Data Analysis Skills Research Articles

Pathways for Enhancing the Teaching Quality of Financial Education through Research Practices

Objective: This study investigates how integrating research practices into financial education can enhance students' learning outcomes, practical skills, and innovation capacity. With the rapid evolution of the financial sector due to globalization and technological advancements, financial education must move beyond traditional theoretical approaches to prepare students for complex real-world challenges. The objective of this research is to explore specific pathways for incorporating research-driven practices into financial curricula to better align education with industry demands. Methods: The study employed a mixed-method approach, combining quantitative and qualitative research methods. Surveys were distributed to 461 students and 121 faculty members from four universities—two research-intensive institutions and two applied colleges—aiming to capture diverse perspectives on the integration of research into teaching. The data were analyzed using descriptive statistics, regression models, and qualitative analysis of interviews with selected participants. The regression analysis focused on the relationship between the frequency of research participation and the development of practical skills and innovation capacity. Results: The regression analysis revealed a significant positive correlation between research participation and improved learning outcomes (β=0.52, p<0.01), practical skills (β=0.47, p<0.01), and innovation capacity (β=0.43, p<0.01). Students who participated in research projects demonstrated a deeper understanding of financial theories, stronger data analysis and decision-making skills, and greater creativity in problem-solving. These results suggest that research engagement significantly enhances students' ability to apply theoretical knowledge in practical contexts. Conclusion: Integrating research practices into financial education bridges the gap between theory and practice, fostering critical thinking, problem-solving skills, and innovation among students. Universities should prioritize research-based learning, offering opportunities for interdisciplinary research, university-business collaborations, and digital platforms to expand student access to research experiences. Future studies should explore the role of interdisciplinary research in further enhancing financial education outcomes, particularly through fields such as data science, behavioral economics, and artificial intelligence.

The digital evolution in toxicology: pioneering computational education for emerging challenges

The educational landscape of toxicology is increasingly integrating computational methodologies due to ethical concerns about animal testing and advancements in biotechnological and data analysis tools. This paper examines the evolution and significance of the Toxicology in the 21st century (Tox21) initiative and its impact on computational toxicology education. It contrasts computational toxicology with traditional methods, highlighting the limitations of conventional approaches and the new perspectives offered by computational techniques. The study emphasizes the importance of incorporating computational toxicology into curricula, including case studies that demonstrate how this integration enhances students’ problem-solving abilities, real-time data analysis skills, and innovation capabilities. Furthermore, it outlines effective teaching content and methods, including software tools, online resources, and academic literature. The paper also addresses the challenges and limitations faced in this educational shift and explores prospects for advancing computational toxicology education. By documenting these developments, the study aims to clarify the current advancements in toxicology education and the preparedness of students to address global chemical safety challenges with innovative solutions.

MEANS OF RESEARCH COMPETENCE FORMATION IN UNIVERSITY STUDENTS DURING BUSINESS FOREIGN LANGUAGE CLASSES

The article examines the means of research competence formation in university students during Business Foreign Language classes. The means of research competence formation through the developing of its key components such as methodological literacy, analytical skills, critical thinking skills and communication skills have been outlined. The development of methodological literacy is seen as a multifaceted process involving the study of the theoretical underpinnings of research, the practical application of methods, the development of critical thinking and data analysis skills. Analytical skills – the ability to process and interpret information – are considered necessary for a deep understanding of language, the effective use of new knowledge and its integration into different contexts. It has been noted that analytical skills help higher education students not only to learn grammar and vocabulary, but also to apply knowledge in real-life situations, to draw logical conclusions and to structure educational information. The development of critical thinking skills is observed as an important element in the successful acquisition of both language and analytical skills. They can be formed by integrating different tasks that encourage students to analyse, evaluate and argue. The development of communication skills is facilitated by the active practice of different formats, with the opportunity not only to learn business vocabulary, but also to master effective strategies of interaction in a work context. The means of developing research competence and its key components in Business English have been indicated. They are discussion of current office work issues, analysis of authentic business texts, translation and interpretation of business documents, presentations (reports), research projects, writing abstracts and business letters.

