Our approach to general chemistry laboratory for engineers in our NSF-funded IUSE project (DUE-1625378) involves the use of design challenges (DCs), an innovation that uses authentic context and practice to transform traditional tasks. These challenges are scaled-down engineering problems related to the NAE Grand Challenges that engage students in collaborative, team-based problem solving via the modeling process. With features aligned with professional engineering practice, DCs are hypothesized to support student motivation for the task as well as for the profession. As an evaluation of our curriculum design, we use Expectancy Value Theory to test our hypotheses by investigating the association between students' value beliefs and confidence with experiences of the DC and student characteristics (i.e., gender and URM status). Using linear regression analysis, we reveal that students find value in completing a DC when they feel like an engineer, are satisfied, perceive the task as collaborative, are provided help by TAs and the tasks are not too difficult. Students report feeling confident under similar conditions. We highlight that although female and URM students feel less confident, their perceptions of collaboration and sense of belongingness to engineering supported their confidence. Given the lack of representation for certain groups in engineering, this study suggests that specially designed curriculum interventions can afford a more inclusive learning experience.

The radical global shift to online teaching that resulted from the initial lockdown of the COVID-19 pandemic forced many science educators into the predicament of translating courses, including teaching laboratories, that were based upon face-to-face or practical goals and conventions into ones that could be delivered online. We used this phenomenon at the scale of a research-intensive, land-grant public institution to understand the various ways that the switch was experienced by a large cohort of 702 undergraduate students taking General Chemistry Laboratory. Data was collected over 3 weeks with identical surveys involving four prompts for open-ended responses. Analysis involved sequential explanatory mixed methods where topic modeling, a machine learning technique, was used to identify 21 topics. As categories of experience, these topics were defined and further delineated into 52 dimensions by inductive coding with constant comparison. Reported strengths and positive implications tie predominantly to the topics of Time Management Across a Lab Activity and a Critique of Instruction. Consistent with other reports of teaching and learning during the pandemic, participants perceived Availability of the Teaching Assistant for Help as a positive implication. Perceptions of weakness were most associated with Having to Work Individually, the Hands On Experience, a Critique of Instruction, and Learning by Doing. Hands on Experience, which was interpreted as the lack thereof, was the only topic made up nearly entirely of weaknesses and negative implications. The topic of Learning by Doing was the topic of greatest occurrence, but was equally indicated as strengths, positive implication, weakness, and negative implication. Ramifications are drawn from the weaknesses indicated by students who identified as members of an underrepresented ethnic minority. The results serve as a reminder that the student experience must be the primary consideration for any educational endeavor and needs to continue as a principal point of emphasis for research and development for online science environments.

Use of modeling as a learning strategy in introductory science courses could serve to support the persistence of all students, including those who identify with a traditionally underrepresented ethnic minority (URM). If students find inherent value in working on modeling-type problems then this authentic practice would aid in transforming personal interest into longer-term career-related beliefs, improving persistence. Yet research supporting this conjecture is negligible. Using Expectancy Value Theory, we compared the motivational beliefs of first-year engineering majors for different chemistry problem types and described a predictive model for modeling-type problems. We hypothesized that students’ task value for different problem types would be influenced by gender, previous experience, and URM status and that previous or ongoing experiences would serve as a precursor for positive value judgments. The research design involved a correlational, single-case method. Data were analyzed using a mixed model analysis of variance and multiple linear regression. Overall, participants found modeling-type problems interesting and useful. However, our regression model revealed that URM status was a significant negative predictor of task value where these students were uninterested in modeling-type problems. However, an experience with a special modeling laboratory course completely changed the interest of URM students, suggesting the potential for modeling as an equitable instructional strategy for building persistence.

