Average Skill Score Research Articles

PEMBELAJARAN MENULIS TEKS PUISI MENGGUNAKAN METODE THINK TALK WRITE ( TTW) BERBANTUAN MEDIA AUDIO VISUAL PADA SISWA KELAS X SMK BINA INSAN BANGSA NGAMPRAH

This study aims to determine students’ interest in learning, especially in writing poetry texts. Students are very difficult in terms of developing an idea or ideas into written form. The methods used by the teacher are sometimes less attractive sometimes less effective. As for the purpose of this study: 1) to know the scenario and implementation in writing poetry texts with method think talk write based audio visual in class X student of SMK Bina Insan Bangsa ; 2) to determine the response of teachers and students in writing in writing poetry texts by method think talk write based media audio visual in class X student of SMK Bina Insan Bangsa; 3) to know the obstacles in writing poetry texts by method think talk write based media audio visual in class X student of SMK Bina Insan Bangsa. The method used is descriptive qualitative with samples student research in class X student of SMK Bina Insan Bangsa. Learning to write poetry texts by using the method think talk write assisted by media audio visual goes well scenarios and their implementation very suitable. Teacher and student against learning write excellent poetry texts. Difficulty from the lowest knowledge result 20 from 100 about disclosure and while the lowest average skill score is 65 less than 100 the contents of the language. From 37 students exist 26 students who get a value above average, KKM= 75 by percentage 95% very high category is declared passed.

Penerapan model Problem Based Learning dalam pembelajaran daring untuk meningkatkan hasil belajar siswa kelas VI di SD Negeri Mulyasari 03

This study aims to improve the learning outcomes of Grade VI students at SD Negeri Mulyasari 03 by applying the Problem Based Learning Model in Online Learning as an effort to improve and enhance the learning process. The research method used was Classroom Action Research, which included planning, acting, observing, and reflecting. The research was conducted in two cycles, each cycle carried out two meetings. The results showed that student learning outcomes improved. In the initial study, the average value was 67.08 with KKM 70 completeness of learning 18.51% after the implementation of the learning improvement in cycle I, the average knowledge value reached 76.67 and the percentage of completeness reached 66.77% and not yet completed 33.23 %. The attitude score for the very good category reached 29.17% and the good category reached 70.83%, and the average skill score reached 69.58 while the percentage of completion reached 54.17% and 45.83% incomplete. In the second cycle, it was found that the average knowledge value reached 77.08 and the percentage of completeness reached 87.50% and 13.50% incomplete. The attitude score of the very good category reached 41.67% and the good category reached 58.33%. The average skill score reached 72.08, while the percentage of completion reached 83.33% and 16.67% unfinished. Based on the data obtained, it can be concluded that using the Problem Based Learning model can improve the learning outcomes of grade VI students at SD Negeri Mulyasari 03, Majenang District.

Development and validation of a storm surge forecasting/hindcasting modelling system for the extensive Río de la Plata Estuary and its adjacent Continental Shelf

The Rio de la Plata (RdP) Estuary is affected by significant surges several times per year. This phenomenon has historically caused catastrophic water-level enlargements of up to 4.44 m, threatening and claiming human lives and producing major economic and material damages. The negative surges are less frequent, but when they do occur, inhibit the access to the principal harbors and waterways and disable the drinking water intakes of the Metropolitan Area of Buenos Aires (the Capital City of Argentina) with a population of more and 16 million people. Recent works suggest that the number and strength of the surge events have been increasing with time. Nevertheless, a state-of-the-art system for the forecast of those events is not available yet. In this work, the implementation of a numerical modelling system for the forecast/hindcast of storm surges and the associated currents in the RdP and the adjacent continental shelf are presented and validated. This pre-operational system is based on an adaptation of the CROCO community ocean model to solve the dynamics associated with the surge. The model was implemented using a set of routines written in open-source programming language (Linux and Python) to be cheap and efficient and to ensure an easy future transfer to the services responsible for the alerts. For a better representation of the regional atmospheric dynamics, wind speed and sea-level pressure used to force the simulations were corrected using direct observations collected at an oceanographic buoy anchored at the estuary. The model system performance in hindcast mode was quantified by comparison with observations from tidal gauges and current meters at several locations of the estuary and the adjacent shelf. Percent errors for water level over the whole estuary and currents in the intermediate and exterior estuary drove to average results of 8 and 13%, respectively. The skill scores resulted, on average, of 0.90 and 0.80, respectively. The model performance in both hindcast and forecast modes was evaluated during historical extreme storm surges. Results support the good performance of the model to simulate even extreme events with average skill scores of 0.97 and 0.92, respectively. Results are encouraging, particularly taking into account the limitations in the atmospheric forcing for the region, where only a relatively small number of direct observations are assimilated by the reanalysis and forecast models.

