Problem-solving Scenarios Research Articles

Exploring medical students’ attitudes on computational thinking in a Saudi university: insights from a factor analysis study

Computational thinking represents an innovative pedagogical paradigm embraced by numerous academic institutions to cultivate the problem-solving acumen of students. Despite its widespread acceptance across diverse disciplines, the integration of computational thinking within medical education remains incomplete. This study seeks to ascertain the attitudes of medical university students in Saudi Arabia regarding computational thinking. Employing an exploratory research design, the investigation encompassed 394 health sciences students, transcending educational backgrounds and gender, with the objective of gaging their attitudes and awareness concerning the value, learning, and perceived difficulty associated with computational thinking within the context of medical curricula. The findings of the study indicate a notably positive disposition among students enrolled in medicine and health informatics programs toward computational thinking, surpassing the attitudes observed in other health disciplines. This discernible preference underscores the potential for integrating computational learning into medical curricula. The results further reveal a pronounced enthusiasm among students for computational thinking, suggesting a genuine interest in leveraging this approach for clinical problem-based learning. Consequently, it can be posited that the incorporation of computational thinking within medical education and clinical problem-solving scenarios warrants active encouragement in forthcoming educational initiatives.

GUI-Driven Real-Time PID Control Tool for Educational Virtual Systems

Abstract: This research presents a pioneering approach in virtual control systems, focusing on developing a highly intuitive Graphical User Interface (GUI) for real-time PID control of LED brightness using Arduino IDE. By embracing a robust pedagogical framework, the study meticulously outlines specific learning objectives that adhere to the SMART criteria, ensuring precise educational outcomes. The key to this research is the tailored design of the GUI, which considers diverse audience needs, prior knowledge, and learning styles. The interfaces are meticulously crafted for optimal user experience, ensuring seamless navigation and engagement. Interactive elements, encompassing simulations, virtual experiments, problem-solving scenarios, and quizzes, foster active participation and hands-on learning. Multimedia elements, such as text, images, videos, animations, and audio, are thoughtfully integrated to cater to varied learning preferences. This paper underscores the critical role of collaborative learning facilitated through discussion forums, chat functionalities, and collaborative virtual environments. The study emphasizes continuous improvement through regular assessments and detailed user feedback analysis. Notably, the research highlights the significant educational impact of the designed GUI. By offering a practical platform where students can dynamically adjust PID parameters and observe immediate effects on LED brightness, the GUI enhances the learning experience in classroom settings. This approach equips students with a tangible understanding of complex PID principles, preparing them for real-world applications. In summary, this research showcases the creation of engaging, practical virtual control system tools, fostering profound and meaningful learning experiences for users within educational contexts. Keywords : control systems, pedagogy, facilitation

Scaffolding Team Minds: Using Metacognitive Training to Boost Social Cognition and Theory of Mind for Effective Collaborative Problem-Solving

Effective teamwork requires both individual domain-specific knowledge and social cognitive skills. In this paper, we discuss a theoretical approach that incorporates metacognitive training to enhance social cognition and theory of mind within teams. By using scaffolding techniques to address cognitive biases, we aim to facilitate efficient collaborative problem-solving. Our goal is to develop individual and team metacognitive awareness in social contexts through various interventions implemented during the preparation, execution, and reflection stages of training. We suggest that metacognitive strategies implemented during team training can enhance individuals’ ability to navigate social interactions and understand others’ perspectives. This approach provides a foundation for researchers interested in studying methods to improve collaboration, for teams seeking to enhance interpersonal understanding, and beneficial for those creating interventions to reduce social cognitive biases and improve theory of mind within collaborative problem-solving scenarios.