Persistence in academic and career settings is a major issue for students enrolled in science and engineering programs, particularly those who identify as female or as members of certain underrepresented ethnic minorities (URM). This exploratory study determined the degree to which organizational justice has explanatory power in complimenting the Mediation Model of Research Experiences (MMRE) in a career-forward laboratory curriculum context. A career-forward approach to curriculum targets persistence by basing the student experience on the content, context, and practices of the targeted career field in developmentally appropriate ways. Participants were 157 undergraduate students taking General Chemistry Laboratory for Engineering Majors. Confirmatory factor analysis of survey responses indicated an acceptable fit for the established four-factor model of organizational justice (χ2(164, n = 157) = 378.447, p = 0.000, IFI = 0.935, CFI = 0.934, NFI = 0.891 RMSEA = 0.092). Bivariate correlations among variables from the two frameworks show that the experience of URM students is different than that of their non-URM peers. Notably, identity as an engineer was more strongly correlated to aspects of organizational justice, and justice played a role in students’ views on teamwork. This supports a prior hypothesis that the negative relationship between teamwork self-efficacy and commitment to an engineering career for URM participants may be related to issues of marginalization within their groups. Evaluation of a combined MMRE organizational justice model with future studies is merited, especially for contexts involving the use of teamwork and/or student collaboration.

This half-day workshop will engage participants in understanding how engineering design practices can be brought into core content classes to support conceptual model development in students as part of the model development cycle. Participants will have a chance to map this learning using frameworks developed by the facilitators.

Our career-forward approach to general chemistry laboratory for engineers involves the use of design challenges (DCs), an innovation that employs authentic professional context and practice to transform traditional tasks into developmentally appropriate career experiences. These challenges are scaled-down engineering problems related to the US National Academy of Engineering’s Grand Challenges that engage students in collaborative problem solving via the modeling process. With task features aligned with professional engineering practice, DCs are hypothesized to support student motivation for the task as well as for the profession. As an evaluation of our curriculum design process, we use expectancy–value theory to test our hypotheses by investigating the association between students’ task value beliefs and self-confidence with their user experience, gender and URM status. Using stepwise multiple regression analysis, the results reveal that students find value in completing a DC (F(5,2430) = 534.96, p < .001) and are self-confident (F(8,2427) = 154.86, p < .001) when they feel like an engineer, are satisfied, perceive collaboration, are provided help from a teaching assistant, and the tasks are not too difficult. We highlight that although female and URM students felt less self-confidence in completing a DC, these feelings were moderated by their perceptions of feeling like an engineer and collaboration in the learning process (F(10,2425) = 127.06, p < .001). When female students felt like they were engineers (gender x feel like an engineer), their self-confidence increased (β = .288) and when URM students perceived tasks as collaborative (URM status x collaboration), their self-confidence increased (β = .302). Given the lack of representation for certain groups in engineering, this study suggests that providing an opportunity for collaboration and promoting a sense of professional identity afford a more inclusive learning experience.

The ChANgE Chem (NSF-1625378) utilizes Cognitive Apprenticeship as a theoretical framework for integrating engineering practices into a freshman chemistry laboratory course for engineering majors with the goal of better supporting all students to degree completion. The activities are structured as three-week Design Challenges (DCs) where students use chemistry knowledge to solve authentic engineering problems. This study explores the experiences of students taking the course in-sequence (i.e. fall of freshman year) versus those taking it out-of-sequence (i.e. spring), where out-of-sequence students have been identified as at higher academic risk. Data was collected through audio and video recordings and post-laboratory surveys. Video recordings were coded using a protocol to identify type and frequency of issues and questions asked. The post-laboratory surveys obtained information concerning students’ perception of task difficulty and their feelings of being like an engineer. The data demonstrated that while out-of-sequence students ask more questions and experience more issues, they did feel like successful engineers and did not find the tasks too difficult. Therefore, additional curriculum supports as well as assistance from a Teaching Assistant are needed in order to positively influence the persistence of out-of-sequence students in spite of the challenges they may face.

