Whatcom Community College (WCC or Whatcom) is a public community college in Bellingham, Washington, in Whatcom County. Established in 1967, Whatcom has been accredited by the Northwest Commission on Colleges and Universities since 1976.
Potters in the Lake Titicaca basin produced a wide variety of ceramic styles over the last 3000 years. Archaeologists have drawn on this variety across space and time to track processes such as the development of multi-community polities during the Late Formative (200 BC- AD 450), the origins and expansion of Tiwanaku (AD 450-1000), the creation and maintenance of political boundaries during the Late Intermediate period (AD 1000-1450), and the strategies of Inca conquest and consolidation (AD 1450–1534). We report on LA-ICP-MS research into Titicaca ceramics and clays conducted at the Field Museum’s Elemental Analysis Facility, and discuss the first effort at a multi-scalar study of raw material and pottery in the region. Ceramic samples from the northern basin include samples from Taraco, Pukara, and neighboring sites, and speak to the diversity of intraregional potting practices during the Late Formative Period. Ceramic samples from the southern basin span the Middle Formative through the Inca periods, and index local and regional practices over two millennia. After presenting our specific case studies, we touch on how shifting scales of locality impact the chemical signatures explored here, the potential for comparative analyses across the region, and future directions for research collaborations.
Engineering instructors often use physical manipulatives such as foam beams, rolling cylinders, and large representations of axis systems to demonstrate mechanics concepts and help students visualize systems. Additional benefits are possible when manipulatives are in the hands of individual students or small teams of students who can explore concepts at their own pace and focus on their specific points of confusion. Online learning modalities require new strategies to promote spatial visualization and kinesthetic learning. Potential solutions include creating videos of the activities, using CAD models to demonstrate the principles, programming computer simulations, and providing hands-on manipulatives to students for at-home use. This Work-in-Progress paper discusses our experiences with this last strategy in statics courses two western community colleges and a western four-year university where we supplied students with their own hands-on kits. We have previously reported on the successful implementation of a hands-on statics kit consisting of 3D printed components and standard hardware. The kit was originally designed for use by teams of students during class to engage with topics such as vectors, moments, and rigid body equilibrium. With the onset of the COVID-19 pandemic and shift to online instruction, the first author developed a scaled down version of the kit for at-home use by individual students and modified the associated activity worksheets accordingly. For the community college courses, local students picked up their models at the campus bookstore. We also shipped some of the kits to students who were unable to come to campus, including some in other countries. Due to problems with printing and availability of materials, only 18 kits were available for the class of 34 students at the university implementation. Due to this circumstance, students were placed in teams and asked to work together virtually, one student showing the kit to the other student as they worked through the worksheet prompts. One community college instructor took this approach as well for a limited number of international students who did not receive their kits in a timely manner due to shipping problems. Two instructors assigned the hands-on kits as asynchronous learning activities in their respective online courses, with limited guidance on their use. The third used the kits primarily in synchronous online class meetings. We found that students' reaction to the models varied by pilot site and presume that implementation differences contributed to this variation. In all cases, student feedback was less positive than it has been for face-to-face courses that used the models from which the take home kit was adapted. Our main conclusion is that implementation matters. Doing hands-on learning in an online course requires some fundamental rethinking about how the learning is structured and scaffolded.
A growing body of research indicates spatial visualization skills are important to success in many STEM disciplines, including several engineering majors that rely on a foundation in engineering mechanics. Many fundamental mechanics concepts such as free-body diagrams, moments, and vectors are inherently spatial in that application of the concept and related analytical techniques requires visualization and sketching. Visualization may also be important to mechanics learners’ ability to understand and employ common mechanics representations and conventions in communication and problem solving, a skill known as representational competence. In this paper, we present early research on how spatial abilities might factor in to students’ conceptual understanding of vectors and associated representational competence. We administered the Mental Cutting Test (MCT), a common assessment of spatial abilities, in the first and last week of the term. We also administered the Test of Representational Competence with Vectors (TRCV), a targeted assessment of vector concepts and representations, in week one and at mid-term. The vector post-test came after coverage of moments and cross products. We collected this assessment data in statics courses across multiple terms at three different colleges. To understand how spatial skills relate to the development of representational competence, we use a multiple regression model to predict TRCV scores using the pre-class MCT scores as well as other measures of student preparation in the form of grades in prerequisite math and physics coursework. We then extend the analysis to consider both MCT and TRCV scores as predictors for student performance on the Concept Assessment Test in Statics. We find that spatial abilities are a factor in students’ development of representational competence with vectors. We also find that representational competence with vectors likely mediates the importance of spatial abilities to student success in developing broader conceptual understanding in statics. We conclude by discussing implications for mechanics instruction.
Workshop Proposal Description Get started with the web based auto-grading platform for MATLAB assignments named MATLAB Grader. Instant feedback on code accuracy and helpful hints on common programming errors help students learn at their own pace and schedule. As students get real-time feedback on their solutions and code, instructors can focus more time on effective teaching. Learning analytics embedded in the auto-grading platform provide instructors with insight into patterns of student learning. Participants will learn how to set up auto-graded MATLAB assignments by adopting existing problems from a catalog, how to modify problems to better suit their assessment goals, and how to develop their own problems that can be automatically graded. Facilitators will share exemplar auto-graded problems, best practices for problem design and use cases for learning analytics built into the platform . The workshop will also include pedagogical models for incorporating auto-graded assignments into a broader assessment regime with more open-ended assignments. The workshop will start with a brief presentation introducing the MATLAB Grader platform and its potential benefits for student learning. Next, participants will solve a sample homework problem in MATLAB Grader to get familiar with the student experience. Participants will then move to the role of the instructor. Facilitators will guide participants step-by-step as they work on their laptops to setup a "sandbox course" on MATLAB Grader and create an assignment using problems from a catalog. Once everyone has set up a course and an assignment, facilitators will demonstrate how to modify a problem and share their perspectives on best practices for developing new problems. Participants will also gain instructor access to a pre-populated example course they can use to explore the learning analytics features. During the second half of the workshop, participants will work independently or in groups to develop their own custom assignments. Throughout the workshop, facilitators will be present to answer questions, offer technical support and aid discussions. Note that this is similar to a ticketed (but free) workshop planned for the 2019 ASEE National Conference in Tampa, FL. Duration 2 hours. Required Supplies Participants should bring a laptop, preferably with MATLAB installed. A local MATLAB installation is not required to use MATLAB Grader, but does make development work easier. Participants are encouraged to bring an existing MATLAB programming assignment that they would like to adapt to the MATLAB Grader environment.
