Scientific Problem Solving Research Articles

Implementation of Gauss Elimination Method on Electrical Circuits Using Python

Problem solving in engineering, science and other disciplines often requires complex and in-depth analysis. A problem that requires effort is determining the value of electric current in a circuit. Generally, the determination of the current value in a circuit with the calculation of Kirchoff's theorem. This research presents an alternative approach to determine the value of electric current in a circuit by combining the Gauss Elimination method and Kirchoff's theorem. The determining process support by Python. This method is effective in finding unknown values in a system of linear equations through matrix operations. A deep understanding of currents in electrical circuits is essential in the design, analysis, and maintenance of electrical systems. The application of the Gauss Elimination Method becomes important in determining the value of current in complicated electrical circuits. The Gauss Elimination Method is able to solve electrical circuit problems using matrix principles to achieve accurate and relevant solutions

An Exploration of Spatial Visualization Skills: Investigating Students' Use of 3D Models in Science Problems during Think-Aloud Interviews.

Effective spatial visualization and reasoning skills are often credited for students' success in science and engineering courses. However, students enrolled in these science courses are not always exposed to or trained properly on the best ways to utilize models to aid in their learning. Improving spatial visualization techniques with 3D models, such as molecular and DNA modeling kits, is often suggested to facilitate students' ability to conceptualize compounds in two and three dimensions. Here, we investigate what techniques students use to conceptualize 2D representations of various biomolecules with the use of 3D models by interviewing undergraduate students from various natural science and engineering disciplines in task-based, think-aloud sessions. After scoring and analyzing the participant data we explored some of the techniques used among successful scoring participants, including the use of informal models to transition between 2D and 3D. Additional techniques used by students who were able to successfully conceptualize 3D images included starting with smaller, granular details to inductively make conclusions when thinking between two and three dimensions. We find that (1) students who anchor their thinking in 3D models show a deeper level of understanding in initially solving science problems successfully, and (2) proper 3D model use and spatial visualization techniques may improve students' abilities to accurately visualize 2D and 3D representations of molecules in science courses. Our results demonstrate that implementing spatial visualization training to teach students how to effectively use 3D models may improve students' problem-solving techniques in science curricula.

Integrating Generative AI in Data Science Programming: Group Differences in Hint Requests

Generative AI applications have increasingly gained visibility in recent educational literature. Yet less is known about how access to generative tools, such as ChatGPT, influences help-seeking during complex problem-solving. In this paper, we aim to advance the understanding of learners’ use of a support strategy (hints) when solving data science programming tasks in an online AI-enabled learning environment. The study compared two conditions: students solving problems in DaTu with AI assistance (N=45) and those without AI assistance (N=44). Findings reveal no difference in hint-seeking behavior between the two groups, suggesting that the integration of AI assistance has minimal impact on how individuals seek help. The findings also suggest that the availability of AI assistance does not necessarily reduce learners’ reliance on support strategies (such as hints). The current study advances data science education and research by exploring the influence of AI assistance during complex data science problem-solving. We discuss implications and identify paths for future research.

Multiple Representations in Physics Learning: A Bibliometric Analysis

The application of multiple representation approach in physics learning has been adopted by several researchers, especially to improve the ability and achieve effective learning. The use of multiple representation approach in physics learning over the past few years has provided good results on student learning outcomes, including being able to improve and develop abstract physics concepts, scientific complex skills, metacognition skills, and problem solving. This research is the result of a review based on bibliometric analysis of multiple representations in physics learning. Data was obtained based on Scopus sources from 2013 to 2023, then obtained data as many as 121 articles which then the data was processed using RStudio and VOSViewer. Based on the results of the analysis using Rstudio and VOSViewer, it also displays other information such as year, country, author, institution, journal, co-word analysis, co-occurrence network, and visual density on occurrence. The results of this study provide a framework of the current trends of multiple representations in physics learning both in the present and some indicators that can be used as opportunities for future research.

