5 resultados para January effect
em Digital Commons at Florida International University
Resumo:
This exploratory study of a classroom with mentoring and neutral e-mail was conducted in a public commuter state university in South Florida between January 1996 and April 1996. Sixteen males and 83 females from four graduate level educational research classes participated in the study.^ Two main hypotheses were tested. Hypothesis One was that those students receiving mentoring e-mail messages would score significantly higher on an instrument measuring attitude toward educational research (ATERS) than those not receiving mentoring e-mail messages. Hypothesis Two was that those students receiving mentoring e-mail would score significantly higher on objective exams covering the educational research material than those not receiving mentoring e-mail.^ Results of factorial analyses of variance showed no significant differences between the treatment groups in achievement or in attitudes toward educational research. Introverts had lower attitudes and lower final exam grades in both groups, although introverts in the mentored group scored higher than those introverts in the neutral group.^ A t test of the means of total response to e-mail from the researcher showed a significant difference between the mentored and neutral e-mail groups. Introverts responded more often than extraverts in both groups.^ Teacher effect was significant in determining class response to e-mail messages. Responses were most frequent in the researcher's classes.^ Qualitative analyses of the e-mail and course evaluation survey and of the content of e-mail messages received by the researcher were then grouped into basic themes and discussed.^ A qualitative analysis of an e-mail and course evaluation survey revealed that students from both the neutral and mentoring e-mail groups appreciated teacher feedback. A qualitative analysis of the mentoring and neutral e-mail replies divided the responses into those pertaining to the class, such as test and research paper questions, and more personal items, such as problems in the class and personal happenings.^ At this point in time, e-mail is not a standard way of communicating in classes in the college of education at this university. As this technology tool of communication becomes more popular, it is anticipated that replications of this study will be warranted. ^
Resumo:
The purpose of this study was to evaluate the effect of cooperative learning strategies on students' attitudes toward science and achievement in BSC 1005L, a non-science majors' general biology laboratory course at an urban community college. Data were gathered on the participants' attitudes toward science and cognitive biology level pre and post treatment in BSC 1005L. Elements of the Learning Together model developed by Johnson and Johnson and the Student Team-Achievement Divisions model created by Slavin were incorporated into the experimental sections of BSC 1005L.^ Four sections of BSC 1005L participated in this study. Participants were enrolled in the 1998 spring (January) term. Students met weekly in a two hour laboratory session. The treatment was administered to the experimental group over a ten week period. A quasi-experimental pretest-posttest control group design was used. Students in the cooperative learning group (n$\sb1$ = 27) were administered the Test of Science-Related Attitudes (TOSRA) and the cognitive biology test at the same time as the control group (n$\sb2$ = 19) (at the beginning and end of the term).^ Statistical analyses confirmed that both groups were equivalent regarding ethnicity, gender, college grade point average and number of absences. Independent sample t-tests performed on pretest mean scores indicated no significant differences in the TOSRA scale two or biology knowledge between the cooperative learning group and the control group. The scores of TOSRA scales: one, three, four, five, six, and seven were significantly lower in the cooperative learning group. Independent sample t-tests of the mean score differences did not show any significant differences in posttest attitudes toward science or biology knowledge between the two groups. Paired t-tests did not indicate any significant differences on the TOSRA or biology knowledge within the cooperative learning group. Paired t-tests did show significant differences within the control group on TOSRA scale two and biology knowledge. ANCOVAs did not indicate any significant differences on the post mean scores of the TOSRA or biology knowledge adjusted by differences in the pretest mean scores. Analysis of the research data did not show any significant correlation between attitudes toward science and biology knowledge. ^
Resumo:
