Journal of Chemical Education最新文献

In this study, a new competency assessment system was developed for the blended learning course “Organic Chemistry Laboratory”. The system utilized a mastery transcript evaluation model and incorporated the Structure of Observed Learning Outcomes (SOLO) taxonomy and Primary Trait Analysis (PTA) scale method. With this system, students can clearly understand the proficiency level that they need to reach both online and in class to achieve their desired course grades. The impact of the assessment method was analyzed by examining 20 sophomore students from a university. The findings highlighted that this new competency-based rubric offers several advantages, such as providing a more comprehensive assessment of students’ abilities, encouraging the development of their enthusiasm for independent learning, and improving their concentration during experiments. All of these benefits contribute to developing their overall competency skills.

Resonance is a foundational organic chemistry concept, but it is consistently misunderstood by undergraduate students. The development of a concept inventory─a multiple-choice assessment where the incorrect answer choices stem from commonly held alternate conceptions─on the concept of resonance could help organic chemistry instructors quickly identify alternate conceptions held by their students and make interventions. While concept inventories have been developed in a variety of areas in chemistry, there is no existing resonance concept inventory despite the difficulty students seem to have with the concept. In this study, open-ended resonance items were designed and administered to first-semester undergraduate organic chemistry students to develop items for a pilot version of the Resonance Concept Inventory (RCI). Validity evidence based on content and response processes for the data obtained using the items was acquired through feedback from organic chemistry faculty and think-aloud interviews conducted with students. The most commonly occurring alternate conceptions on the concept of resonance were identified, and a 14-item pilot version of the RCI was developed.

A one-pot multicomponent synthesis of unsymmetrical indole-substituted methane derivative based on two consecutive reactions of p-methylbenzaldehyde with N-methylindole and 5,5-dimethyl-1,3-cyclohexanedione is described as an experiment that was carried out by second-year undergraduate chemistry students individually in a laboratory classroom. The experiment provides an opportunity for students to carry out novel organic chemistry transformations for the synthesis of complex molecules from simple substrates, which is also the main pedagogical goal. Salient features of this teaching experiment include (a) multicomponent synthesis and good operability, (b) the absence of catalyst and any additives, (c) high yield and atomic economy, and (d) the use of inexpensive and green solvent. This laboratory experiment combines organic synthesis, TLC, NMR, and IR analysis. Several important concepts, such as green chemistry, chem- and regioselectivity, conjugated 1,4-addition, and atomic economy, are also discussed.

Artificial intelligence (AI) technology has the potential to revolutionize the education sector. This study sought to determine the efficacy of ChatGPT to correctly answer questions a learner would use and to elucidate how the AI was processing potential prompts. Our goal was to evaluate the role of prompt formats, response consistency, and reliability of ChatGPT responses. Analyzing prompt format, we see that the data do not demonstrate a statistically significant difference between multiple-choice and free-response questions. Neither format achieved scores higher than 37%, and testing at different locations did not improve scores. Interestingly, ChatGPT’s free version provides accurate responses to discipline-specific questions that contain information from unrelated topics as distractors, improving its accuracy over the free-response questions. It is important to consider, while ChatGPT can identify the correct answer within a given context, it may not be able to determine if the answer it selects is correct computationally or through analysis. The results of this study can guide future AI and ChatGPT training practices and implementations to ensure they are used to their fullest potential.

Chemistry education research demonstrates the value of open-ended writing tasks, such as writing-to-learn (WTL) assignments, for supporting students’ learning with topics including reasoning about reaction mechanisms. The emergence of generative artificial intelligence (AI) technology, such as chatbots ChatGPT and Bard, raises concerns regarding the value of open-ended writing tasks in the classroom; one concern involves academic integrity and whether students will use these chatbots to produce sufficient responses to open-ended writing tasks. The present study investigates the degree to which generative AI chatbots exhibit mechanistic reasoning in response to organic chemistry WTL assignments. We produced responses from three generative AI chatbots (ChatGPT-3.5, ChatGPT-4, and Bard) to two WTL assignments developed to elicit students’ mechanistic reasoning. Using previously reported machine learning models for analyzing student writing in response to the WTL assignments, we analyzed the chatbot responses for the inclusion of features pertinent to mechanistic reasoning. Herein, we report quantitative analyses of (1) the differences between chatbot responses on the two assignments and (2) the differences between chatbot and authentic student responses. Findings indicate that chatbots respond differently to different WTL assignments. Additionally, the chatbots rarely incorporated the discussion of electron movement, a key feature of mechanistic reasoning. Furthermore, the chatbots, in general, do not engage in mechanistic reasoning at the same level as students. We contextualize the results by considering academic integrity with the assumption that students’ intentions are to engage in academically honest behavior, and we focus on understanding the ethical uses of generative AI for classroom assignments.

