Problem-solving Approach Research Articles

Redefining computational thinking: A holistic framework and its implications for K-12 education

Abstract In the realm of K-12 Education, the growing significance of Computational Thinking has sparked extensive inquiry into its nature and instructional methodologies. Despite a wealth of literature on the subject, ongoing debates persist regarding its fundamental components. Across global educational landscapes, Computational Thinking is being incorporated into curricula with varying degrees of emphasis, ranging from robotics to computer coding to broader algorithmic problem-solving approaches. This article aims to reassess established definitions of Computational Thinking and propose a nuanced understanding that highlights the necessity and importance of data in contemporary problem-solving contexts. Additionally, we present a comprehensive framework aimed at cultivating Computational Thinking skills in students, encompassing technical competencies alongside cognitive and metacognitive processes. Subsequently, we offer (1) a refined definition emphasizing the importance of data, (2) a comprehensive framework outlining essential components to foster Computational Thinking skills in students, and (3) a discussion of these concepts within the context of K-12 education.

Implementation effectiveness of ‘Problem solving for better health’ training in Lesotho using mixed methods and the reach, effectiveness, adoption, implementation and maintenance (RE-AIM) framework

BackgroundHealthcare resources have been concentrated in urban areas, leaving rural regions vulnerable to poorer health outcomes. The Problem Solving for Better Health (PSBH) program was implemented to enhance healthcare systems in resource-limited regions by training personnel to maximize existing resources in problem-solving. This study evaluated the implementation effectiveness of PSBH-Nursing (PSBHN), a nationally led initiative to train nurses in PSBH in Lesotho.MethodsA mixed-methods study employing a single-group pre-test post-test design was conducted, guided by the RE-AIM theory. Training occurred from November 2021 to June 2022. Nurses completed the Problem-Solving Inventory (PSI) before and 3–6 months after training to measure changes in problem-solving efficacy. Quality scores were assigned to nurses’ planned quality improvement projects; project implementation was assessed 3–6 months after training. In-depth interviews (IDIs) explored changes in knowledge, problem-solving efficacy, and skills. Statistical analyses utilized paired T-tests and logistic regressions using STATA 17; content analysis was conducted on IDIs using NVivo12.ResultsOf 300 nurses, 89 were trained (30%) in the first year. Mainly medium or high-quality scores were achieved for the project designed. However, among 79 participants, only 49.4% reported initiating their projects. Overall problem-solving efficacy improved 3–6 months after training, but the increase was not statistically significant. Nurses reported improved knowledge, confidence and communication skills, enhanced problem-solving approaches, and increased emotional maturity in solving problems. A one-unit increase in project quality score correlated with a 35.0% increase in the odds of project initiation.ConclusionPSBHN demonstrated improved knowledge and minimal improvement in problem-solving efficacy among nurses 3–6 months post-training. However, application of skills gained in implementing their projects was insufficient. Still, PSBHN shows promise in addressing healthcare challenges in resource-limited settings. Some participants were able to start their projects but the inconsistency in follow-through suggests a need for more research into the factors that can improve completion of implementation for better health outcomes.

Design thinking in action: a quantitative study of design thinking practices in innovation projects

PurposeDesign thinking is widely recognized as an effective problem-solving approach in the professional and academic world, albeit with varying interpretations. It has been studied in multiple forms – as a tool, a practice, a skill and a mindset – leading to ongoing debates about its fundamental nature. This study aims to explore the use of design thinking in practice and determine how its application varies depending on the characteristics of the innovation projects, namely, the types of goals pursued and the level of uncertainty involved.Design/methodology/approachUsing a survey methodology and a knowledge-intensive empirical setting, this study analyzes a data set of 221 innovation consulting projects based on design thinking conducted by European consulting firms and design agencies.FindingsBy analyzing the survey data, the authors identify six distinct sets of design thinking practices: discovering user needs, understanding the problem addressed, challenging existing assumptions, navigating the problem-solution pair, ideating through visualizations and learning through prototypes. The authors also identify configurations of these design thinking practices that are used to address different innovation project goals and levels of uncertainty.Practical implicationsThe study draws attention to the need for design thinking practitioners to be aware of how different innovation project goals and levels of uncertainty can be pursued/addressed through the use of alternative configurations of design thinking practices.Originality/valueTo the best of the authors knowledge, this study is one of the first large-scale quantitative analyses of the nature of design thinking in action, providing a solid foundation for future research on design thinking.

