Learning (Good Handwriting In Greek) By Teaching (A Humanoid Robot)

We report on a follow-up study of the Co-Writer project at EPFL [1]; we confirm their findings, extend the applicability to another language with a different alphabet (Greek) and go into an in-depth qualitative study of the child-robot relationship. The core idea of "learning by teaching" is that the student learns by undertaking to teach what they are supposed to learn which motivates them into ownership of the process. Although a highly effective method [2], there are serious practical obstacles in scaling learning by teaching to larger numbers or extending it to younger learners and to certain skills such as handwriting. This is where we enlist the assistance of a humanoid robot to help a young learner with her handwriting by assuming the role of the cacographer pupil who asks help from its human friend. The robot pretends writing mistakes similar to the child's own; the child recognizes the errors as such even when she would refuse to acknowledge them in her own writing, and makes an extra effort for better writing as the robot's instructor; the robot improves its writing; the child goes through another round of amelioration; and, hopefully, gets in the habit of better writing. In order to extend the original study for the Greek language and alphabet we first needed to collect data from beginner writers, children of 6-9 years. The nine-month study for collecting and evaluating handwriting samples from primary school students in Cyprus in order to examine and describe cacography for the Greek alphabet used a questionnaire, an evaluation sheet for the letter formation and copies of students' notebooks. It involved four primary schools in Limassol, Cyprus and a total of 68 students and 11 teachers. We were thus able to obtain a consensus on what constitutes poor letter writing in Greek. All writing samples were evaluated by teachers and were classified based on Chandra et al. [3] taxonomy. The qualitative research involved three case studies of children who held two sessions each with the humanoid programmable robot NAO. We video recorded the child-robot interactions and assessed their progress in handwriting. In all three cases, albeit not in the same degree, we saw that (a) the child-robot interaction quickly improved; the increasing number of correct remarks from all children in only two meetings shows the comfort that they gained with lab environment and the robot itself and (b) the correctness of children remarks and their comments about letters shows their ability to distinguish the correct from the wrong letters and to justify their answers. Both conclusions confirm the findings of the Co-Writer project [4]

Lehren und Lernen mit dem Computer. T. 1 Computereinsatz im Fachunterricht - Nutzung des Computers als Medium und Werkzeug

Copy held by FIZ Karlsruhe / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekSIGLEDEGerman

Risk factors for development of hemolytic uremic syndrome in a cohort of adult patients with STEC 0104:H4 infection.

The outbreak of Shiga toxin producing E.coli O104:H4 in northern Germany in 2011 was one of the largest worldwide and involved mainly adults. Post-diarrheal hemolytic uremic syndrome (HUS) occurred in 22% of STEC positive patients. This study's aim was to assess risk factors for HUS in STEC-infected patients and to develop a score from routine hospital parameters to estimate patient risks for developing HUS. In a cohort analysis, adult patients with STEC infection were included in five participating hospitals in northern Germany between May and July 2011. Clinical data were obtained from questionnaires and medical records, laboratory data were extracted from hospitals' electronic data systems. HUS was defined as thrombocytopenia, hemolytic anemia and acute renal dysfunction. Random forests and multivariate logistic regression were used to identify risk factors for HUS and develop a score using the estimated coefficients as weights. Among 259 adults with STEC infection, vomiting (OR 3.48,95%CI 1.88-6.53), visible blood in stools (OR 3.91,95%CI1.20-16.01), age above 75 years (OR 3.27, 95%CI 1.12-9.70) and elevated leukocyte counts (OR 1.20, 95%CI 1.10-1.31, per 1000 cells/mm(3)) were identified as independent risk factors for HUS. A score using these variables has an area under the ROC curve of 0.74 (95%CI 0.68-0.80). Vomiting, visible blood in stools, higher leukocyte counts, and higher age indicate increased risk for developing HUS. A score using these variables might help to identify high risk patients who potentially benefit from aggressive pre-emptive treatment to prevent or mitigate the devastating consequences of HUS

Laboratory values in patients without evidence of hemolytic uremic syndrome (HUS) at first presentation to health care center.

*<p>Mann-Whitney U test.</p