Chemistry Education Research and Practice最新文献

Peer Instruction (PI), a student-centred teaching method, engages students during class through structured, frequent questioning, facilitated by classroom response systems. The central feature of PI is the ConcepTest, a question designed to help resolve student misconceptions around the subject content. Within our coordination chemistry PI session, we provide students two opportunities to answer each question – once after a round of individual reflection, and then again after a round of augmented reality (AR)-supported peer discussion. The second round provides students with the opportunity to “switch” their original response to a different answer. The percentage of right answers typically increase after peer discussion: most students who answer incorrectly in the individual round switch to the correct answer after the peer discussion. For the six questions posed, we analysed students’ discussions, in addition to their interactions with our AR tool. Furthermore, we analyse students’ self-efficacy, and how this, in addition to factors such as ConcepTest difficulty influence response switching. For this study, we found that students are more likely to switch their responses for more difficult questions, as measured using the approach of Item Response Theory. Students with high pre-session self-efficacy switched from right-to-wrong (p < 0.05) and wrong-to-different wrong less often, and switched from wrong-to-right more often than students with low self-efficacy. Students with a low assessment of their problem solving and science communication abilities were significantly more likely to switch their responses from right to wrong than students with a high assessment of those abilities. Analysis of dialogues revealed evidence of the activation of knowledge elements and control structures.

Representations in chemistry are the tools by which students, instructors, and chemists reason with chemical concepts that are abstract. Although representations are regularly used within the chemistry classroom, there is more to uncover regarding the ways students interact with representations when given chemistry tasks. This study aimed to address this gap in knowledge. In this study, eighteen students enrolled in second semester general chemistry were recruited for data collection. Semi-structured interviews were utilized to observe how students approached a similar set of dipole–dipole interaction tasks when given four distinct representations. Analysis of the data revealed that students’ approaches to these tasks were affected by the newly explicit features present within each representation. Additionally, the ordering in which the representations were presented to the students influenced the specific features students took notice of and implemented into their approaches to the tasks. These findings can better inform instruction and future research involving chemical representations such that students will form a solid foundation in working with and pulling relevant information from various representations when solving chemistry tasks.

Proton nuclear magnetic resonance (¹H NMR) spectroscopy is an essential characterization tool for organic chemists widely taught in the undergraduate chemistry curricula. Previous work has focused on how students advance from novice to expert in interpreting ¹H NMR spectra. However, we need to know more about how ¹H NMR spectroscopy is taught within undergraduate curricula. We sought to characterize instructors’ topic-specific pedagogical content knowledge (PCK) for teaching ¹H NMR spectroscopy as a starting point to investigate how ¹H NMR spectroscopy is taught. Participants from multiple institutions—six teaching assistants, six novice instructors, and three experienced instructors—collaboratively completed content representations (CoRes) in focus groups. Through qualitative analysis of interview transcripts and CoRes, we characterized instructors' topic-specific PCK in ¹H NMR spectral interpretation. Analysis of instructors’ responses and collective PCK elucidates the role that teaching context, experience, and disciplinary background may contribute to the character of PCK. Implications of this work include the need for research on the integration of explicit learning objectives and teaching strategies for representational competence and skills, understanding and supporting student affective experiences when learning NMR, and instructional contexts that increase autonomy in learning.

General spectroscopy is known to be difficult for novice students due to its complex and abstract nature. In this study we used a first-year chemistry Mini Spec laboratory activity to uncover language barriers to student learning in spectroscopy. Analysis revealed that language barriers generated conceptual difficulties for English as Second Language (ESL) students. As well as demonstrating difficulty with understanding of the origin of spectral lines identified in prior research, this work surfaces previously unreported language difficulties which were characterized in terms of technical and non-technical language. These include observations that ‘refract’ and ‘diffract’ appeared poorly delineated for students, the teleological animism of ‘jump’ to describe excited electron transitions towards the ground state, and the non-technical term ‘discrete’ being difficult for students to understand and construct meaning for. In addition to this, students battled with the symbolic language required to depict the formation of spectral lines. Several solutions to the language difficulty are proposed including the re-sequencing of macroscopic, sub-microscopic and symbolic teaching and reconsidering the usefulness of certain non-technical terms for teaching and learning spectroscopy.

Understanding how individual students cognitively engage while participating in small group activities in a General Chemistry class can provide insight into what factors may be influencing their level of engagement. The Interactive–Constructive–Active–Passive (ICAP) framework was used to identify individual students’ level of engagement on items in multiple activities during a General Chemistry course. The effects of timing, group size, and question type on engagement were investigated. Results indicate students’ engagement varied more in the first half of the term, and students demonstrated higher levels of engagement when working in smaller groups or subsets of larger groups when these groups contained students with similar levels of knowledge. Finally, the relation between question type (algorithmic versus explanation) and engagement depended on the activity topic. In an activity on Solutions and Dilutions, there was a significant relation where algorithmic items had higher occurrences of Interactive engagement. The implications of this work regarding teaching and research are discussed.