The addition of a small excess of triethyl orthoformate to an alcoholic mixture of NiCl₂·6H₂O and triphenylphosphine (PPh₃) results in an increase in the typical isolated yield of [NiCl₂(PPh₃)₂] from below 50% to over 85%. The impact of water when present in the reaction medium in this system is discussed, and results from the application of the same synthetic approach to the syntheses of [NiBr₂(PPh₃)₂], [NiCl₂(dppe)], and [NiBr₂(dppe)] are presented. A simple synthesis of NiCl₂·2H₂O by the dehydration of NiCl₂·6H₂O at 80 °C can be performed as an optional step to decrease the quantity of triethyl orthoformate required for the preparation of [NiCl₂(PPh₃)₂] and/or [NiCl₂(dppe)]. The experiments are flexible and accommodate a variety of laboratory schedules and student skill levels. Each synthesis can be readily completed within a 3 h laboratory period.

This communication follows up to two previously published manuscripts concerning classroom response systems and multiple-choice questions. Here, more than 250 multiple-choice and true-false items for the basics in quantitative instrumental element analysis with keys and brief explanations are presented. Guidelines for designing questions for exams are revisited for developing exercise material, and the generation of distractors based on responses to open-ended questions is investigated within a routine teaching context.

We present a showcase of our experience with videos complementing analytical chemistry lectures to familiarize undergraduate students with instrumental element analysis. This includes a detailed account of how we planned, produced, and utilized a video to review the course content at the end of the semester. The analytical case study focused on the determination of magnesium in two well water samples with emphasis on flame atomic absorption spectroscopy, while also comparing results with inductively coupled plasma optical emission spectroscopy and titration measurements. During the lecture, we engaged students by asking them for suggestions on how to carry out the measurements before showing the respective video sections. A survey among the students revealed a remarkably positive response to this approach. We demonstrate our video production approach by making decisions and choices from the video production, such as recording and editing, explicit and conclude with practical advice for planning and producing similar videos to visualize case studies.

Current laboratory-based practical classes are arranged so that all students can complete the required activities on time. With this system there is no incentive for students to optimize the time they spend in the laboratory or have awareness of whether they are conducting the activities in a timely manner. However, the acceptable timeframes for specific basic laboratory procedures within industry are not known. This survey-based study aimed to gain a perception of the employed analytical chemists on the importance of time in conducting practical procedures. The participants were also asked to indicate what duration of time would be acceptable to complete specific basic laboratory practical procedures within industry based on their experience. This was compared to the time that final year chemistry students took to complete basic laboratory practical procedures. Our findings highlighted that time is an important factor in the workplace and should be considered a key competency when preparing analytical chemists. Participants in higher education assumed more time was given in industry to conduct laboratory procedures than those who were working in industry. Students took considerably longer to complete the activities than were perceived to be timely within industry. Speed in conducting practical skills was considered especially important in the pharmaceutical industry. Overall, our findings highlight that working in a timely manner should be considered within an analytical chemistry curriculum and embedded within assessments. Students who aspire to work within industry should have awareness of the importance of generating acceptable data while working in a timely manner.

Enzymes provide attractive targets for drug development. Quantitative analysis of enzyme reactions can lead to rational drug discovery. For undergraduates majoring in biochemistry or pharmacy and engaged in drug discovery-related work, it is essential to acquire a comprehensive understanding of enzyme kinetics, including experimental methods and the fundamental principles of drug screening. Being overexpressed in cancer, MTHFD2 is an emerging anticancer drug target. Herein, we used MTHFD2 to develop a high-throughput drug screening laboratory course based on enzyme kinetics for upper-division undergraduate students. The learning activities that were designed for students included Escherichia coli-based protein expression, protein purification, enzyme activity assay, setting up a high-throughput drug screening assay, and data analysis. The main purpose of this one-week laboratory education course is to provide students with a better understanding of enzyme kinetics, high-throughput drug screening and to help them grasp the relationship between enzyme kinetics and drug discovery. This hands-on course provides students an opportunity to learn how theoretical knowledge is applied in real practice.