Enhancing critical thinking and problem-solving skills in upper elementary students through game-based learning

Introduction. The acquisition of knowledge by students to more actively develop their minds through challenging activities in the form of contextual problem analysis and academically oriented training in thinking skills is still lacking. Solving an inappropriate problem can trigger students' reluctance to try to solve the problems presented because the problem presented will be an early "gateway" as a stimulus that can subsequently stimulate students' thinking, so the skill of the teacher in "packaging" a problem as interesting as possible may be one of the determining factors in the success of the application of the learning model. Study participant and methods. This study included approximately 600 middle school students (grades four through six) in Indonesia, situated in a township with a median family income of IDR72,000,000/year and a median household income of IDR48,000,000/year, where 9.3% lived in poverty. The ethnically diverse composition featured 40.22% Javanese. The chosen school lacked academic tracking in social studies classes for grades 4-6 and had a willing teacher for Game-Based Learning (GBL) interventions. Using a quasi-experimental design, three GBL intervention classes (62 pupils) were randomly selected from five sections taught by the participating teacher, while seven classes (115 students) received conventional instruction. The study aimed to evaluate GBL's impact on social studies education, employing Denah Education Game (DENDA) with specific objectives for territories. The results. The findings indicate that students in the Game-Based Learning (GBL) group had a slightly higher average post-test score (M = 3.66) compared to conventional students (M = 3.60). Similarly, the average score of GBL students on the delayed post-test (M = 2.11) was slightly higher than the score of conventional students (M = 2.00). However, both the post-test (F(1,96) =0.07, p >0.05) and delayed post-test (F(1,91) =0.45, p >0.05) did not show a consistent effect, according to these results. The study indicates that the Game-Based Learning (GBL) intervention successfully enhances students' understanding with slightly higher post-test and delayed post-test scores compared to traditional teaching methods. The findings emphasize the importance of student discourse in game-based scenarios, with higher-level conversations predominantly observed in intra- and inter-group discussions. Despite fluctuations in intellectual activities, student engagement and critical thinking remain high. However, challenges in addressing gender differences and implementing GBL in conventional classroom settings need further research and development focus. Conclusion. The study supports integrating Game-Based Learning (GBL) into conventional classrooms, noting no significant differences from traditional teaching. However, caution is advised due to implementation challenges. Gender differences underscore the need for further exploration of GBL effectiveness across genders and grade levels. Positive impacts on critical thinking are seen through student-centered learning and authentic problem-solving scenarios. GBL aligns with best teaching practices, emphasizing engagement and student-driven learning. While acknowledging limitations, the research calls for ongoing exploration of GBL's potential in fostering critical thinking and aligning it with traditional educational principles for maximum effectiveness in diverse classrooms.

Contexts proposed by teachers in Papua for developing mathematics hots assessment instruments: A phenomenological study

The success of a school centers on teachers' ability to create well-aligned educational tools. The Merdeka Belajar curriculum requires adapting assessments, including Higher-Order Thinking Skills (HOTS) questions for real-world problem-solving scenarios. This study explored contexts proposed by teachers in Papua for developing Mathematics HOTS questions. A phenomenological approach within a qualitative framework was employed involving 24 mathematics teachers from public and private schools in focus group discussions. Participants included twenty teachers from Papua, two from Central Indonesia and two from Western Indonesia. Additionally, five teachers from Papua participated in in-depth interviews. Data was analyzed using Creswell’s model with Atlas.ti software. Teachers developed HOTS assessment instruments based on daily life, scientific and social contexts. However, no cultural contexts were incorporated into these instruments by the interviewed teachers. This study highlights the importance of teacher preparedness in aligning contextual learning with the Merdeka Belajar curriculum and reveals a significant gap in using cultural contexts for HOTS assessments among teachers in Papua. These insights contribute to the discourse on math education in Indonesia advocating for the integration of cultural elements into the freedom to learn initiative.

The Effect of Product Involvement, Perceived Value, and Attitude as Mediation on the Intention to Use “POSPAY” Apps by PT Pos Indonesia (Persero) to Create the Right Marketing Strategy through a Marketing 4.0 Perspectives

