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More diversity is now shown in students gaining admission into universities, many who are ill-equipped for first-year studies and assessment writing. This can result in a failing grade for some, which can impact their success and progression. This study contributes to the student success literature by reporting on the six-step one-on-one targeted intervention strategy devised to support the 33 out of 500 students who were unsuccessful in their first university assessment and its resubmission. The study also details the theoretical framework that underpinned the subject--Carol Dweck's growth mindset, Mezirow's transformative learning theory, and the maxim "Your success is our goal"! The study determined that: (1) the intervention was successful for the 33 students who each passed the assessment; (2) a pre- and postintervention writing skills assessment showed an improvement of +0.67 to give an average of 3.48, where 3 is a pass; and (3) at interview, students (76.9%) reported their improved writing abilities and that the intervention support was helpful. The study concluded that failing students can be successful when they are encouraged to use a growth mindset and individually supported to develop their writing skills. [Note: The page range (147-164) shown on the PDF is incorrect. The correct page range is 147-163.]

A measure of teacher identity specific to teachers of mathematics was developed and assessed, the teacher of mathematics identity (ToMI) scale. A sample of teachers was recruited from a state-based mathematics association to complete an online survey including items based on the theories of Mead, Erikson, and Wenger. The subscales of belonging to a mathematics community, self-efficacy as a teacher of mathematics, and enthusiasm to be a teacher of mathematics were derived using exploratory factor analysis (n = 301) and then confirmed with confirmatory factor analysis (n = 311) with randomly allocated independent subsamples. These subscales were related and, when combined to form a single factor, explained a substantial proportion of the variance in the data, suggesting that the ToMI scale can be used as three separate subscales or combined to form a single overarching construct. Overall, ToMI and subscale scores were used in the validation process. Tests of validity were run in the two randomly allocated subsamples independently, allowing for replication of findings. As predicted based on the literature, the ToMI scale and subscales were related to the number of years teaching mathematics, the size of teacher of mathematics network accessed by teachers, and participation in mathematics-specific self-directed professional learning and wellbeing while teaching mathematics. These results reveal this initial iteration of the ToMI scale as valid concerning the underlying teacher identity theory, providing an important research avenue to pursue our understanding and development of effective teachers of mathematics.

This article outlines an approach to bridging the gap between the theory and practice of differentiated instruction. Differentiated instruction has long been suggested as a pedagogical approach to cater for student individuality and diversity, particularly in mixed-ability classrooms. Although the theory of differentiated instruction has been applied widely, such instruction has not been taken up widely in teaching practice. The first part of the article explores the relationship of theory and practice of differentiated instruction in relation to pedagogical content knowledge, teacher efficacy, formative assessment, teacher confidence and competence and professional learning. This exploration uses exemplar cases from mathematics teaching to pave the way for an outline, in the second part of the article, of how differentiated instruction could be implemented for the mixed-ability groupings increasingly engaged in the Australian secondary mathematics classroom. A protype practice framework for teachers is presented as part of a project being conducted in regional Australia, with the overall aim of assisting teachers in developing and implementing strategies for differentiated instruction in secondary mathematics classrooms.

This paper describes a design-based implementation research (DBIR) approach to the development and trialling of a new generation massive open online course (ngMOOC) situated in an instructional setting of undergraduate mathematics at a regional Australian university. This process is underscored by two important innovations: (a) a basis in a well-established human cognitive architecture in terms of cognitive load theory; and (b) point-of-contact feedback based in a well-tested online system dedicated to enhancing the learning process. Analysis of preliminary trials suggests that the DBIR approach to the ngMOOC construction and development supports theoretical standpoints that argue for an understanding of how design for optimal learning can utilise conditions, such as differing online or blended educational contexts, in order to be effective and scalable. The ngMOOC development described in this paper marks the adoption of a cognitive architecture in conjunction with feedback systems, offering the groundwork for use of adaptive systems that cater for learner expertise. This approach seems especially useful in constructing and developing online learning that is self-paced and curriculum-based.