Impact of Plai-Zampen programs on librarians' professional development for technological advancement and management

The purose of this study is to assess the impact of the programs initiated by the Philippine Librarians Association, Inc.- Zamboanga Peninsula (PLAI-ZamPen) for the last 5 years on Librarians’ Professional Development for Technological Advancement and Management. It highlights librarians' adaptation to technological demands, emphasizing skills in software, systems, and data analysis. Employing a quantitative research design with a descriptive survey method, the study utilizes 86 librarian respondents to evaluate its profiles, program impact, and effectiveness variations based on library types, membership duration, and roles. Using tools like the Kruskal-Wallis H Test and Weighted Mean, the study provides a comprehensive analysis, emphasizing the importance of ongoing professional development for libraries to remain relevant and responsive in hybrid learning environments. The findings revealed a significant positive impact, with programs effectively equipping librarians with essential skills and fostering a culture of innovation. The analysis of membership demographics highlights a predominance of academic librarians and a mix of experienced and novice members, underscoring the inclusivity and effectiveness of PLAI-ZamPen's initiatives. In conclusion, this study this affirm that the programs initiated by PLAI-ZamPen significantly enhance librarians' professional development, particularly in the realms of technological advancement and management. The positive impact of the programs extend beyond individual skill enhancement; it also bolsters libraries' abilities to adapt to evolving community needs, thereby ensuring continued relevance and excellence in service delivery. It is recommended that continued innovation and expansion of professional development programs, focusing on emerging technological trends and management strategies will be taken into account. Thus, it will enhance librarians' proficiency in digital tools and foster global collaboration, ensuring that libraries remain essential hubs of knowledge and service excellence.

External constraints that led to physiology lab improvements.

The modifications were in response to changing constraints, including time, money, space, student background, and my knowledge and comfort. The lab went from emphasizing experiments with the attendant troubleshooting and data analysis skills to a lab focused more on giving prehealth professional students the motivation to learn physiology problem-solving skills by providing real cases. In the lab, students watched and listened to a random student try to use these problem-solving skills to solve the problem. This made them appreciate how much others also struggle in solving the problem. Some students with imposter syndrome think their classmates immediately know how to solve a problem, and therefore, seeing others also struggle has the potential to reduce imposter syndrome. Rather than having the students do experiments, they did kinesthetic activities with mechanical models to generate data without biological variation. They then graphed their data, thus improving their ability to actually read graphs rather than memorize patterns.NEW & NOTEWORTHY I learned to explicitly recognize the current and projected constraints of instructor comfort, money, space, student background (poor graph reading and problem-solving skills), student safety, and time and energy on the possible goals and methods to attain them for an undergraduate physiology lab. I cannot decide if changing constraints allowed me to reexamine my goals or whether it forced me to reexamine my goals. In either case, the reexamination of my goals (and their priorities), within the context of the constraints, allowed me to redesign the labs to better meet my new goals within this new context.

Pengembangan Video Penelitian Kuantitatif dalam Meningkatkan Kemampuan Analisis Data Mahasiswa

This research aims to develop video tutorials on quantitative methods in correlation and regression analysis. This type of research is Research and Development (R&D) with the ADDIE approach, namely Analysis, Design, Development, Implementation and Evaluation. The results obtained in this research were that the design stage included material and appearance, the development stage was a continuation of the design stage, the implementation stage was carried out on 60 semester 5 students. Next, evaluate the results of the video tutorial based on suggestions and comments from media expert validators and material experts. The average feasibility test results obtained were 85.625% in the very feasible category. The resulting learning video is considered very feasible and effective in improving students' data analysis skills with an improvement score of 29, 47%.

