A computational experiment investigating common organic chemistry mechanisms has been developed and implemented in a junior/senior-level physical chemistry laboratory course at two institutions. Students investigated ...
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A computational experiment investigating common organic chemistry mechanisms has been developed and implemented in a junior/senior-level physical chemistry laboratory course at two institutions. Students investigated various reactions that proceed via S(N)1, S(N)2, E1, and E2 mechanisms using hybrid indicate that students at both institutions were able to better visualize and interpret the 3D representation of transition states, stepwise reaction mechanisms, and reaction coordinate diagrams of the aforementioned reactions.
This article presents computational chemistry exercises that are designed to be incorporated into an undergraduate physical chemistry course. This activity teaches computational chemistry as it is performed in higher-...
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This article presents computational chemistry exercises that are designed to be incorporated into an undergraduate physical chemistry course. This activity teaches computational chemistry as it is performed in higher-level research (in a command-line environment and executed on a high-performance computing cluster) to provide students with a foundation of computational chemistry skills for more advanced computational chemistry research. The activity is also a practical application of topics taught in physical chemistry courses, using the linear combination of atomic orbitals molecular orbital (LCAO-MO) theory description of homonuclear diatomic molecules as a basis to introduce students to computational chemistry techniques, density functional theory calculations of physical observables, and the analysis of computational results. Results from a survey assessing students' learning gains demonstrate that these exercises produce significant gains in students' computational skills, highlighting the efficacy of this activity in achieving its primary goals.
In this paper, a problem set activity focused on understanding and applying unsupervised and supervised chemometric methods for the analysis of biodiesel-diesel blended fuels is described. This problem set was utilize...
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In this paper, a problem set activity focused on understanding and applying unsupervised and supervised chemometric methods for the analysis of biodiesel-diesel blended fuels is described. This problem set was utilized in two upper-level analytical elective courses aimed for junior and senior level students. The data set consists of peak areas taken from gas chromatograms comprising various biodiesel concentrations and feedstock types. Students are tasked with analyzing the data set using principal component analysis (PCA), hierarchical cluster analysis (HCA), and k-nearest neighbors (kNN). The primary purpose of this problem set is to gain hands-on experience manipulating and drawing conclusions about large data sets using chemometric methods. The problem set activity utilizes a large GCMS data set with many varieties of sample types and can be included at any institution with no need for a GCMS instrument on campus.
Novice chemists often struggle with the highly visualnature ofsome chemistry topics. To make visually demanding concepts, such asisomerism and stereochemistry, more accessible to students, chemistryinstructors have lo...
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Novice chemists often struggle with the highly visualnature ofsome chemistry topics. To make visually demanding concepts, such asisomerism and stereochemistry, more accessible to students, chemistryinstructors have long recommended the use of molecular model kitsas visual aids. However, studies pertaining to student model usagehave shown that students are unlikely to spontaneously use molecularmodels to solve problems, even though it was shown that students thatactively manipulated the models are more likely to correctly completevisually demanding organic chemistry tasks. Here we report an activitythat engages students in molecular model usage while exploring structuralisomerism. The activity consists of three sections and is designedto be completed after students have been introduced to structuralisomerism. We chose to implement the activity during the first laboratorysession after the content introduction. The activity takes approximately35 min to complete, regardless of virtual or in-person *** surveys from two academic quarters showed that over 70%of students indicated that the modeling tool improved their 3D perceptionof molecules. However, a smaller percentage of students indicatedthat they would use the modeling tool as a supplement to their normalstudy habits.
The COVID-19 pandemic and its related restrictions forced the reorganization of learning methodology and gave a central role to remote learning. Laboratory experiments are the most affected activity, and several alter...
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The COVID-19 pandemic and its related restrictions forced the reorganization of learning methodology and gave a central role to remote learning. Laboratory experiments are the most affected activity, and several alternatives were described. This work proposes to create calculation tools by simply programming in Visual Basic of Excel to emulate the data acquisition of specific laboratory experiments. The approach appears useful in experiments with a simple setup followed by data analysis. The experiment of gas volumetric properties allows fixing pressure and temperature conditions and measuring the occupied volume. The developed program emulates such operations and reports a computed volume. Further data reduction is the same in both procedures. Such a virtual experience was successfully used with groups of over 100 students. The results obtained were satisfactory compared with those obtained in the laboratory. Detailed analysis of the grades shows that acquired skills are comparable in both methodologies. Consequently, the virtual approach is a flexible option for remote laboratory teaching to complement traditional experimentation.
In this paper, we propose a new method for selecting cases for in situ, immediate interview research: detector-driven classroom interviewing (DDCI). Published work in educational data mining and learning analytics has...
