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  1. Understanding the thought processes of students as they progress from initial (incorrect) answers toward correct answers is a challenge for instructors, both in this pandemic and beyond. This paper presents a general network visualization learning analytics system that helps instructors to view a sequence of answers input by students in a way that makes student learning progressions apparent. The system allows instructors to study individual and group learning at various levels of granularity. The paper illustrates how the visualization system is employed to analyze student responses collected through an intervention. The intervention is BeginToReason, an online tool that helps students learn and use symbolic reasoning-reasoning about code behavior through abstract values instead of concrete inputs. The specific focus is analysis of tool-collected student responses as they perform reasoning activities on code involving conditional statements. Student learning is analyzed using the visualization system and a post-test. Visual analytics highlights include instances where students producing one set of incorrect answers initially perform better than a different set and instances where student thought processes do not cluster well. Post-test data analysis provides a measure of student ability to apply what they have learned and their holistic understanding. 
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  2. Online learning has become desirable for many students. In the U.S., more than one-third of all enrolled students participate in at least one online course [13]. The most effective online learning environments allow students to work at their own pace, from any location, at any time, and to receive automated feedback. In light of these benefits and the likely protracted impact of the current public health crisis, the trend toward online learning is likely to increase. 
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  3. null (Ed.)
    To develop code that meets its specification and is verifiably correct, such as in a software engineering course, students must be able to understand formal contracts and annotate their code with assertions such as loop invariants. To assist in developing suitable instructor and automated tool interventions, this research aims to go beyond simple pre- and post-conditions and gain insight into student learning of loop invariants involving objects. As students develop suitable loop invariants for given code with the aid of an online system backed by a verification engine, each student attempt, either correct or incorrect, was collected and analyzed automatically, and catalogued using an iterative process to capture common difficulties. Students were also asked to explain their thought process in arriving at their answer for each submission. The collected explanations were analyzed manually and found to be useful to assess their level of understanding as well as to extract actionable information for instructors and automated tutoring systems. Qualitative conclusions include the impact of the medium. 
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  4. Object-based development using design-by-contract (DbC) is broadly taught and practiced. Students must be able to read and write symbolic DbC assertions that are sufficiently precise and be able to use these assertions to trace program code. This paper summarizes the results of using an automated tool to pinpoint fine-grain difficulties students face in learning to symbolically trace code involving objects. The pilots were conducted in an undergraduate software engineering course. Quantitative results show that data collected by the tool can help to identify and classify learning obstacles. Qualitative findings help validate student misunderstandings underlying these difficulties. Analysis of exam questions helps understand the persistence of student learning to read and write simple assertions about code behavior. Together, these results provide directions for intervention. 
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  5. In this BoF we discuss the tenets of culturally responsive computer science and how teachers, professors and providers of professional development can include culturally responsive perspectives in their classes. In contrast to other academic fields, which typically include rigid curricular tracks ostensibly based on academic performance, talent, or ability that pose structural barriers to access to rigorous academic instruction for underrepresented students, the field of computer science education is explicitly focused on broadening participation, as evidenced by the SIGCSE community's consistent emphasis on equitable representation. Culturally responsive computing (CRC) is founded on culturally responsive teaching (CRT) and on CRT's three tenets: asset building (in contrast to deficit approaches), reflection, and connectedness. CRC frames these tenets for the specifics of computing education. CRC's tenet that all students are capable of digital innovation should drive teachers' interactions and relationships with students. CRC also requires that teachers be continually reflective about their privilege and constraints and how those are connected with our worldviews. This topic is significant because teachers must be connected to their students in non-traditional ways that prize diversity as an asset to innovation. The participants are expected to include professors, lecturers, high school teachers and industry experts who are interested in employing culturally responsive computing approaches in their own teaching and professional development activities. A major goal of the BoF is to establish connections among the participants to promote the sharing of resources and best practices. 
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  6. You develop a plan for testing the prototype for a new learning strategy in your class or across institutions. How can you ensure that your plan is clearly understood by reviewers and the managing NSF program officer? What goes through the reviewer's mind once a proposal is submitted? What prompts one proposal to be recommended for funding but another declined? Close examination of the panel review process can inform proposal writing and ensure that reviewers will understand an idea, identify its merit, and value a PI's vision of how the work will broaden participation in STEM education. This workshop steps through the NSF proposal review process from submission of proposal to award or decline, touching on NSF intellectual merit and broader impact criteria, mapping the project pipeline to appropriate evaluation. Participants gain insight into writing a good review and improving one's own proposal writing. For further information and travel support see: https://people.cs.clemson.edu/~etkraem/UPCSEd/. Laptops recommended. 
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  7. You develop the prototype for a new learning strategy, and want to test it in class or across institutions. You identify an NSF program that supports proposals for the idea, and then what? What goes through the minds of reviewers once a proposal is submitted? What prompts one proposal to be recommended for funding while another is declined? Close examination of the panel review process can inform proposal writing and ensure that reviewers will understand a PI’s idea, identify its merit, and value a PI’s vision of how the work will broaden participation in STEM education. This workshop steps through the NSF proposal review process from submission of a proposal to award or decline, touching on elements of a good review, NSF intellectual merit and broader impact criteria, elements of a good proposal, and volunteering to review proposals. Participants gain insight into writing a good review and improving one’s own proposal writing. The interactive workshop leads participants through each topic by introducing related issues, engaging participants in group exercises designed to explore and share their understanding of the issues, and providing “expert” opinion on these issues. Examples include funded and non-funded projects and a Top Ten List of Do’s and Don’ts. One night of lodging and workshop registration fees will be covered by an NSF grant for the first 25 participants who submit their own one-page proposal summary to the organizers one month prior to the workshop and participate fully in the workshop. For further information see - https://people.cs.clemson.edu/~etkraem/UPCSEd/ 
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