Química Nova Interativa - QNInt - o portal do conhecimento da SBQ: conectando ciência e educação

The Química Nova Interativa (QNInt) portal was launched in 2009 by the Brazilian Chemical Society (SBQ) to offer free quality content for broad audiences. QNInt provides peer-reviewed articles from SBQ journals on science & society, chemical concepts, classroom activities and educational research. With 3,000,000 visits, QNInt also offers a unique library of interactive molecules. In the International Year of Chemistry QNInt served for distributing pH kits and registering data from IUPAC's Global Water Experiment, yielding Brazil the largest share of the global pH data set. The portal performance makes QNInt a valuable resource for connecting science to education.

Visualização no ensino de química: apontamentos para a pesquisa e desenvolvimento de recursos educacionais

Visualization is a fast-growing field in science education. This review covers 171 articles published between 2001 and 2010 in 14 science education journals. Major findings include: i - despite the predominance of English speaking countries, interest in the topic has increased in several countries; ii - qualitative research is increasing, but quantitative methodologies prevail; iii - the role of peer interaction in group activities is little investigated; iv - research on the way students and teachers use visualization tools is increasing, but most publications focus on the tools; v - structure of matter remains the most common subject covered.

Automatic evaluation and data generation for analytical chemistry instrumental analysis exercises

In general, laboratory activities are costly in terms of time, space, and money. As such, the ability to provide realistically simulated laboratory data that enables students to practice data analysis techniques as a complementary activity would be expected to reduce these costs while opening up very interesting possibilities. In the present work, a novel methodology is presented for design of analytical chemistry instrumental analysis exercises that can be automatically personalized for each student and the results evaluated immediately. The proposed system provides each student with a different set of experimental data generated randomly while satisfying a set of constraints, rather than using data obtained from actual laboratory work. This allows the instructor to provide students with a set of practical problems to complement their regular laboratory work along with the corresponding feedback provided by the system's automatic evaluation process. To this end, the Goodle Grading Management System (GMS), an innovative web-based educational tool for automating the collection and assessment of practical exercises for engineering and scientific courses, was developed. The proposed methodology takes full advantage of the Goodle GMS fusion code architecture. The design of a particular exercise is provided ad hoc by the instructor and requires basic Matlab knowledge. The system has been employed with satisfactory results in several university courses. To demonstrate the automatic evaluation process, three exercises are presented in detail. The first exercise involves a linear regression analysis of data and the calculation of the quality parameters of an instrumental analysis method. The second and third exercises address two different comparison tests, a comparison test of the mean and a t-paired test.

Diagrammatic scale for the assessment of blast on wheat spikes

The correct quantification of blast caused by the fungus Magnaporthe oryzae on wheat (Triticum aestivum) spikes is an important component to understand the development of this disease aimed at its control. Visual quantification based on a diagrammatic scale can be a practical and efficient strategy that has already proven to be useful against several plant pathosystems, including diseases affecting wheat spikes like glume blotch and fusarium head blight. Spikes showing different disease severity values were collected from a wheat field with the aim of elaborating a diagrammatic scale to quantify blast severity on wheat spikes. The spikes were photographed and blast severity was determined by using resources of the software ImageJ. A diagrammatic scale was developed with the following disease severity values: 3.7, 7.5, 21.4, 30.5, 43.8, 57.3, 68.1, 86.0, and 100.0%. An asymptomatic spike was added to the scale. Scale validation was performed by eight people who estimated blast severity by using digitalized images of 40 wheat spikes. The precision and the accuracy of the evaluations varied according to the rater (0.82