Meningkatkan Keaktifan dan Hasil Belajar Materi Himpunan melalui Model Pembelajaran Jigsaw Berbantuan Android

This study aims to improve the activeness as well as mathematics learning achievement on sets topic through the Jigsaw learning model, grade VII B students of SMP Negeri 12 Semarang odd semester of 2018/2019 academic year. The research process consists of two cycles, in which each cycle covers for steps namely planning, action, observation and reflection. The research data were in the form of observation sheet notes, test results, and assignment results. The type of collected data is qualitative and quantitative data. Technique of data collection applies documentation, observation and analysis of learning results. Research instruments cover score list, notes of teaching and learning journal, and observation sheet. Data validation is done by involving observer and colleagues involved during the collaboration. Data analysis was performed using descriptive comparative technique by comparing pre, first and second cycle data. This step was then followed with critical analysis by conducting the reflection. Previously, the average knowledge score of grade VII B students on set topic was 55, while the average skill score was 56. Later on, after the jigsaw learning model was applied, average of the knowledge score increased to 65.6 at the first cycle, and 81.3 at the second cycle. Meanwhile the average of skill score was increased to 71.9 at the first cycle and 83.6 at the second cycle. These results indicate that there is an increase at the mathematics learning achievement for grade VII B students. In addition, students’ activities are increasingly optimal; they show quite positive responses towards teaching and learning activity.

Medical faculty members\u2019 perception of smartphones as an educational tool

BackgroundThe rapid adoption of modern technology has changed many aspects of our life and communication; it has the power to influence and change the way we teach, learn and practice different types of professions mainly teaching and health care providing. Smartphone applications are increasingly becoming popular and widespread. Generally, these applications are likely to play a significant role in supporting education, in general, and medical education, in particular. This study aims at investigating how medical faculty members are using smartphones in medical education and practice, and how they perceive them as an educational tool at university level.MethodsThe researchers have distributed an online questionnaire - including three parts: a demographic part with five variables; a 15-item part of various applications of the smartphones; and a 14-item part measuring attitudes towards using these smartphones - among medical faculty members at two Palestinian universities.Setting and participantsMedical faculty members working at two Palestinian universities. Data have been collected from 30 participants out of 72 representing a response rate of 41.6%.ResultsThe average skills score with smartphones usage is (3.18) which tells that faculty members use smartphones to support their teaching practices. In general, faculty members are positive towards smartphones as a prospective teaching tool since the average attitude towards using smartphones is (3.60). The study results show no significant differences among faculty members based on the five demographic variables, i.e. university, title, department affiliation, gender, and years of experience.ConclusionIt seems that the majority of faculty members believe that smartphones would be a significant instrument as well as addition to their teaching practices.

PENGGUNAAN MODEL PEMBELAJARAN KOOPERATIF TIPE GROUP INVESTIGATION SEBAGAI UPAYA PENINGKATAN KETERAMPILAN MENGAMATI PADA MATERI TEMA 3 BENDA DISEKITARKU SISWA KELAS III SDN 20 CAKRANEGARA

This Classroom Action Research (CAR) was conducted at SDN 20 Cakranegara with the aim of increasing the value of students' skills, especially in the theme material 3 Objects around me through the use of a cooperative learning approach Type Group Investigation (GI). The type of research used is Classroom Action Research which consists of planning, implementation, observation, and reflection. The subjects of this study were 44 grade students of SDN 20 Cakranegara. PTK is carried out in two cycles. Cycle I consists of 3 meetings and cycle II consists of 2 meetings. The action in this study was to use a cooperative learning model type Group Investigation (GI). The value of student skills is obtained during the learning process in the form of performance appraisal at each meeting. Furthermore, the collected data were analyzed descriptively quantitatively. From the results of data analysis, it was found that the achievement of the skills of students in the first cycle was as follows; of 44 students as many as 34 students (77.27%) who obtained a value of ≥70 and as many as 10 people (20.73%) had not reached the value of ≥70. The average skill score of students in cycle I is 70.80. Cycle II of 44 students as many as 40 students (90.91%) who obtained a value of ≥70 and as many as 4 people (9.09%) had not reached the value of ≥70. The average skill score of the second cycle students is 86.70. The determined performance indicator is 85% of students obtain a skill score of ≥70 with the Good category. Thus it can be concluded that the cooperative learning model of the Group Investigation type can increase the value of the skills of third grade students of SDN 20 Cakranegara.