Multiparametric assays for risk stratification are widely used in the management of both node negative and node positive hormone receptor positive invasive breast cancer. Recent data from multiple sources suggests that different tests may provide different risk estimates at the individual patient level. The TEAM pathology study consists of 3284 postmenopausal ER+ve breast cancers treated with endocrine therapy Using genes comprising the following multi-parametric tests OncotypeDx®, Prosigna™ and MammaPrint® signatures were trained to recapitulate true assay results. Patients were then classified into risk groups and survival assessed. Whilst likelihood χ2 ratios suggested limited value for combining tests, Kaplan-Meier and LogRank tests within risk groups suggested combinations of tests provided statistically significant stratification of potential clinical value. Paradoxically whilst Prosigna-trained results stratified Oncotype-trained subgroups across low and intermediate risk categories, only intermediate risk Prosigna-trained cases were further stratified by Oncotype-trained results. Both Oncotype-trained and Prosigna-trained results further stratified MammaPrint-trained low risk cases, and MammaPrint-trained results also stratified Oncotype-trained low and intermediate risk groups but not Prosigna-trained results. Comparisons between existing multiparametric tests are challenging, and evidence on discordance between tests in risk stratification presents further dilemmas. Detailed analysis of the TEAM pathology study suggests a complex inter-relationship between test results in the same patient cohorts which requires careful evaluation regarding test utility. Further prognostic improvement appears both desirable and achievable.

This paper examines Grade 6 students' thinking about geometrical solids and their properties in the context of a computer-based task. The main focus is to explore how students interact with a number of tasks based on the dynamic transformation of computer-based representations of 3D solids in a geometry classroom with the aid of a Dynamic Geometric Environment. The analysis of two teaching experiments suggests that the dynamic transformations of geometrical solids encourage the students to investigate relationships between the solids and their properties and their 2D representations. Through the tasks, students realize the existence of non-trivial conventions in 2D representations and become aware that angles and edge dimensions may be distorted. The study provides insight into student learning around geometric solids and their properties, and consequently an opportunity to enhance the teaching of 3D geometry.

Undertaking a systematic review can have many benefits, beyond any theoretical or conceptual discoveries pertaining to the underlying research question. This paper explores the value of utilising a hybrid academic team when undertaking the systematic review process, and shares a range of practical strategies. The paper also comments on how such a hybrid team sits in a continuum of cooperation, coordination and collaboration. Key recommendations include choosing a great team, communicating well, documenting everything, and being explicit--for the benefit of your research team, and the readers of your systematic review.

The twin processes of collaborative inquiry and generative dialogue underpin two closely aligned and increasingly influential school leadership development programs, one in Alberta, Canada, and the other in New South Wales, Australia. This paper focuses primarily on the Australian program, the character of which has been strongly influenced by its Canadian predecessor. Of interest in the paper is the nature of the foundations of collaborative inquiry and generative dialogue, and the relationship of these processes to an expressed need for better leadership development in the Australian school sector. David Townsend and Pam Adams, who are principally responsible for generating a school leadership development model based on the use of both collaborative inquiry and generative dialogue, have sought to show how these two processes should function seamlessly, but there is more to be said about the nature of their relationship. This paper seeks to throw more light on the integral role played by generative dialogue in empowering collaborative inquiry in the context of school leadership development.

This article outlines a Teacher of Mathematics Identity (ToMI) framework as an innovative theoretical foundation for supporting teachers of mathematics in regional, rural and remote (RRR) Australia. The framework is based on the identification of systemic challenges and provision of adaptive solutions, beginning with localised challenges faced in RRR communities. In unpacking the ToMI framework, this article outlines the basis for a longitudinal study designed to develop interconnected collaborative networks for teachers of mathematics in order to help them develop their professional identity. These networks include professional learning opportunities and systematic feedback and support regimes, such as mentoring, all within a community of practice supported by a professional affiliate organisation. Once the efficacy and applicability of the framework is established, it is likely to apply to other teaching disciplines, in particular, to STEM teaching areas, but also to other subject areas, as well as other countries, that might share similar systemic challenges.

