Journal of Chemical Education最新文献

Active learning through interactive exploration significantly enhances student engagement and understanding of chemistry. This educational activity demonstrates Principal Component Analysis (PCA) and Partial-Least-Square-Discriminant Analysis (PLS-DA), two foundational machine learning techniques widely applied in contemporary research. Interactive Python-based programs offer accessible educational platforms for students exploring chemical data, requiring no prior programming experience. This application allows learners to actively engage in feature exploration and dimensionality reduction processes, applied to clustering and classifying binary AB equiatomic solid state compounds. Students can actively select and modify chemical and physical features, observing in real time how these choices impact the effectiveness of the PCA and PLS-DA clustering models. Initially, PCA enables unsupervised visualization of natural clustering and correlations among compounds without prior labeling. Subsequently, by employing PLS-DA, students develop supervised models capable of predicting crystal structures, explicitly illustrating supervised versus unsupervised learning paradigms. The activity highlights the importance of explainability in machine learning models rather than operating the models as a ″black box″. Beyond learning fundamental concepts, the activity encourages students to participate in genuine exploratory processes, mirroring the investigative approaches historically utilized by researchers and practiced today. By experimenting freely with data sets and computational methods, students experience firsthand the iterative nature of scientific discovery, fostering deeper insight into both chemical informatics and the broader research methodology.

Undergraduate organic chemistry is considered a complicated subject, repeatedly identified as difficult by learners. To succeed, students must master the complex conventions of the organic chemistry language and use multiple types of visual representations. Understanding organic chemistry heavily relies on visual thinking skills, necessary for integrating new and highly specific visual input in visualization. Despite educators’ attempts to employ varied teaching strategies, many students struggle with the visual translations required to engage in multilevel thinking. To address and support students’ discipline-oriented visual literacy skills while teaching organic chemistry, we developed and implemented an intervention involving 10 tasks based on the application of neuropedagogy-based strategies expected to support the development of visual literacy skills (VLS). The VLS tasks were introduced during the semester in otherwise traditional lectures, keeping up with the rapid teaching pace required by the university curricula. As a preliminary evaluation of the intervention, we focused on students’ achievements and their overall perception of the course and the VLS tasks. Our findings suggest a positive correlation between the number of performed VLS tasks and students’ achievements. Moreover, students’ perspectives toward the course and VLS tasks’ perceived influence on their organic chemistry-related visual abilities were positive. Through this intervention, we learn that integrating neuropedagogy-based instructional strategies to promote visual literacy in undergraduate organic chemistry during lecturing is feasible and may potentially improve students’ achievements with minimal in-class effort while maintaining the course pace and curricular goals.

Stereochemistry is a conceptually demanding area of chemistry, requiring learners to mentally manipulate three-dimensional structures while applying multiple rules simultaneously. Traditional reliance on 2D diagrams and rote memorization can hinder mastery, particularly in predicting substituted cyclohexane conformations. This study explored a hybrid instructional method that integrates tabular representations with collaborative learning to reduce visuospatial barriers and support systematic reasoning. A single-stage cluster sample of graduate-level (M.Sc.) chemistry students (N = 40) from the University of Kerala participated in the intervention. Using a sequential explanatory mixed-methods design, single-group quantitative pre–post analyses and paired-samples t tests indicated improvements in accuracy and reasoning within this cohort. Qualitative feedback corroborated these trends, suggesting that tabular frameworks may enhance recall, reduce cognitive load, and clarify rule integration through peer discussion. Together, the findings provide preliminary evidence that this structured and collaborative approach could serve as a low-cognitive-load pedagogy to support learning in stereochemistry, with potential implications for innovative instructional strategies in organic chemistry education.

Learning chemistry requires students to integrate macroscopic observations, submicroscopic models, and symbolic representations. However, connecting these representations remains a major challenge, particularly in inorganic chemistry, where the nomenclature of compounds presents persistent difficulties. The coexistence of systematic, Stock, and traditional naming systems leads to inconsistencies and confusion, even for simple compounds such as CO₂, H₂SO₄, and Ni(OH)₂. As a result, many students rely on rote memorization, diminishing engagement, and retention. To address this challenge, we developed Salt Wars, an educational card game designed to strengthen students’ mastery of inorganic nomenclature. The game requires players to combine cations and anions to form valid compounds and name them using different nomenclature systems. This activity fosters the recognition of chemical patterns, promotes logical reasoning, and encourages collaborative and competitive learning in a relaxed environment. Salt Wars was implemented with 92 first-year undergraduate students at the Facultad de Quı́mica, UNAM. Participants completed a standardized nomenclature test and a perception survey before and after gameplay. Results showed a statistically significant improvement in students’ ability to name inorganic compounds, as well as positive attitudes toward the game’s educational value and enjoyment.

This study investigates the performance of different OpenAI GPT model versions (GPT-3.5 Turbo, GPT-4 Turbo, GPT-4o, o1-preview and GPT-5 at different reasoning effort values) in solving chemistry problems across various educational and conceptual difficulty levels. The evaluation, aimed at assessing both accuracy and reasoning quality, was based on a data set comprising 150 multiple-choice questions and 10 open-ended questions at the high school level, as well as 75 multiple-choice questions, 10 open-ended questions, and 100 stoichiometry exercises at the university level. The results reveal a clear trend of improvement in both accuracy and consistency with successive GPT model versions, with o1-preview and GPT-5 demonstrating the highest overall performance due to their reasoning capabilities. Error analysis shows that, while conceptual understanding is generally strong, computational mistakes remain frequent, particularly in tasks related to chemical equilibrium exercises and redox reaction balancing, though GPT-5 markedly reduced these errors compared to earlier models. Additionally, misinterpretations of questions requiring judgment or historical context have emerged as a recurring issue. While prompt formulation influences performance in specific contexts, such as redox balancing, the overall sophistication of the model appears to be the primary determinant of performance. These findings suggest that recent advancements in large language models have significantly enhanced their potential for chemistry education, although careful oversight remains necessary to address numerical inaccuracies and interpretative limitations.