Simulation Based Learning in Selected Clinical Skills among Nursing Students in Selected Nursing College of Pune

Simulator METIman is considered high fidelity, prehospital/nursing modal to teach the fundamentals of nursing practice, which is a computerized manikin that stimulates the real life settings. Method: Quantitative research approach, Pre-experimental one group Pre test - Post test research design adopted for the study. The samples were 60 nursing students. Simple Random sampling technique was used. Tool included ; Demographic Proforma of the sample & Checklist was used to assess the skills on selected clinical skills. Reliability of tool was 0.86. Pretest followed by Simulation based learning by use of METIman that simulates with the control of computer, for performing the selected clinical skills i.e. Cardio Pulmonary Resuscitation, Tracheostomy suctioning, Auscultation of various normal and abnormal heart and lungs sounds and rate, rhythm of respiratory system; followed by Post test .Result: Majority of 57% of the student nurses had poor skill score, 42% of them had average skill score and only 2% of them had good skill score, Paired t-test applied. T-value was found to be -12.668 with 59 degrees of freedom. Corresponding p-value was found to be very small (of order of 0.001) the null hypothesis H0 is rejected and hence H1 is accepted, indicates simulation based learning had significantly improved the skill of the nursing students . Majority of nursing students are of excellent opinion regarding simulation based learning to enhance the clinical skill. Discussion: The findings of the present study revealed that simulation based learning is effective advanced technology to improve the clinical skill among nursing students . Similar findings were observed in study where use of simulation to teach Cardiopulmonary Resuscitation skills was effective as the number of attempts required by nursing students is less.

Projection of Future Extreme Precipitation and Flood Changes of the Jinsha River Basin in China Based on CMIP5 Climate Models.

Projecting future changes in extreme flood is critical for risk management. This paper presented an analysis of the implications of the Fifth Coupled Model Intercomparison Project Phase (CMIP5) climate models on the future flood in the Jinsha River Basin (JRB) in Southwest China, using the Xinanjiang (XAJ) hydrologic model. The bias-corrected and resampled results of the multimodel dataset came from the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP). Relatively optimal general circulation models (GCMs) were selected with probability density functions (PDFs)-based assessment. These GCMs were coupled with the XAJ model to evaluate the impact of climate change on future extreme flood changes in the JRB. Two scenarios were chosen, namely: a midrange mitigation scenario (Representative Concentration Pathway 4.5, RCP4.5) and a high scenario (RCP8.5). Results show that: (1) The XAJ model performed well in simulating daily discharge and was suitable for the study area, with ENS and R2 higher than 0.8; (2) IPSL-CM5A-LR and MIROC-ESM-CHEM showed considerable skill in representing the observed PDFs of extreme precipitation. The average skill scores across the total area of the JRB were 0.41 to 0.66 and 0.53 to 0.67, respectively. Therefore, these two GCMs can be chosen to analyze the changes in extreme precipitation and flood in the future; (3) The average extreme precipitation under 20- and 50-year return period across the JRB were projected to increase by 1.0–33.7% under RCP4.5 and RCP8.5 during 2020 to 2050. The Upper basin is projected to experience the largest increase in extreme precipitation indices, possibly caused by a warmer climate. The extreme flood under 20- and 50-year return period will change by 0.8 to 23.8% and −6.2 to 28.2%, respectively, over this same future period. Most of scenarios projected an increase during the near future periods, implying the JRB would be likely to undergo more flooding in the future.

Monthly and Seasonal Rainfall Forecasting in Southern Brazil Using Multiple Discriminant Analysis

Abstract A multiple discriminant analysis was employed to forecast monthly and seasonal rainfall in southern Brazil. The methodology used includes six steps: data acquisition, preprocessing, feature extraction, feature selection, classification, and evaluation. The predictors (atmospheric, surface, and oceanic variables) and predictand (rainfall) were obtained from the Twentieth Century Reanalysis (version 2), as well as from the HadISST1 (Met Office Hadley Centre) and Global Precipitation Climatology Centre (GPCC) databases. The definition of key regions (feature extraction step) was performed using spatial principal component analysis. In the selection step, the rainfall time series were allocated into terciles, which were related to the predictors via multiple discriminating analyses. The results revealed that ⅓ of the predictors are associated with atmospheric pressure and also emphasized the role of atmospheric circulation over the Antarctic region and its surroundings. Surface variables (albedo and soil moisture) were also of great importance in the forecasting. The average skill score (gain over climatology) was 29%. It is concluded that the proposed model is a reliable alternative for use in forecasting monthly and seasonal rainfall over southern Brazil.