Formative assessment is a crucial aspect of teaching and learning in the classroom, but there is evidence that there has been a lack of effective implementation of formative assessment in practice. In response, this article outlines the design and development of a formative assessment framework that can be implemented as a consistent whole-school approach to embedding practice that is owned and developed by teachers. The approach outlined in the framework, therefore, is designed to integrate formative assessment practices within a school system context, providing advice and support to school leaders and teachers. The framework in practice should act to enable teachers and students to develop new understandings and perspectives about each other and the nature of teaching and learning, as well as ways to implement new practices of teaching and learning supported by reflective modes of active participation.

Biomarkers lie at the heart of precision medicine. Surprisingly, while rapid genomic profiling is becoming ubiquitous, the development of biomarkers usually involves the application of bespoke techniques that cannot be directly applied to other datasets. There is an urgent need for a systematic methodology to create biologically-interpretable molecular models that robustly predict key phenotypes. Here we present SIMMS (Subnetwork Integration for Multi-Modal Signatures): an algorithm that fragments pathways into functional modules and uses these to predict phenotypes. We apply SIMMS to multiple data types across five diseases, and in each it reproducibly identifies known and novel subtypes, and makes superior predictions to the best bespoke approaches. To demonstrate its ability on a new dataset, we profile 33 genes/nodes of the PI3K pathway in 1734 FFPE breast tumors and create a four-subnetwork prediction model. This model out-performs a clinically-validated molecular test in an independent cohort of 1742 patients. SIMMS is generic and enables systematic data integration for robust biomarker discovery.

Many women with hormone receptor-positive early breast cancer can be managed effectively with endocrine therapies alone. However, additional systemic chemotherapy treatment is necessary for others. The clinical challenges in managing high-risk women are to identify existing and novel druggable targets, and to identify those who would benefit from these therapies. Therefore, we performed mRNA abundance analysis using the Tamoxifen and Exemestane Adjuvant Multinational (TEAM) trial pathology cohort to identify a signature of residual risk following endocrine therapy and pathways that are potentially druggable. A panel of genes compiled from academic and commercial multiparametric tests as well as genes of importance to breast cancer pathogenesis was used to profile 3825 patients. A signature of 95 genes, including nodal status, was validated to stratify endocrine-treated patients into high-risk and low-risk groups based on distant relapse-free survival (DRFS; Hazard Ratio = 5.05, 95% CI 3.53-7.22, p = 7.51 × 10-19). This risk signature was also found to perform better than current multiparametric tests. When the 95-gene prognostic signature was applied to all patients in the validation cohort, including patients who received adjuvant chemotherapy, the signature remained prognostic (HR = 4.76, 95% CI 3.61-6.28, p = 2.53× 10-28). Functional gene interaction analyses identified six significant modules representing pathways involved in cell cycle control, mitosis and receptor tyrosine signaling; containing a number of genes with existing targeted therapies for use in breast or other malignancies. Thus the identification of high-risk patients using this prognostic signature has the potential to also prioritize patients for treatment with these targeted therapies.

The emerging concept of generative dialogue is accompanied by strong claims for its benefit. A literature review identified six dominant models of generative dialogue across the range of disciplines of education, business studies, counselling and psychology. Through the analysis, commonalities and differences between the different models are identified, with an ultimate goal of providing an overarching description of those crucial attributes that make generative dialogue and its implementation beneficial as a management tool in education.

