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The Math-Up Skills Tests (MUST) has been used in multiple research projects conducted by the Networking for Science Advancement (NSA) team to determine how automaticity skills (what can be done without a calculator) in arithmetic can be used to predict if students will be successful (course average = 69.5%+) in general chemistry. This study expands our investigations to include how students’ quantitative literacy/quantitative reasoning (QL/QR) abilities influence their success. The NSA team studied multiple classes at eight universities (n = 1,915) within a broad geographic setting in one large, majority-minority southwestern US state. In a short amount of required classroom time, it is possible to identify students at the beginning of the semester who will struggle in first- and second-semester general chemistry (Chem I and Chem II). Results show a strong correlation between students’ automaticity MUST skills and their QL/QR ability (r = 0.60) and indicate that when taking both diagnostic assessments into consideration, convincing signals appear allowing for the identification of almost 50% of the Chem I students and about 45% of the Chem II students who will not succeed. With the addition of the QL/QR to the first-week assessments, about 9% more students who enter the courses underprepared were identified than when only the MUST was administered. Outcomes indicate that students with at least average arithmetic and QL/QR automaticity abilities are those who are better prepared for these courses. For on-sequence students with at least one average or above diagnostic score, 88.3% Chem I and 90.5% Chem II were successful.

This contribution reports the process and outcomes of a multiyear effort that supported institutions in reforming general chemistry using multidimensional learning approaches in the form of performance expectations. Performance expectations are based on evidence-centered assessment design principles and describe what learners should be able to do with their knowledge, a subtle (but profound) shift from traditional course learning goals. The effort grew from the recommendations of a task force appointed in 2015 by the American Chemical Society’s Division of Chemical Education and Society Committee on Education. This task force recommended a participatory process for creating general chemistry performance expectations that was distributed over, and also coordinated across, multiple institutions. With support from the ACS Education Division, this recommendation was enacted through workshops which supported faculty in developing activities and assessments that integrated content, science and engineering practices, and cross-cutting concepts—a three-dimensional structure based on the National Research Council report A Framework for K-12 Education. From these workshops, a group of faculty committed to implementing three-dimensional performance expectations in their courses evolved. In practice, these faculty found that their institutional work resulted in designing learning performances that, while also three-dimensional, were of narrower content focus than is typical of performance expectations. This development process also led faculty to use the structures of evidence-centered design and multidimensional learning to document learning activity designs in new ways, generating a consensus activity structure. As examples of how faculty used this consensus activity structure as a new way to examine student learning and performances, development artifacts from four of the participating institutions is presented.

One particular challenge in chemistry learning is developing students’ atomic level understanding of chemical processes. It is necessary to help students learn how to critique atomic models rather than accept them as “truth.” In this study, we used a resources-based framework to examine how students made sense of macroscopic level information to account for what was happening at the atomic level. We interviewed 20 students enrolled in the first semester of general chemistry. Each student completed three exercises. The first exercise involved a card sorting task and the second exercise involved constructing an atomic model to learn how students made sense of the atomic level of a reaction involving the mixing of aqueous silver nitrate and aqueous sodium chloride to produce a precipitate. Next, students engaged in an exercise in which they were shown three conflicting atomic level animations of the same experiment and they were charged with selecting the animation that was most scientifically accurate. We analyzed the general patterns of characterization that emerged when students engaged in the card sorting and modeling exercise and the conflicting animation exercise using a resources framework. We contend that students apply and sometimes misapply knowledge resources to make sense of the atomic level. The process affects decisions that they make and stances that they develop about the accuracy of atomic level models.

This mixed method study investigation uses eye tracking and qualitative analysis to investigate the impact of animation variation and visual feedback on the critique of submicroscopic representations of experimental phenomena. Undergraduate general chemistry students first viewed an experimental video of a precipitation or oxidation reduction (redox) reaction. Next, they viewed the corresponding animations and were shown a visualization of where they had looked. Critique of the chemically relevant features in the animations and viewing pattern were monitored using participant generated drawings, verbal responses, graphic organizers, and eye tracking. Viewing and critique of chemically relevant features were found to increase after engaging with structured animations and visual feedback. Findings from this study support the use of structured variations and visual feedback in developing critical consumers of visual information, empowering students to describe and develop their understanding of chemical phenomena and become more purposeful visual consumers.

In this qualitative study, we examined how a group of seventeen first semester General Chemistry students responded when they were shown contrasting molecular animations of a reduction–oxidation (redox) reaction between solid copper and aqueous silver nitrate for which they first viewed a video of the actual experiment. The animations contrasted in that they portrayed different reaction mechanisms for the redox reaction. One animation was scientifically accurate and reflected an electron exchange mechanism, while the other was purposefully inaccurate and represented a physical exchange between the ions. Students were instructed to critique each animation for its fit with the experimental evidence and to ultimately choose the animation that they felt best depicted the molecular level of the chemical reaction. Analyses showed that most students identified that the electron exchange animation was the more scientifically accurate animation; however, approximately half of the students revised their drawings to fit with the inaccurate physical exchange animation. In addition, nearly all students thought that both animations were correct and useful for understanding salient information about the redox reaction. The results indicate that when students are shown contrasting animations of varying accuracy they make errors in deciding how the animations are supported and refuted by the evidence, but the treatment is effective. Contrasting animations promote students to think deeply about how animations fit with experimental evidence and is a promising way to engage students to think deeply about animations.