Randomized, controlled trial of the effectiveness of simulation education: A 24-month follow-up study in a clinical setting

Critical care nurses' knowledge and skills in adhering to evidence-based guidelines for avoiding complications associated with intubation and mechanical ventilation are currently limited. We hypothesized that single simulation education session would lead to a long-lasting higher level of skills among critical care nurses. A randomized controlled trial was conducted in a 22-bed adult mixed medical-surgical intensive care unit in Finland during the period February 2012-March 2014. Thirty out of 40 initially randomized critical care nurses participated in a 24-month follow-up study. Behavior and cognitive development was evaluated through a validated Ventilator Bundle Observation Schedule and Questionnaire at the baseline measurement and repeated 3 times during simulation and real-life clinic settings. After simulation education, the average skills score increased from 46.8%-58.8% of the total score in the final postintervention measurement (Ptime < .001, Ptime × group = .040, and Pgroup = .11). The average knowledge scores within groups did not change significantly. The average between-group difference in skills scores was significant only at the measurement taken at 6 months (P = .006). Critical care nurses' skills in adhering to evidence-based guidelines improved in both groups over time, but the improvements between the study groups was significantly different only at 6 months and was no longer evident after 2 years following a single simulation education.

On the value of combining different modelled soil moisture products for European drought monitoring

summary In the context of evaluating the occurrence of drought events over Europe, soil moisture maps provide an invaluable resource to quantify the effects of rainfall deficits on vegetated lands. Spatially distributed models represent one of the main options, alongside satellite remote sensing, to successfully monitor this quantity over large areas in a cost effective way. This work has the double aim of: (i) intercomparing three soil moisture outputs obtained by different land-surface models (LISFOOD, CLM and TESSEL) through long (at least 6 years of data between 2001 and 2011) in-situ measured datastreams, and (ii) quantifying the added value of combining the estimates of these three models by means of a simple ensemble approach. Generally, the three models return similar soil moisture anomalies over most of Europe, with few notable exceptions during summer in Mediterranean regions. The comparison with in-situ data suggests no substantial differences among the models, with LISFLOOD slightly outperforming the other two in terms of correlation as also supported by a pairwise comparison. The combined soil moisture anomalies obtained via the ensemble-mean approach are characterized by an increase of both the correlation and the accuracy in retrieving extreme events compared to the single models; however, the number of observed extreme events actually captured by the ensemble model does not increase significantly if compared to the single models. Overall, the ensemble model results are skillful, with an all site average skill score of about 0.4.

Assessment of essential newborn care services in secondary-level facilities from two districts of India.

India faces a formidable burden of neonatal deaths, and quality newborn care is essential for reducing the high neonatal mortality rate. We examined newborn care services, with a focus on essential newborn care (ENC) in two districts, one each from two states in India. Nagaur district in Rajasthan and Chhatarpur district in Madhya Pradesh were included. Six secondary-level facilities from the districts-two district hospitals (DHs) and four community health centres (CHCs) were evaluated, where maximum institutional births within districts were taking place. The assessment included record review, facility observation, and competency assessment of service providers, using structured checklists and sets of questionnaire. The domains assessed for competency were: resuscitation, provision of warmth, breastfeeding, kangaroo mother care, and infection prevention. Our assessments showed that no inpatient care was being rendered at the CHCs while, at DHs, neonates with sepsis, asphyxia, and prematurity/low birthweight were managed. Newborn care corners existed within or adjacent to the labour room in all the facilities and were largely unutilized spaces in most of the facilities. Resuscitation bags and masks were available in four out of six facilities, with a predominant lack of masks of both sizes. Two CHCs in Chhatarpur did not have suction device. The average knowledge score amongst service providers in resuscitation was 76% and, in the remaining ENC domains, was 78%. The corresponding average skill scores were 24% and 34%, highlighting a huge contrast in knowledge and skill scores. This disparity was observed for all levels of providers assessed. While knowledge domain scores were largely satisfactory (> 75%) for the majority of providers in domains of kangaroo mother care and breastfeeding, the scores were only moderately satisfactory (50-75%) for all other knowledge domains. The skill scores for all domains were predominantly non-satisfactory (< 50%). The findings underpin the need for improving the existing ENC services by making newborn care comers functional and enhancing skills of service providers to reduce neonatal mortality rate in India.