New skills in symbolic data analysis for official statistics

The paper draws attention to the use of Symbolic Data Analysis (SDA) in the field of Official Statistics. It is composed of three sections presenting three pilot techniques in the field of SDA. The three contributions range from a technique based on the notion of exactly unified summaries for the creation of symbolic objects, a model-based approach for interval data as an innovative parametric strategy in this context, and measures of similarity defined between a class and a collection of classes based on the frequency of the categories which characterize them. The paper shows the effectiveness of the proposed approaches as prototypes of numerous techniques developed within the SDA framework and opens to possible further developments.

Integrating Behavioural Economics into Skill Development

Abstract The contemporary economic scenario, characterized by modern technology and global relationships, demands a workforce equipped with both traditional economic knowledge and modern skills. This research explores the evolving trends in economics skill development, focusing on how educational institutions are adapting their curricula to meet these emerging demands. Traditional lecture-based methods, as criticized by early scholars like Becker and Watts, are increasingly being replaced by interactive, student-centred methodologies that foster critical thinking and problem-solving abilities. The integration of digital tools and data analytics into economics education, highlighted by McGoldrick and Peterson, reveals the broader shift toward data-driven decision-making in the global economy. Furthermore, the integration of behavioural economics, data science, and other interdisciplinary fields, enhancing students' ability to apply economic concepts to real-world experiments. This research employs a diverse-methods approach, combining surveys of educators and students with content analysis of current economics programs, to identify key trends in skill development. This study reveals a strong emphasis on data analysis skills, the integration of interdisciplinary content, and the adoption of experiential learning methods such as internships and case studies. These shifts specify a move away from traditional theory to practical, applied learning experiences enhance the students to meet demands of the modern economy. The study concludes with recommendations for better investment in educational resources, and an increased focus on experiential learning. By adapting these trends, economics education can continue to produce professionals capable of navigating the people towards global economy.

Accountant Skill Gen Z Fresh Graduates in Digital Era: A Systematic Literature Review

Purpose: The purpose of this study is to investigate the impact of emerging technologies on the skills required for accountants in the digital era, particularly focusing on the skills needed by Gen Z fresh graduates. Method: The present study builds on a systematic literature review of 41 academic articles published in Scopus Database between 2017 and 2024. It is based on the “preferred reporting items for systematic reviews and meta-analyses” (PRISMA) method. Synthesising research through a transparent, rigorous and replicable process makes it possible to explore and identify accountant skill in digital era. Findings: The findings highlighted the need for accountants to possess digital literacy skills, data analytics skills, and the ability to work collaboratively with professionals from other fields. The study also emphasized the importance of continuous professional development to keep pace with the rapid technological advancements in accounting. Originality/Value: This paper offers a comprehensive literature review on impact of emerging technologies on the skills required for accountants in the digital era, particularly focusing on the skills needed by Gen Z fresh graduates. It could provide a insight and guidance for accounting fresh graduate to possess digital literacy skills, data analytics skills, and soft skills to adapt to technological changes and meet the needs of the dynamic accounting industry.

Barriers to the implementation of antimicrobial stewardship programmes in long-term care facilities: a scoping review.

Long-term care facilities (LTCFs) present specific challenges for the implementation of antimicrobial stewardship (AMS) programmes. A growing body of literature is dedicated to AMS in LTCFs. We aimed to summarize barriers to the implementation of full AMS programmes, i.e. a set of clinical practices, accompanied by recommended change strategies. A scoping review was conducted through Ovid-MEDLINE, CINAHL, Embase and Cochrane Central. Studies addressing barriers to the implementation of full AMS programmes in LTCFs were included. Implementation barriers described in qualitative studies were identified and coded, and main themes were identified using a grounded theory approach. The electronic search revealed 3904 citations overall. Of these, 57 met the inclusion criteria. All selected studies were published after 2012, and the number of references per year progressively increased, reaching a peak in 2020. Thematic analysis of 13 qualitative studies identified three main themes: (A) LTCF organizational culture, comprising (A1) interprofessional tensions, (A2) education provided in silos, (A3) lack of motivation and (A4) resistance to change; (B) resources, comprising (B1) workload and staffing levels, (B2) diagnostics, (B3) information technology resources and (B4) funding; and (C) availability of and access to knowledge and skills, including (C1) surveillance data, (C2) infectious disease/AMS expertise and (C3) data analysis skills. Addressing inappropriate antibiotic prescribing in LTCFs through AMS programmes is an area of growing interest. Hopefully, this review could be helpful for intervention developers and implementers who want to build on the most recent evidence from the literature.

