A Study of Mentor Principal Training in Pennsylvania

Abstract The purpose of this qualitative case study was to identify, investigate, and describe the espoused Pennsylvania Principal Mentoring Network (PPMN) training program and protocols for the principals who served as mentors for newly hired principals in Pennsylvania. This study posed three research questions: (1) what was the espoused training provided to mentor principals in Pennsylvania both prior to and during their mentoring experiences that prepared them to mentor newly hired principals?; (2) what were the program coordinators’ perspectives on the espoused training delivered by the PPMN for the respective mentors and to what degree was the training program the same or different through the term of each coordinator?; and (3) how does this espoused training compare and subsequently align to the competencies required of mentor principals highlighted in the research literature? Through reviewing documents and conducting interviews, the author found that each principal mentor had participated in some form of mentor training. Each mentor principal had the opportunity to experience and access standard mentor training orientations, published newsletters and regional meetings, and the National Institute for School Leadership (NISL) five-day Instructional Leadership Institute’s condensed professional development series. The PPMN State Coordinators indicated that the PPMN attracted qualified mentor principals who modeled a results driven, research-based mentor training program. Throughout the existence of the PPMN, subtle changes to the mentor training program were identified but the focus, goals, and outcomes of the training remained intact. The PPMN mentor training process had aligned fairly consistently to the research literature base and framework for this research study. Although minimal references to adult learning theory were found in this study, it is recommended that future mentor training programs strongly consider the efficacy of including this area within the scope and sequence of the training program. In addition, due to the unavailability of certain documents and no central repository for information, future research inquiries should be geared toward existing programs that are strongly organized and currently functioning

ScratchMaths: evaluation report and executive summary

Since 2014, computing has been part of the primary curriculum. ‘Scratch’ is frequently used by schools, and the EEF funded this trial to test whether the platform could be used to improve pupils’ computational thinking skills, and whether this in turn could have a positive impact on Key Stage 2 maths attainment. Good computational thinking skills mean pupils can use problem solving methods that involve expressing problems and their solutions in ways that a computer could execute – for example, recognising patterns. Previous research has shown that pupils with better computational thinking skills do better in maths. The study found a positive impact on computational thinking skills at the end of Year 5 – particularly for pupils who have ever been eligible for free school meals. However, there was no evidence of an impact on Key Stage 2 maths attainment when pupils were tested at the end of Year 6. Many of the schools in the trial did not fully implement ScratchMaths, particularly in Year 6, where teachers expressed concerns about the pressure of Key Stage 2 SATs. But there was no evidence that schools which did implement the programme had better maths results. Schools may be interested in ScratchMaths as an affordable way to cover aspects of the primary computing curriculum in maths lessons without any adverse effect on core maths outcomes. This trial, however, did not provide evidence that ScratchMaths is an effective way to improve maths outcomes

Forecast horizon aggregation in integer autoregressive moving average (INARMA) models

This paper addresses aggregation in integer autoregressive moving average (INARMA) models. Although aggregation in continuous-valued time series has been widely discussed, the same is not true for integer-valued time series. Forecast horizon aggregation is addressed in this paper. It is shown that the overlapping forecast horizon aggregation of an INARMA process results in an INARMA process. The conditional expected value of the aggregated process is also derived for use in forecasting. A simulation experiment is conducted to assess the accuracy of the forecasts produced by the aggregation method and to compare it to the accuracy of cumulative h-step ahead forecasts over the forecasting horizon. The results of an empirical analysis are also provided

State-space ARIMA for supply-chain forecasting

ARIMA is seldom used in supply chains in practice. There are several reasons, not the least of which is the small sample size of available data, which restricts the usage of the model. Keeping in mind this restriction, we discuss in this paper a state-space ARIMA model with a single source of error and show how it can be efficiently used in the supply-chain context, especially in cases when only two seasonal cycles of data are available. We propose a new order selection algorithm for the model and compare its performance with the conventional ARIMA on real data. We show that the proposed model performs well in terms of both accuracy and computational time in comparison with other ARIMA implementations, which makes it efficient in the supply-chain context

The Mass Dependance of Satellite Quenching in Milky Way-like Halos

Using the Sloan Digital Sky Survey, we examine the quenching of satellite galaxies around isolated Milky Way-like hosts in the local Universe. We find that the efficiency of satellite quenching around isolated galaxies is low and roughly constant over two orders of magnitude in satellite stellar mass ($M_{*}$ = $10^{8.5}-10^{10.5} \, M_{\odot}$), with only $\sim~20\%$ of systems quenched as a result of environmental processes. While largely independent of satellite stellar mass, satellite quenching does exhibit clear dependence on the properties of the host. We show that satellites of passive hosts are substantially more likely to be quenched than those of star-forming hosts, and we present evidence that more massive halos quench their satellites more efficiently. These results extend trends seen previously in more massive host halos and for higher satellite masses. Taken together, it appears that galaxies with stellar masses larger than about $10^{8}~M_{\odot}$ are uniformly resistant to environmental quenching, with the relative harshness of the host environment likely serving as the primary driver of satellite quenching. At lower stellar masses ($< 10^{8}~M_{\odot}$), however, observations of the Local Group suggest that the vast majority of satellite galaxies are quenched, potentially pointing towards a characteristic satellite mass scale below which quenching efficiency increases dramatically.Comment: 14 pages, 8 figure