Kent Crippen is a Professor of STEM education in the School of Teaching and Learning at the University of Florida and a Fellow of the American Association for the Advancement of Science. His research involves the design, development, and evaluation of STEM cyberlearning environments as well as scientistteacher forms of professional development. Operating from a design-based research perspective, this work focuses on using innovative, iterative and theoretically grounded design for the dual purpose of addressing contemporary, complex, in situ learning problems while concurrently generating new theoretical insight related to the process of learning and the relationships among the people, tools and context of the problem space.

The isolation, structure determination, and biological activities of a new linear pentapeptide, caldoramide (5), from the marine cyanobacterium Caldora penicillata from Florida are described. Caldoramide (5) has structural similarities to belamide A (4), dolastatin 10 (1), and dolastatin 15 (2). We profiled caldoramide against parental HCT116 colorectal cancer cells and isogenic cells lacking oncogenic KRAS or hypoxia-inducible factors 1α (HIF-1α) and 2α (HIF-2α). Caldoramide (5) showed differential cytotoxicity for cells containing both oncogenic KRAS and HIF over the corresponding knockout cells. LCMS dereplication indicated the presence of caldoramide (5) in a subset of C. penicillata samples.

A motivation of our research is to make inroads in the daunting task of chemical analysis of the brain's composition and temporal changes. We recently introduced a new soft ionization process for use in mass spectrometry (MS). This new technique called laserspray ionization (LSI) has advantages of speed of analysis, high spatial resolution for imaging, mass range extension, and improved fragmentation common with multiply charged ions. We have interfaced LSI with ion mobility spectrometry (IMS) for separation of gas phase ions from mixtures by charge and cross-section (size/shape) and, in a second dimension, with high resolving power by mass-to-charge permitting powerful deconvolution of sample complexity, even with identical masses (isomers), directly from surfaces. LSI interfaced with mass spectrometers having electron transfer dissociation (ETD) capabilities produces similar backbone fragmentation as ESI as demonstrated for the protein ubiquitin as well as for peptides directly from tissue. We have extended LSI to vacuum mass spectrometers and determined that ionization occurs with vacuum or thermal assistance without the need of voltage or lasers. LSI imaging of mouse brain tissue sections is demonstrated to determine the location of gadolinium-based complexes synthesized for use as magnetic resonance imaging (MRI) agents. Conventional MALDI failed. The LSI images are complemented by MRI and microscopy results of the same mouse brain and, additionally, provide a molecular view of the endogenous chemical composition. MS images of mouse brain tissue from a clozapine treated mouse are compared with results obtained for endogenous lipids, peptides and small proteins in the same tissue. Protocols are being developed for high spatial resolution LSI imaging.

The laboratory environment can offer valuable first-person experiences that complement and extend the process of learning from other parts of a course. To this end, we are developing a unique laboratory curriculum for undergraduate general chemistry for engineers that more deeply engage students in authentic science and engineering practice. Our NSF-funded Improving Undergraduate STEM Education (IUSE) project involves curriculum reform for improving the experience of freshman engineering students taking general chemistry involves a series of Design Challenges, which are problem-based laboratory activities based upon the NAE Grand Challenges for Engineering. These Design Challenges situate chemistry concepts and skills in an authentic engineering context with supports for the engineering design process. For engineering majors, contextualizing the learning of chemistry in such a way is theorized to strengthen the connection between the domain knowledge of chemistry and its application in everyday work, which enhances interest, efficacy and learning. The user-centered design process enables us to keep our focus on the involvement of our target audience in all stages of development. In this paper, we present results from usability testing to illustrate our iterative evidence-based development process and offer results of an initial pilot study from across one semester of student use. For usability, data sources include video-recorded observations, field notes, student artifacts. For the pilot study, the assessed outcomes include chemistry content knowledge, self-efficacy, metacognition, and motivational variables. Both qualitative and quantitative analyses are used to address the research questions. Plans for additional re-design of the model and further study are discussed.