INVALSI data: assessments on teaching and methodologies

The school system has always aimed to achieve quality teaching, which is able, on the one hand, to give adequate responses to the expectations of all the stakeholders and, on the other, to introduce tools, actions, and checks through which the training offer can be constantly improved. This process is undoubtedly linked to scientific research. Researchers and Academics start from the data available to them or collect new ones, to discover and/or interpret facts and to find answers and new cues of reflection. A favorable environment for this work was the Seminar “INVALSI data: a research and educational teaching tool”, in its fourth edition in November 2019. The volume consists of six chapters, which are arise within the aforementioned Seminar context and, while dealing with heterogeneous topics, offer important examples of research both on teaching and on the methodologies applied to it. As a Statistical Service, which for years has taken care of the collection and dissemination of data, we hope that in this, as in the other volumes of the series, the reader will find confirmation of the importance that data play, both in scientific research and in practice in classroom

Toward Quality Preceptorship: A Dyad Sudy

Problem: Approximately 70% of newly graduated nurses work in hospital settings, but their turnover rates are high, costly to employers, and due, in part, to lack of satisfaction with job orientation processes. Effective preceptorship is widely regarded as pivotal to newly graduated nurses’ successful transition to the professional nurse role; yet, the critical elements of preceptorship have not been empirically determined. Numerous researchers proffer the preceptor - newly graduated nurse interpersonal relationship as key, but preceptorship research has not been focused on this dyadic interaction. Consequently, its true impact remains unknown. Accordingly, this study addressed the following research question, “Are the effects of preceptorship a function of the preceptor – newly graduated nurse interpersonal relationship?”Methodology: A reciprocal, standard dyadic design was used. Survey participants included 50 preceptor-newly graduated nurse dyads recruited from nine Midwestern U.S. hospitals. The differences between and relationships among dyad-member perceptions of the preceptorship experience, newly graduated nurse competence, and work engagement were explored. Informed by Kashy and Kenny’s (2000) Actor –Partner Interdependence Model, actor and partner effects of the preceptorship experience on work engagement and perceptions of newly graduated nurse competence were explored using Bayesian inference analyses.Results: Approximately 42% and 52% of the variance in preceptors’ and newly graduated nurses’ perceptions of newly graduated nurse competence, respectively, were predicted by their collective perceptions of the preceptorship experience. Dyad-member perceptions of the preceptorship experience strongly predicted their own perceptions of newly graduated nurse competence. Preceptor perceptions of the preceptorship experience weakly predicted newly graduated nurse work engagement. Newly graduated nurse perceptions of the preceptorship experience predicted neither their own nor their preceptor’s work engagement.Conclusions: Findings of this study provide initial evidence that preceptor and newly graduated nurse perceptions of the preceptorship experience have direct effects on work engagement and perceptions of newly graduated nurse competence. Therefore, hospital employers should take care to ensure positive preceptorship experiences, including the development of effective preceptor – newly graduated nurse interpersonal relationships, to achieve desired outcomes. Ongoing dyadic preceptorship research is needed to further establish the preceptor-newly graduated nurse relationship as a critical determinant of preceptorship outcomes

Transforming Assessment and Learning: Making the System Work. Proceeding of the 2022 International Conference on Assessment and Learning

https://research.acer.edu.au/ical/1000/thumbnail.jp

USE OF COMPUTER SOFTWARE TO DO MATHEMATICS AND THE MATHEMATICS ACHIEVEMENT OF STUDENTS IN PUERTO RICO USING RESTRICTED 2015 NAEP

This quantitative study explored the relationship between the mathematics achievement patterns of eighth grade students in Puerto Rico and their use of computer software application programs for doing mathematics. The theoretical framework used is the educational production function, which allowed the use of a function to analyze this relationship. The researcher analyzed 2015 restricted National Assessment of Educational Progress (NAEP) mathematics data. Data analysis consisted of descriptive statistical analysis and multilevel modeling analysis. Control variables to measure socioeconomic status and absenteeism were included in the multilevel model. Results of this study showed that average scores on NAEP 2015 were higher for students who use computer programs to do mathematics with less frequency than students who use it with more frequency. Understanding the relationship between the use of computer programs to do mathematics and the mathematics achievement of these students help the mathematics education community to cautiously create policies that do not focused on frequency of using technology. The researcher provided a discussion of the results and implications for researchers, administrators and teachers that would help them to target on the improvement of mathematics achievement of students in Puerto Rico. Este trabajo cuantitativo exploró la relación entre patrones de aprovechamiento matemático de estudiantes de octavo grado en Puerto Rico y el uso de programas de computadora para hacer matemáticas. El marco teórico es la función de producción educativa, el cual permitió el uso de una función para explicar esta relación. La investigadora analizó datos restringidos del 2015 de la Evaluación Nacional del Progreso Educativo de Matemáticas (NAEP, por sus siglas en inglés). El análisis de datos consistió en estadística descriptiva y análisis multinivel. En este último, la investigadora utilizó variables control para medir el nivel socioeconómico y el ausentismo de los estudiantes. Los resultados de este estudio mostraron que los estudiantes que usaron programas matemáticos con mayor frecuencia obtuvieron puntajes promedio más altos en NAEP 2015 que los estudiantes que los usaron con menor frecuencia. Entender la relación entre el uso de programas de computadora y el aprovechamiento académico de estos estudiantes ayuda a la comunidad de educadores en matemática a crear, con cautela, políticas educativas que no se enfoquen en la frecuencia del uso de tecnología. La investigadora incluyó una discusión de los resultados así como implicaciones para investigadorxs, administradorxs y maestrxs que pueden ayudarlos a identificar prácticas que mejorarán el aprovechamiento matemático de estudiantes en Puerto Rico

