Journal of Chemical Education最新文献

Calorimetry is one of the best experiments to do in an introductory-level chemistry laboratory course, as it has high accuracy and requires relatively inexpensive materials. Like other traditional general chemistry laboratory experiments, calorimetry is not easily converted to at-home or remote experimentation. The in-lab experiment typically requires relatively inaccessible equipment, such as alcohol-based thermometers with a range of at least 20° to 110 °C, analytical balances, and either Bunsen burners or hot plates. We present a modified calorimetry experiment designed with an accessibility-first approach during remote laboratory instruction in response to the COVID-19 pandemic. The modification uses clinical thermometers, hanger balances, and microwaves to determine the specific heats of the metals. The mean of the reported specific heat values of a United States coin (penny) and steel materials in the traditional lab version differs by 0.131 and 0.179 J/g·°C, respectively, of literature values. Conversely, these values for the aforementioned materials in the remote version differ from the values in the literature by 0.158 and 0.133 J/g·°C, respectively. Despite the utilization of nonscientifically standard materials in the remote experiment, the specific heat values in lab and remote settings produce comparable results. This presents an opportunity for our accessibility designed at-home lab to be used as a prelab or make up assignment as part of an inclusive lab course.

Instructors use of Artificial Intelligence (AI) language models (i.e., chatbots) as an educational resource will require an understanding of students’ AI literacy, namely their ability to critically reflect on the relevance, trustworthiness, and quality of these tools in the context of chemistry. This study sought to describe students' AI literacy via open-ended surveys of general chemistry I students and students in an upper-level chemistry elective. Thematic analysis was used to create a deeper understanding of chemistry students’ AI literacy when considering chatbots. Based on students’ responses, they were categorized as either with reservations toward chatbots or without reservations toward chatbots. Thematically, students tended to either reason with the utility/benefit of the tool or reason with concern toward the accuracy of the tool. Results suggest that students are more of a range between these two extremes. This new deeper understanding of AI literacy in chemistry can support instructional practices and inform future research efforts in AI literacy.

Spectroscopy Unlocked is an escape room activity cocreated by student and staff authors. The escape room presents students with a series of activities that they must complete in the laboratory in order to reveal a series of codes and clues that can be combined to “unlock” the escape room. Students were highly engaged with the escape room, and evaluation of the activity revealed that students agreed that the format of the activity facilitated their learning and that the activities provided an appropriate level of challenge. The activity can be integrated into introductory chemistry courses, and it may be possible to adapt the activity to change the level or content to meet the specific needs of other courses.

This article provides information about designing, implementing, and evaluating an online cooperative game─Vikings game─to assist high school and undergraduate students in reviewing contents related to thermochemistry, chemical equilibrium, and chemical kinetics. It is a free-of-charge game and is available in both English and Portuguese. The game was introduced into the classroom as an educational review tool, offering an innovative approach to supplement traditional problem-solving classes. Also, upon evaluating student learning, it became evident that the game significantly contributed to educational enhancement. The learners expressed highly favorable opinions about the game, considering it an innovative and valuable complementary didactic tool.

Modeling and using multiple representations are regarded as useful methods for problem solving. However, models are usually demonstrated by teachers rather than actively constructed by students, and students find it hard to connect macro- and submicrorepresentations and comprehend the meaning conveyed by symbols. With the intention of coping with these issues, we propose the method of Modeling Using Multiple Connected Representations, and the key teaching process is delineated as follows: (1) perceive macroinformation; (2) deduce submicroinformation; (3) integrate macro- and submicroinformation into the mental model; (4) transform the mental model into explicit model; and (5) form the problem solution. A case study was carried out to integrate Modeling Using Multiple Connected Representations into the curriculum. The 10th grade students employed multiple connected representations to accomplish the modeling activities of the series electrolytic cell and transferred the case to a new context to solve problems. Students’ handouts, class observations, tests, and interviews were used for data collection. In this preliminary case study, observations show that students were engaged in the Modeling Using Multiple Connected Representations approach, and data suggest that modeling may aide students in problem solving. Further study appears warranted to examine how student engagement using this approach supports success in problem solving.