Use of design thinking to develop a benchmarking tool to assess documentation procedures in a hospital pharmacy aseptic compounding unit: a case study

ObjectivesThis paper combines the concepts of design thinking and benchmarking in an aseptic manufacturing context. Design thinking is a problem-solving approach that aims to understand user needs, generate ideas, prototypes...

Analysis of Tourism Area Development in Bukit Lawang, North Sumatra

This study aims to analyze the development of the Bukit Lawang tourism area. The research employs descriptive and qualitative data analysis, focusing on a problem-solving approach that is based on descriptions rather than numerical data. The purpose of using a qualitative research method is to facilitate a better understanding of information from the sources used as data, providing an effective comprehension of the ecotourism development strategy being studied. The qualitative analysis involves data collection through interviews, observations, documentation, and other methods. The research findings indicate that income from the development of the Bukit Lawang tourism sector has not significantly impacted the local revenue (PAD) of Langkat Regency as a whole. This is because Bukit Lawang tourism has not been fully implemented and managed effectively by the government. Tourism and conservation activities in Bukit Lawang have yet to be supported by proper tourism area planning, which is essential for sustainable tourism. The land division by the government is currently limited to conservation areas, plantations, and community-owned lands. Sustainable tourism land use planning would make Bukit Lawang a more responsive area. Achieving a sustainable tourism area in Bukit Lawang requires the involvement of both the government and local communities.

Design of the Mathsolve Learning Media with a Problem-Solving Approach by Schoenfeld on Sequences and Series Material

Design of the Mathsolve Learning Media with a Problem-Solving Approach by Schoenfeld on Sequences and Series Material

A prelude to revisionism? The stalemated peace model and the emergence of multipolarity in international order

ABSTRACT Stalemated peace processes are indicative of serious problems for international order, relating to its legitimacy and viability. They may indicate potential opportunities or herald revisionist moments. Yet, the dominant research methodologies, conceptual, and practical doctrines of the post-Cold War order, related to peacemaking, have indicated a convergence around limited goals for peacemaking, peace missions, international mediation, and conflict resolution. At best, this has led to negative forms of peace, stalemates, or a victor's peace in many conflict-affected states and regions. Such problem-solving approaches, which operate within the often contradictory frameworks of the liberal international order, Realism, multipolarity, and geopolitical pragmatism, have led to unintended consequences because of such parsimony. This article examines the post-Cold War consequences of these developments in peacemaking and related UN and other peace approaches in practice and in theory. It focuses on the emergence of the concept of “stalemated peace”.

Empowering Society through Assistive Technologies: The Role of Universities in Development and Implementation

This research article explores the significant role of universities in the development and implementation of assistive technologies that empower marginalized populations, particularly the visually impaired. With an emphasis on integrating computer science, engineering, and information technology disciplines, the study highlights the necessity for educational institutions to address societal challenges through innovative technological solutions. The paper discusses essential capabilities for assistive technologies, including advanced reading systems, writing aids, and navigation tools that enhance independence and accessibility for visually challenged individuals. Furthermore, it proposes a collaborative framework that allows students to engage with real-world problems while working alongside industry mentors, fostering a practical problem-solving approach that makes academic projects more relevant and impactful. By leveraging the vast resources available within educational institutions and establishing platforms for mentorship and collaboration, universities can significantly contribute to the advancement of assistive technologies, ultimately promoting inclusivity and equity in society. The article concludes by emphasizing the need for ongoing investment in research and development in this area, thereby ensuring that assistive technologies meet the evolving needs of diverse populations.