Pospay is an app from PT Pos Indonesia (Persero). The research’s background highlights the competitive pressures in the financial services industry and the necessity for transformational companies to innovate through digital offerings such as the Fintech app. The implications of this research complete a new understanding for the marketing department at PT Pos Indonesia on how to increase customer intention to use. This research can provide evaluation materials and references for implementing the right marketing strategy from the perspective of Marketing 4.0, especially to increase intention to use it with variable mediation of consumer attitudes. The results of this research can provide an overview of the fact that perceived value is the most powerful variable that contributes to efforts to increase intention to use the Pospay App. The key research problems are the need to identify the determinants of user intention in adopting FinTech apps, the role of consumer attitude in mediating these determinants, product involvement, and the practical implications for marketing strategy development. The research employs a mixed method with a descriptive approach and uses a type-3 problem-solving scenario. Quantitative data is collected through surveys, and qualitative insights are gathered via interviews or focus group discussions. Structural Equation Modelling (SEM) – Partial Least Square (PLS) with WarpPLS software is used to analyze data testing the hypothesis. The research results are as follows: Product involvement does not have a significant effect on the intention to use but has a significant effect on consumer attitudes; Perceived value has a significant effect on the intention to use and consumer attitudes; Consumer attitude has a significant effect on the intention to use and mediates the influence of perceived value on intention to use but does not moderate the influence of product involvement on intention to use. The research will provide actionable recommendations for PT Pos Indonesia, enabling them to tailor their marketing strategies better through a Marketing 4.0 perspective to meet customer needs and preferences.

Analysis of Students' Critical Thinking Disposition in Science Learning

The study aimed to analyze the specific dispositions that contribute to effective critical thinking among prospective science students. Utilizing a descriptive survey method, the study involved 52 participants from different universities, aiming to gather comprehensive data on their critical thinking dispositions. The research instrument, a structured questionnaire comprising 36 items derived from Ennis's critical thinking indicators, was validated and tested for reliability, ensuring its efficacy in measuring the intended constructs. The findings revealed that the overall critical thinking disposition of the students was predominantly below the critical threshold, with significant variability across different indicators. For instance, indicators such as seeking and offering clear statements and reasons scored relatively high, while others like taking into account the total situation scored lower. This disparity highlights the need for targeted interventions to enhance specific critical thinking dispositions. The study recommends integrating contextual and inquiry-based learning approaches, which have been shown to effectively foster critical thinking by engaging students in real-world problem-solving scenarios. Moreover, incorporating collaborative and experiential learning experiences can further nurture critical thinking skills, promoting deeper understanding and innovation. The research emphasizes the importance of developing specific disposition like open-mindedness to improve the critical thinking capabilities of prospective science teachers, ultimately enhancing their academic performance and preparedness to tackle complex scientific issues.

Exploring the Educational Efficacy and Potential of 24-Hour Hackathon Programming Marathon – HackEmotion

This paper addresses the issue of modern didactics and student motivation for self-learning as well as tackling significant practical challenges. In technical and STEAM education, achieving high levels of motivation is particularly important, as students often become overwhelmed by the vast amount of information and opportunities which lead to diminished interest. At the Institute of Computer Science at the University of Silesia in Katowice, a Hackathon – a 24-hour programming marathon – was organized to enhance student engagement. During this event, students confronted a critical problem in modern societye: emotion recognition. The goal was to develop solutions and help for fostering emotion recognition skills in young people with real-world implementation potential. Additionally, students tested their abilities under time pressure, honed their group work competencies, and faced real-time problem-solving scenarios. This paper presents an evaluation of the event’s impact and analyzes the results of a post-event survey, providing feedback to improve the quality of future Hackathons. The main research questions we posed during the research were: RQ1: At what level of quality was the Hackathon event organized? Whether students were well informed and felt cared for during this event? RQ2: What aspects and properties motivate students most to take part in events organized at the university like Hackathon? RQ3: What competencies, knowledge and skills were developed by participants in the Hackathon? RQ4: Do students consider issues related to recognizing emotions important and the created applications possible to use in practice? In this paper, we answer these questions using statistical analysis as well as simple machine learning models.

Teaching advanced undergraduate classes in a problem-solving context: The Cognitive Sherlock Approach

Engaging students in deep learning, especially in advanced undergraduate courses, can be challenging. Understanding individual concepts and their relations is key, as misunderstanding can hinder the uptake of future ideas. Students’ need to engage is addressed in the proposed Cognitive Sherlock Approach—a teaching method that encourages students to become detectives of their cognitive/thinking processes while solving a problem. This method involves presenting a problem-solving scenario that students revisit with each new concept, employing targeted teaching strategies to sustain engagement and reinforce individual concepts and their links. The approach utilizes various pedagogical strategies, including “Meta-Questions,” structured concept maps, structured group activities, a big-picture overview of the course, and a comprehensive review at the end. The success of this approach is largely dependent on the teacher’s efforts to establish a core course objective within a problem-solving context and to provide students with structured concepts maps to facilitate deeper student learning.

