Journal of Chemical Education最新文献

The growing presence of generative artificial intelligence (GenAI), such as ChatGPT, has already begun to alter the scientific landscape. In addition to the utility of GenAI, there are also concerns about its ethical use. The rapid introduction of GenAI means that science undergraduate curricula need to be updated to address this technological evolution. To that end, we report here an assignment for an organic materials chemistry course incorporating ChatGPT. This two week activity involves students using ChatGPT to generate short essays on course topics and then critiquing and editing the generated information. Students reported that this assignment helped their understanding of the course topics and that they enjoyed the activity overall. Additionally, we address some of the issues we encountered when implementing this assignment due to the unpredictable nature of ChatGPT, and the solutions we found for them. Overall, students felt that this assignment was valuable for improving their grasp of the course topics without an excessive time commitment.

A microscale synthesis of a naphthalimide fluorescent was redesigned, upscaled, and integrated into the syllabus of an undergraduate introductory organic chemistry laboratory course as an inquiry-based experiment teaching basic thin layer chromatography (TLC) techniques. The students’ goal is to monitor the reaction of 4-chloro-1,8-naphthalic anhydride with different primary amines using TLC, as part of a two-day project cycle, and students were required to submit a written report for summative assessment. Students generally encounter four fluorescent spots: two blue and two yellow. To evaluate the students’ overall experience in conducting this experiment over two consecutive academic years, they were asked to report on their confidence and excitement levels at both the beginning and end of the project cycle. The results showed that the majority of the students felt more confident and excited about the experiment after its completion, reporting an increase above 80% and 60% for both years, respectively.

A comprehensive laboratory exercise is described whereby students measure oscillations in electric potential between iron and carbon electrodes immersed in an acidic solution of hydrogen peroxide. The oscillations observed vary greatly in complexity. After collecting the data, students use a kinetic mechanism to qualitatively model some of the less complex oscillations. The experiment is straightforward to carry out and uses materials commonly found in chemistry laboratories. In addition, the proposed mechanism involves a variety of iron species that are familiar to students of chemistry.

Training in hands-on research is essential for developing core scientific skills in undergraduate students and expanding their career prospects in STEM fields. However, limited internship availabilities, financial constraints, and time demands often make these opportunities inaccessible. To address this gap, we designed and implemented a Course-based Undergraduate Research Experience (CURE) into a biochemistry curriculum through a multiweek computational protein-design project. A cohort of 79 upper-division undergraduate students with prior knowledge of protein chemistry were challenged with the research question: Can rationally designed mutations in an α helix of the model helical protein AvrPto enhance its overall structural stability? Using freely available computational tools such as PyMOL, Discovery Studio Visualizer, AGADIR, AlphaFold 3, Rosetta-suite, and GROMACS, students learned to design novel mutations in helix H1 of the AvrPto protein to enhance its α-helical propensity and study their effects on the overall protein structure, stability, and dynamics. The objective is to help students apply foundational concepts of chemistry to address a complex biological problem. Pedagogically, the study allows students to build transferable skills in protein design, molecular modeling, simulation workflows, and critical scientific reasoning. These skills are invaluable for careers in academia, biotechnology, and pharmaceutical industries. For educators, it provides a scalable framework for integrating authentic research into teaching that is adaptable across various chemistry and biochemistry programs.

Transgender and gender nonconforming (TGNC) students face unique forms of marginalization in Science, Technology, Engineering, and Mathematics (STEM), yet their experiences are often obscured by aggregating LGBTQIA+ populations into a single category. This qualitative study examines how TGNC students experience stigma and navigate belonging within introductory chemistry courses, which is a context where disciplinary norms often reflect cisnormative and exclusionary values. Guided by Goffman’s Stigma Theory and Handley’s Situated Learning Theory, we analyzed two case studies informed by semistructured interviews and supporting survey data. Findings reveal that both students perceived chemistry as a space where their identities were devalued or incompatible with dominant norms, resulting in identity misalignment and constrained participation. Despite these challenges, neither participant fully disidentified from STEM, suggesting that the exclusion they experienced was specific to the culture of chemistry rather than science more broadly. These cases illustrate how stigma and disciplinary culture intersect to shape TGNC students’ sense of legitimacy, belonging, and self-concept in the sciences. We argue that chemistry education must move beyond presumed neutrality to critically engage with the sociopolitical dimensions of the field. Creating inclusive chemistry learning environments will require confronting the structural and cultural norms that render TGNC students invisible or unsafe.

