Problem Solving In Chemistry Research Articles

CACTUS: Chemistry Agent Connecting Tool Usage to Science.

Large language models (LLMs) have shown remarkable potential in various domains but often lack the ability to access and reason over domain-specific knowledge and tools. In this article, we introduce Chemistry Agent Connecting Tool-Usage to Science (CACTUS), an LLM-based agent that integrates existing cheminformatics tools to enable accurate and advanced reasoning and problem-solving in chemistry and molecular discovery. We evaluate the performance of CACTUS using a diverse set of open-source LLMs, including Gemma-7b, Falcon-7b, MPT-7b, Llama3-8b, and Mistral-7b, on a benchmark of thousands of chemistry questions. Our results demonstrate that CACTUS significantly outperforms baseline LLMs, with the Gemma-7b, Mistral-7b, and Llama3-8b models achieving the highest accuracy regardless of the prompting strategy used. Moreover, we explore the impact of domain-specific prompting and hardware configurations on model performance, highlighting the importance of prompt engineering and the potential for deploying smaller models on consumer-grade hardware without a significant loss in accuracy. By combining the cognitive capabilities of open-source LLMs with widely used domain-specific tools provided by RDKit, CACTUS can assist researchers in tasks such as molecular property prediction, similarity searching, and drug-likeness assessment.

An effective multistep fourteenth-order phase-fitting approach to solving chemistry problems

An effective multistep fourteenth-order phase-fitting approach to solving chemistry problems

Implementation and Evaluation of a Team-Based Electrochemistry Module in a Large Undergraduate Class

Introductory chemistry courses at the undergraduate level offer students a foundation in chemistry principles and an opportunity to develop problem-solving skills. These principles and skill sets are widely applicable across disciplines, and thus first year chemistry courses are a gateway for many programs in science, technology, engineering, and mathematics (STEM). While first-year chemistry courses are essential for STEM students, the resulting large-enrolment classes in universities can lead to challenges in implementing active learning and in helping students to reach the course learning outcomes. The evolving field of Chemistry Education Research (CER) offers data and insight for improving teaching and learning strategies at the undergraduate level. We propose and evaluate an electrochemistry team-based problem-solving module as an active learning component of a large, first-year, blended chemistry course. In this paper, we explore the process for developing the module and evaluate this learning approach through focus groups, a large class survey, and student experience interviews. Through a preliminary case study approach, our findings suggest the interactive module is useful for enhancing conceptual understanding and problem-solving in chemistry, and improving academic confidence in electrochemistry learning outcomes. Moreover, students valued their engagement with the team-based problem-solving modules as an opportunity to build community, learn collaboratively, and successfully approach relevant problems.

Assessing the Role of Mobile Applications in Improving Stoichiometry Understanding among Matriculation College Students: An Investigation

Mobile learning is anticipated to enrich learning experiences, enabling students to access educational content regardless of time or place. In light of the widespread use of smartphones for daily activities and ubiquitous mobile access to the internet, the mobile learning approach becomes feasible. The digital era has initiated significant transformations across various facets of contemporary life, with education being no exception. However, a persistent challenge lies in identifying suitable digital learning platforms and tools to effectively engage students in learning at their own pace, particularly in disciplines such as chemistry at Matriculation College. Chemistry, being a highly complex subject, demands abstract thinking and diverse problem-solving approaches. Computational Thinking (CT) emerges as a potential problem-solving technique in 21st-century learning that is applicable in teaching and learning chemistry. These skills are considered essential for enhancing the digital technology innovation capacity and should be nurtured among students. Therefore, the purpose of this study is to assess the current teaching and learning methods in chemistry and determine the necessity for a mobile learning application that introduces CT as a problem-solving technique among matriculation college students studying chemistry. Findings reveal that lecturers mainly use conventional teaching methods, incorporating blended learning through platforms such as YouTube for video lectures and the distribution of notes through messaging apps like WhatsApp and Telegram platforms. Notably, there is no standardized technique employed by lecturers in teaching chemistry problem-solving. However, all of them acknowledge the potential of mobile learning applications that integrate CT to effectively engage students in developing problem-solving skills, particularly in the context of solving stoichiometric problems.