Critical Thought Pattern Differences and Problem-Solving Approaches in Communication between People from the US and Japan

Effective communication between individuals from the United States and Japan can be particularly challenging due to the profound cultural differences that influence their critical thought patterns and problem-solving approaches. These differences manifest in various ways, including contrasting perspectives on individualism versus collectivism, egalitarianism versus hierarchy, directness versus indirectness, and linear versus holistic thinking styles. In interactions between Americans and Japanese, these cultural disparities can lead to misunderstandings, misinterpretations, and communication barriers. To address these challenges, it is crucial to develop an understanding of the underlying cultural factors that shape communication styles in both cultures. This article delves into these cultural differences, highlighting how they impact formal and informal communication settings. Furthermore, we discuss practical strategies and techniques that can be employed to bridge these gaps, facilitate better understanding, and enhance the effectiveness of cross-cultural communication between individuals from the United States and Japan. By recognizing and addressing these cultural nuances, we can foster more harmonious and productive interactions across these two distinct cultural contexts.

Visualizing Engineering: A Practitioner’s Perspective on Engineering Education

Visualizations are integral to the fields of science and engineering, serving as essential tools for both education and professional practice. They encompass a diverse range of modalities, from illustrations to simulations, and play vital roles in facilitating conceptual understanding, scientific discovery, and communication. In engineering education, visual representations are fundamental to problem-solving approaches, requiring learners to navigate complex information through graphical, conceptual, and mathematical components. This paper delves into the role of visualizations as didactic external representations – emphasizing the importance of design choices informed by both empirical evidence and craft-based knowledge. We discuss the gap between visualization research and practice, and showcase visualization stimuli across various scientific subject matter, exemplifying the diverse applications and pedagogical potential of visualizations for engineering education. We also outline key research challenges and opportunities, advocating for partnership between visualization practitioners, researchers and educators to address these challenges.

Location-inventory-pricing model in closed-loop supply chain network under the robust-fuzzy optimisation method

ABSTRACT This paper discusses the modelling and solution of a location-inventory-pricing problem in a closed-loop supply chain network to maximise profit. The Robust-Fuzzy Optimization (RFP) method has been used to control the uncertainty parameters. With the increase in the uncertainty rate, the value of the optimal price and the value of the optimal target values increase. Due to the inefficiencies identified in methods and their variants presented in similar research, Whale Optimization Algorithm (WOA) and League Championship Algorithm (LCA) have been used to improve the current approach and present higher efficiency in problem-solving. Also, the examination of the results shows that the time to solve the problem with meta-heuristic algorithms is much shorter compared to the exact method, and with the increase of the problem size, the solution time increases exponentially. Therefore, by numerical comparison, it can be concluded that WOA resulted in a higher profit than the LCA in an acceptable time.

Harvest planning for efficient and integrated food supply chains: a combined project-operations management approach

ABSTRACT This paper presents a harvest planning model designed for small agricultural producers to enhance strategic decision-making, ultimately improving profitability and sustainability. The proposed methodology combines an interactive problem-solving approach with systems thinking, integrating both qualitative and quantitative analyses. Three scenarios are used to validate the model, adjusting for supply chain costs, demand, and product prices. The results demonstrate the model’s adaptability to increased costs and scalability with heightened demand. Specifically, the model identifies a plan that significantly increases profitability for agricultural producers. The integrated methodology, along with the consideration of the main goals and needs of the stakeholders, provides a comprehensive vision of the situation faced by small producers. This approach allows them to strategically address challenges related to profitability and the marketing of their products, highlighting its transformative potential for enhancing the profitability and sustainability of small producers.

A Transformation of the Way of Thinking: Key Principles in Programming Education Inspired by Pascal

The work of Niklaus Wirth, designer of the Pascal programming language, has led to the introduction of programming in schools in many countries often leading to a transformation in the way of thinking. In this article, we provide a retrospective analysis of the Lithuanian experience driven by Pascal and discuss the main ideas about teaching programming originating from this experience. We conducted a qualitative study by means of interviews with experts involved in the development of programming education during its early phases to examine their memories and perspectives. Programming education in Lithuania started with the Pascal-inspired Young Programmers’ School by Correspondence, founded in 1981, which had a great influence on the Lithuanian programming elite. For this purpose, a compiler for a subset of Pascal was developed for students taking their first steps towards programming, or more precisely, algorithmic thinking. Many innovations were developed and brought into practice. The ones that have proved their worth and have not lost their relevance are the subject of this article. These include assessing program text readability, cultivating programming style, program reading tasks, creative thinking tasks, problem-solving approaches, detailed compiler error messages, automatic error fixing, and compiler advice to novice programmers. While some concepts became obsolete with technological advancements, others remain relevant, directly or as inspiration for new ideas, forming the basis of this study.