Click chemistry and bioorthogonal reactions have revolutionized chemical biology, offering powerful tools for selective molecular transformations in complex biological environments. Despite their widespread adoption in research, these concepts are rarely included in undergraduate laboratory curricula due to the cost, instability, or complexity of many commonly used reagents. In this work, we present a simple and rapid, yet visually engaging, laboratory experiment for second-year undergraduate students that introduces the principles of click and bioorthogonal chemistry through the formation of a diazaborine heterocycle between 2-formylphenylboronic acid and benzylhydrazine. The experiment is conducted in a phosphate-buffered saline (PBS) solution enriched with lysine, glucose, and glutathione, creating an artificial cellular environment, and requires only standard reagents and basic equipment. Students observe product formation via precipitation, calculate yields, and reflect on the implications of compatibility and selectivity in biological settings. Additionally, the learning outcomes were assessed through lab notebooks, in-class performance, and a postlab quiz. In summary, the proposed activity effectively introduces boron click chemistry in an accessible context and demonstrates the relevance of bioorthogonal reactions in modern chemical biology.

Although the use of representations is crucial for problem-solving in chemistry, students often encounter challenges when using them. Hence, various interventions have been designed to support students’ use of chemistry representations, which can motivate students to modify their visual behavior. However, to fully understand how these interventions affect students, it is crucial not only to understand how they are using representations but also to understand how and to what extent their visual behavior changes in response to these interventions. Since learning may induce complex changes in eye movement across spatial, temporal, and psychophysiological dimensions, a key methodological challenge is how to comprehensively characterize these changes in instructional settings. However, relying on single metrics offers only fragmented insights, capturing isolated aspects of students’ information processing, whereas simultaneous interpretation of multiple eye-tracking metrics presents considerable challenges. In light of this, we conducted two studies using stereochemistry tasks to explore how changes in eye movements can be comprehensively characterized in students who participated in an intervention and those who did not. By calculating the average absolute bounded normalized change across multiple eye-tracking metrics, as Δ_Gaze, and additionally examining the change of individual eye-tracking metrics across tasks, we were able to characterize both overall and detailed changes in students’ eye movements while considering the multifaceted nature of eye-tracking data. In this article, we illustrate the potential and limitations of this methodological approach.

This study presents an innovative undergraduate experiment that integrates the preparation and sensing application of conductive hydrogels to explore hydrogen bonding. By constructing a poly(vinyl alcohol)/polyethylene glycol/phytic acid (PVA/PEG/PA) conductive hydrogel system, the mechanism and application of hydrogen bonding are made observable through thermoplastic behavior and human motion sensing. Using a one-step sol–gel method, PVA/PEG/PA hydrogels are prepared with component ratios adjusted to influence mechanical properties and thermoplasticity. Practice sessions, like circuit conductivity verification and human motion signal collection, transform the abstract theory of hydrogen bonding into a multisensory learning experience and address the limitations of traditional lecture-heavy methods which often struggle to demonstrate the practical impact of molecular-level interactions. This integration of synthesis, characterization, and application significantly enhances educational effectiveness and cultivates problem-solving skills through a hands-on investigation. This teaching model offers an integrated approach for polymer physicochemistry courses, cultivating engineering thinking and scientific inquiry abilities.

Over the past decade, numerous computer-assisted retrosynthesis reaction prediction methods have been reported in the chemical literature, several of which are also shared as open-source code. Reports of integrating these modern open-source retrosynthetic prediction techniques into the chemical education classroom, however, is largely absent. This article describes our efforts to teach a computer-assisted retrosynthesis workshop series using open-source reaction prediction software and methods. In addition to three workshops on selected open-source reaction prediction methods, the series included workshops on Python programming and introductory cheminformatics using the RDKit cheminformatics toolkit. A pre and post survey was distributed to better understand participant familiarity and workshop outcomes. Participants indicated that they had minimal experience with cheminformatics, and open-source retrosynthesis software, however after the workshop series they indicated increased familiarity, interest, and desire to pursue additional training related to open-source retrosynthesis software and methods. We conclude this article with our experiences and ideas for future improvements. The workshop materials and code are available with an open source license, and educators are encouraged to adapt and improve the lessons (https://github.com/UA-Libraries-Research-Data-Services/retrosynthesis).

The mechanistic approach to teaching introductory-level organic chemistry─Organic One and Two (Organic I and II) in the United States─continues to predominate since its introduction through Morrison and Boyd’s legendary textbook. In this approach, reactions are taught alongside their electron-pushing mechanisms (EPMs), thereby providing students with a logical method to learn the transformations. Rather than use EPMs as a tool to learn the corresponding reactions, most of the chemical education research (CER) over the past two decades indicates that students need the reactions to infer their EPMs. From a constructivist perspective, the students’ consistent use of structural representations of reactant(s), intermediate(s), and product(s) to propose EPMs illustrates their sense-making processes. As such, instruction on reactions should precede instruction on EPMs, indicating that the standard mechanistic approach may not be cognitively feasible for most students. This Perspective contains four main sections. First, the CER on how students solve electron-pushing tasks is presented to substantiate the claim about students’ use of structural representations to infer EPMs. Second, these research data are interpreted using a constructivist framework. Third, another body of CER is presented to support the assertion of cognitive disconnect. Fourth, the work of three groups who are developing significant improvements to delivering and assessing the mechanistic approach is briefly presented, followed by a few considerations for research and teaching moving forward.