SpatialGE: A user-friendly web application to democratize spatial transcriptomics analysis.

Spatial transcriptomics (ST) is a powerful tool for understanding tissue biology and disease mechanisms. However, its potential is often underutilized due to the advanced data analysis and programming skills required. To address this, we present spatialGE, a web application that simplifies the analysis of ST data. The application spatialGE provides a user-friendly interface that guides users without programming expertise through various analysis pipelines, including quality control, normalization, domain detection, phenotyping, and multiple spatial analyses. It also enables comparative analysis among samples and supports various ST technologies. We demonstrate the utility of spatialGE through its application in studying the tumor microenvironment of melanoma brain metastasis and Merkel cell carcinoma. Our results highlight the ability of spatialGE to identify spatial gene expression patterns and enrichments, providing valuable insights into the tumor microenvironment and its utility in democratizing ST data analysis for the wider scientific community.

Global biomarker trends in triple-negative breast cancer research: a bibliometric analysis

Background: Triple-negative breast cancer (TNBC) is defined as breast cancer that is negative for estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor-2 (HER-2) in cancer tissue. The lack of specific biomarkers makes the diagnosis and prognosis of TNBC challenging. Method: A comprehensive literature review and bibliometric analysis was performed using CiteSpace, VOSviewer and Scimago Graphica. Results: TNBC biomarker research has been growing rapidly in recent years, reflecting the enormous academic interest in TNBC biomarker research. A total of 127 journals published relevant studies and 1749 authors were involved in the field, with developed countries such as the United States, France, and the United Kingdom contributing greatly to the field. Collaborative network analysis found that the research in this field has not yet formed good communication and interaction, and the partnership should be strengthened in the future in order to promote the in-depth development of TNBC biomarker research. Comprehensive analysis of keywords and co-cited literature, etc. found that TNBC biomarker research mainly focuses on immune checkpoint markers, microenvironment-related markers, circulating tumour DNA, metabolic markers, genomics markers and so on. These research hotspots will help to better understand the molecular characteristics and biological processes of TNBC, and provide more accurate biomarkers for its diagnosis, treatment and prognosis. Conclusions: The bibliometric analysis highlighted global trends and key directions in TNBC biomarker research. Future developments in TNBC biomarker research are likely to be in the direction of multi-omics integration, meticulous study of the microenvironment, targeted therapeutic biomarkers, application of liquid biopsy, application of machine learning and artificial intelligence, and individualised therapeutic strategies. Young scholars should learn and collaborate across disciplines, pay attention to new technologies and methods, improve their data analysis skills, and continue to follow up on the latest research trends in order to meet the challenges and opportunities in the field of TNBC biomarkers.

Research Preparedness of Students in A Teacher’s Undergraduate in Guangdong Province, China

In today’s world, where science and technology are becoming increasingly important, it can be said that the main objective of our education system is that students structure the information rather than receive prepared information and are raised as scientific literates. Qualified people who produce, reach and use the information are required for this. Undoubtedly, there are many variables in achieving this objective. The purpose of this study is to determine the evaluation of the students' research preparation level of the students and teachers of students a teacher’s undergraduate in Guangdong province, and use it as a basis for improving scientific research ability. Level evaluation. Specifically, the age, gender, grade, and course/project of the students surveyed, as well as the gender, teaching years, and level of education of the teachers interviewed. Assessment of level in teaching, procedures and processes, data organization and analysis etc. Based on the research results, it is recommended to carry out a series of activities to improve students' scientific research ability. These activities can include strengthening teaching and guidance, improving procedures and processes, providing more data organization and analysis skills training, etc. Through these capacity-building activities, we hope to promote the progress of students in the field of scientific research, improve their research preparation level, and thus better meet future academic and professional challenges.