Cross-modal zero-sample diagnosis framework utilizing non-contact sensing data fusion

Gearboxes, fundamental components in the domains of manufacturing, transportation, and aerospace apparatus, are highly susceptible to impairments. The emerging technique of non-contact sensing measurement holds promise as a valuable tool for real-time monitoring and diagnosis of gearboxes, especially in challenging, dynamic environments. However, historical non-contact diagnostic techniques often face difficulties due to load-variation-induced interference, which leads to inconsistent diagnostic results. Moreover, acquiring sufficient non-contact sensing data for specific rare or severe gearbox faults can be exceedingly challenging and, at times, unattainable. This data scarcity limits the application of existing supervised and semi-supervised non-contact diagnostic methods. To address these limitations, this paper develops a novel diagnostic model, called Non-Contact Sensing Data Fusion Driven Cross-Modal Zero-sample Diagnostic Network. Specifically, we first develop a novel central fusion module to facilitate feature-level fusion at both global and local scales utilizing infrared thermal and acoustic data, thereby establishing a rich and comprehensive fault representation. Following that, we construct an end-to-end cross-modal zero-sample diagnostic architecture to mine and fuse complementary fault information. This approach enhances zero-sample diagnostic performance through efficient information utilization and cross-modal feature fusion. Afterward, we adopt a cross-modal self-enhancing fusion strategy during the training phase, which improves the information fusion performance of intra-class features from various modalities. This strategy effectively reduces misclassification risks and augments the robustness of the proposed zero-sample diagnostic network against interference from load variations. Comprehensive experimental results confirm that our proposed NCFZD sets the new state-of-the-art in multiple non-contact, zero-sample diagnostic scenarios, reaching HM scores of 86.06 %, 81.53 %, and 62.56 % respectively. By incorporating the information fusion theory, this model advances gearbox diagnostics in non-contact sensing and contributes to the broader field of information fusion theory by demonstrating its practical application in real-world problem-solving scenarios.

OPPORTUNITIES AND CHALLENGES OF USING ChatGPT IN THE ELT SCENARIO OF UTAS, NIZWA, OMAN

This academic research explores the opportunities and challenges of using Chat Generative Pre-trained Transformer (ChatGPT) in the English Language Teaching (ELT) in a university in Oman. Recent researches have proven that ChatGPT provides various benefits and opportunities in education. Students can gain from different problem-solving scenarios provided by ChatGPT. Moreover, teachers will be freed from heavy marking-load allowing them to spend more time on lesson planning (Hong, 2023). The study aims to find out the possible prospects and challenges of employing ChatGPT in the teaching and learning of English, which naturally influence research and educational policy making as well. The study adopted qualitative methods for data collection and analysis, using literature review and semi-structured interviews. The findings show that the use of ChatGPT in ELT has been much more beneficial and promising, as evidenced by the limited research available. However, there are potential risks associated with over-reliance on ChatGPT and the need for appropriate training and guidance for teachers and students. The study suggests that further research is needed to explore the full potential of ChatGPT in ELT and to address the challenges associated with its.

Mathematical Competence of Practicing Engineers in Engineering Tasks

Due to the complexity of the problems that engineers must solve; they must receive training in real-life problem-solving scenarios. The Engineering Accreditation Council (EAC) and Board of Engineering of Malaysia (BEM) place a significant emphasis on engineering competencies in Program Learning Outcome (PLO), including the ability to apply mathematical knowledge to engineering problems. However, students at universities face challenges in understanding engineering mathematics, as they are not typically taught by specialized instructors. Therefore, a phenomenological approach was utilized in this study to identify the mathematical competencies (MC) among practicing engineers in manufacturing workplaces. Three engineers were selected as potential respondents, but only one participated in the study. Data was collected through intensive interviews conducted in the workplace. The phenomenological reduction technique was employed, utilizing Epoche, Identification of significant statements, Meaning Units, Textural Description of the Experience, Structural Descriptions of the Experience, and Textural-Structural Synthesis phenomenology for data analysis. This method offers a logical, systematic, and coherent design that produces an essential description of the experience. The study's findings indicate that mathematical competencies frequently used by engineers include mathematical thinking, problem-solving skills, and mathematical communication. This study could inform instructors about developing mathematical competencies relevant to real-life problem-solving in engineering activities and academic programs at their institutions.