Self-explaining refers to the generation of inferences about causal connections between objects and events for one's own consumption. Self-explaining is amongst the practices of science deemed essential for scientific competence; therefore, a valued learning outcome in itself. Nonetheless, generation of authentic explanations is seldom promoted in college science instruction. This work examined the effect of engagement in self-explaining on conceptual understanding of chemistry. Learning and performance tasks were completed individually in the classroom ecology of a large-enrolment General Chemistry course in the US. The study spanned a period of five semesters including pilot-tests and replications. The self-explaining intervention followed a multi-condition comparison design that used performance on a post-test to assess learning. Students were randomly assigned to the following conditions: reviewing a correct explanation, explaining correct or incorrect answers, explaining agreement with answers produced by others, and explaining their own answers. A cohort of students who underwent standard instruction with no intervention and had prepared for formal examination served as reference. The self-explaining cohorts performed better than the reference group, and in one case was the difference statistically significant. Findings suggest that self-explaining activities support students’ conceptual understanding at least as much as instruction. This study contributes evidence for the self-explaining effect and the ICAP hypothesis in a discipline where no evidence is available. Furthermore, it adds to the relatively little work in self-explaining that has explored naturalistic learning environments. This work supports the incorporation of self-explaining activities in the repertoire of instructional practices for General Chemistry.

RateMyProfessors.com (RMP) is the most popular commercial website to evaluate instructors, and houses a wealth of student-generated information in the form of ratings and reviews. This study investigated whether general chemistry students who use RMP were different from other students, and their reasons to use and contribute to the site. A pool of 398 students were surveyed. The survey gathered demographic information, patterns and frequency of use, and information to characterise participants in terms of their learning/grade orientation. Data analysis included descriptive and inferential statistics and the application of mixture models (latent class analysis and latent profile analysis). There were no significant differences between contributors and non-contributors in terms of gender, major, year status, grade point average, course load, previous chemistry grade and learning/grade orientation. Findings for this sample do not support the common assumption that students use RMP to shop for easy instructor...

The work herein presents a laboratory experience designed to foster clear connections between chemistry concepts, experimental measurements, and laboratory techniques. The experience consists of three different experiments to be completed in sequence over several laboratory sessions. First the density of the samples is determined, then the specific heat capacity is measured, and finally the cooling curves are determined for the analytes. The experimental work covers fundamental concepts in chemistry (i.e., density, calorimetry, and first-order kinetics), and guides students to develop an overarching comprehension of the chemical and physical properties of the analytes. The analytes are copper alloys with other metals (i.e., Sn, Zn, and Al) with variable chemical compositions. These alloys are robust (i.e., thermally stable, durable), and allow for the collection of reproducible data under the proposed experimental design, as shown in the work herein. The discussion of student-gathered data and results supports the feasibility of the laboratory experience for its implementation in General Chemistry laboratory programs.

Self-explaining refers to the generation of inferences about causal connections between objects and events. In science, this may be summarised as making sense of how and why actual or hypothetical phenomena take place. Research findings in educational psychology show that implementing activities that elicit self-explaining improves learning in general and specifically enhances authentic learning in the sciences. Research also suggests that self-explaining influences many aspects of cognition, including acquisition of problem-solving skills and conceptual understanding. Although the evidence that links self-explaining and learning is substantial, most of the research has been conducted in experimental settings. There remains a need for research conducted in the context of real college science learning environments. Working to address that need, the larger project in which this work is embedded studied the following: (a) the effect of different self-explaining tasks on self-explaining behaviour and (b) the effect of engaging in different levels of self-explaining on learning chemistry concepts. The present study used a multi-condition, mixed-method approach to categorise student self-explaining behaviours in response to learning tasks. Students were randomly assigned to conditions that included the following: explaining correct and incorrect answers, explaining agreement with another's answer, and explaining one's own answer for others to use. Textual, individual data was gathered in the classroom ecology of a university, large-enrolment general chemistry course. Findings support an association between the self-explaining tasks and students' self-explaining behaviours. Thoughtful design of learning tasks can effectively elicit engagement in sophisticated self-explaining in natural, large-enrolment college chemistry classroom environments.