Self-efficacy of Data Literacy among Primary and Secondary School Teachers in Guangdong Province

The application of educational big data provides new basis for teachers to improve teaching and promote student development. However, there are still many challenges in using data to solve complex educational problems. Teacher data literacy has become the key to transforming educational data into effective teaching strategies. The study sought to gain a better understanding of the current state of primary and secondary school Teachers self-efficacy of data literacy and put forward some suggestions for teacher data literacy training. This study used a quantitative methodology. 813 primary and secondary school teachers from Guangdong Province, China, completed a questionnaire on self-efficacy of data literacy. (1) Primary and secondary school teachers reported significantly high levels of self-efficacy in data literacy (mean=3.624). Among the dimensions, the data awareness and ethics dimension had the highest self-efficacy (mean=3.738) and the data research dimension had a lower self-efficacy (mean=3.358). (2)There were significant differences in the primary and secondary school teachers’ self-efficacy of data literacy with different ages, educational backgrounds, and school locations. Primary and secondary school teachers generally recognized the importance of data literacy training. Older teachers who worked in rural schools and had low levels of education have the lowest level of self-efficacy for data literacy. For primary and secondary school teachers' low level of data analysis skills and weak data transformation strategy ability, teacher data literacy training adopts an embedded teamwork approach, integrating multiple resources to build a data team, integrating big data technology throughout the entire teaching process, and helping teachers to use new data and technologies to understand students' needs in a timely manner, to select teaching methods, and to solve real-world problems. It makes data literacy the foundation of teachers' teaching and promotes the development of all students.

Challenges and Opportunities of Information Technology Management in Big Data Era

This paper comprehensively explores the challenges and opportunities in Information Technology management during the era of big data. It begins by delving into the definition, characteristics, and sources of big data, highlighting its paramount significance for enterprises and organizations. Addressing issues such as data security, privacy protection, processing capacity bottlenecks, and data quality and trustworthiness, effective strategies are proposed. Recommendations include establishing a robust data governance system, leveraging real-time computing, and employing efficient analytical tools, emphasizing reinforced data security measures and enhanced employee training. For tackling data quality and trustworthiness concerns, the paper underscores the importance of establishing a comprehensive data quality management system. Furthermore, a detailed examination of the application of big data in predictive analysis and decision support is provided, along with suggestions to foster a data-driven decision-making culture and enhance employee data analytics skills. In looking ahead, the paper encourages continuous attention to technological innovation, advocating adjustments in IT management strategies to align with the evolving demands of the big data era.

Purchasing Patterns Analysis in E-commerce: A Big Data-driven Approach and Methodological

This research aims to analyze purchasing patterns in e-commerce using a Big Data-based approach and data analysis methods. Leveraging advanced technology and analytical methodology, this research explores consumer behavior, market trends, and factors influencing purchasing decisions in e-commerce. Through collecting transaction data from leading e-commerce platforms and applying rigorous data analysis techniques, this research identifies significant patterns and provides valuable insights for e-commerce companies. This research shows that big data has great potential in understanding consumer behavior and market trends in e-commerce. In contrast, sophisticated data analysis methods are essential in interpreting the large and complex data generated by e-commerce. The findings of this research significantly contribute to the development of the e-commerce industry by helping companies improve their marketing strategies and business decision-making. However, this research also needs help, as it requires data analysis skills and privacy issues. To overcome these challenges, collaboration between researchers, e-commerce companies, and governments is needed to develop the necessary data analysis expertise and ensure that consumer data is managed securely and ethically. Thus, this research provides a more holistic view of consumer behavior and market dynamics in e-commerce, assisting companies and policymakers in addressing challenges and opportunities in an ever-evolving landscape.