A large number of students across the globe each year enroll in general chemistry courses as an academic requirement to obtain their degree. Although many take chemistry courses, it is not a subject sought out by many as a potential career. In some instances, chemistry hinders students from achieving their career goals. A plethora of chemical education research has focused on improving student attitude, self-efficacy, and motivation to enhance academic performance and retention in chemistry. However, only a few reports focus on the factors that affect student perception and self-efficacy towards chemistry. These factors are important as they can help us implement targeted interventions to improve perceptions and self-efficacy as we seek to increase diversity in STEM fields. In this research study, the most influential factors that affect a student's perception of chemistry are uncovered, and whether these factors are related to gender identity, letter grade, or pursuit of chemistry as a career. For our study population, the course instructor and course structure are the two most influential factors in a student's perception of chemistry. In addition, academically low-achieving students (i.e., students who earned Cs or lower in a course) are more likely to list the course structure as an influential factor, and high-achieving students (i.e., students who earned Bs or higher in a course) are more likely to select the course instructor as an influential factor. The majority (66%) of students who selected the course instructor as an influential factor believed that they would perform well in future chemistry courses, while 47% of those who selected the course structure had the same belief in their future chemistry performance. Overall, less than 11% of the study population (51 of 447 students) were interested in pursuing chemistry as a career after completing CHEM 1. However, the answer to increasing the number of chemistry majors could be held within course design and teaching pedagogy. This research study seeks to highlight the relationship between gender and letter grade with factors that influence perception of chemistry, and we hope the results can guide instructors as they consider course structure and teaching pedagogy.

Recent efforts in organic chemistry education research focus on investigating activities and strategies designed to elicit students’ mechanistic reasoning. This study investigates how a scaffolded case comparison activity implemented in an introductory organic chemistry course elicits and supports students’ mechanistic reasoning in an authentic classroom setting. The activity included an adaptation of a previously reported reasoning scaffold to support small-group student discussions comparing organic reactions. We analyzed students’ written responses to the in-class activity using Hammer's resources framework and Toulmin's argumentation model, interwoven to create an anti-deficit approach to exploring students’ developing reasoning. The analysis of students’ written artifacts sought to identify ways in which a scaffolded case comparison implemented in a collaborative class setting may support students’ engagement in complex reasoning and argumentation development. We found that the in-class activity elicited students’ writing about various aspects of mechanistic reasoning, including identifying explicit and implicit properties, dynamic reasoning, and multivariate reasoning. These findings indicate that the activity can engage students in complex mechanistic reasoning aspects in the classroom setting. Furthermore, this study extends the literature by detailing the nuances of students’ developing causal reasoning with energetic and electrostatic accounts as shown in their writing. The results highlight students’ emerging causal reasoning with varying levels of complexity and conceptual integration. This study provides direct implications for instructors seeking to implement similar classroom activities. The findings indicate directions for future research on the development of instructional activities and tools that further support students’ developing causal reasoning, such as adapting existing scaffolding structures to support argumentation development and the integration of challenging concepts such as energetics.

Research on student learning in organic chemistry indicates that students tend to focus on surface level features of molecules with less consideration of implicit properties when engaging in mechanistic reasoning. Writing-to-learn (WTL) is one approach for supporting students’ mechanistic reasoning. A variation of WTL incorporates peer review and revision to provide opportunities for students to interact with and learn from their peers, as well as revisit and reflect on their own knowledge and reasoning. However, research indicates that the rhetorical features included in WTL assignments may influence the language students use in their responses. This study utilizes machine learning to characterize the mechanistic features present in second-semester undergraduate organic chemistry students’ responses to two versions of a WTL assignment with different rhetorical features. Furthermore, we examine the role of peer review on the mechanistic reasoning captured in students’ revised drafts. Our analysis indicates that students include both surface level and implicit features of mechanistic reasoning in their drafts and in the feedback to their peers, with slight differences depending on the rhetorical features present in the assignment. However, students’ revisions appeared to be primarily connected to the peer review process via the presence of surface features in the drafts students read (as opposed to the feedback received). These findings indicate that further scaffolding focused on how to utilize information gained from the peer review process (i.e., both feedback received and drafts read) and emphasizing implicit properties could help support the utility of WTL for developing students’ mechanistic reasoning in organic chemistry.

Sensemaking is an important way of learning and engaging in science. Research has shown that sensemaking activities, such as questioning, hypothesizing, and model building, are pivotal in developing critical thinking and problem-solving skills in science education. This paper investigates the role of computational simulations in facilitating sensemaking in chemistry education, specifically examining how these simulations can sustain the sensemaking process. Through a detailed case study in a physical chemistry course, we explore the interplay between students' real-world experiences, theoretical knowledge, and computational simulations. This analysis reveals that computational simulations, by providing interactive and visual representations of chemical phenomena, can create a conducive environment for sensemaking, where students actively engage in exploring and resolving conceptual uncertainties. Based on these results, we argue that computational tools, when effectively integrated into educational settings, can facilitate sensemaking in science education.