The purpose of this study was to describe technology learning methods that teachers attend and perceive as effective. The goal was to provide district personnel data that may be utilized when planning for more effective technology staff development. This study examined (1) the methods of learning instructional technology that are being utilized by teachers and administrators and (2) why these methods are being utilized in two Texas school districts. Data was collected from educators via an online survey consisting of demographics, technology training methods, level of technology use (CBAM 1 item), stages of adoption and technology level of use (LoTi, 50-item). Educators with different technology levels of use (high, low) differed on their perceptions and utilization of technology training methods. Specifically, educators with different technology levels of use differed in their perceptions of independent online help, and learning through trial and error technology training methods. Results from the study showed that educators tended to use the technology training method that they perceived as most effective. Educators tended to utilize learning by trial and error, peer support, and technology personnel support the most frequently for learning technology integration Educators' in the study had varying technology levels of use based on their educator categories. Administrators tended to score much higher than both elementary and secondary teachers on their technology levels of use. Participants gave a variety of reasons for utilizing certain technology training methods most frequently. The most popular reason was that the method fit into their time schedule followed by the location of the training. The least given reason was that it was the best method for learning the technology skill.

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / The objective was to evaluate the milk quality coming from Region Northwest Rio Grande Sul, under different technology levels, from October 2007 to September 2010, at different seasons. The variables were fat, protein, lactose, total solids, somatic cell count (SCC) and total bacterial count (TBC) of milk. Data were analyzed using mixed model with repeated measure data, having the effect of fixed production system, years and seasons, and random effect dairy farm designated in each production system. The results were compared with the standard required by Normative Instruction 51 (NI 51) of 18 September 2002 (Minisério da Agricultura, Pecuária e Abastecimento). There were significant differences between the systems of production for fat and total bacterial count milk, with higher values in non specialized system. All variables were influenced by season, featuring in the autumn, fat, protein, total solids and higher TBC. The lactose content was influenced by the production system, presenting the most specialized and smaller in the not specialized, and the season, being higher in winter and lower in autumn. There was a high percentage of samples in disagreement with the NI 51 to TBC and SCC, especially those belonging to dairy farm partially and not specialized. / Foi avaliada a qualidade do leite oriundo da Mesorregião Noroeste do Rio Grande do Sul, sob distintos níveis tecnológicos, no período de outubro de 2007 a setembro de 2010, nas diferentes estações do ano. As variáveis analisadas foram gordura, proteína, lactose, sólidos totais, contagem de células somáticas (CCS) e contagem bacteriana total (CBT) do leite. Os dados foram analisados por meio de modelo misto com medida repetida no tempo, tendo como efeito fixo os sistemas de produção, anos e estações do ano, e efeito aleatório a unidade produtora de leite (UPL) designada em cada sistema de produção. Os resultados foram comparados com o padrão exigido pela Instrução Normativa 51 (IN 51) de 18 de setembro de 2002 (Ministério da Agricultura, Pecuária e Abastecimento). Observou-se diferenças significativas entre os sistemas de produção para os teores de gordura e contagem bacteriana total do leite, com valores superiores no sistema não especializado. Todas as variáveis tiveram influência da estação do ano, apresentando, no outono, teor de gordura, proteína, sólidos totais maior e CBT menor. O teor de lactose foi influenciado pelo sistema de produção, apresentando-se maior no especializado e menor no não especializado, assim como pela estação do ano, sendo maior no inverno e menor no outono. Observou-se uma porcentagem alta de amostras em desacordo com a IN 51, para CBT e CCS, principalmente as pertencentes a UPL`s do sistema semi e não especializado.