The American steel worker; a twenty-five years' experience in the selection, annealing, working, hardening and tempering of various kinds and grades of steel,

Mode of access: Internet.

Beitrage zur Theorie der Singularitaten der algebraischen Linien-Complexe beliebigen Grades.

Thesis (doctoral)--Konigliche Ludwig-Maximilians-Universitat Munchen.

Les anciennes universités et la collation des grades.

Includes bibliography.

A Basic book collection for elementary grades.

Mode of access: Internet.

Grades and standards for nursery plants.

Cover title.

Books for adult beginners, grades I to VII

Mode of access: Internet.

Mathematics for the elementary school [grades 4-6]

Each grade consists of a set of 3 v. (pt.1, Text [1 v.]--pt.2, Teacher's commentary [2 v.]).

Special method in reading the grades, including the oral treatment of stories and the reading of classics,

Mode of access: Internet.

Typing mineral deposits using their grades and tonnages in an artificial neural network

A test of the ability of a probabilistic neural network to classify deposits into types on the basis of deposit tonnage and average Cu, Mo, Ag, Au, Zn, and Pb grades is conducted. The purpose is to examine whether this type of system might serve as a basis for integrating geoscience information available in large mineral databases to classify sites by deposit type. Benefits of proper classification of many sites in large regions are relatively rapid identification of terranes permissive for deposit types and recognition of specific sites perhaps worthy of exploring further. Total tonnages and average grades of 1,137 well-explored deposits identified in published grade and tonnage models representing 13 deposit types were used to train and test the network. Tonnages were transformed by logarithms and grades by square roots to reduce effects of skewness. All values were scaled by subtracting the variable's mean and dividing by its standard deviation. Half of the deposits were selected randomly to be used in training the probabilistic neural network and the other half were used for independent testing. Tests were performed with a probabilistic neural network employing a Gaussian kernel and separate sigma weights for each class (type) and each variable (grade or tonnage). Deposit types were selected to challenge the neural network. For many types, tonnages or average grades are significantly different from other types, but individual deposits may plot in the grade and tonnage space of more than one type. Porphyry Cu, porphyry Cu-Au, and porphyry Cu-Mo types have similar tonnages and relatively small differences in grades. Redbed Cu deposits typically have tonnages that could be confused with porphyry Cu deposits, also contain Cu and, in some situations, Ag. Cyprus and kuroko massive sulfide types have about the same tonnages. Cu, Zn, Ag, and Au grades. Polymetallic vein, sedimentary exhalative Zn-Pb, and Zn-Pb skarn types contain many of the same metals. Sediment-hosted Au, Comstock Au-Ag, and low-sulfide Au-quartz vein types are principally Au deposits with differing amounts of Ag. Given the intent to test the neural network under the most difficult conditions, an overall 75% agreement between the experts and the neural network is considered excellent. Among the largestclassification errors are skarn Zn-Pb and Cyprus massive sulfide deposits classed by the neuralnetwork as kuroko massive sulfides—24 and 63% error respectively. Other large errors are the classification of 92% of porphyry Cu-Mo as porphyry Cu deposits. Most of the larger classification errors involve 25 or fewer training deposits, suggesting that some errors might be the result of small sample size. About 91% of the gold deposit types were classed properly and 98% of porphyry Cu deposits were classes as some type of porphyry Cu deposit. An experienced economic geologist would not make many of the classification errors that were made by the neural network because the geologic settings of deposits would be used to reduce errors. In a separate test, the probabilistic neural network correctly classed 93% of 336 deposits in eight deposit types when trained with presence or absence of 58 minerals and six generalized rock types. The overall success rate of the probabilistic neural network when trained on tonnage and average grades would probably be more than 90% with additional information on the presence of a few rock types.