After developing field sampling protocols and making a series of consultations with investigators involved in research in CSSS habitat, we determined that vegetationhydrology interactions within this landscape are best sampled at a combination of scales. At the finer scale, we decided to sample at 100 m intervals along transects that cross the range of habitats present, and at the coarser scale, to conduct an extensive survey of vegetation at sites of known sparrow density dispersed throughout the range of the CSSS. We initiated sampling in the first week of January 2003 and continued it through the last week of May. During this period, we established 6 transects, one in each CSSS subpopulation, completed topographic survey along the Transects A, C, D, and F, and sampled herb and shrub stratum vegetation, soil depth and periphyton along Transects A, and at 179 census points. We also conducted topographic surveys and completed vegetation and soil depth sampling along two of five transects used by ENP researchers for monitoring long-term vegetation change in Taylor Slough. We analyzed the data by summarizing the compositional and structural measures and by using cluster analysis, ordination, weighted averaging regression, and weighted averaging calibration. The mean elevation of transects decreased from north to south, and Transect F had greater variation than other transects. We identified eight vegetation assemblages that can be grouped into two broad categories, ‘wet prairie’ and ‘marsh’. In the 2003 survey, wet prairies were most dominant in the northeastern sub-populations, and had shorter inferred-hydroperiod, higher species richness and shallower soils than marshes, which were common in Subpopulations A, D, and the southernmost regions of Sub-population B. Most of the sites at which birds were observed during 2001 or 2002 had an inferred-hydroperiod of 120-150 days, while no birds were observed at sites with an inferred-hydroperiod less than 120 days or more than 300 days. Management-induced water level changes in Taylor Slought during the 1980’s and 1990’s appeared to elicit parallel changes in vegetation. The results described in detail in the following pages serve as a basis for evaluating and modifying, if necessary, the sampling design and analytical techniques to be used in the next three years of the project.
Resumo:
Following on our previous year’s work on ‘Effect of hydrologic restoration on the habitat of the Cape Sable seaside sparrow (CSSS)’, we presented first year results at the Cape Sable seaside sparrow – fire planning workshop at Everglades National Park in December 2003. Later, with almost the same set of crews as in the previous year, we started field work in the first week of January and continued till May 26, 2004. Protocols for sampling topography and vegetation in 2004 were identical to the previous year. In the early season, we completed topographic surveys along two remaining transects, B and E (~16.5 km), and vegetation surveys along three transects, D, E and F (~10.8 km), leaving only the vegetation sampling on transects B and C to be completed in 2005. During April and May, vegetation sampling was completed at 230 census sites, making the total of 409 CSSS census sites for which we have complete vegetation data. We updated data sets from both 2003 and 2004, and analyzed them together using cluster analysis, ordination, weighted-averaging regression and analysis of variance, as we had in 2003. Additionally, we used logistic regression to examine the effect of vegetation structural parameters on the recent occurrence of CSSS. We also analyzed vegetation observations recorded by the sparrow census team in 1981 and annually between 1992 and 2004 to assess historical patterns of vegetation change in CSSS habitat.
Resumo:
The major activities in Year 3 on ‘Effect of hydrologic restoration on the habitat of the Cape Sable seaside sparrow (CSSS)’ included presentations, field work, data analysis, and report preparation. During this period, we made 4 presentations, two at the CSSS – fire planning workshops at Everglades National Park (ENP), one at the Society of Wetland Scientists’ meeting in Charleston, SC, and a fourth at the Marl Prairie/CSSS performance measure workshop at ENP. We started field work in the third week of January and continued till June 3, 2005. Early in the field season, we completed vegetation surveys along two transects, B and C (~15.1 km). During April and May, vegetation sampling was completed at 199 census sites, bringing to 608 the total number of CSSS census sites with quantitative vegetation data. We updated data sets from all three years, 2003-05, and analyzed them using cluster analysis and ordination as in previous two years. However, instead of weighted averaging, we used weighted-averaging partial least square regression (WA-PLS) model, as this method is considered an improvement over WA for inferring values of environmental variables from biological species composition. We also validated the predictive power of the WA-PLS regression model by applying it to a sub-set of 100 census sites for which hydroperiods were “known” from two sources, i.e., from elevations calculated from concurrent water depth measurements onsite and at nearby water level recorders, and from USGS digital elevation data. Additionally, we collected biomass samples at 88 census sites, and determined live and dead aboveground plant biomass. Using vegetation structure and biomass data from those sites, we developed a regression model that we used to predict aboveground biomass at all transects and census sites. Finally, biomass data was analyzed in relation to hydroperiod and fire frequency.