A professional development programme based on biomimicry to improve stem project creativity of science student teachers

In Thailand, science, technology, engineering and mathematics (STEM) education is being promoted to support science student teachers by conducting projects to extend their learning skills and to turn them into innovators. This study aimed to develop a professional development programme (PDP) based on biomimicry to improve STEM project creation for science student teachers and to evaluate the implementation result of this programme. The 60-hour programme, designed for 29 science student teachers from a teacher training institute in southern Thailand, was collaboratively developed to align with stakeholders’ needs. It comprised four main lessons incorporating biomimicry principles and an eight-step problem-solving approach. The design process included stakeholder input, expert validation, and iterative improvement. The PDP integrated a coaching approach to facilitate problem synthesis and enhance learning outcomes. It underwent multiple stages of design, drafting, and expert validation before finalization. The programme’s effectiveness was evaluated through the creativity of resulting STEM projects using class observations, a creativity evaluation form, and interviews. Data analysis employed content analysis and interpretatiove methods. The implementation resulted in six innovative biomimicry-inspired STEM projects, demonstrating the programme's success in fostering creativity and innovation among future educators. This study contributes to the advancement of STEM education in Thailand by providing a structured approach to developing science student teachers' project creation skills.

Challenges in Malaysian Design Industry

The Malaysian design industry follows a market-need-driven approach, where marketing-oriented managers guide designers to address anticipated high-demand markets. However, challenges persist in understanding designers' problem-solving approaches due to implicit practices. This research emphasizes the hindrance caused by insufficient communication and collaboration among managers, designers, and researchers, impeding a comprehensive grasp of innovation processes in the manufacturing sector. The paper advocates a pragmatic examination of designers' experiences, highlighting sensemaking, speculative imagination, and improvisation as crucial design activities. Results show Malaysian industrial designers face consistent challenges with management, impacting the development process. The study contributes to formulating a practical solution for fostering creativity among managers, designers, and stakeholders in the design industry.

AI-Powered Gesture-Controlled Interactive System for Real-Time Mathematical Problem Solving and Visualization

In this paper, we are working on an AI based gesture-controlled system which responses to the hand motion of user and solves computer generated mathematical problems without any need of mouse, keyboard or even getting off from their sit. Dubbed MathVision, the system uses contemporary machine learning techniques like OpenCV for detecting gestures and Google Gemini LLM technology for interpreting math equations—atop a relatively straightforward interface. A webcam or other camera captures hand movements on gestural drawings equations that are then converted into a usable format which can be interactively scrolled, deleted and confirmed by making specific gestures with the hands. A trained model to detect finger gestures when writing math expressions, with custom mathematical layers. MathVision serves as an educational software product, providing educational interactivity to a general process of problem-solving where students receive problems and can either solve mathematical exercises by hand or type their solutions. The purpose of this technology is to combine classical problem-solving approaches with the power new computational tools, so that math could be more interactive and effortless. MathVision converts visual manipulations into instant mathematical answers, and offers an interactive way to understand difficult math’s topics in a highly interactive manner. Combining gesture recognition with AI-based problem solving would change the future of our education; revolutionizing instruction and transmission of mathematical concepts across all levels.