Isomerism is an important concept in organic chemistry, causing compounds with the same molecular formulas to show different physical and chemical properties as a result of different arrangements of the atoms. In this study, a flowchart that brings together various concepts related to isomerism for different topics in organic chemistry courses and that helps students determine the isomeric relationships between compounds was developed, and its effectiveness was examined. This flowchart comprises two main concepts: constitutional isomers and stereoisomers. The main concept of stereoisomers includes the concepts of conformers and configurational isomers. The generated flowchart was carefully developed to be comprehensive in terms of the concepts it contained and appropriate for the undergraduate level. The study was carried out with 36 students enrolled in Organic Chemistry I and II courses of a state university. The students were given a set of questions consisting of 20 items, and they were asked to determine the isomeric relationships between pairs of compounds and to write justifications with and without the flowchart. In addition, all students were interviewed, and their opinions about the effectiveness of the flowchart were obtained. The findings revealed that the students’ use of the flowchart significantly improved their performance in determining and explaining isomeric relationships. In addition, the students found the flowchart useful in the process of answering the questions, because it helped them remember concepts and also guided them. These results show that the flowchart developed in this study as a pedagogical tool for isomerism in organic chemistry is effective.

Educational debts in STEM are issues that continue to plague the field by filtering out potential STEM graduates early in their college career, often associated with the assumption that some students are naturally gifted, while others are destined to change career paths. This study aims to present how the application of QuantCrit principles helps unearth a counterstory for traditional explanations of underperformance of Black and Latine students in General Chemistry I. The study found that the biggest driver of performance differences among Black and Latine students in General Chemistry I was the attendance and participation in the in-classroom component of the curriculum. Additionally, the study found that black students had lower attendance rates in the course despite engaging in the online portion at high rates. To explore potential explanations for the lower attendance of black students the results from a campus wide climate survey were investigated. These results highlight the importance of implementing QuantCrit principles to uncover counterstories and address educational debt in STEM, particularly for Black and Latine students.

The rapid integration of generative artificial intelligence (AI) into educational settings prompts an urgent examination of its efficacy and the strategies that students employ to harness its potential. This study focuses on preservice chemistry teachers use of generative AI for chemistry-specific problem-solving and task completion. We found that there is a prevalent reliance on copy-pasting tactics in initial prompting approaches, and students need guidance to improve their prompting abilities. By implementing the “Five S” prompting framework, we explore the evolution of student prompts and the resultant satisfaction with AI-generated responses. Our findings indicate that, while students initially struggle with the nuances of effective prompting, the adoption of structured frameworks significantly enhances their perceived quality of AI-generated answers. This research sheds light on the current state of AI use among students but also underscores the importance of targeted educational frameworks to refine AI interaction in academic contexts. In particular, we suggest critical engagement and methodological prompt engineering strategies to maximize the educational benefits of generative AI technologies.

This study examines how preservice science teachers (PSTs) use multiple levels of representation in chemistry (macroscopic, microscopic, symbolic, and algebraic) as a result of engaging in argument-based inquiry in three different conditions: laboratory-only, technology-only, and a combination of technology and laboratory. The Science Writing Heuristic (SWH) approach was used to provide an argument-based inquiry environment under each condition. This study was conducted over the course of one semester, lasting 14 weeks in total, in a Chemistry I course. The study used an embedded single-case study design, and the participants consisted of 20 PSTs. Data included vignettes and video recordings. Video recordings of each of the PSTs’ discussions were analyzed for multiple levels of representation in chemistry in the design and claims and evidence components of the SWH approach for each week. Vignettes were analyzed by using content analysis. The results reveal that the PSTs prefer engaging in the combination of laboratory and technology conditions in terms of representational use, with this condition being the most beneficial in promoting development of representational competency. The results also highlight that the PSTs tend to consider technology beneficial for understanding the microscopic level of representation. Through a combination of laboratory and technology, PSTs are able to create arguments by utilizing and linking the multiple levels of representation necessary for building an understanding of chemistry.

In an age dominated by digital technologies, instilling digital literacy within educational curricula is imperative. This study explores the innovative integration of computational chemistry in post-16 upper-secondary education. Learners actively modeled foundational principles like chemical bonding, van der Waals interactions, molecular geometry, and electron density using individual laptops with the Gaussian computational software. The efficacy of this approach was assessed through pre- and post-test measures, utilizing Likert-type scale questions to gauge shifts in students’ confidence in core chemistry topics and knowledge-based tests. The results show that students’ confidence in general chemistry is rapidly boosted by the intervention, followed by a moderate rise in their knowledge.