INVALSI data: assessments on teaching and methodologies

The school system has always aimed to achieve quality teaching, which is able, on the one hand, to give adequate responses to the expectations of all the stakeholders and, on the other, to introduce tools, actions, and checks through which the training offer can be constantly improved. This process is undoubtedly linked to scientific research. Researchers and Academics start from the data available to them or collect new ones, to discover and/or interpret facts and to find answers and new cues of reflection. A favorable environment for this work was the Seminar “INVALSI data: a research and educational teaching tool”, in its fourth edition in November 2019. The volume consists of six chapters, which are arise within the aforementioned Seminar context and, while dealing with heterogeneous topics, offer important examples of research both on teaching and on the methodologies applied to it. As a Statistical Service, which for years has taken care of the collection and dissemination of data, we hope that in this, as in the other volumes of the series, the reader will find confirmation of the importance that data play, both in scientific research and in practice in classroom

Predicting Success of Minority Nursing Students on the New NCLEX-RN.

The purpose of this study was to identify academic variables that could be used to forecast success for minority, baccalaureate (BSN) students enrolled in higher education in the south. A second purpose was to develop a methodological framework for predicting success on the post-1988 versions of the National Council Licensure Examination for Registered Nurses (NCLEX-RN), that enhanced external validity, and generalizability. The best predictors of success for minority BSN nursing students were the Mosby assesstest, school comprehensive exit exams, GPA microbiology, the college cumulative GPA, nursing course cumulative GPA, and ACT composite. The sample included 216 Black graduates of three BSN programs located in Louisiana, who took the July 1988 through July 1991 versions of NCLEX-RN. The findings indicated that high ACT scores are not necessarily predictive of NCLEX success, and the ACT and pre-admit GPAs should be used cautiously in eliminating minority students from nursing education. A methodological design that incorporated discriminant analysis, factor analysis and a four stage variable selection process, employed prior to a stepwise procedure was used. The equation derived was externally valid, stable across schools, and correctly classified 96% of the students used in the variable analysis. Only two of forty-two subjects (4.8%), known to belong to the fail group, were misclassified. The cross-validation, correct classification rate for BSN graduates of a different school was 76%, and showed 26% improvement over what was expected by chance alone

The role of the HCD/CAIAT Project in improving the ability of science teachers for constructing HCD test items in the Kingdom of Saudi Arabia