Improving Students’ Science Problem Solving Ability through the Implementation of Problem Based Learning Models Assisted by Animation Media

The low ability of students to solve science problems is caused by the lack of effectiveness in the use of learning models and media. This study aims to analyze the effect of problem-based learning models assisted by animation media on the ability to solve science problems for grade IV elementary school students. The research method used was an experiment using a posttest-only control design. The samples taken using the simple cluster random sampling technique amounted to 30 students in the experimental group and 30 students in the control group. Data analysis techniques used includes descriptive statistics and inferential statistics by testing hypotheses using t-tests. The results showed that the average score in the experimental group was 82.4, while in the control group was 59.1. The results of the hypothesis test showed that the value of Sig. (2-tailed) was 0.000 < 0.05 or less than (α=0.05), indicating a significant difference in science problem-solving ability between students in the experimental group and the control group. Based on the results of the study, it can be concluded that the problem-based learning model assisted by animation media has a significant influence on the science problem-solving ability of grade IV elementary school students. With the results of this research, it is hoped that teachers can integrate problem-based learning models and animation media in the learning process to improve students' science problem-solving abilities in elementary schools.

Development and Implementation of Visualization of CPU Components using AR

Augmented Reality (AR) technology presents innovative solutions for visualizing complex concepts and systems. This paper investigates the utilization of AR in the visualization of CPU (Central Processing Unit) components, with the objective of augmenting comprehension and learning within computer architecture. By developing an AR application, CPU components are depicted in three dimensions, enabling users to interactively explore and comprehend their functionalities and interconnections. The paper delineates the design and execution of the AR system and discusses its potential advantages for education, training, and technical problem-solving in computer science and engineering. Keywords: Augmented Reality, CPU Components, Visualization, Computer Architecture.

ViralFlow v1.0-a computational workflow for streamlining viral genomic surveillance.

ViralFlow v1.0 is a computational workflow developed for viral genomic surveillance. Several key changes turned ViralFlow into a general-purpose reference-based genome assembler for all viruses with an available reference genome. New virus-agnostic modules were implemented to further study nucleotide and amino acid mutations. ViralFlow v1.0 runs on a broad range of computational infrastructures, from laptop computers to high-performance computing (HPC) environments, and generates standard and well-formatted outputs suited for both public health reporting and scientific problem-solving. ViralFlow v1.0 is available at: https://viralflow.github.io/index-en.html.

Pupils’ School Performance and Their Cognitive Abilities to Solve Problems

The paper describes the results of a study whose main aim was to find the correlation between a pupil’s school grades in Czech language (native), mathematics and physics and pupils' cognitive predispositions to problem solving in science and mathematics diagnosed by the Lawson Classroom Test of Scientific Reasoning and the Culture of Problem Solving test. The total of 180 pupils from the Czech Republic aged 14–15 took part in this study. The results show that pupils with better grades in the monitored subjects achieve better results in both tests. It also turns out that there are generally statistically insignificant differences between the results of pupils assessed by grades 1 or 2, and between the results of pupils assessed by grades 3 or 4. Pupils’ performance in the two tests might help to strengthen the objectivization of grading at school. They might also help to identify the indicators important for the development of problem-solving skills. The research specifically points at the need of developing algebraic thinking, conception of infinity, spatial imagination, geometric imagination in the plane, proportional reasoning and the abilities of the control of variables.

Elementary School Students’ Understanding of “Results” and “Discussion” in a Process of Scientific Problem-Solving: From the Perspective of the Distinction Between Observations and Inferences

Elementary School Students’ Understanding of “Results” and “Discussion” in a Process of Scientific Problem-Solving: From the Perspective of the Distinction Between Observations and Inferences

Analysis of Field Dependent and Field Independent Cognitive Styles in Solving Science Problems in Elementary Schools

This research aims to determine the results of the Science Problem Solving Test, describing students' Field Dependent and Field Independent cognitive styles in solving science problems. The research method used is Mixed Methods, which uses Sequential Explanatory Design. The research results showed that the field-independent and field-dependent students' science problem-solving tests were good. This is proven by using a one-sample t-test with a Sig (2-tailed) result of 0.005. which is smaller than 0.05. The cognitive style of field-dependent students in solving science problems, according to the Polya Stage theory, have difficulty absorbing information, so they do not understand the problem and are unable to explain using their sentences, think globally. The cognitive style of field-independent students in solving science problems is effortless to absorb information so that they can understand the situation thoroughly, analytically, and systematically so that they can present the correct solution steps by determining arithmetic operations that are relevant to the problem.