Nothing New Under the Sun?

This article investigates the potential impact of generative artificial intelligence, specifically OpenAI's GPT, on the field of biblical studies, particularly biblical Hebrew. The study is divided into three main categories: (1) knowledge retrieval or language understanding, (2) generative modeling or creative problem solving, and (3) command interpretation or query parsing. Experiments are conducted using OpenAI's GPT, the ETCBC's BHSA dataset, and Text-Fabric Python libraries. Results demonstrate GPT's limitations and proficiencies in biblical Hebrew and its capacity to employ its proficiencies creatively in problem-solving scenarios involving multifaceted forms of reasoning. The study concludes that understanding the capabilities and potential trajectories of these technologies is vital for biblical Hebrew scholarship, as they already possess the capacity to disrupt established scholarly norms and democratize access to advanced tools.

Fixed-Point Results for Mappings Satisfying Implicit Relation in Orthogonal Fuzzy Metric Spaces

This research paper introduces a comprehensive study on fixed points in orthogonal fuzzy metric spaces. The primary objective is to establish the existence and uniqueness of fixed points for self-mappings satisfying implicit relation criteria in complete orthogonal fuzzy metric spaces. By doing so, our proven results extend and generalise well-known findings in the field of fixed-point theory. To demonstrate the significance of the established results, several related examples are provided, serving to support and validate the theoretical findings in orthogonal fuzzy metric spaces. The implications of these results are discussed, shedding light on their potential applications in various practical scenarios. In addition to theoretical advancements, the paper also demonstrates a practical application of our established results in solving integral equations. This application exemplifies the effectiveness and versatility of the proposed approach in real-world problem-solving scenarios.

Numerical solution and error analysis of the Thomas–Fermi type equations with integral boundary conditions by the modified collocation techniques

This paper introduces modified collocation techniques that utilize Chebyshev and Legendre polynomials for solving Thomas–Fermi type equations with integral-type boundary conditions. Firstly, the problems under consideration have been transformed into corresponding integral equations to avoid singularity at the origin. Then, the modified collocation methods have been applied to achieve practical numerical solutions. The existence of unique solutions for each integral equation is established through corresponding theorems. Notably, proposed techniques do not require approximation of higher derivatives such as x′ and x′′. This aspect not only simplifies the computational process but also enhances the precision of the method by avoiding potential errors associated with derivative approximations. To ensure the reliability of the current method, error analysis is conducted for each approach under general conditions. Furthermore, the effectiveness of the technique is substantiated by including practical examples in the paper. These examples serve as empirical evidence, showcasing the efficiency of proposed approaches in realistic problem-solving scenarios.

Development of a tailored concussion education program for athletes: a pragmatic multimethods design and integrated knowledge translation approach from needs assessment to design

ObjectivesTo understand Canadian university athletic programme concussion management needs, and to describe development and content of a tailored online concussion education tool for Canadian university/college athletes.DesignAn integrated knowledge translation multiphased,...