Breast cancer (BC) is the most prominent tumor type among women, accounting for 32% of newly diagnosed cancer cases. BC risk factors include inherited germline pathogenic gene variants and family history of disease. However, the etiology of the disease remains occult in most cases. Therefore, in the absence of high-risk factors, a polygenic basis has been suggested to contribute to susceptibility. This information is utilized to calculate the Polygenic Risk Score (PRS) which is indicative of BC risk. This study aimed to evaluate retrospectively the clinical usefulness of PRS integration in BC risk calculation, utilizing a group of patients who have already been diagnosed with BC. The study comprised 105 breast cancer patients with hereditary genetic analysis results obtained by NGS. The selection included all testing results: high-risk gene-positive, intermediate/low-risk gene-positive, and negative. PRS results were obtained from an external laboratory (Allelica). PRS-based BC risk was computed both with and without considering additional risk factors, including gene status and family history. A significantly different PRS percentile distribution consistent with higher BC risk was observed in our cohort compared to the general population. Higher PRS-based BC risks were detected in younger patients and in those with FH of cancers. Among patients with a pathogenic germline variant detected, reduced PRS values were observed, while the BC risk was mainly determined by a monogenic etiology. Upon comprehensive analysis encompassing FH, gene status, and PRS, it was determined that 41.90% (44/105) of the patients demonstrated an elevated susceptibility for BC. Moreover, 63.63% of the patients with FH of BC and without an inherited pathogenic genetic variant detected showed increased BC risk by incorporating the PRS result. Our results indicate a major utility of PRS calculation in women with FH in the absence of a monogenic etiology detected by NGS. By combining high-risk strategies, such as inherited disease analysis, with low-risk screening strategies, such as FH and PRS, breast cancer risk stratification can be improved. This would facilitate the development of more effective preventive measures and optimize the allocation of healthcare resources. [ABSTRACT FROM AUTHOR]

Background/Aim: Breast cancer remains the most prevalent type of cancer among women worldwide, and it remains the primary cause of cancer-related deaths in this demographic. Neuroendocrine breast cancer (NBC), an uncommon subtype comprising less than 1% of cases, typically occurs in older women and displays as a slow-growing, low-grade condition. NBC exhibits distinct histological patterns and immunohistochemical markers. Given the limited data on NBC, assays are required that will provide information on molecular profiling and assist in clinical decision making. The aim of the study was to investigate whether a modern Multigene Assay (MGA) could assist on treatment planning of NBC patients. Case Report: A cohort of four patients was analyzed using a MGA. The presented cases featured young, pre-menopausal women with clear NBC, lacking family history. All were lymph nodenegative, with robust expression of neuroendocrine markers. Despite high hormone receptor expression, all tumors were poorly differentiated with elevated Ki67 levels. Oncotype DX analysis indicated a need for chemotherapy in three cases and not in one. This underscores the heterogeneity within NBC, emphasizing the importance of personalized treatment decisions. Conclusion: While NBC is rare and lacks extensive studies, the use of multigene assays like Oncotype DX may play a pivotal role in treatment planning, especially in cases with varying histological parameters. [ABSTRACT FROM AUTHOR]

Student mathematics performance and the need for work-ready graduates to be mathematics-competent is a core issue for many universities. While both student and teacher are responsible for learning outcomes, there is a need to explicitly acknowledge the weak mathematics foundation of many university students. A systematic literature review was undertaken of identified innovations and/or interventions that may lead to improvement in student outcomes for university mathematics-based units of study. The review revealed the importance of understanding the foundations of student performance in higher education mathematics learning, especially in first year. Pre-university mathematics skills were identified as significant in student retention and mathematics success at university, and a specific focus on student pre-university mathematics skill level was found to be more effective in providing help, rather than simply focusing on a particular at-risk group. Diagnostics tools were found to be important in identifying (1) student background and (2) appropriate intervention. The studies highlighted the importance of appropriate and validated interventions in mathematics teaching and learning, and the need to improve the learning model for mathematics-based subjects, communication and technology innovations.