Exploring the Integration of ChatGPT in Inquiry-based Learning: Teacher Perspectives

ChatGPT, an AI-powered service known for its effective delivery of information and solutions, has the potential to transform education, scientific problem-solving, and student learning. However, to fully harness its advantages, understanding the pedagogical approach needed is essential. This study explores teachers' awareness of ChatGPT and the inquiry-based learning (IBL) 5E model, examines ChatGPT's effective use within IBL, and investigates teachers' perceptions and experiences when integrating ChatGPT into the IBL framework. Employing an exploratory qualitative approach, this research gains insight into teachers' perspectives on ChatGPT's integration into IBL. The study involves two distinct focus groups comprising Junior Secondary School (JSS) and Senior Secondary School (SSS) science teachers in Nigeria. The findings highlight that while some teachers have actively integrated ChatGPT into the IBL 5E model and are already experiencing its benefits, others are at varying stages of awareness and adoption. The interest and curiosity expressed by some teachers suggest a potential for broader adoption as educators become more familiar with ChatGPT's capabilities within the context of IBL. This aligns with the idea that technology integration often involves a phased approach, with early adopters paving the way for broader usage.

Enhancing Scientific Problem-Solving and Learning Achievement of Lower Secondary Students through Active Learning Management

Enhancing Scientific Problem-Solving and Learning Achievement of Lower Secondary Students through Active Learning Management

The Influence of the Talking Stick Cooperative Learning Model in Science Subjects on the Activeness of Elementary School Students

There are several students who, when answering questions, especially in the subject of science given by the teacher, still feel embarrassed and fearful. Moreover, it is not only the fear of answering; some students also lack the willingness to express their opinions. Consequently, the teaching and learning activities predominantly employ lecture methods, which may not always align with the subject matter being taught. The objective of this research is to examine the influence of the cooperative learning model, specifically the Talking Stick, on the science learning activities of fifth-grade students. The research design is experimental with a pre-test and post-test group design. The researcher included the entire population of fifth-grade students, totaling 30 students, comprising 15 male and 15 female students, at SDN 1 Krembung. In this study, the researcher used a saturated sampling technique with a sample size of 30 respondents. Data were collected through questionnaires and analyzed using a one-sample t-test. The results of the one-sample t-test indicated a ρ value of 0.00 for both pre-test and post-test results, signifying ρ < α, with α = 0.05. This indicates a difference in students' activity in solving science problems before and after utilizing the Talking Stick model. Based on the group averages, the pre-test average was 56.8, and the post-test group average was 71. Cooperative learning models are developed to achieve student performance, including academic achievement, tolerance, acceptance of diversity, and the enhancement of social skills. The primary goal of cooperative learning is to maximize student performance to improve academic achievement and understanding, both individually and as a group.

The Effect of STEM Education on the Hypothetical-Creative Reasoning Skills of the Pre-school Pre-service Teachers

The study aims to explore the effect of STEM education on the hypothetical-creative reasoning skills of the pre-school pre-service teachers. The pre-school pre-service teachers were educated with STEM education for 14 weeks within the scope of the study. A mixed-method was employed in the study. The quantitative data were collected with the "Hypothetical-creative Reasoning Skills Inventory” in the study. The hypothetical-creative reasoning Inventory was applied to the pre-school pre-service teachers as a pre-test before the STEM education and a post-test after the STEM education. The qualitative data were obtained with a semi-structured interview form applied to the pre-school pre-service teachers. At the end of the study, it was found that STEM education developed the pre-school pre-service teachers' hypothetical-creative reasoning skills. The qualitative data also supported this result. The pre-school pre-service teachers claimed that they used the steps of determining the situation, collecting necessary data, suggesting solutions, doing research, analysing data, evaluating, that is, scientific problem solving during STEM education.

Empowering Problem-solving in Computer Science: A Need Analysis for a Computational Thinking Mobile Learning Application

The advancement of digital technology has revolutionized education across all levels, giving rise to digital learning as a novel pedagogical environment. Among the subjects at the forefront of this transformation is computer science, introduced in matriculation colleges to supplant traditional information technology courses. However, computer science poses inherent complexity, demanding abstract thinking and diverse problem-solving methodologies. Computational thinking (CT) emerges as a promising approach to address these challenges, recognized as a vital skillset for fostering innovation in digital technology among students. The ubiquity of smartphones and mobile internet facilitates the adoption of mobile learning, offering students the flexibility to access educational content anytime, anywhere. Consequently, this need analysis study aims to assess current teaching practices in computer science and identify the need for mobile learning applications that integrate CT as a problem-solving technique among matriculation college students. Interviews with three computer science lecturers revealed a reliance on conventional pedagogy with limited blended learning approaches through college portals. Notably, specific techniques for imparting programming problem-solving skills were lacking. Nonetheless, it is noteworthy that all instructors recognized the considerable potential of mobile learning applications in effectively engaging students and facilitating the development of problem-solving proficiency.

