Pre-tests are a non-graded assessment tool used to determine pre-existing subject knowledge. Typically pre-tests are administered prior to a course to determine knowledge baseline, but here they are used to test students prior to topical material coverage throughout the course. While counterintuitive, the pre-tests cover material the student is not expected to know, but serve as a motivational ...

Previous research has shown that participants’ comprehension of spatial information described in text improves when either graphics or animation accompanies the text (Morrison & Tverksy, 2001). This relationship was found to be true in all cases for low spatial ability participants; however, it was only true under the most difficult conditions for high spatial ability participants. When given e...

Individual differences can influence a learner’s ability to extract information from dynamic, interactive animations. (Lowe, 2004). In three previous experiments, the author demonstrated that 1) spatial ability; and 2) the frequency with which participants interacted with an animated computer model made significant contributions to performance on a spatial visualization task in which they had t...

the genetic parameters and (co) variance components of body weight at birth (bw), weaning (ww) and six months of age (bw6) and average daily gain (adg) pre and post-weaning of afshari sheep were estimated using restricted maximum likelihood (reml) methodology and animal model implemented in dfreml software. the likelihood ratio test (lrt) was used to compare the models. year of birth, age of mo...

Background: Based on the onset of events, most common neonatal sepsis is early-onset (EONS), which occurs within first 72 hours life. Blood culture gold standard for EONS, but this examination takes a long time to provide results. However, latest method obtained determine shift left granulocytic image by counting Immature Granulocyte (IG). This study aims evaluate accuracy IG Ratio diagnosing E...

In this paper, we propose a new graph-based classifier which uses a special network, referred to as optimal K-associated network, for modeling data. The K -associated network is capable of representing (dis)similarity relationships among data samples and data classes. Here, we describe the main properties of the K -associated network as well as the classification algorithm based on it. Experime...