‘We just had to try it’ - Virtual mentoring experiences of students and their lecturers- Namibia

Abstract Background Mentoring is the backbone of nursing in the classroom and clinical practice. Online learning became the teaching mode of choice during the Covid-19 pandemic. Nurse training institutions were caught off guard with the sudden changes as they were not prepared for the imposed restrictions. Reliance on face-to-face mentoring (FFM) was greatly disrupted because of restrictions on public gatherings and closure of schools. Students needed to continue learning, lectures needed to keep their jobs and nurse training institutions needed to be viable in the midst of the Covid-19 crisis. This study explored virtual mentoring (VM) experiences among third-and-fourth nursing students and their lecturers. Methods An exploratory qualitative design was used. Purposive sampling was used for students and convenient sampling on lecturers. Data collection instrument was designed and pilot tested. Six focus groups from students (n = 46) were conducted. Telephone interviews were conducted with lecturers (n = 18). Data were analysed using NVivo 12. Results Five key themes were identified on both groups; (i) Preparation of adequate teaching content is crucial, (ii) problem-solving scenarios to promote student expertise, (iii) group work and use of social media platforms promote socialisation, (iv) personalized feedback important for psychological support and (v) use of videos during lectures was paramount for nonverbal communication. Institutional support and learning of IT skills to navigate through the Learning Management System were recommended as ways of strengthening VM experiences. Conclusions Although both FFM and VM produced positive mentoring experiences, mentoring activities such as modelling, scaffolding, coaching, articulation, reflection and exploration were not clearly understood as mentoring activities. Future research should explore teaching pedagogies to strengthen VM. Key messages • Innovative techniques for nonverbal communication are important during online learning as they mentor students on communication skills and boost self-esteem. • Knowledge on navigation of the LMS and its various features that support virtual mentoring is paramount both for students and lecturers to meet learning outcomes.

An ensemble knowledge transfer framework for evolutionary multi-task optimization

The cognitive capability of learning from past experiences to resolve relevant tasks at hand is a hallmark of humans. The emerging evolutionary multi-task transfer optimization (EMTO) fashion pursues such intelligent behavior by exploring useful knowledge drawn from solving one task to accelerate the optimization process of other related tasks. However, in practical scenario, knowledge drawn from various task domains may not always benefit the solving process of one another, and source-target domain mismatch is likely to induce notorious negative transfer, which is a critical concern in EMTO. Domain adaption aims to narrow the gap between distinct domains so as to curb negative transfer. Generally, different strategies possess distinct advantages in different situations, no one can dominate others in all cases. Taking this cue, we present a novel bandit-mechanism-based ensemble method to determine the proper domain adaption strategy online in the context of EMTO. Besides, the intensity of cross-task knowledge transfer is adapted according to historical experiences of the population. We carry out extensive experiments to examine the performance of proposed approach, demonstrating its superiority in comparison to state-of-the-art peers in multi-task problem-solving scenario. Our work thus sheds light on a new alternative way for automatic domain adaption for knowledge transfer across problems.

Experimental demonstration of deterministic quantum search for multiple marked states without adjusting the oracle.

Grover's search algorithm is a well-known quantum algorithm that has been extensively studied and improved to increase its success rate and enhance its flexibility. However, most improved search algorithms require an adjustment of the oracle, which may not be feasible in practical problem-solving scenarios. In this work, we report an experimental demonstration of a deterministic quantum search for multiple marked states without adjusting the oracle. A linear optical setup is designed to search for two marked states, one in a 16-state database with an initial equal-superposition state and the other in an 8-state database with different initial nonequal-superposition states. The evolution of the probability of finding each state in the database is also measured and displayed. Our experimental results agree well with the theoretical predictions, thereby proving the feasibility of the search protocol and the implementation scheme. This work is a pioneering experimental demonstration of deterministic quantum search for multiple marked states without adjusting the oracle.

Citation is Inescapable: Enhancing Students’ Referencing Skills with an Online APA Escape Room

Referencing is an important component to upholding academic integrity in university writing, but it can be difficult to teach in a way that really “sticks” for students. Students (and, sometimes, educators) often perceive referencing as boring and tedious because of the seemingly-countless rules involved with each unique style. Even when offered foundational instruction in a referencing style, students often struggle to independently solve citation challenges that require the confidence to apply specific rules and a degree of personal judgment. Looking to enhance students’ proficiency and confidence with referencing, a team of three Learning Strategists co-developed an online escape room to engage students in an active and fun way as they collaborate on problem-solving scenarios for APA Style. In this workshop, participants will learn why and how the escape room was developed, try out an abridged version of the escape room, and discuss how this and other game-based approaches to teaching could be used to facilitate academic integrity learning.