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The role of teachers in fostering creative processes in children is essential. However, high stakes instruction and teaching to the test inundates our current classrooms. This study explores the relationship between ACT/SAT scores and creativity among pre-service teachers. One hundred eighteen undergraduate students identified as Education majors were given the Epstein Creativity Competencies Inventory (ECC-i). Their total creativity score and four different subskill areas were analyzed: Capturing; Challenging: Broadening; and Surrounding. The students' ACT and SAT admission scores were then compared with their scores on the Epstein Inventory. Those students with lower end ACT scores, scored higher on the creativity survey than students with higher end ACT scores. However, SAT and creativity relationships were not found. It is time to change the value that we are placing on testing and rethink the space and time allocated to classroom environments that allow for deep and critical thinking.

In Australia, the soil-borne disease common root rot (Bipolaris sorokiniana) (CRR) in wheat (Triticum aestivum L.) leads to substantial yield losses, yet has limited visible aboveground symptoms, making detection and identification labor intensive. Near-infrared (NIR) spectroscopy offers an early potential identification solution for CRR in wheat and has previously been reported with success for crop disease detection. This study investigated the ability of nondestructive NIR spectroscopy in combination with deep neural networks (DNN), logistic regression (LR), and principal component analysis combined with support vector machines (PCA-SVM) for early-stage CRR detection in wheat. NIR spectra of five different wheat varieties with varying resistance to CRR were collected in two seasons of glasshouse and three seasons of field trials using a portable spectrometer. Results demonstrated that DNN outperformed LR and PCA-SVM, achieving 66%–91% average classification accuracy in glasshouse trials and an average accuracy of 73% with up to 87% in field trials, effectively distinguishing inoculated and non-inoculated wheat plants from seedling to anthesis stages. Validation with a third season of field data achieved an average of 77% accuracy for the most susceptible variety during the stem elongation stage. NIR reflectance within 1600–1700 nm was identified as most important for estimating CRR presence, with initial detection occurring 35 days after sowing (DAS) in the glasshouse and 46 DAS in the field. In conclusion, a NIR spectrometer with a DNN model successfully performed disease classification, with the potential as a portable early disease detection tool to assist farm management decisions. [ABSTRACT FROM AUTHOR]

In Australia, the soil-borne disease common root rot (Bipolaris sorokiniana) (CRR) in wheat (Triticum aestivum L.) leads to substantial yield losses, yet has limited visible aboveground symptoms, making detection and identification labor intensive. Near-infrared (NIR) spectroscopy offers an early potential identification solution for CRR in wheat and has previously been reported with success for crop disease detection. This study investigated the ability of nondestructive NIR spectroscopy in combination with deep neural networks (DNN), logistic regression (LR), and principal component analysis combined with support vector machines (PCA-SVM) for early-stage CRR detection in wheat. NIR spectra of five different wheat varieties with varying resistance to CRR were collected in two seasons of glasshouse and three seasons of field trials using a portable spectrometer. Results demonstrated that DNN outperformed LR and PCA-SVM, achieving 66%–91% average classification accuracy in glasshouse trials and an average accuracy of 73% with up to 87% in field trials, effectively distinguishing inoculated and non-inoculated wheat plants from seedling to anthesis stages. Validation with a third season of field data achieved an average of 77% accuracy for the most susceptible variety during the stem elongation stage. NIR reflectance within 1600–1700 nm was identified as most important for estimating CRR presence, with initial detection occurring 35 days after sowing (DAS) in the glasshouse and 46 DAS in the field. In conclusion, a NIR spectrometer with a DNN model successfully performed disease classification, with the potential as a portable early disease detection tool to assist farm management decisions. [ABSTRACT FROM AUTHOR]

Common root rot (CRR) caused by the soilborne pathogen Bipolaris sorokiniana (teleomorph Cochliobolus sativus) is becoming increasingly prevalent worldwide. Identification of CRR is difficult and time‐consuming for human assessors due to the non‐distinctive above‐ground symptoms, with browning of subcrown internodes and roots the most distinguishing symptom of infection. CRR disease has been recognized as a significant disease for cereal crops in many countries. In 2009, CRR in Australia was estimated to cause $30 million average annual yield loss for wheat and $13 million for barley. Recent evidence indicates CRR may be more prevalent than expected in Australian wheat cropping areas due to lack of research on this disease. Low levels of B. sorokiniana survive in the soil for up to 10 years and attack plants at early stages of growth. Therefore, mitigating CRR in wheat and barley may not be practical at the late stages of infection due to lack of effective methods; however, early detection might be viable to alleviate the impact of this disease. A comprehensive overview of CRR caused by B. sorokiniana, including disease background, worldwide economic losses, management methods, potential CRR detection using multispectral and hyperspectral sensors and the research focus over the past 50 years is provided in this article. This review paper is expected to provide thorough supplemental information for current studies about CRR and proposes recommendations for whole‐of‐field disease scouting methods to farmers, enabling reduced time and cost for CRR management and increasing wheat and barley production worldwide. [ABSTRACT FROM AUTHOR]

