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As a discipline, health organisation and management is focused on health-specific, collective behaviours and activities, whose empirical and theoretical scholarship…
As a discipline, health organisation and management is focused on health-specific, collective behaviours and activities, whose empirical and theoretical scholarship remains under-utilised in the field of implementation science. This under-engagement between fields potentially constrains the understanding of mechanisms influencing the implementation of evidence-based innovations in health care. The aim of this viewpoint article is to examine how a selection of theories, models and frameworks (theoretical approaches) have been applied to better understand phenomena at the micro, meso and macro systems levels for the implementation of health care innovations. The purpose of which is to illustrate the potential applicability and complementarity of embedding health organisation and management scholarship within the study of implementation science.
The authors begin by introducing the two fields, before exploring how exemplary theories, models and frameworks have been applied to study the implementation of innovations in the health organisation and management literature. In this viewpoint article, the authors briefly reviewed a targeted collection of articles published in the Journal of Health Organization and Management (as a proxy for the broader literature) and identified the theories, models and frameworks they applied in implementation studies. The authors then present a more detailed exploration of three interdisciplinary theories and how they were applied across three different levels of health systems: normalization process theory (NPT) at the micro individual and interpersonal level; institutional logics at the meso organisational level; and complexity theory at the macro policy level. These examples are used to illustrate practical considerations when implementing change in health care organisations that can and have been used across various levels of the health system beyond these presented examples.
Within the Journal of Health Organization and Management, the authors identified 31 implementation articles, utilising 34 theories, models or frameworks published in the last five years. As an example of how theories, models and frameworks can be applied at the micro individual and interpersonal levels, behavioural theories originating from psychology and sociology (e.g. NPT) were used to guide the selection of appropriate implementation strategies or explain implementation outcomes based on identified barriers and enablers to implementing innovations of interest. Projects aiming to implement change at the meso organisational level can learn from the application of theories such as institutional logics, which help elucidate how relationships at the macro and micro-level have a powerful influence on successful or unsuccessful organisational action. At the macro policy level, complexity theory represented a promising direction for implementation science by considering health care organisations as complex adaptive systems.
This paper illustrates the utility of a range of theories, models and frameworks for implementation science, from a health organisation and management standpoint. The authors’ viewpoint article suggests that increased crossovers could contribute to strengthening both disciplines and our understanding of how to support the implementation of evidence-based innovations in health care.
The study aimed to understand the effect of instructional coaching on teachers' implementation of a science teaching improvement programme and whether it varies in schools…
The study aimed to understand the effect of instructional coaching on teachers' implementation of a science teaching improvement programme and whether it varies in schools of different socioeconomic statuses.
The authors conducted an experimental study. A total of 59 seventh-grade classrooms from a representative sample of public schools from the city of Buenos Aires, Argentina, were provided with research-based science educative curriculum materials (ECM) as resources to improve their teaching. A randomly selected treatment group received additional instructional coaching. Coaches met one-on-one with teachers on a weekly basis, providing pedagogical support to enact the ECM. After a 12-week intervention, the authors analyzed science teaching practices as evidenced in students' notebooks. The authors used a fidelity framework to understand the programme's implementation (with and without coaching), considering its adherence, dosage and quality, and compared how it varied across schools.
While teachers in both groups used the ECM in their science lessons (i.e. with high adherence), instructional coaching almost tripled science teaching time (i.e. the dosage) but did not increase the quality of implementation (i.e. the percentage of inquiry-based science activities taught). In low socioeconomic status schools, the effect of coaching on dosage was even more intense.
This study provides robust evidence on the impact of instructional coaching on teaching improvement programmes in science in developing countries, an under researched topic. The findings may contribute to developing targeted coaching interventions considering their effectiveness in different school contexts.
Purpose – The aim of this study is to determine the effects of inquiry instruction incorporating with STEM learning on Chemistry Education of Malikussaleh University…
Purpose – The aim of this study is to determine the effects of inquiry instruction incorporating with STEM learning on Chemistry Education of Malikussaleh University students’ science process skills and science attitudes.
