8 research outputs found
On asymptotic Boronkov-Sakhanenko inequality with unbounded parameter set
Integral analogues of Cramér-Rao's inequalities for Bayesian parameter estimators proposed initially by Schützenberger (1958) and later by van Trees (1968) were further developed by Borovkov and Sakhanenko (1980). In this paper, new asymptotic versions of such inequalities are established under ultimately relaxed regularity assumptions and under a locally uniform nonvanishing of the prior density and with R1 as a parameter set. Optimality of Borovkov-Sakhanenko's asymptotic lower bound functional is established
Metabolomic profiling of reactive persulfides and polysulfides in the aqueous and vitreous humors
Diabetes and Overexpression of proNGF Cause Retinal Neurodegeneration via Activation of RhoA Pathway
Identification of cyclins A1, E1 and vimentin as downstream targets of heme oxygenase-1 in vascular endothelial growth factor-mediated angiogenesis
Improved production of lipid contents by cultivating Chlorella pyrenoidosa in heterogeneous organic substrates
Examining the acceptance and use of online social networks by preservice teachers within the context of unified theory of acceptance and use of technology model
Social network sites (SNSs) has a big potential to improve teaching and
learning experience. It has become a necessity for teachers to transfer
this technologies to learning environments has become a requirement. For
this reason, the use of SNSs in the education process of preservice
teachers who are the teachers of the future and examination of variables
that have an impact on the acceptance of these technologies are found
important. The use of SNSs in teacher education will enable preservice
teachers to be more willing to use information technologies and will
improve their skills in using these technologies. For the reasons given,
in this study, it is aimed to examine the acceptance and use of SNSs by
preservice teachers for educational purposes on the basis of unified
theory of acceptance and use of technology model. The study was designed
according to relational screening model. Study group of the study
consists of 274 preservice teachers at a university in 2017. Data were
collected via various scales and personal information form at the end of
an application process of 14weeks+14weeks. Descriptive statistics,
linear multiple hierarchical regression analysis and structural equation
model were used in analysing the data. As a result of the study, it was
determined that the acceptance of SNSs for educational purposes was
affected respectively by social effect, performance expectation and
effort expectation, and behavioral intention of using these technologies
affected the actual use. Besides, variables of moderators that were
effective on acceptance and use were also determined