Visualizing the Cascade Effect of Redesigning Features in an EMR System

Electronic Medical Record (EMR) systems are complex systems with interdependent features. Redesigning one feature of the system can create a cascade effect affecting the other features. By calculating the cascade effect, the designers can understand how each individual feature could be affected. This understanding allows them to maximize the positive effects and avoid negative consequences of their redesign activities. To understand the cascade effect, the designers can look at their computations’ results; a task that becomes more difficult when the number of features grows. To reduce their task load, we propose a tool for visualizing the cascade effect of redesigning features in an EMR system. Our preliminary evaluation with six graduate students shows that visualizing the cascade effect reduces the task load and slightly improves their performance when analyzing the cascade effect. Ways for improving the tool include (i) showing the computation results within the visualization, and (ii) allowing the designers to compare the cascade effect generated by redesigning different features

Language Learning Tool for Refugees

A large number of refugees need to learn a new language in order to transition to, or settle in, a new country. Most refugees have access to smartphones with which they can access mobile language learning tools. However, refugees in different stages of their journeys have different language learning needs. Identifying the unique needs of refugees is essential to design language learning tools that support their language learning activities. Through a two-part participatory design study, we identify and compare the tacit and latent language learning needs of two different groups of Syrian refugees: a group in transition in Lebanon, and a group settling in Germany. The Syrian refugees we worked with in Lebanon are studying English to transition to another country with better living conditions. On the other hand, the Syrian refugees we worked with in Germany are trying to learn German to better integrate into German society. Our results show overlapping needs and specific needs for the two groups of refugees. We present our findings and discuss the opportunities and challenges for designing language learning tools to support the language learning activities of refugees.Peer Reviewe

Emergency Online Learning in Low-Resource Settings: Effective Student Engagement Strategies

We aim to identify the engagement strategies that higher education students, engaging in emergency online learning in low-resource settings, perceive to be effective. We conducted a sequential mixed-methods study based on Moore’s interaction framework for distance education. We administered a questionnaire to 313 students engaging in emergency online learning in low-resource settings to examine their perceptions of different engagement strategies. Our results showed that student–content engagement strategies, e.g., screen sharing, summaries, and class recordings, are perceived as the most effective, closely followed by student–teacher strategies, e.g., Q and A sessions and reminders. Student–student strategies, e.g., group chat and collaborative work, are perceived as the least effective. The perceived effectiveness of engagement strategies varies based on the students’ gender and technology access. To support instructors, instructional designers, and researchers, we propose a 10-level guide for engaging students during emergency online classes in low-resource settings

Convalescent plasma in patients admitted to hospital with COVID-19 (RECOVERY): a randomised controlled, open-label, platform trial

SummaryBackground Azithromycin has been proposed as a treatment for COVID-19 on the basis of its immunomodulatoryactions. We aimed to evaluate the safety and efficacy of azithromycin in patients admitted to hospital with COVID-19.Methods In this randomised, controlled, open-label, adaptive platform trial (Randomised Evaluation of COVID-19Therapy [RECOVERY]), several possible treatments were compared with usual care in patients admitted to hospitalwith COVID-19 in the UK. The trial is underway at 176 hospitals in the UK. Eligible and consenting patients wererandomly allocated to either usual standard of care alone or usual standard of care plus azithromycin 500 mg once perday by mouth or intravenously for 10 days or until discharge (or allocation to one of the other RECOVERY treatmentgroups). Patients were assigned via web-based simple (unstratified) randomisation with allocation concealment andwere twice as likely to be randomly assigned to usual care than to any of the active treatment groups. Participants andlocal study staff were not masked to the allocated treatment, but all others involved in the trial were masked to theoutcome data during the trial. The primary outcome was 28-day all-cause mortality, assessed in the intention-to-treatpopulation. The trial is registered with ISRCTN, 50189673, and ClinicalTrials.gov, NCT04381936.Findings Between April 7 and Nov 27, 2020, of 16 442 patients enrolled in the RECOVERY trial, 9433 (57%) wereeligible and 7763 were included in the assessment of azithromycin. The mean age of these study participants was65·3 years (SD 15·7) and approximately a third were women (2944 [38%] of 7763). 2582 patients were randomlyallocated to receive azithromycin and 5181 patients were randomly allocated to usual care alone. Overall,561 (22%) patients allocated to azithromycin and 1162 (22%) patients allocated to usual care died within 28 days(rate ratio 0·97, 95% CI 0·87–1·07; p=0·50). No significant difference was seen in duration of hospital stay (median10 days [IQR 5 to >28] vs 11 days [5 to >28]) or the proportion of patients discharged from hospital alive within 28 days(rate ratio 1·04, 95% CI 0·98–1·10; p=0·19). Among those not on invasive mechanical ventilation at baseline, nosignificant difference was seen in the proportion meeting the composite endpoint of invasive mechanical ventilationor death (risk ratio 0·95, 95% CI 0·87–1·03; p=0·24).Interpretation In patients admitted to hospital with COVID-19, azithromycin did not improve survival or otherprespecified clinical outcomes. Azithromycin use in patients admitted to hospital with COVID-19 should be restrictedto patients in whom there is a clear antimicrobial indication

インフォーマル学習環境における学習者中心の語彙学習支援システムに関する研究

付記する学位プログラム名: デザイン学大学院連携プログラム京都大学0048新制・課程博士博士(情報学)甲第22577号情博第714号新制||情||122(附属図書館)京都大学大学院情報学研究科社会情報学専攻(主査)教授 緒方 広明, 教授 守屋 和幸, 教授 黒田 知宏学位規則第4条第1項該当Doctor of InformaticsKyoto UniversityDFA

Emergency remote teaching in low-resource contexts: How did teachers adapt?

28th International Conference on Computers in Education, 23-27 November 2020, Web conference.The COVID-19 pandemic forced students and teachers to engage in emergency remote learning. Remote learning is particularly challenging for students and teachers in lowresource contexts. We aim to analyze the adaptation process of teachers who engaged in remote emergency teaching in low-resource contexts. We conduct ten interviews with teachers who provided emergency online teaching in Lebanon. We show that there was a decrease in synchronous student-teacher, student-content, and student-student interactions due to the scarcity of resources. We also show how the teachers adapted their practice to cope with these challenges, and how their adaptation process increased asynchronous student-teacher and student-content interactions

Learning false friends across contexts

LAK’18: 8th International Learning Analytics and Knowledge (LAK) Conference, SMC Conference & Function Centre in Sydney, Australia on March 5–9, 2018.False friends are words in two languages that look or sound similar but differ significantly in meaning in some or all contexts. False friends are confusing for language students and could result in frustration and communication problems. This paper proposes a method to diagnose and prevent false friends mistakes based on students’ past learned words, current location and time. The proposed method uses records from the SCROLL system (System for Capturing and Reminding Of Learning Log) to analyze the previous activity of students. We assume that the past activity of a student can be used to predict the meaning intended by the student when looking up a polysemous word. The identification of the intended meaning in the student's current context is then used to provide the student with the appropriate translation, warnings and quizzes, possibly improving the learning process and avoiding false friends future mistakes