La generacion y evaluacion de evidencia y explicaciones cientificas es una competencia fundamental que la ensenanza de las ciencias procura cultivar. Como estrategia de aprendizaje, la auto-explicacion se refiere a la generacion de parte de los estudiantes de inferencias causales. Esto en ciencia se relaciona con la construccion de sentido sobre como y por que ocurren los fenomenos. Una cantidad sustancial de investigacion empirica ha mostrado que las actividades que promueven auto-explicacion mejoran el aprendizaje de las ciencias. A pesar del potencial de este tipo de estrategias, comunmente la instruccion universitaria presenta la quimica como retorica de conclusiones, inculcando con ello la idea de que la quimica es una mera coleccion de hechos. La fragil comprension del concepto, la falta de acceso a literatura y la carencia de investigacion relacionada con el campo de la educacion quimica son algunos de los factores que contribuyen al poco uso de las auto-explicaciones. Este articulo pretende contribuir a mejorar la comprension de las auto-explicaciones en educacion quimica y describir el estado actual de la investigacion sobre el tema a nivel de la ensenanza universitaria. Este trabajo se basa en investigacion preliminar que estudia maneras de promover las auto-explicaciones durante la instruccion de quimica y evaluar como diferentes niveles de su uso influyen en el aprendizaje de contenidos de quimica

The room temperature oxidation of carbon nano-onions (CNOs) with ozone was investigated. The reaction was performed under mild conditions and oxidized products with high concentrations of oxygen-containing functional groups were obtained. The reaction products were characterized by Boehm titrations, additional oxidant/reductant treatments, and Raman and DRIFTS FT-IR spectroscopy. Electrochemical studies indicate changes in the surface chemistry of ozonized CNOs (oz-CNOs), exhibiting a larger total surface area and pore structure, which enables efficient accumulation of charge in the oz-CNOs film.

The inflammatory effects of carbon nanoparticles (NPs) are highly disputed. Here it is demonstrated that endotoxin-free preparations of raw carbon nanotubes (CNTs) are very limited in their capacity to promote inflammatory responses in vitro, as well as in vivo. Upon purification and selective oxidation of raw CNTs, a higher dispersibility is achieved in physiological solutions, but this process also enhances their inflammatory activity. In synergy with toll-like receptor (TLR) ligands, CNTs promote NLRP3 inflammasome activation and it is shown for the first time that this property extends to spherical carbon nano-onions (CNOs) of 6 nm in size. In contrast, the benzoic acid functionalization of purified CNTs and CNOs leads to significantly attenuated inflammatory properties. This is evidenced by a reduced secretion of the inflammatory cytokine IL-1β, and a pronounced decrease in the recruitment of neutrophils and monocytes following injection into mice. Collectively, these results reveal that the inflammatory properties of carbon NPs are highly dependent on their physicochemical characteristics and crucially, that chemical surface functionalization allows significant moderation of these properties.

The electrochemical reactions of carboxylic and lactone groups on carbon nano-onions (CNOs) in aqueous solutions result in non-Kolbe products: alcohols, ketones, ethers and epoxides. The anodic/cathodic conversion of ox-CNOs was assessed by Boehm titrations and by Raman and DRIFTS-FTIR (diffuse reflectance infrared Fourier transform spectroscopy). The electrochemical properties of oxidized carbon nano-onions were investigated by cyclic voltammetry in aqueous solutions. The ox-CNOs are electrochemically active as a result of the reduction of the oxygen-containing groups.

With the constant growing complexity of electronic devices, the top-down approach used with silicon based technology is facing both technological and physical challenges. Carbon based nanomaterials are good candidates to be used in the construction of electronic circuitry using a bottom-up approach, because they have semiconductor properties and dimensions within the required physical limit to establish electrical connections. The unique electronic properties of fullerenes for example, have allowed the construction of molecular rectifiers and transistors that can operate with more than two logical states. Carbon nanotubes have shown their potential to be used in the construction of molecular wires and FET transistors that can operate in the THz frequency range. On the other hand, graphene is not only the most promising material for replacing ITO in the construction of transparent electrodes but it has also shown quantum Hall effect and conductance properties that depend on the edges or chemical doping. The purpose of this review is to present recent developments on the utilization carbon nanomaterials in molecular electronics.

The preparation and electrochemical properties of a novel type of composite made of small carbon nano-onions (CNOs) with poly(diallyldimethylammonium chloride) (PDDA) or chitosan (Chit) were investigated by cyclic voltammetry and electrochemical impedance spectroscopy. Composite films on glassy carbon electrode surfaces were deposited by a coating method, applying a drop of solution containing the suspended CNOs and filler, PDDA or Chit. Composites form relatively porous structures on the electrode surface and exhibit typical capacitive behavior, as well as excellent mechanical and electrochemical stability over a wide potential window, from +600 to −600 mV. The capacitance of the films is primarily related to the amount of CNOs incorporated into the layer of the filler. The capacitance ranges between 20 and 30 F g−1 of incorporated CNOs. The composites also show a low relaxation time from resistive to capacitive behavior, therefore indicating that they can operate as capacitors in short time windows.