Grades do have a bearing

I am afraid that I need to challenge the assertion made by Rachel Airley in her letter (PJ, 10 March 2012, p308) that “there is no clear cut evidence that UCAS points obtained at school have any bearing on final degree performance”. Research from the Higher Education Funding Council for England — the body responsible for the distribution of funding to universities in England — shows that educational attainment before entry to higher education (ie, A-level grades) is the most important factor in determining academic success on undergraduate degree programmes.1,2 Indeed, research I have recently conducted on a cohort of MPharm students at Aston University (which will hopefully be published in a peer-reviewed academic journal shortly) demonstrates a strong positive correlation between UCAS Tariff points per A-level and final degree classification. As Dr Airley highlights in her letter, competition for places on MPharm programmes remains fierce and, in response to high levels of demand, her own institution has increased its standard entry offer. If UCAS Tariff points have little predictive ability of performance on the MPharm programme then, aside from minimising the administrative burden that the admissions process places on an institution, what is the logic behind increasing standard entry offers?

Factors affecting the alignment of *grades and reading scores for third-grade students on the Florida Comprehensive Assessment Test

The purpose of this study was to aid in understanding the relationship between current Reading report card grading practices and standards-based state standardized testing results in Reading and factors associated with the alignment of this relationship. Report card and Florida Comprehensive Assessment Test (FLAT) data for 2004 were collected for 1064 third grade students in nine schools of one feeder pattern in Florida's Miami-Dade County Public Schools. A Third Grade Teacher Questionnaire was administered to 48 Reading teachers. The questionnaire contained items relating to teachers' education, teaching experience, grading practices, and beliefs about the FCAT, instructional Reading activities, methods, and materials. ^ Findings of this study support a strong relationship between report card grades and FCAT Reading achievement levels. However, individual school correlational analysis showed significant differences among schools' alignment measures. Higher teacher alignment between grades and FCAT levels was associated with teachers spending more time on individualized methods of Reading instruction and to teachers feeling there was not enough time to teach and help individual students. Lower teacher alignment of grades and achievement levels was associated with teachers taking homework into account in the final Reading grade. Teacher alignment of grades and achievement levels was not associated with teacher beliefs concerning the FCAT, instructional activities in Reading and Language Arts, the Reading program used, the model of delivery of the Reading program, instruction or type of instructional planning done by the teachers. ^ This study highlights the need for further investigations related to determining additional teacher factors that may affect the alignment relationship between report card grades and standards-based state standardized testing results. ^

The relationship of aptitude, course grades, and program length, to performance on a standards based test (NCLEX -RN)

The purpose of this study was threefold: first, to investigate variables associated with learning, and performance as measured by the National Council Licensure Examination for Registered Nurses (NCLEX-RN). The second purpose was to validate the predictive value of the Assessment Technologies Institute (ATI) achievement exit exam, and lastly, to provide a model that could be used to predict performance on the NCLEX-RN, with implications for admission and curriculum development. The study was based on school learning theory, which implies that acquisition in school learning is a function of aptitude (pre-admission measures), opportunity to learn, and quality of instruction (program measures). Data utilized were from 298 graduates of an associate degree nursing program in the Southeastern United States. Of the 298 graduates, 142 were Hispanic, 87 were Black, non-Hispanic, 54 White, non-Hispanic, and 15 reported as Others. The graduates took the NCLEX-RN for the first time during the years 2003–2005. This study was a predictive, correlational design that relied upon retrospective data. Point biserial correlations, and chi-square analyses were used to investigate relationships between 19 selected predictor variables and the dichotomous criterion variable, NCLEX-RN. The correlation and chi square findings indicated that men did better on the NCLEX-RN than women; Blacks had the highest failure rates, followed by Hispanics; older students were more likely to pass the exam than younger students; and students who passed the exam started and completed the nursing program with a higher grade point average, than those who failed the exam. Using logistic regression, five statistical models that used variables associated with learning and student performance on the NCLEX-RN were tested with a model adapted from Bloom's (1976) and Carroll's (1963) school learning theories. The derived model included: NCLEX-RNsuccess = f (Nurse Entrance Test and advanced medical-surgical nursing course grade achieved). The model demonstrates that student performance on the NCLEX-RN can be predicted by one pre-admission measure, and a program measure. The Assessment Technologies Institute achievement exit exam (an outcome measure) had no predictive value for student performance on the NCLEX-RN. The model developed accurately predicted 94% of the student's successful performance on the NCLEX-RN.