Data analytics skills required for accounting industry jobs: analysis and strategies

Purpose of the research. There’s a lack of specific advice / tactics for those interested in switching from public practice to industry. Purpose of the research is to fill the current gap and provide specific tactics for aspiring professionals both in terms of understanding the skills required to make a transition, as well as the ways to develop those skills.Methodology. This study employed a qualitative research approach to explore the data analytics skills required for audit and corporate accounting jobs. The study adopted a case study design to examine the specific data analytics skills required for audit and corporate accounting roles.Originality / value of the research. By combining the researcher's personal experience, industry insights, and academic literature, this study provides valuable insights into the data analytics skills required for audit and corporate accounting roles. The study's findings and recommendations offer practical guidance for auditors transitioning to corporate accounting positions and for corporate accountants seeking career advancement.Findings. This article delved deeply into the data analytics skills required in corporate reporting, but absent in audit due to job differences. The article provides an overview the current software market and provide practical tips on learning and practicing new tools that could (1) provide required skills for a successful industry shift and (2) cementing and upscaling your role in reporting department.

Empowering students through active learning in educational big data analytics

PurposeThis paper explores how Educational Big Data Analytics can enhance student learning. It investigates the role of active learning in improving students’ data analysis skills and critical thinking. By actively engaging students in data analysis assessments, the aim is to equip them with the skills to navigate the data-rich educational landscape.MethodsThe study uses a teaching strategy that combines structured and unstructured data analysis using Python tools and ChatGPT APIs. It presents five assignments, each highlighting data analysis skills and encouraging critical thinking.ResultsThe paper offers insights into how the teaching strategy effectively enhances students’ data analysis and critical thinking skills. It investigates the specific impact of active learning on students’ engagement with educational data. The study reveals that all students can complete a comprehensive project, integrating the skills they have learned in the five assignments related to educational big data while incorporating the educational implications from their respective disciplines.ConclusionThe key lies in instructors being able to design individual assignments that link practical experiences, enabling each teaching session’s effectiveness to accumulate in students’ personal experiences and practical skills, ultimately empowering them with the abilities necessary to work effectively with Educational Big Data Analytics. The findings of this study make a valuable contribution to the ongoing conversation about enhancing the educational experience for students in this data-rich era.

Artificial intelligence development and dissemination impact on the sports industry labor market.

The objective of this study is to explore the impact of artificial intelligence (AI) development on the sports industry labor market, the ways in which AI has influenced the demand for labor, created new job opportunities, and impacted existing job roles. It refers to the inductive approach in the spirit technological determinism theory. It is based on the literature review and written qualitative, semi-structured interviews (N = 14) with sports human resources, management, and technology professionals (purposive sampling). Analysis involved inductive coding and line-by-line analytics of the data. The labor market implications of AI in the sports industry are multifaceted. New job roles are likely to emerge, demanding a blend of AI expertise, data-analysis skills, and sports domain knowledge. Professionals in roles such as sports data analysts and marketing experts may find increasing opportunities. However, certain jobs undergo transformation as AI automates routine tasks. It requires individuals to upskill or transition to roles that require a deeper understanding of AI. This necessitates the creation of responsibilities focused on ethical AI governance and oversight. It is important to research the impact of AI dissemination on the sports industry labor market in a holistic manner because the effects of AI are complex and far-reaching. While there are potential benefits to the implementation of AI, there are also potential risks and challenges that need to be addressed, the implementation of AI in the sports industry could have broader social and ethical implications that need to be considered.

Puzzling Over Patterns

Social scientists in the United States face impacts of legislative attacks on critical thinking in classrooms from K-12 through college. Reduction and removal of content and pedagogy designed to develop and discuss critical thinking present challenges for anthropologists by increasing inequality in access and engagement for learners at all levels. Community engagement and creative problem solving can inform the development of learning opportunities for people who process and approaching complex problems differently. Puzzling, when used in learning processes, can increase inclusivity to facilitate learning data analysis skills with different types of learners. Activities like these allow for involvement in analysis and interpretation of data and add to anthropologists’ toolkits to learn, systematize, explain, and use social science informed knowledge.