The objective of this research is to participate in improving the quality of education in the Kingdom of Saudi Arabia (KSA) by developing the skills of Saudi female science teachers in writing higher cognitive demand (HCD) questions of exemplary quality. It is an evaluative study that follows the descriptive method of research design by depending on a combination of both quantitative and qualitative inquiry. Therefore, various instruments for collecting data were employed. The sample size of 409 represents all of the female science teachers who work in the girls' schools in the urban area of Al Ahsa, a city in KSA. A suggested program called HCD/CAIAT is introduced and the main objective of the present evaluative research is to examine this project’s functional potential to improve the researched sample related practices. The project includes an innovative software package, the Computer Aided Item Analysis Technique (CAIAT) designed purposely for this research in the Arabic language to provide the sample teachers with the two parameters of classical item analysis that indicate the strengths or weaknesses of a test question (difficulty and discrimination). This package is introduced through a training course that also trains the teachers in skills of question construction and teaching on HCD level. The CAIAT is intended to stimulate the teachers' professional development (PD) by raising their awareness of the validity of their HCD test items and encouraging/assisting them to improve their HCD questions over time which is anticipated to help improve their instruction. This concept of utilising CAIAT for improving teachers' practices is breaking new ground and establishing a basis for further development in the field of study. The main purpose of the research is to answer the following two major questions. The first is to what extent can the HCD/CAIAT project assist female science teachers in Saudi schools to improve their ability to analyse their test questions, so as to write exemplary HCD test items and to teach at HCD level (Effectiveness dimension)? And the second is, to what extent could this be reflected in their on-going practice both for the test construction and for teaching (Adoption dimension)? The findings have indicated that the sample teachers' prior background in the researched concepts and skills (HCD and IAT) are limited. However, the effectiveness dimension findings showed that the teachers have successfully acquired all of the project's abilities/skills: knowledge of HCD concepts, skills of writing HCD instructional objectives and HCD questions, and using/utilising CAIAT successfully for assessing their test items. For the adoption dimension, the HCD/CAIAT package was successful in encouraging the teachers to adopt HCD and IAT which was a result of the successful role of the CAIAT software in stimulating the teachers' PD for learning (on their own) how to improve their assessment skills for HCD levels. Furthermore, the research has identified ten study variables, which are the teachers' background characteristics, in order to test the statistical significance of their role in the reported differences amongst the results found for the various aspects measured by the research data collection instruments. These teachers' characteristics are: educational qualification, prior training on test construction skills, prior training on IAT, key stage (intermediate/secondary), level of graduation (GPA/equivalent), years of experience in teaching, specialisation subject, prior experience in using computers, possess of a PC at home and ability to use some mainstream software packages. Statistically, the impact of these variables on the teachers' acquisition or adoption of the project's concept and skills was found very limited; which supports generalizability of the research findings. It is recommended that the Ministry of Education (MoE) at KSA adopt the HCD/CAIAT package in order to encourage all KSA female science teachers to tackle HCD levels in their instruction and assessment, which is very likely to have a positive impact on their efforts in teaching thinking and inducing creativity. Ten other recommendations were also suggested

Nursing Educators\u27 and Nursing Leaders\u27 Views on Practice Readiness in Novice Nurses

A perceived discrepancy exists in understanding between nursing educators\u27 and hospital nurse leaders\u27 views on job performance expectations and the reality of current job performance that may contribute to the difficulty experienced by novice nurses during their transition period. Lack of clarity in expectations may lead novice nurses to change jobs or leave the nursing profession within the first year of practice. The purpose of this descriptive study, guided by Benner\u27s novice to expert theory, was to determine whether a difference exists between hospital nurse leaders\u27 beliefs and nursing educators\u27 beliefs about the frequency and competency levels, including leadership for novice nurses transitioning into practice, critical care nursing performance, teaching and collaboration, ability to plan and evaluate, interpersonal relations and communications, and professional development. Survey data were collected from 52 nursing educators and 52 hospital nurse leaders using the Schwirian\u27s 6-dimension scale of nursing performance and analyzed using MANOVA and independent t tests. No differences were identified between hospital nurse leaders\u27 and nurse educators\u27 beliefs on the frequency and competency level in all areas examined for novice nurses transitioning into practice. Hospital nurse leaders\u27 and nurse educators\u27 expectations for novice nurses aligned. Further research should focus on ways to strengthen novice nurses\u27 knowledge, critical thinking, and skills so they are better prepared to enter the transition period. Outcomes from this study may be used to improve education and transition to practice for novice nurses, which can result in positive social change

On the quantification of complexity and diversity from phenotypes to ecosystems

A cornerstone of ecology and evolution is comparing and explaining the complexity of natural systems, be they genomes, phenotypes, communities, or entire ecosystems. These comparisons and explanations then beget questions about how complexity should be quantified in theory and estimated in practice. Here I embrace diversity partitioning using Hill or effective numbers to move the empirical side of the field regarding the quantification of biological complexity. First, at the level of phenotypes, I show that traditional multivariate analyses ignore individual complexity and provide relatively abstract representations of variation among individuals. I then suggest using well-known diversity indices from community ecology to describe phenotypic complexity as the diversity of distinct subsidiary components of a trait. I show how total trait diversity can be partitioned into within-individual complexity (alpha diversity) and between- individual components (beta diversity) within a hierarchical framework. Second, I use simulations to demonstrate that na ̈ıve measures of standardized beta diversity such as turnover or local/regional dissimilarity are biased estimators when the number of sampled units (e.g., quadrats) is less than the “true” number of communities in a system (if it exists). I then propose using average pairwise dissimilarities and show that this measure is unbiased regardless of the number of sample units. Moreover, the measure is intuitively interpreted as the average proportional change in composition as one moves from one sample to the next. Finally, I apply a hierarchical Bayesian approach to the estimation of species abundances within and among samples, communities, or regions. This strategy accommodates difficult problems of bias and uncertainty in the estimation of the diversity of the underlying communities while providing integrated estimates of uncertainty. Moreover, multilevel hierarchies are possible. We can then use model comparison to determine whether patches/communities/habitats within regions or sets are distinct subcommunities of a metapopulation, or whether they are “arbitrary” distinctions from one contiguous system