Comparison of Linear Functions in Middle Grades Textbooks from Singapore and the United States

Many U.S. students do not perform well on mathematics assessments with respect to algebra topics such as linear functions, a building-block for other functions. Poor achievement of U.S. middle school students in this topic is a problem. U.S. eighth graders have had average mathematics scores on international comparison tests such as Third International Mathematics Science Study, later known as Trends in Mathematics and Science Study, (TIMSS)-1995, -99, -03, while Singapore students have had highest average scores. U.S. eighth grade average mathematics scores improved on TIMMS-2007 and held steady onTIMMS-2011. Results from national assessments, PISA 2009 and 2012 and National Assessment of Educational Progress of 2007, 2009, and 2013, showed a lack of proficiency in algebra. Results of curriculum studies involving nations in TIMSS suggest that elementary textbooks in high-scoring countries were different than elementary textbooks and middle grades texts were different with respect to general features in the U.S. The purpose of this study was to compare treatments of linear functions in Singapore and U.S. middle grades mathematics textbooks. Results revealed features currently in textbooks. Findings should be valuable to constituencies who wish to improve U.S. mathematics achievement. Portions of eight Singapore and nine U.S. middle school student texts pertaining to linear functions were compared with respect to 22 features in three categories: (a) background features, (b) general features of problems, and (c) specific characterizations of problem practices, problem-solving competency types, and transfer of representation. Features were coded using a codebook developed by the researcher. Tallies and percentages were reported. Welch's t-tests and chi-square tests were used, respectively, to determine whether texts differed significantly for the features and if codes were independent of country. U.S. and Singapore textbooks differed in page appearance and number of pages, problems, and images. Texts were similar in problem appearance. Differences in problems related to assessment of conceptual learning. U.S. texts contained more problems requiring (a) use of definitions, (b) single computation, (c) interpreting, and (d) multiple responses. These differences may stem from cultural differences seen in attitudes toward education. Future studies should focus on density of page, spiral approach, and multiple response problems.

A descriptive study of the ratio of approval to disapproval demonstrated by music teachers and classroom teachers in first, second, and third grades

The purpose of this study was to determine the approval to disapproval ratios of feedback given by music and classroom teachers to first, second and third grades. Eight teachers from a South Florida Elementary School were selected for this study. Twelve 20-minute videos were taken for further examination. Analyses of data using percentage formulas were used to determine the ratio of each of the teacher reinforcement. Classroom teachers gave 2.3% social approval feedback, 59% academic approval feedback, 22% social disapproval feedback, 16.5% academic disapproval feedback, and 0% errors. Music teachers gave .7% social approval feedback, 67% academic approval feedback, 22% social disapproval feedback, 10% academic disapproval feedback, and 0% errors. Today's teachers are 8% more academically approving than thirty years ago. Results also show that today's music teachers are still more approving than classroom teachers.

Modulating membership grades to gain consensus for fuzzy set uncertainty values in a clinical decision support system

This paper deals with a very important issue in any knowledge engineering discipline: the accurate representation and modelling of real life data and its processing by human experts. The work is applied to the GRiST Mental Health Risk Screening Tool for assessing risks associated with mental-health problems. The complexity of risk data and the wide variations in clinicians' expert opinions make it difficult to elicit representations of uncertainty that are an accurate and meaningful consensus. It requires integrating each expert's estimation of a continuous distribution of uncertainty across a range of values. This paper describes an algorithm that generates a consensual distribution at the same time as measuring the consistency of inputs. Hence it provides a measure of the confidence in the particular data item's risk contribution at the input stage and can help give an indication of the quality of subsequent risk predictions. © 2010 IEEE.