Development of problem-solving skills supported by metacognitive scaffolding: insights from students’ written work

Despite problem solving being a core skill in chemistry, students often struggle to solve chemistry problems. This difficulty may arise from students trying to solve problems through memorising algorithms. Goldilocks Help serves as a problem-solving scaffold that supports students through structured problem solving and its elements, such as planning and evaluation. In this study, we investigated how first-year chemistry students solved problems, when taught with Goldilocks Help, and whether their problem-solving success and approaches changed over the course of one semester. The data comprised of student written problem-solving work, and was analysed using frequency analysis and grouped based on the problem-solving success and the extent of the demonstrated problem-solving elements. Throughout the course of semester, students exhibited increasingly consistent demonstration of structured problem solving. Nonetheless, they encountered difficulties in fully demonstrating such aspects of problem solving as understanding and evaluating concepts, which demand critical thinking and a firm grasp of chemistry principles. Overall, the study indicated progress in successful and structured problem solving, with a growing proportion of students demonstrating an exploratory approach as time progressed. These findings imply the need for incorporation of metacognitive problem-solving scaffolding, exposure to expert solutions, reflective assignments, and rubric-based feedback into wide teaching practice. Further research is required to extend the exploration of the effectiveness of metacognitive scaffolding, in particular via think-aloud interviews, which should help identify productive and unproductive uses of the problem-solving elements.

Use of PhET Simulations as A Virtual Laboratory to Improve Students' Problem Solving Skills

In the Radiochemistry course so far there have been no experimental activities because there are no laboratory facilities. However, with the use of technology, students can now easily access a wealth of educational resources online. This research aims to determine the effect of using the PhET Simulations as a virtual laboratory on students' problem solving skills. This research used mixed methods that combines quantitative and qualitative research. A quasi-experiment was carried out using a one group pretest-posttest design then continued with in-depth interviews. The instruments used in this research consisted of written tests to collect data on problem solving skills, questionnaires to collect student response, and interview guides to collect data on the problem solving process. Data in the form of problem solving skills were analyzed statistically using the SPSS 22.0 program while data obtained through questionnaires and interviews were analyzed descriptively. The results of the hypothesis test using Wilcoxon signed rank test show a significant value of 0.001, which means that PhET simulations as a virtual laboratory improve students’ problem solving skills. Students are divided into high-medium-low groups based on problem solving ability and the majority of students are in the medium-ability group. Students responded positively to PhET Simulations as a virtual laboratory. In addition, interview transcripts provide an overview of how students think when solving chemistry problems.

Generic Science Skills Profile of High School Students in Working on Chemistry Questions Based on Gender

The exploration of generic science skills in solving chemistry problems can be influenced by various factors, one of which is gender bias in the learning process. This research aims to measure students' generic skills in solving chemistry problems based on gender. This study is quantitative descriptive research with a pre-experimental method using a One-Shot Case Study design. The sample consists of 20 eleventh-grade students, with 10 male students and 10 female students, selected based on gender and the taught material. Data collection techniques include measurement techniques, observation techniques, and interview techniques. The data analysis technique used is quantitative descriptive analysis. The results of the research show difference in the scores of generic science skills between female and male students. Female students have higher scores in direct observation indicators (80 vs. 79) and logical inference (83 vs. 79). However, there is no significant difference in the cause-and-effect law indicator (74 vs. 74). Meanwhile, male students have a slight advantage in the abstraction indicator (67 vs. 66) and concept building (76 vs. 74). Of the five indicators examined in the form of tests, the abstraction indicator obtains the lowest score, while the highest score is in the logical inference indicator. From these results, there is no significant difference in the generic science skills of male and female students.