Human patient simulation education in the nursing management of patients requiring mechanical ventilation: A randomized, controlled trial

Knowledge among critical care nurses and their adherence to evidence-based guidelines for preventing ventilator-associated pneumonia is reported to be low. The aim of our study was to evaluate the effectiveness of human patient simulation (HPS) education in the nursing management of patients requiring mechanical ventilation. A prospective, parallel, randomized controlled trial with repeated measurements was conducted in a 22-bed adult mixed medical-surgical intensive care unit in Finland from February-October 2012. Thirty critical care nurses were allocated evenly to intervention and control groups (n = 15 each). The effectiveness of HPS education was evaluated through the validated Ventilator Bundle Questionnaire and Ventilator Bundle Observation Schedule at baseline and repeated twice-after the clinical and simulation settings, respectivley. After HPS education, the average skill scores (Ventilator Bundle Observation Schedule) in the intervention group increased significantly (46.8%-60.0% of the total score) in the final postintervention observation. In the average skill scores, a linear mixed model identified significant time (Pt < .001) and group (P(g) = .03) differences and time-group interactions (P(t*g) = .02) between the study groups after the HPS education. In contrast, the model did not identify any significant change over time (P(t) = .29) or time-group interactions (P(t) = .69) between groups in average knowledge scores (Ventilator Bundle Questionnaire). Our study identified significant transfer of learned skills to clinical practice following HPS education but no influence on the level of participants' factual knowledge.

Introduction of structured physical examination skills to second year undergraduate medical students

Introduction: Effective learning of physical examination skills (PES) requires suitable teaching and learning techniques and assessment methods. The Tribhuvan University (Nepal) curriculum recommends involving the departments of Medicine and Surgery in PES training (PEST) for second year students as a part of early clinical exposure. The project was developed to make teaching/learning of PES structured, involving eight clinical sciences departments and using appropriate methods for teaching and assessment in KIST Medical College, Nepal. Methods: Irby’s three stages of clinical teaching model (Preparation, Teaching, Reflection), was applied for teaching. Skill acquisition was based on Millers’ learning pyramid at “show how level” and Dreyfus’ competency model at “competent level”. Teaching/learning was conducted in small groups. A tutorial, demonstration and practice (TDS) model was developed for teaching/learning techniques based on a simple five-step method for teaching clinical skills. Assessment of effectiveness of training was done at “reaction level” as per Kirkpatrick’s model based on students’ feedback, “shows how level” as per Miller’s pyramid of learning by OSCE and “competent level” as per Dreyfus’ model using retro-pre questionnaire. Results: The analysis of retro-pre questionnaire based on the Dreyfus model found the average skill score (max score 184), before the introduction of the project module as 15.9 (median = 13.5) and after as 116.5 (median = 116). A paired t-test showed the difference to be statistically significant (100.5&plusmn;23 and 95% CI 95.45 – 105.59). The average overall feedback score for the students on PES training based on seven items on a five point Likert scale was found to be 4.30. The mean total objective structured clinical examination (OSCE) score was 3.77 (SD+/- 0.33) out of 5; 80% of students scored more than 70%. Conclusion: Students learned most of the skills with the implementation of the structured PES module and did well in the OSCE. Students and faculty were satisfied with the training and assessment.

Introduction of structured physical examination skills to second year undergraduate medical students