An on-the-go infield machine vision system was developed to measure internode length (i.e., the distance between main stem nodes) of cotton (Gossypium hirsutum L.) plants, which is a significant indicator of past water stress. An infield vehicle was developed to convey the machine vision system automatically across the crop canopy. This paper presents an evaluation of the devised system under a range of operational and field conditions. On average, the vision system's internode length detection rate ranged from 12 measurements per 100 plants for compact plants when the sun was directly overhead with respect to the camera, to 64 measurements per 100 plants for vigorous plants when the sunlight was perpendicular to the camera view angle. Imaging at night time using 850 nm near-infrared illumination resulted in internode length detection rates not significantly different from the most reliable daylight conditions. Both across-row and along-row operations of the system were evaluated, with the system yielding internode length measurements for groundspeeds up to 0.20 m/s for along-row operation. Visual occlusion of the main stem nodes by foliage and variations in natural lighting conditions were observed to be the principal reasons for internode lengths not being detected successfully for every plant. However, from the success rates observed, it is concluded that the system has the practical capability to map internode length across a field and hence, identify spatial trends in internode length from which trends in plant water stress can be inferred. [ABSTRACT FROM AUTHOR]

Institutions of higher education, states, and local K-12 districts have been challenged to improve math and science education for our nation's students. In the past few years, there has been renewed interest in inquiry-based, activity-oriented instruction in science for students with disabilities. Yet, there still exists the need for further empirical evidence to support instructional improvements for students with more involved emotional and behavioral disabilities. This study describes a program in which 18 middle school students with serious emotional disturbances were instructed, over the course of 8 weeks, on "Matter" by two different instructional approaches. Students in one classroom received a traditional textbook approach to science content, whereas students in another classroom received science instruction by a hands-on, thematic approach. Over the course of instruction, data were collected regarding students' behavior and achievement. Results indicate that, overall, students in the hands-on instructional program performed significantly better than the students in the textbook program on two of three measures of science achievement, a hands-on assessment and a short-answer test. The students did not differ on a multiple-choice format test. With regard to behavior, there were no significant differences in behavioral problems found between the two groups of students over the course of the study. Findings are discussed in relation to instructional implications for students with disabilities in the science classroom.

By comparing two classes (onsite and remote), this study assesses the influence of interactive video technology on how students learn in one library and information science (LIS) distance learning course. Students in this course participated voluntarily in the study by completing a questionnaire, and some elected to participate in a focus group at the end of the course. The results revealed that students in both classes became more comfortable with the technology, had positive attitudes, and achieved the learning objectives for the course. Students identified the top three positive factors that enhanced their learning as (1) class discussions with more diverse perspectives, (2) use and familiarity with the technology, and (3) class interactions. Students identified the top three negative factors that hindered their learning as (1) audio problems, (2) technology glitches and delays, and (3) intimidation to participate by the large screen, with two large classes and talking heads visible to everyone. In conclusion, the benefits of interactive video far outweigh the barriers. (Contains 11 tables and 29 notes.)

Accelerated Reader (AR) is a computerized reading reward program by Renaissance Learning Inc. (RLI) that offers schools management software with computer quizzes of books identified by reading level (RL) and assigned points in order for children to read books, take quizzes, and earn points. Schools or teachers decide whether to offer prizes in exchange for points in the reading reward system. Some schools develop elaborate prize schemes, while others use points as the reward or translate points into grades. In this article, the author analyzes AR and the influence of reading rewards on learning and library media centers. She concludes that AR should not be the determining factor of what books are in school library media collections nor influence what books students can select and read independently from those collections. When schools pull the plug on AR, school library media collections will be left with AR books labeled by reading levels and points that will not make sense to the next generation of students.

Discussion of school library media programs, educational reform, and the national guidelines set forth in "Information Power" focuses on a study of 48 school library media programs in the New England region. Surveys and observations by student interns from the University of Rhode Island library school are compared and analyzed. Results outlined in six tables. (LRW)

Explains FLIP it, a four-stage nonlinear information literacy research process that allows flexibility at each stage of the problem-solving approach. Highlights include intelligent thinking, how FLIP it has been used, how it relates to information literacy standards, and research on the FLIP it model. (LRW)