Artificial Intelligence Generative Tools and Conceptual Knowledge in Problem Solving in Chemistry

In recent years, artificial intelligence (AI) has emerged as a valuable resource for teaching and learning, and it has also shown promise as a tool to help solve problems. A tool that has gained attention in education is ChatGPT, which supports teaching and learning through AI. This research investigates the difficulties faced by ChatGPT in comprehending and responding to chemistry problems pertaining to the topic of Introduction to Material Science. By employing the theoretical framework proposed by Holme et al., encompassing categories such as transfer, depth, predict/explain, problem solving, and translate, we evaluate ChatGPT’s conceptual understanding difficulties. We presented ChatGPT with a set of thirty chemistry problems within the Introduction to Material Science domain and tasked it with generating solutions. Our findings indicated that ChatGPT encountered significant conceptual knowledge difficulties across various categories, with a notable emphasis on representations and depth, where difficulties in representations hindered effective knowledge transfer.

Fibonacci wavelets operational matrix approach for solving chemistry problems

The key idea and contribution of this study are to present the innovative functional matrix approach for solving the two chemical, mathematical problems such as the absorption of CO2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$C{O}_{2}$$\\end{document} into phenyl glycidyl ether (PGE) and the chemical kinetic problem. These chemical problems are characterized as a system of nonlinear ODEs with initial and boundary conditions. Numerical outcomes are obtained to establish the simplicity and efficacy of the developed scheme. Graphs and tables show how consistently and effectively the developed strategy works. Results obtained show that the newly adopted technique is more precise and effective than other methods such as Adam–Bashforth–Moultan method (ABM), Runge–Kutta method (RK4), Adomian Decomposition method (ADM), and residual method (RM). Mathematical software called Mathematica 11.3 has been used to perform all calculations. Theorems explain the convergence of this approach.

University Students’ Common Mistakes During Algorithmic Problem Solving in General Chemistry

Algorithmic problem solving is accepted as the process of application of knowledge to novel situation and is an integral part of most science courses. It is known that students are not very successful in solving chemistry problems. In this study, the students’ mistakes and difficulties while solving general chemistry problems were investigated. The study sample consists of 80 students who were enrolled in a chemistry course taught at the first year of university. To collect data a test consists of four problems was developed and implemented to 80 university chemistry students. The results of the study show that many of the students; had lack of prior knowledge, had lack of knowledge of mathematical procedures and these affected correct solutions of the problem, did not use the necessary units with appropriate exchanges, had difficulties to connect the topic with the problem and had not gained studying habits, as necessary. Keywords: General chemistry, Problem solving, Students’ difficulties DOI: 10.7176/DCS/13-1-05 Publication date: January 31 st 2023

Assessment of chemistry knowledge in large language models that generate code.

In this work, we investigate the question: do code-generating large language models know chemistry? Our results indicate, mostly yes. To evaluate this, we introduce an expandable framework for evaluating chemistry knowledge in these models, through prompting models to solve chemistry problems posed as coding tasks. To do so, we produce a benchmark set of problems, and evaluate these models based on correctness of code by automated testing and evaluation by experts. We find that recent LLMs are able to write correct code across a variety of topics in chemistry and their accuracy can be increased by 30 percentage points via prompt engineering strategies, like putting copyright notices at the top of files. Our dataset and evaluation tools are open source which can be contributed to or built upon by future researchers, and will serve as a community resource for evaluating the performance of new models as they emerge. We also describe some good practices for employing LLMs in chemistry. The general success of these models demonstrates that their impact on chemistry teaching and research is poised to be enormous.

Analysis of Chemistry Problem-Solving Ability in Symbolic Level for Senior High School Students