Introduction: Effective learning of physical examination skills (PES) requires suitable teaching and learning techniques and assessment methods. The Tribhuvan University (Nepal) curriculum recommends involving the departments of Medicine and Surgery in PES training (PEST) for second year students as a part of early clinical exposure. The project was developed to make teaching/learning of PES structured, involving eight clinical sciences departments and using appropriate methods for teaching and assessment in KIST Medical College, Nepal. Methods: Irby’s three stages of clinical teaching model (Preparation, Teaching, Reflection), was applied for teaching. Skill acquisition was based on Millers’ learning pyramid at “show how level” and Dreyfus’ competency model at “competent level”. Teaching/learning was conducted in small groups. A tutorial, demonstration and practice (TDS) model was developed for teaching/learning techniques based on a simple five-step method for teaching clinical skills. Assessment of effectiveness of training was done at “reaction level” as per Kirkpatrick’s model based on students’ feedback, “shows how level” as per Miller’s pyramid of learning by OSCE and “competent level” as per Dreyfus’ model using retro-pre questionnaire. Results: The analysis of retro-pre questionnaire based on the Dreyfus model found the average skill score (max score 184), before the introduction of the project module as 15.9 (median = 13.5) and after as 116.5 (median = 116). A paired t-test showed the difference to be statistically significant (100.5±23 and 95% CI 95.45 – 105.59). The average overall feedback score for the students on PES training based on seven items on a five point Likert scale was found to be 4.30. The mean total objective structured clinical examination (OSCE) score was 3.77 (SD+/- 0.33) out of 5; 80% of students scored more than 70%. Conclusion: Students learned most of the skills with the implementation of the structured PES module and did well in the OSCE. Students and faculty were satisfied with the training and assessment.

Implementing and designing self-care ability exam plan in discharged peritoneal dialysis patients

Objective To design self-care ability exam plan in discharged peritoneal dialysis (PD)patients and analysis its outcome.Methods A total of 43 discharged PD patients were selected by convenience sampling method,patients' PD related knowledge and skill was assessed using self-developed “PD knowledge evaluation form” and “skill of exchange liquid evaluation form”,then they were given individualized specify training.After 6 months,their self-care abilities were evaluated using “ PD patients' self-care ability questionnaire” designed by the researcher group.The correlation between their self-care ability and their PD related knowledge and skill was analyzed.Results The highest knowledge score of 43 discharged PD patients was 89 and the lowest was 33,and the average score was (59.43 ± 16.06).The average skill score of 43 discharged PD patients was (71.79 ±7.62),with the highest score of 85 and the lowest score of 60.PD patients had a good master of recording,goods preparation and diet,while their attention on the complications was poor.For the skill test,they mastered the skill of irrigation and perfusion.The self-care ability score of PD patients was (155.72 ± 10.42) and PD patients' self-care ability scores were positively correlated with their knowledge and skill scores (r ＝ 0.637,0.566,respectively ; P ＜ 0.01).Conclusions The implementation of self-care ability exam for outpatients PD patients can identify weak points of patients' knowledge and skills and categorize patients into different levels.Individual training plan can be developed and implemented to improve their selfcare abilities. Key words: Peritoneal dialysis; Self-care ability; Individualized specify training

Soft computing techniques in ensemble precipitation nowcast

This study presented various soft computing techniques for forecasting the hourly precipitations during tropical cyclones. The purpose of the current study is to present a concise and synthesized documentation of the current level of skill of various models at precipitation forecasts. The techniques involve artificial neural networks (ANN) comprising the multilayer perceptron (MLP) with five training methods (denoted as ANN-1, ANN-2, ANN-3, ANN-4, and ANN-5), and decision trees including classification and regression tree (CART), Chi-squared automatic interaction detector (CHAID), and exhaustive CHAID (E-CHAID). The developed models were applied to the Shihmen Reservoir Watershed in Taiwan. The traditional statistical models including multiple linear regressions (MLR), and climatology average model (CLIM) were selected as the benchmarks and compared with these machine learning. A total of 157 typhoons affecting the watershed were collected. The measures used include numerical statistics and categorical statistics. The RMSE criterion was employed to assess the suitable scenario, while the categorical scores, bias, POD, FAR, HK, and ETS were based on the rain contingency table. Consequently, this study found that ANN and decision trees provide better prediction compared to traditional statistical models according to the various average skill scores.

Generation of Ensemble Streamflow Forecasts Using an Enhanced Version of the Snowmelt Runoff Model1