Thinking What No One Else Has Thought: Investigating the Scientific Creativity of Primary School Students in a Science Class

For the advancement of humanity, scientific creativity is a crucial skill for coming up with innovations, addressing existing issues and interpreting particular scientific phenomena. The present study aimed to determine the scientific creativity level of 23 primary school students. In a single cross-sectional study, a descriptive survey questionnaire modelled on the Scientific Structure Creativity Model (SSCM) incorporated a seven-item scientific creativity test specifically designed to align with the backgrounds of primary school students. The results show that the students have a balance between a low or intermediate scientific creativity level. Of the 23 respondents, 8 have a low scientific creativity level, 8 have an intermediate scientific creativity level and 7 have a high scientific creativity level. The respondents are the most scientifically creative in creative science problem solving. The researchers recommend an intervention such as integrating the arts into the STEM curriculum to help develop students’ scientific creativity.

Review of Collocation Methods and Applications in Solving Science and Engineering Problems

Review of Collocation Methods and Applications in Solving Science and Engineering Problems

The public's overwiev on the introduction of games, play, and gamification in Romanian libraries

Games, play and gamification are essential for all ages because they allow players to develop useful 21st century skills such as digital literacy, critical and scientific thinking, problem solving, comprehension and communication skills, storytelling skills, etc. The new generation of digital natives requires a different approach in learning new things and libraries could take advantage of that by using gamification on learning content. In this way, libraries could become more welcoming spaces, more open to the public and much more interested in what the public wants. To find out what people think about the idea of playing games at the library, the idea of libraries using gamified activities or if the public would like to use gamified apps on the library websites, a questionnaire-based survey was administered on Facebook and WhatsApp between February 2 and February 8, 2024. Analysis of the answers obtained shows that the Romanian public is open to the idea of libraries where reading, communicating, socializing, acquiring knowledge in various fields such as literature, history, geography can be combined in a fun and enjoyable way with play, games and gamification. Respondents would also like to use gamification on library websites such as a book lending app.

Getting back to the real world

Today, STEM and/or STEAM frameworks dominate the discourse around science education and what constitutes a ‘scientific’ literacy. While no one definition prevails in the literature, this literacy is often defined in the context of a current national concerns and focuses largely on Eurocentric (western) models of science and/ or scientific knowledge in terms of concepts, models, theories, or principles. As it currently stands, the term STEM is mostly used when addressing educational policy and curriculum choices in schools, aimed at improving competitiveness in science and technology with implications for workforce and economic development (often with some missing voices from women and Indigenous communities). Without an important socio-cultural critique, education of this kind can maintain and promote hegemonic beliefs and values while ignoring collateral problems relating to scientific or technological development: many of which have been linked to social and environmental injustice. In this paper, I offer three perspectives in an effort to decentre the discourse around the STEM movement. Using the overlapping themes of biocultural diversity, two-eyed seeing and guided inquiry, I offer suggestions on how to reframe science education as an interdisciplinary practice centred on student and community needs. In these ways, science education can ‘get back to the real world’ and promote creative approaches to science literacy, problem solving and cultural inquiry.

Domain-specific knowledge and domain-general abilities in children's science problem-solving.

Problem-solving in early and middle childhood is of high relevance for cognitive developmental research and educational support. Previous research on science problem-solving has focussed on the process and strategies of children handling challenging tasks, but less on providing insights into the cognitive network that enables science problem-solving. In this study, we aimed to investigate whether performance in science problem-solving is mainly determined by domain-specific rule knowledge, by domain-general cognitive abilities or both. In our study, 215 6- to 8-year-old children completed a set of three domain-specific rule knowledge tasks and three corresponding problem-solving tasks that were content-coherent, as well as a vocabulary task, and a reasoning task. Correlational and regression analyses revealed a negligible impact of domain-specific rule knowledge on corresponding problem-solving tasks. In contrast, the associations between problem-solving performance in different domains and the associations between problem-solving performance and domain-general abilities (vocabulary and reasoning) were comparably strong. The findings suggest that science problem-solving in primary school children primarily relies on domain-general cognitive abilities. Implications of these findings are discussed with regard to cognitive theories and early science education.