Analysis of Chemistry Problem-Solving Ability in Symbolic Level for Senior High School Students. Objective: The study aims to analyze the ability to solve symbolic level of chemistry problems on buffer solution. Methods: This research used descriptive qualitative method. Population in this study was used as research sample, i.e sixty students from XI MIPA. Data collection was carried out using a three-tier multiple choice diagnostic test and a student response questionnaire. Findings: The results showed that the ability to solve symbolic level chemistry problems on buffer solution was still low, with an average percentage of understanding the concept was 9.77%, misconceptions was 57.75%, and not understanding the concept was 32.48%. Students’ responses to the use of three-tier multiple-choice questions were positive, with a percentage of 74.30%; students gave good responses to the three-tier test, so this test is categorized as good to identify the level of student understanding in solving symbolic level chemistry problems on buffer solution. Concusion: The research findings confirmed that the diagnostic three-tier test is a good diagnostic test to analysis chemistry problem-solving skills. Keywords: chemistry problem solving ability, symbolic level, three-tier diagnostic test. Abstrak: Analisis Kemampuan Penyelesaian Masalah Kimia dalam Level Simbolik bagi Siswa SMA. Tujuan: Penelitian ini bertujuan untuk menganalisis kemampuan menyelesaikan soal kimia tingkat simbolik pada materi larutan penyangga. Metode: Penelitian ini menggunakan metode kualitatif deskriptif. Seluruh populasi dalam penelitian ini dijadikan sampel yaitu seluruh siswa kelas XI MIPA yang berjumlah 60 siswa. Pengumpulan data dilakukan dengan menggunakan tes diagnostik Three Tier Multiple Choice dan angket respon siswa. Hasil: Hasil penelitian menunjukkan bahwa kemampuan menyelesaikan soal kimia tingkat simbolik pada materi larutan penyangga masih rendah, dengan persentase rata-rata paham konsep 9,77%, miskonsepsi 57,75%, dan tidak paham konsep 32,48%. Respon siswa terhadap penggunaan soal three-tier multiple choice adalah positif dengan persentase 74,30%; siswa memberikan respon yang baik pada tes three-tier, sehingga bentuk tes ini dikategorikan baik untuk mengidentifikasi tingkat pemahaman siswa dalam menyelesaikan soal kimia level simbolik pada materi larutan penyangga. Kesimpulan: Temuan penelitian mengkonfirmasi bahwa tes diagnostik three-tier yang dikembangkan merupakan salah satu bentuk tes yang baik untuk mengetahui keterampilan pemecahan masalah kimia siswa. Kata kunci: kemampuan pemecahan masalah kimia, level simbolik, three tier diagnostic test. DOI: http://dx.doi.org/10.23960/jpp.v13.i1.202310

Students’ Strategies, Struggles, and Successes with Mechanism Problem Solving in Organic Chemistry: A Scoping Review of the Research Literature

Students’ Strategies, Struggles, and Successes with Mechanism Problem Solving in Organic Chemistry: A Scoping Review of the Research Literature

A Phase-Fitting Singularly P-Stable Cost-Effective Two-Step Method for Solving Chemistry Problems

A Phase-Fitting Singularly P-Stable Cost-Effective Two-Step Method for Solving Chemistry Problems

IDENTIFICATION OF PROBLEM-SOLVING DIFFICULTIES OF MOROCCAN PUPILS AND TRAINEE TEACHERS IN LEARNING THE REDOX REACTION CONCEPTS: ELECTROLYSIS CASE

The present study aims to identify and compare difficulties in the acquisition of the knowledge and skills for solving electrolysis redox reactions encountered by Moroccan second-year baccalaureate (high school) students (novices in electrolysis problem-solving) and by trainee teachers of physics and chemistry (experts in electrolysis problem solving) at the Regional Center of Education and Training Professions in Rabat. The students and trainee teachers were asked to answer explicit and implicit questions; these questions were classified as simple or complex. Moroccan learners demonstrated mastery of basic problem-solving skills and chemical concepts, including repeating given knowledge, solving reaction equations, calculating the quantity of matter, calculating the concentration of a solution, and using a RICE (reach, impact, confidence, and effort) table. These skills were analyzed based on the objectives of each question and the skills required to solve each question. Both categories of learners were able to solve all of the problems presented in the questions. The participants included 107 students and 110 trainee teachers; the data were collected during the 2020/2021 school year and analyzed using Statistical Package for the Social Sciences (SPSS). The performances of the two groups were compared. On average, the trainee teachers (rank: 137) scored higher than the students (rank: 80) on the problem-solving skills defined in the redox learning outcomes. Thus, the trainee teachers performed better on the questions than the students, indicating a clear difference in mastery of the skills required to solve chemistry problems. However, although the trainee teachers were considered experts and solved the problems more successfully than the students (novices), not all the trainee teachers had mastered all necessary conceptual and methodical skills related to the topic of electrolysis.