Harshburger, Brian J., Von P. Walden, Karen S. Humes, Brandon C. Moore, Troy R. Blandford, and Albert Rango, 2012. Generation of Ensemble Streamflow Forecasts Using an Enhanced Version of the Snowmelt Runoff Model. Journal of the American Water Resources Association (JAWRA) 48(4): 643‐655. DOI: 10.1111/j.1752‐1688.2012.00642.xAbstract: As water demand increases in the western United States, so does the need for accurate streamflow forecasts. We describe a method for generating ensemble streamflow forecasts (1‐15 days) using an enhanced version of the snowmelt runoff model (SRM). Forecasts are produced for three snowmelt‐dominated basins in Idaho. Model inputs are derived from meteorological forecasts, snow cover imagery, and surface observations from Snowpack Telemetry stations. The model performed well at lead times up to 7 days, but has significant predictability out to 15 days. The timing of peak flow and the streamflow volume are captured well by the model, but the peak‐flow value is typically low. The model performance was assessed by computing the coefficient of determination (R2), percentage of volume difference (Dv%), and a skill score that quantifies the usefulness of the forecasts relative to climatology. The average R2 value for the mean ensemble is &gt;0.8 for all three basins for lead times up to seven days. The Dv% is fairly unbiased (within ±10%) out to seven days in two of the basins, but the model underpredicts Dv% in the third. The average skill scores for all basins are &gt;0.6 for lead times up to seven days, indicating that the ensemble model outperforms climatology. These results validate the usefulness of the ensemble forecasting approach for basins of this type, suggesting that the ensemble version of SRM might be applied successfully to other basins in the Intermountain West.

Comments on “Finite Samples and Uncertainty Estimates for Skill Measures for Seasonal Prediction”

Different skill measures present differing dependence on the intrinsic predictability level as well as differing dependence on sample size. Kumar (2009) computed the expected skill of idealized forecasts with varying levels of predictability using the anomaly correlation (AC), the Heidke skill score (HSS), and the ranked probability skill score (RPSS) as skill measures. An important consideration for seasonal climate forecasts, as demonstrated by Kumar (2009), is that these skill measures may vary significantly from their expected values when they are computed from relatively short forecast histories. In carrying out his skill measure characterizations, Kumar (2009) assumed that the forecast variance was equal to the climatological variance. Additionally, when computing average skill scores, forecast distributions were assumed to have identical means (signals) for a given predictability level. Here we examine some implications of those assumptions. This comment is organized as follows. In section 2 we present a perfect model framework for examining predictability. A natural requirement for predictability is that the forecast and climatological distributions be different. In the case of joint normal distributions, the existence of predictability (positive signal variance) implies that the forecast variance is less than the climatological variance. In this case, inflating the forecast variance to be equal to the climatological variance results in underconfident forecasts and lower probabilistic skill scores. In section 3 we compute the three skill scores for a given forecast signal (single initial condition) and for a set of forecasts with a specified signal to noise variance ratio (multiple initial conditions). The expected skill of a single forecast depends on both signal level and forecast variance. The AC depends on the ratio of squared signal to forecast variance, while the dependence of HSS and RPSS on signal level and forecast variance is more complex. A consequence of this functional dependence is that the AC of a set of forecasts is equal to that of a single forecast with the signal equal to the signal standard deviation. However, there is no similar relation for HSS and RPSS, and assuming a fixed signal as in Kumar (2009) generally overestimates HSS and always overestimates RPSS. We also present a useful approximation relating the RPSS and AC of a set of forecasts.

The effect of interrupted 5-day training on Integrated Management of Neonatal and Childhood Illness on the knowledge and skills of primary health care workers

The conventional 8-day Integrated Management of Neonatal and Childhood Illness (IMNCI) training package poses several operational constraints, particularly due to its long duration. A 5-day training package was developed and administered in an interrupted mode of 3 days and 2 days duration with a break of 4 days in-between, in a district of Haryana state in northern India. Improvement in the knowledge and skills of 50 primary health care workers following the interrupted 5-day training was compared with that of 35 primary health care workers after the conventional 8-day IMNCI training package. The average score increased significantly (P < 0.05) from 46.3 to 74.6 in 8-day training and from 40.0 to 73.2 in 5-day training. Knowledge score improved for all health conditions, like anaemia, diarrhoea, immunization, malnutrition, malaria, meningitis and possible severe bacterial infection, and for breastfeeding in 8-day as well as in 5-day training. Average skills score for respiratory problems increased from 38 to 57 in 8-day training and from 41 to 91 in 5-day training. Corresponding increases in skill scores for diarrhoea assessment were from 28 to 67 and 48 to 75, and for breastfeeding assessment from 33 to 84 and 42 to 86 in 8-day and 5-day training, respectively. Average counselling skill score also rose from 42 to 89 in 8-day and from 37 to 70 in 5-day training. A direct cost saving of US$813 for a batch of 25 trainees and an indirect cost saving of 3 days per trainee and resource person makes the interrupted 5-day IMNCI training more cost-effective.