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In this paper, we propose a new method for selecting cases for in situ, immediate interview research: detector-driven classroom interviewing (DDCI). Published work in educational data mining and learning analytics has yielded highly scalable measures that can detect key aspects of student interaction with computer-based learning in close to real-time. These measures detect a variety of constructs and make it possible to increase the precision and time-efficiency of this form of research. We review four examples that show how the method can be used to study why students become frustrated and how they respond, how anxiety influences how students respond to frustration, how metacognition interacts with affect, and how to improve the design of an adaptive learning system. Lastly, we compare DDCI to other mixed-methods approaches and outline opportunities for detector-driven classroom interviewing in research and practice, including research opportunities, design improvement opportunities, and pedagogical opportunities for teachers.
PurposeThe professional development (PD) of teachers is vital to student learning, yet PD continues to be plagued by positivist assumptions and low teacher buy-in. Because PD is based on persuasion, and because the ro...
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PurposeThe professional development (PD) of teachers is vital to student learning, yet PD continues to be plagued by positivist assumptions and low teacher buy-in. Because PD is based on persuasion, and because the roles of PD providers and receivers are not as discrete as they appear, rhetorical theory offers a valuable framework for understanding teacher PD. This study applied rhetorical theory to educator PD to elucidate the complex roles that educators take on as the event unfolds, whether in person or on social ***/methodology/approachThis collective instrumental case study used a holistic design structure to examine how educators embrace, resist or otherwise respond to the roles they are given in PD in person and using social media;and how educators use the affordances of X (formerly Twitter) to shift rhetorical roles in X-based PD activities. A taxonomy was developed to apply the theory accurately and consistently. Data collection included semi-structured interviews and participants' PD-related X use. Interviews were analyzed using descriptive coding by theme. X data was analyzed in three dimensions by use type, topic and rhetorical *** participants exhibited enthusiasm about both receiving and providing PD. Analysis of the participants' perceptions of their PD and of their PD-related X use revealed shifting and layered ways they embrace, resist and otherwise engage with the roles they are given in PD, as well as the complex ways they used the affordances of X to engage with all of the available roles ***/valueIn examining teacher PD using an ecological model of the rhetorical situation, this case study demonstrated the usefulness of rhetoric as a framework for PD that recognizes the nuanced and powerful roles teachers fulfill in their own PD activities in person and on social media.
A Fourier transform infrared (FTIR) experiment appropriateforan upper-level undergraduate laboratory such as chemical instrumentationis described. Students collect FTIR spectra of four protio-solventsand their deutera...
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A Fourier transform infrared (FTIR) experiment appropriateforan upper-level undergraduate laboratory such as chemical instrumentationis described. Students collect FTIR spectra of four protio-solventsand their deuterated analogues. In addition to qualitatively observingC-H and O-H peaks shift to lower energy upon deuteration,students apply a simple harmonic oscillator model to predict the magnitudeof the shifts and gain an understanding of the relationship betweenreduced mass and vibrational frequencies. Vibrational calculationsare then performed to corroborate the experimental results and allowstudents to visualize the normal modes involved via animations ofthe vibrations. This experiment is suitable to be used as either anin-person or online laboratory.
Chemistry undergraduates regularly deal with three-dimensional (3D) information such as molecular geometry and symmetry. Facile mental manipulation of 3D information can help students succeed in chemistry, while poor ...
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Chemistry undergraduates regularly deal with three-dimensional (3D) information such as molecular geometry and symmetry. Facile mental manipulation of 3D information can help students succeed in chemistry, while poor skills can hinder performance. Tools such as model kits are commonly employed to help visualize abstract concepts for students with poor spatial ability. Augmented reality (AR) and 3D viewing technology are promising tools and have seen increased use in educational settings. Research to explore viewing technology in undergraduate chemistry has largely been used to display molecular representations. Visualization tools for 3D information are lacking in analytical chemistry. AR and 3D technologies can be used to create and distribute representations of systems, equilibria, and 3D data. This study explores the Merge platform for use in an analytical chemistry course with a focus on chemical equilibrium and electrochemistry. Models and plots were given to students in four modules covering equilibrium, acid base chemistry, electrochemical principles, and voltammetry. Student opinion of the technology was assessed using student surveys after each module and at the end of the semester. Students generally found the intervention helpful for their understanding but noted that complex 3D objects can cause cognitive overload. The tool shows promise as a visual aid for analytical chemistry and other undergraduate courses.
Preprocessing is a critical step in the analysis pipeline of spectroscopic data. However, students are rarely introduced to preprocessing when learning spectral techniques in laboratory courses which in turn may affec...
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Preprocessing is a critical step in the analysis pipeline of spectroscopic data. However, students are rarely introduced to preprocessing when learning spectral techniques in laboratory courses which in turn may affect and delay their progress in the field. Despite its undoubtable importance, students will be mainly performing spectroscopic analysis in the context of a research project where preprocessing is encountered as part of a routine or "recipe" to follow. In this work, a Python-based application has been developed that allows facile application of common spectral preprocessing techniques with instantaneous results to support student learning. The developed application, i.e. Porchlight, and supplied Jupyter notebooks can substitute costly commercial software and make spectroscopic analysis widely available to students, trainees, and users in general.
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