Level of Creative Thinking Among Prospective Chemistry Teachers

Creative thinking is one of the skills considered in facing the 21st-century era. Similar to other science domains, creative thinking is also crucial in chemistry learning. The variety of problems in chemistry makes students must be creative thinkers to solve chemistry problems faced. In the classroom, a chemistry teacher has a role in encouraging students’ creative thinking. Other than that, this role also applies to prospective chemistry teachers who will have the same responsibility in the future. Therefore, this study aims to identify the level of creative thinking among prospective chemistry teachers, and identify the aspect of creative thinking that needs to improve. The research design used in this study was a quantitative approach with descriptive research. There were 92 prospective chemistry teachers in Pekanbaru, Riau-Indonesia selected using simple random sampling. Data were collected using open-ended questions and analyzed using the rubric of scoring. Once scoring was done, the score obtained was presented in form of a percentage of score to determine the level of creative thinking. The finding reveals that the level of creative thinking of prospective chemistry teachers was moderate (percentage score of 35.43). The prospective chemistry teachers were at a low level of flexibility and fluency with a percentage score of 27.29 and 27.42 respectively. This finding could be a consideration for any stakeholder to improve the quality of education by taking steps to improve creative thinking among prospective chemistry teachers. With the hope, that none of the students in the future found is at a low level of creative thinking because the students have been taught by competent teachers.

Description of Critical Thinking Ability at XI IPA 1 Grade of SMAN 7 Padang in Solving Chemistry Problems on Reaction Rate Material

During learning process students tend to be passive and memorize with teacher’s explanations. This causes students’ critical thinking skills in finding solutions problems that do not develop optimally. Qualitative descriptive research aims to describe students’ critical thinking at XI IPA 1 grade of SMAN 7 Padang skills in solving chemistry problems on reaction rate material. The research sampling technique used purposive sampling in the XI IPA 1 grade with 38 students. The research data will be analyzed using the qualitative analysis technique of the Miles and Huberman (1984) model consists of data reduction, data display and verification. The research instruments are problem test with 5 questions referring to critical thinking indicators by Ennis (1996) including elementary clarification, basic support, inference, advanced clarification, strategies tactics and interviewing selected students. The results showed that RF subjects of students with high critical thinking skills 4 critical thinking indicators, such as elementary clarification, inference, advanced clarification, strategy and tactics. AM subjects with medium critical thinking skills fulfill 3 critical thinking indicators, elementary clarification, basic support, and inference. While the subject of AZ students with low critical thinking skills only fulfills 2 critical thinking indicators, constist of advanced clarification ,strategy and tactics.

Assessment of Context-Based Chemistry Problem-Solving Skills: Test Design and Results from Ninth-Grade Students

Assessment of Context-Based Chemistry Problem-Solving Skills: Test Design and Results from Ninth-Grade Students

Improving student success in chemistry through cognitive science

Chemistry educator Alex H. Johnstone is perhaps best known for his insight that chemistry is best explained using macroscopic, submicroscopic, and symbolic perspectives. But in his writings, he stressed a broader thesis, namely that teaching should be guided by scientific research on how the brain learns: cognitive science. Since Johnstone’s retirement, science’s understanding of learning has progressed rapidly. A surprising discovery has been when solving chemistry problems of any complexity, reasoning does not work: students must apply very-well-memorized facts and algorithms. Following Johnstone’s advice, we review recent discoveries of cognitive science research. Instructional strategies are recommended that cognitive studies have shown help students learn chemistry.

The Application of Conservation Method in Senior High School Chemistry Problem-solving and the Analysis of Problem-solving Ideas

The Application of Conservation Method in Senior High School Chemistry Problem-solving and the Analysis of Problem-solving Ideas