Design/Methodology/Approach – The pre-experimental design, which is a mixed method approach is used in the study that included a pretest-posttest one group model and descriptive quantitative.
Findings – As a result of data analysis that STEM learning significantly enhances students’ science process skills and attitudes toward inquiry instruction. This study examines how participation in a semester long inquiry-based STEM learning project that involves interdisciplinary skills, sociological research on attitudes, and behaviors enhances the scientific and quantitative literacies of STEM students.
Research Limitations/Implications – Quantitative research is needed to determine the more common effects of learning outcomes. However, this study only determines a self-assessment on science attitudes. The other one is a limitation on the participants and reviewing aspects of learning with more variables in order to obtain more optimal results.
Practical Implications – The results of this study have practical implications in terms of hands-on activities. The learning model can be used to explain the concept of multidisciplinary studies and particularly to students and their parents. It will be a useful model for lecturers, personal tutors, and any other practitioners involved in hands-on activities.
Originality/Value – This paper innovative at a conceptual level of education development for students, graduates, and it is very simple descriptive papers. It will be of value to anybody with an interest in education competitiveness issues.
In 1976, in a speech at Ruskin College, Oxford, Prime Minister James Callaghan asked ‘Why is it that such a high proportion of girls abandon science before leaving…
In 1976, in a speech at Ruskin College, Oxford, Prime Minister James Callaghan asked ‘Why is it that such a high proportion of girls abandon science before leaving school?’ (Gillard, 2018). Little has changed over the last 40 years; a recent report from the National Audit Office (2018, p. 28) stated that only 8% of science, technology, engineering and mathematics (STEM) apprenticeships were taken up by women in 2016/2017 and that the shortage of STEM skills in the workforce is a key UK economic problem. However, just as the Aldridge marriage has been the source of considerable interest and the site of significant financial investment in terms of designer kitchens and expensive holidays, so has the issue of ‘girls in science’ been a consistently debated topic and taken up a large chunk of government and industry spending. Research (Archer et al., 2013) suggests that although children enjoy their science experiences in school, too few pupils aspire to a STEM career. It reveals that the pupils most likely to aspire to careers in science are those whose families have high ‘science capital’ which ‘refers to the science-related qualifications, understanding, knowledge (about science and “how it works”), interest and social contacts (e.g. “knowing someone who works in a science-related job”)’ (Archer et al., 2016, p. 3).
Episodes of The Archers are full of scientific talk, from herbal leys to plate meters. This chapter looks at how the science capital in Ambridge is shared. Why is Alice Carter an engineer and not Emma Grundy? Will Kiera Grundy choose physics A level? Who are the female STEM role models? How can the concept of science capital help us to understand the career paths of Ambridge residents? Will the young girls of Ambridge remedy the gender imbalance in STEM careers?
The Computing Research Association (CRA) was formed in 1972 as the Computer Science Board (CSB), which provided a forum for the chairs of Ph.D.-granting computer science…
The Computing Research Association (CRA) was formed in 1972 as the Computer Science Board (CSB), which provided a forum for the chairs of Ph.D.-granting computer science departments to discuss issues and share information (CRA, 2009). Since 1989, women have never accounted for more than 24% of the computer science faculty at any given rank (e.g., assistant, associate, or full professor). Currently, women represent 21.7%, 15.4%, and 11.7% of computer science faculty at the assistant, associate, and full professor ranks, respectively. Women have been as much as 24% of the Ph.D. graduates in computing in a single year. Since 1998, African Americans have never accounted for more than 2.0%, 1.4%, and 0.7% of the assistant, associate, and full professors, respectively, in computer science. Furthermore, African Americans have never accounted for more than 2% of the Ph.D. graduates in computer science in a single year over that same time period. It appears women and African Americans overall are underrepresented among the ranks of computer science faculty, but to what extent?