Our research programme, a part of which is presented in this paper, looked at four year old children's ability to use manipulatives in the construction of cube models. We looked at how pre-school children managed the creation of cube nets as a mathematical problem and whether graphical representations of solutions could become a useful tool in a child's quest for solving the nets of a cube mathematical problem. We followed the work of twenty four-year old children who were asked to solve a cube creation geometry mathematical problem. In order for the problem to be successfully solved, graphical representations of solutions had to be developed. The data analysis showed that, during the course of the programme, children developed the ability to use manipulatives in order to solve the mathematical problem. The development of strategies for graphically representing the solutions also seemed to have played an important role in solving the specific mathematical problem. [Corresponding Author: Konstantinos Zacharos]

Simple Summary: The aim of this study was to explore the utility of cascade family testing (CFT) in families of breast cancer patients who carry specific genetic variations. We conducted genetic analysis in a group of breast cancer patients and identified genetic variations in over 20% of them; thus, CFT was recommended to their first-degree relatives. Among those tested, the majority were asymptomatic females and mainly offspring, siblings, or parents of the patients. The study showed that CFT was most commonly performed in families with high-risk genetic findings, and we concluded that CFT could be a valuable approach for preventing hereditary cancers by identifying at-risk family members. We also emphasized the need for improved genetic counseling and communication to ensure effective implementation. Background: Hereditary cancer predisposition syndromes are responsible for approximately 5–10% of all diagnosed cancer cases. In order to identify individuals at risk in a cost-efficient manner, family members of individuals carrying pathogenic alterations are tested only for the specific variant that was identified in their carrier relative. The purpose of this study was to investigate the clinical use and implementation of cascade family testing (CFT) in families of breast cancer patients with pathogenic/likely pathogenic variants (PVs/LPVs) in cancer-related predisposition genes. Methods: Germline sequencing was carried out with NGS technology using a 52-gene panel, and cascade testing was performed by Sanger sequencing or MLPA. Results: In a cohort of 1785 breast cancer patients (families), 20.3% were found to have PVs/LPVs. Specifically, 52.2%, 25.1%, and 22.7% of patients had positive findings in high-, intermediate-, and low-penetrance breast cancer susceptibility genes, respectively. Although CFT was recommended to all families, only 117 families (32.3%) agreed to proceed with genetic testing. Among the first-degree relatives who underwent CFT, 70.3% were female, and 108 of 121 (89.3%) were cancer free. Additionally, 42.7%, 36.7%, and 20.6% were offspring, siblings, and parents of the subject, respectively. Our data suggest that CFT was mostly undertaken (104/117, 88.8%) in families with positive findings in high-risk genes. Conclusions: Cascade family testing can be a powerful tool for primary cancer prevention by identifying at-risk family members. It is of utmost importance to implement genetic counseling approaches leading to increased awareness and communication of genetic testing results. [ABSTRACT FROM AUTHOR]

Background/Aim: Germline copy number variation (CNV) is a type of genetic variant that predisposes significantly to inherited cancers. Today, next-generation sequencing (NGS) technologies have contributed to multi gene panel analysis in clinical practice. Materials and Methods: A total of 2,163 patients were screened for cancer susceptibility, using a solution-based capture method. A panel of 52 genes was used for targeted NGS. The capture-based approach enables computational analysis of CNVs from NGS data. We studied the performance of the CNV module of the commercial software suite SeqPilot (JSI Medical Systems) and of the non-commercial tool panelcn.MOPS. Additionally, we tested the performance of digital multiplex ligation-dependent probe amplification (digitalMLPA). Results: Pathogenic/likely pathogenic variants (P/LP) were identified in 464 samples (21.5%). CNV accounts for 10.8% (50/464) of pathogenic variants, referring to deletion/duplication of one or more exons of a gene. In patients with breast and ovarian cancer, CNVs accounted for 10.2% and 6.8% of pathogenic variants, respectively. In colorectal cancer patients, CNV accounted for 28.6% of pathogenic/likely pathogenic variants. Conclusion: In silico CNV detection tools provide a viable and cost-effective method to identify CNVs from NGS experiments. CNVs constitute a substantial percentage of P/LP variants, since they represent up to one of every ten P/LP findings identified by NGS multigene analysis; therefore, their evaluation is highly recommended to improve the diagnostic yield of hereditary cancer analysis. [ABSTRACT FROM AUTHOR]