet to visualize and keep track of time, and to communicate temporal information to the team. These findings suggest that documenters shape the temporal rhythms of not only their own work but also the rhythms of the electronic record and medical process. We discuss the implications of these rhythms for EHR redesign to support real-time documentation in high-risk, safety-critical settings. CCS CONCEPTS • Human-centered computing~Field studies • Humancentered computing~Empirical studies in HCI

Objective: Despite growing use of electronic health records, many resuscitation settings still use paper-based documentation. The fast-paced and safety-critical nature of trauma and medical resuscitation environments pose challenges for real-time documentation. This study aims to understand paper-based documentation practices and inform the design of efficient electronic documentation solutions for supporting safety-critical medical processes.Methods: Data were collected through in situ observations of nurse documenters during resuscitation events and postevent interviews with nurses. These data were analyzed using frequency distribution and qualitative, open-coding techniques. Data analysis focused on the following 3 main documentation factors: temporal distribution of documentation, total number of filled out sections on the paper flow sheet across all resuscitations, and completeness of documentation per resuscitation.Results: Findings from this study highlight the time-critical nature of these settings, showing that 74% of the documentation was completed within the first 15 minutes of the resuscitation. Some sections of the paper flow sheet were filled out more than others, and a few sections were left incomplete across all events. Interviews with nurses provided insight about documentation experiences in a fast-paced environment, including variable usage of flow sheet based on nurse experience level and patient scenarios, supplemental documentation mechanisms, and information needs and preferences.Conclusions: Several design implications are discussed to inform the design of effective electronic documentation systems. Design implications focus on layout structure, prepopulating items, section placement, and completion status of the flow sheet. Future plans for research focus on combining video review with in situ observations and conducting detailed interviews with nurses to better understand their documentation experiences and preferences.

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We analyzed the nature of verbal communication among team members in a dynamic medical setting of trauma resuscitation to inform the design of a speech-based automatic activity recognition system. Using speech transcripts from 20 resuscitations, we identified common keywords and speech patterns for different resuscitation activities. Based on these patterns, we developed narrative schemas (speech “workflow” models) for five most frequently performed activities and applied linguistic models to represent relationships between sentences. We evaluated the narrative schemas with 17 new cases, finding that all five schemas adequately represented speech during activities and could serve as a basis for speech-based activity recognition. We also identified similarities between narrative schemas of different activities. We conclude with design implications and challenges associated with speech-based activity recognition in complex medical processes.