Compressed School Week Cultural Bias against English Second Language Student Performance on Standardized Exams

Financial constraints have driven K-12 schools in the isolated mountain regions of USA to reduce costs by shortening the teaching week These regions have a high relative population of Hispanic Mexican immigrants who are English Language Learners ELL Hispanic immigrants come to USA to work but generally at low wages so it is a financial strain to pay childcare during the week to avoid losing a day of work At the same time teachers are under pressure from the No Child Left Behind national initiative to ensure all students pass standardized tests There is some evidence that shorter school weeks does not negatively impact student learning However we argue that a shorter school week negatively impacts ELL student performance on standardized exams and if this were true it would be unfair to immigrants so the practice should be changed We empirically tested the effectiveness of various school week formats using a large sample of rural schools in Oregon with a high concentration of ELL students from Hispanic Mexican cultures N 62

Using recursive regression to explore nonlinear relationships and interactions: A tutorial applied to a multicultural education study

This paper discusses how a seldom-used statistical procedure, recursive regression (RR), can numerically and graphically illustrate data-driven nonlinear relationships and interaction of variables. This routine falls into the family of exploratory techniques, yet a few interesting features make it a valuable compliment to factor analysis and multiple linear regression for method triangulation. By comparison, nonlinear cluster analysis also generates graphical dendrograms to visually depict relationships, but RR (as implemented here) uses multiple combinations of nominal and interval predictors regressed on a categorical or ratio dependent variable. In similar fashion, multidimensional scaling, multiple discriminant analysis and conjoint analysis are constrained at best to predicting an ordinal dependent variable (as currently implemented in popular software). A flexible capability of RR (again as implemented here) is the transformation of factor data (for substituting codes). One powerful RR feature is the ability to treat missing data as a theoretically important predictor value (useful for survey questions that respondents do not wish to answer). For practitioners, the paper summarizes how this technique fits within the generally-accepted statistical methods. Popular software such as SPSS, SAS or LISREL can be used, while sample data can be imported in common formats including ASCII text, comma delimited, Excel XLS, and SPSS SAV. A tutorial approach is applied here using RR in LISREL. The tutorial leverages a partial sample from a study that used recursive regression to predict grades from international student learning styles. Some tutorial portions are technical, to improve the ambiguous RR literature. Accessed 17,736 times on https://pareonline.net from March 16, 2009 to December 31, 2019. For downloads from January 1, 2020 forward, please click on the PlumX Metrics link to the right

Effectiveness of Peer Assessment in a Professionalism Course Using an Online Workshop

An online Moodle Workshop was evaluated for peer assessment effectiveness. A quasi-experiment was designed using a Seminar in Professionalism course taught in face-to-face mode to undergraduate students across two campuses. The first goal was to determine if Moodle Workshop awarded a fair peer grader grade. The second objective was to estimate if students were consistent and reliable in performing their peer assessments. Statistical techniques were used to answer the research hypotheses. Although Workshop Moodle did not have a built-in measure for peer assessment validity, t-tests and reliability estimates were calculated to demonstrate that the grades were consistent with what faculty expected. Implications were asserted to improve teaching and recommendations were provided to enhance Moodle.</jats:p

Exploring Socio-Cultural Factors Impacting Agriculture in Information System Acceptance

Agricultural Information Systems (AIS) can provide several advantages for farmers in taking informed decisions regarding land, labour, livestock, and crop planning. However, there are not many empirical studies in examining the adoption of these AIS by farmers, especially in developing countries in Africa. This study adopts an unconventional socio-cultural approach in examining if the farmers think the use of AIS improves economic production, at the individual level of analysis. The purpose of this qualitative ethnographic study is to explore the socio-cultural success factors that improve employee acceptance of agriculture information system at some rural Nigerian farms. The results of this study could be disseminated to all rural Nigerian farm owners so they will know the critical success factors that improve employee acceptance of agriculture information system thereby increasing wheat production to reduce their national agricultural crisis. Another positive social change implication of the results of this on-going research would be to inspire researchers to replicate and extend this study in regions experiencing agricultural crises

B2C Decisions in Multi-Dialect Markets: Proposed Sequential Mixed-Method Multiple Case Grounded-Theory Study

This paper is a conceptual proposal for conducting a mixed-method multiple case study on a consumer behaviour topic in an emerging nation. Government administrators and marketing managers need current, reliable consumer behaviour models to serve the public and to achieve a profitable return on investment in Nigeria. There is a shortage of online consumer behaviour research in some highly populated emerging economies in Africa, such as in Nigeria, especially concerning the influence of demographic and socio-cultural factors. The purpose of this study will be to produce a visual, conceptual model of consumer decision making factors for the unique socio-cultural population. The purpose of this study is to scientifically explore the ground truth of Nigerian consumer online purchasing decisions to build a practical model for e-commerce stakeholders. The results of this study should be interesting for other researchers due to the novel sequential mixed-method grounded theory and multiple case study literal replication design. Nigerian e-commerce marketing managers and policymakers in the population could benefit financially from this extension to the body of knowledge

Search for gravitational-lensing signatures in the full third observing run of the LIGO-Virgo network

Gravitational lensing by massive objects along the line of sight to the source causes distortions of gravitational wave-signals; such distortions may reveal information about fundamental physics, cosmology and astrophysics. In this work, we have extended the search for lensing signatures to all binary black hole events from the third observing run of the LIGO--Virgo network. We search for repeated signals from strong lensing by 1) performing targeted searches for subthreshold signals, 2) calculating the degree of overlap amongst the intrinsic parameters and sky location of pairs of signals, 3) comparing the similarities of the spectrograms amongst pairs of signals, and 4) performing dual-signal Bayesian analysis that takes into account selection effects and astrophysical knowledge. We also search for distortions to the gravitational waveform caused by 1) frequency-independent phase shifts in strongly lensed images, and 2) frequency-dependent modulation of the amplitude and phase due to point masses. None of these searches yields significant evidence for lensing. Finally, we use the non-detection of gravitational-wave lensing to constrain the lensing rate based on the latest merger-rate estimates and the fraction of dark matter composed of compact objects

How Lean Six Sigma Risk Management Was Used at a Clean Energy Plant

The global pursuit of higher quality and corporate social responsibility are motivating corporations to set climate preservation goals and to employ quality theory processes, notably lean six sigma methods. One of the significant contemporary social responsibility initiatives is climate preservation. Climate conservation has been dramatically achieved through the increases efficient production of clean energy, such as hydroelectricity and nuclear power plants. However, advanced quality management processes are needed to effectively and safely operate electricity generation plants of any type due to their potential to cause significant man-made accidental disasters if certain critical processes become out of control. This chapter explores how lean six sigma quality theories were applied for risk management at a renewable energy hydroelectricity facility. Quality inspections were collected from a plant in New York, USA. A statistical process control model was developed based on the attribute and continuous inspection data. </jats:p