Data science lacks a distinctive identity and a theory-informed approach, both for its own sake and to properly be applied conjointly to the social sciences. This paper’s…
Data science lacks a distinctive identity and a theory-informed approach, both for its own sake and to properly be applied conjointly to the social sciences. This paper’s purposes are twofold: to provide (1) data science an illustration of theory adoption, able to address explanation and support prediction/prescription capacities and (2) a rationale for identification of the key phenomena and properties of data science so that the data speak through a contextual understanding of reality, broader than has been usual.
A literature review and a derived conceptual research model for a push–pull approach (adapted for a data science study in the management field) are presented. A real location–allocation problem is solved through a specific algorithm and explained in the light of the adapted push–pull theory, serving as an instance for a data science theory-informed application in the management field.
This study advances knowledge on the definition of data science key phenomena as not just pure “data”, but interrelated data and datasets properties, as well as on the specific adaptation of the push-pull theory through its definition, dimensionality and interaction model, also illustrating how to apply the theory in a data science theory-informed research. The proposed model contributes to the theoretical strengthening of data science, still an incipient area, and the solution of the location-allocation problem suggests the applicability of the proposed approach to broad data science problems, alleviating the criticism on the lack of explanation and the focus on pattern recognition in data science practice and research.
The proposed algorithm requires the previous definition of a perimeter of interest. This aspect should be characterised as an antecedent to the model, which is a strong assumption. As for prescription, in this specific case, one has to take complementary actions, since theory, model and algorithm are not detached from in loco visits, market research or interviews with potential stakeholders.
This study offers a conceptual model for practical location–allocation problem analyses, based on the push–pull theoretical components. So, it suggests a proper definition for each component (the object, the perspective, the forces, its degrees and the nature of the movement). The proposed model has also an algorithm for computational implementation, which visually describes and explains components interaction, allowing further simulation (estimated forces degrees) for prediction.
First, this study identifies an overlap of push–pull theoretical approaches, which suggests theory adoption eventually as mere common sense, weakening further theoretical development. Second, this study elaborates a definition for the push–pull theory, a dimensionality and a relationship between its components. Third, a typical location–allocation problem is analysed in the light of the refactored theory, showing its adequacy for that class of problems. And fourth, this study suggests that the essence of a data science should be the study of contextual relationships among data, and that the context should be provided by the spatial, temporal, political, economic and social analytical interests.
The present investigation aims to present the status of planetary science research in India using different scientometric indicators, as reflected in the Web of Science…
The present investigation aims to present the status of planetary science research in India using different scientometric indicators, as reflected in the Web of Science Core Collection database.
The researcher adopted systematic approaches to retrieve the data from the Web of Science Core Collection database for 20 years by using AAS Astronomical subject keywords. A total of 1,504 Indian publications and 55,572 World's publications were considered for analysis. The data were analyzed using the biblioshiny application of bibliometrix to investigate the most productive countries/territories, institutions, authors, research fields, journals, keywords, and h, g-index. The VOSviewer program is used to construct and visualize scientometric networks and analyze the co-occurrence of terms. “Webometric Analyst 2.0” is used to retrieve the Altmetric attention scores for the articles.
The results revealed that the publications on planetary science research has increased over time, with an annual growth rate of 9.66%. The study also revealed the prolific authors and institutions, productive journals and most frequently cited journals. The USA was the major collaborating partner of India. The results also provided valuable information on the citations made to these papers on planetary science, including a total number of citations, average citations per item, cited rate and h-index. There were 28,086 citations to 1,504 papers. The top 67 citation papers were the h-core papers on planetary science in India. Altmetric score for planetary science articles ranged from 1 to 2,418. Twitter (69%), news outlets (16%), blogs (6%), and Facebook (6%) were the most popular Altmetric data resources.
This investigation is the first attempt to employ scientometrics and visualization techniques to planetary science research in India.