This study investigates how final-year Nigerian undergraduate chemistry students perceive and respond to unexpected results during laboratory experiments. Qualitative descriptive survey research method was employed in this study, and data was collected through observation, focus group discussions, and unstructured oral interviews. 156 students taking final year chemistry practical were sampled, and a total of 48 students across 12 groups were observed to have experienced experiments that went wrong, out of which 14 were engaged in focus group discussions and 6 presented for individual interviews, with at least a member of each group represented. The data were analyzed thematically to identify patterns in students’ perceptions and responses. The findings show that students primarily attributed unexpected results to procedural mistakes, faulty equipment, or impure materials and responded by retracing steps, repeating experiments, discarding nonconforming results, or comparing outcomes with peers. While some students attempted to bypass or modify steps in the prescribed procedures, such actions reflected corrective rather than investigative mind sets. These findings highlight the influence of structured, cookbook-style laboratory tasks, which position unexpected outcomes as errors to be corrected rather than phenomena to be explored. The study concludes that promoting inquiry-based laboratory experiences and reflective assessment practices is important for helping students develop critical cognitive understandings of unexpected results. It further recommends redesigning practical tasks to integrate guided inquiry and process-focused inquiry to help students explore and explain anomalies rather than eliminate them.

Climate change education plays a critical role in preparing students to understand and address global environmental challenges. This study investigates the impact of a green chemistry-based organic chemistry laboratory experiment (focused on ultrasonic-assisted biodiesel synthesis) on undergraduate students’ green chemistry understanding and climate change hope and self-efficacy. Participants engaged in the synthesis and analysis of biodiesel, integrating core concepts of green chemistry with real-world environmental relevance. Quantitative data from pre- and postsurveys showed good internal structure validity and internal consistency reliability in the research context. Correlational analysis demonstrated strong positive relationships among these constructs, particularly after the experiment, suggesting the importance of integrating cognitive and affective learning outcomes in climate change education. The quantitative results revealed significant improvements in students’ understanding of green chemistry principles, their hope (Personal- and Collective-Sphere Willpower and Waypower, PW and CW, respectively), and their self-efficacy toward climate change. Qualitative reflections further illustrated students’ increased awareness and confidence in contributing to climate solutions. Gender-based analysis revealed that female students scored significantly higher on PW than male students after the biodiesel experiment, while the gender difference in Lack of Willpower and Waypower (LW) was eliminated following the experiment. These results suggest that the biodiesel project not only fostered more positive hope among students but also helped reduce gender disparities in hope-related outcomes. The findings from the study highlight the value of experiential, sustainability-focused chemistry education in fostering both cognitive learning and affective engagement with environmental issues, emphasizing the role of green chemistry as a transformative approach in climate change education.

This qualitative study examines the potential of head-mounted displays (HMDs) for providing remote support in a university setting. It focuses on whether immersive technologies, such as HMDs with augmented reality (AR), could be a useful addition to or alternative to traditional remote support formats, particularly for practical, action-oriented activities, such as laboratory work. Three case studies in which students were supervised as part of their final theses or examinations were conducted to document and evaluate user experiences, challenges, and potential. Following initial skepticism regarding the technology, particularly regarding technical aspects, the participants’ attitude turned largely positive with increased use. HMDs proved particularly helpful in laboratory environments, enabling intuitive, present, and context-sensitive support. Key advantages included real-time communication, visual participation from a first-person perspective, support through digital additions to the field of view using AR, and hands-free operation. At the same time, it was demonstrated that the technology is particularly effective in small settings. These results suggest new perspectives for the use of immersive technologies in digital university teaching, particularly for remote supervision of practical activities.

This paper describes an activity for the TLC identification of the unknown medicinal components of the real-life over-the-counter pain medications acetylsalicylic acid, acetaminophen, ibuprofen, and naproxen, alone or in combination with methocarbamol or diphenhydramine. The activity is very simple for technical staff to set up and for students to carry out. It uses little material, poses minimal health hazards, and produces little waste, while effectively demonstrating TLC in terms of intermolecular phenomena linked to structure.

While active learning has shown benefits in chemistry education, there is limited application of these strategies specifically aimed at strengthening students’ understanding of quality parameters in laboratory settings. This study explores the effectiveness of an educational activity based on an active learning approach to reinforce the use of quality parameters in quantitative chemical analysis. The activity involved undergraduate students in the context of the Laboratory of Quantitative Analytical Chemistry. The students worked in collaborative groups, making decisions about the design of their procedures and the implemented analysis. In the laboratory experiment, the students evaluated two methods to determine ascorbic acid: implementing the use of electrodes modified or not with gold nanoparticles and applying the square wave voltammetry technique. The learning outcomes were evaluated through pre- and post-tests, resulting in a gain in subject knowledge with the intervention. Also, the participants expressed their satisfaction with the experiment, recognizing different attributes of the experience, such as the application of prior knowledge, the integration of an electroanalytical method, the opportunity to decide their implemented methodology, and teamwork. The integration of active learning in the laboratory curriculum not only achieved a gain of subject content among the participants but also resulted in a rewarding experience for them. This study serves as a model for curricular upgrades to integrate experimental laboratories based on an active learning approach to improve the academic experience and preparation of future chemists.