An Analysis of Cooperating Teacher Feedback: A Qualitative Inquiry

Cooperating teachers are a key component to the success of student teaching internships, serving an integral part in “raising” a teacher. To effectively facilitate the student teaching internship, teacher preparation programs must identify cooperating teachers who align philosophically with the pedagogical training delivered by university programs (Korthagen & Kessels, 1999; Tom, 1997), specifically, cooperating teachers who can reinforce the theoretical framework underpinning the professional coursework pre-service teachers experience in university teacher preparation programs. This qualitative study sought to better understand the feedback provided to future school-based agricultural education (SBAE) teachers during their student teaching experience. Through initial and secondary coding, the research team identified themes among the feedback provided to student teachers by their cooperating teachers. The study revealed cooperating teacher feedback reflects the pedagogical training provided via the teacher preparation program, specifically, around effective teaching behaviors. Understanding the cooperating teacher feedback provides insight for teacher preparation programs

Multivariate Design of Experiments for Engineering Dimensional Analysis

We consider the design of dimensional analysis experiments when there is more than a single response. We first give a brief overview of dimensional analysis experiments and the dimensional analysis (DA) procedure. The validity of the DA method for univariate responses was established by the Buckingham $\Pi$-Theorem in the early 20th century. We extend the theorem to the multivariate case, develop basic criteria for multivariate design of DA and give guidelines for design construction. Finally, we illustrate the construction of designs for DA experiments for an example involving the design of a heat exchanger

Universality of citation distributions revisited

Radicchi, Fortunato, and Castellano [arXiv:0806.0974, PNAS 105(45), 17268] claim that, apart from a scaling factor, all fields of science are characterized by the same citation distribution. We present a large-scale validation study of this universality-of-citation-distributions claim. Our analysis shows that claiming citation distributions to be universal for all fields of science is not warranted. Although many fields indeed seem to have fairly similar citation distributions, there are quite some exceptions as well. We also briefly discuss the consequences of our findings for the measurement of scientific impact using citation-based bibliometric indicators