Bridging Boundaries to Acquire Research and Professional Skills: Reflecting on the Impact and Experiences of Technology-Enabled Collaborative Cross-Institutional and Transnational Social Work Placement Projects

Worldwide, social work educators’ teaching and learning practices are founded on social justice principles and recognised for their evidence-based, interpersonal, cross-cultural, and problem-solving approaches. Placements are integral to social work education preparing students for practice. Learning experienced on such placements, particularly those involving research, can assist students to develop a broad understanding of diversity, inequality, and anti-oppressive practice in local, national, or international contexts. Technology-enhanced, online research opportunities have revolutionised research placements. This article offers a reflective dialogue on the insights gained from two transnational, technology-enhanced social work research-based placements. The first example reviews three student-led, rural-focused inquiries completed in Australia and Ireland; the second pertains to students physically situated in Ireland and who engaged in collaborative online projects while completing their USA-based social work placements online. The authors reflect on the experiences and the skills the students developed and how the application of technology helped meet an increasing need for environmentally sustainable practices in teaching, learning, and research on placement. Publicly available student reflections on significant knowledge and practice benefits gained from their transnational experiences are considered. The study highlights how reflective practice assisted in the enactment of research in online contexts.

Enhancing supply chain resilience through artificial intelligence: Analyzing problem-solving approaches in logistics management

In an increasingly complex and unpredictable global economy, supply chain resilience has emerged as a critical priority for organizations striving to adapt to disruptions and maintain operational continuity. Artificial intelligence (AI) has proven to be a transformative force in addressing the challenges of logistics and supply chain management, offering innovative solutions for forecasting, decision-making, and operational efficiency. This research explores how AI-driven approaches can solve specific supply chain challenges, including demand variability, disruption management, inventory optimization, transportation inefficiencies, and supplier relationship management. The review proposes a comprehensive analysis of AI technologies such as predictive analytics, real-time monitoring systems, optimization algorithms, and autonomous systems, highlighting their contributions to enhancing supply chain resilience. By leveraging AI, organizations can improve their ability to predict disruptions, optimize resource allocation, and respond dynamically to real-time challenges. The research incorporates case studies and real-world applications to illustrate successful implementations of AI in logistics, as well as lessons learned from failed attempts. Additionally, the review examines the benefits of integrating AI into supply chain operations, such as improved risk management, enhanced decision-making, and increased adaptability to uncertainties. However, it also addresses the challenges of AI adoption, including high implementation costs, data privacy concerns, and organizational resistance to change. By presenting actionable insights and recommendations, this research aims to provide a roadmap for organizations seeking to harness AI to strengthen their supply chain resilience. The findings underscore the transformative potential of AI technologies in fostering robust, adaptive, and efficient supply chain systems capable of withstanding future uncertainties and disruptions. Keywords: Supply Chain, Artificial Intelligence, Logistics Management, Review.

Impacts of different gamified problem-solving integration approaches on elementary math: an engagement and metacognitive knowledge perspective

This mixed-method study investigated the effects of two distinct gamified problem-solving integration approaches on student engagement and metacognitive knowledge in elementary mathematics contexts. Data collected from 59 elementary students revealed varied impacts across three types of engagement (behavioral, affective, cognitive) and metacognitive knowledge dimensions (self, task, strategy). Interviews with teachers and students provided insights into these outcomes, highlighting how specific game mechanics influenced different types of engagement and metacognitive knowledge under the two approaches. The findings offer practical implications for future gamification integration in elementary mathematics, including considerations for the selection and timing of game mechanics to optimize learning outcomes.

Breast cancer identification using machine learning and hyperparameter optimization

Breast cancer identification can be analyzed through genomic analysis using gene expression data, one type of which is mRNA. This involves analyzing gene expression patterns of breast tissue samples to distinguish breast cancer from healthy tissue or to differentiate subtypes of different breast cancers. This research developed the right computational model for breast cancer classification using machine learning and hyperparameter optimization algorithms. The primary objective of this research is to utilize various machine learning algorithms to classify breast cancer based on gene expression and enhance the models developed in previous studies. This paper provides an extensive literature review of prior breast cancer classification research and offers new theoretical perspectives. This research used a problem-solving approach with conventional machine learning techniques, most notably the decision tree. It also evaluates other machine learning algorithms for comparison, including k-nearest neighbor, naïve bayes, random forest, extra tree classifier, and support vector machine. The evaluation process used classification reports that provide insight into the precision, recall, F1-score, and accuracy of each machine learning model. The evaluation results show that the performance of the decision tree algorithm model is superior and impressive, achieving 99.73% accuracy and a score of 1 for precision, recall, and F1-score.