The process of using Learning Analytics (LA) to improve teaching works from the assumption that data should be readily shared between stakeholders in an educational organization. However, the design of LA tools often does not account for considerations such as data privacy, transparency and trust among stakeholders. Research in human-centered design of LA does attend to these questions, specifically with a focus on including direct input from K-12 educators. In this paper, we present a series of design studies to articulate and refine conjectures about how privacy and transparency might influence better trust-building and data sharing within four school districts in the United States. By presenting the development of four sequential prototypes, our findings illuminate the tensions between designing for existing norms versus potentially challenging these norms by promoting meaningful discussions around the use of data. We conclude with a discussion about practical and methodological implications of our work to the LA community.

Educators use a wide variety of data to inform their practices. Examples of these data include forms of information that are commonplace in schools, such as student work and paper-based artifacts. One limitation in these situations is that there are less efficient ways to process such everyday varieties of information into analytics that are more usable and practical for educators. To explore how to address this constraint, we describe two sets of design experiments that utilize crowdsourced tasks for scoring open-ended assessments. Developing crowdsourced systems and their resulting analytics introduced a variety of challenges, such as attending to the expertise and learning of the crowd. In this paper, we describe the potential efficacy of design decisions such as screening the crowd, providing multimedia instruction, and asking the crowd to explain their answers. We also explore the potential of crowdsourcing as a learning opportunity for those participating in the collective tasks. Our work offers key design implications for leveraging crowdsourcing to process educational data in ways that are relevant to educators, while offering learning experiences for the crowd.

The isogeny-based scheme CSIDH is a promising candidate for quantum-resistant static-static key exchanges with very small public keys, but is inherently difficult to implement in constant time. In the current literature, there are two directions for constant-time implementations: algorithms containing dummy computations and dummy-free algorithms. While the dummy-free implementations come with a 2x slowdown, they offer by design more resistance against fault attacks. In this work, we evaluate how practical fault injection attacks are on the constant-time implementations containing dummy calculations. We present three different fault attacker models. We evaluate our fault models both in simulations and in practical attacks. We then present novel countermeasures to protect the dummy isogeny computations against fault injections. The implemented countermeasures result in an overhead of 7% on the Cortex-M4 target, falling well short of the 2x slowdown for dummy-less variants.

Crowdsourcing has shown promise in education domains. For example, researchers have leveraged the wisdom of the crowd to process grading in MOOCs and develop learning resources. An untapped domain is harnessing the crowd to systematically process educational data in classrooms -- data that provide key instructional insights but take time to process, such as paper-based assessments. In this paper, we describe an experiment of a crowdsourcing task to effectively process classroom-based data and explore the potential of crowdsourcing as a learning opportunity for the crowdworkers. We discuss implications for designing crowdsourced assessment tasks to yield both high quality output and enriching learning experiences for those involved in the crowdsourcing task.

School mission statements promising to transform students into leaders have become commonplace. Yet there appears to be a disconnect between educational practices and their application to real challenges pertaining to students' communities and to society as a whole. This gap results in a low sense of agency and presents an opportunity to develop tools that foster informed civic engagement and participation.

Sociocultural theories of learning regard oral storytelling as a fundamental step towards literacy development. Collaborative play can lead to richer and sustained stories among children of young age. We describe an interactive learning environment called The Conference of the Birds (CoB). By allowing two users to interact with the interface at the same time, the CoB allows children separated by physical or cultural distances to collaborate by creating narratives together. Through the CoB, children connect, cooperate and create joint stories, fostering the development of literacy, as well as collaboration and authorship skills. In this paper we describe the principles, theories and design decisions that supported the creation of the CoB, and briefly discuss how kids can collaboratively create stories in a digital environment.

GridFTP, included in the Globus Toolkit, is a high-performance, reliable and secure data transfer protocol used in Grid Computing. SETA, an acronym in Portuguese for Specialized File Transfer Service, is a web application developed using the Globus Java API [1], called jGlobus, and was inspired by Globus Online (GO) [2]. This tool was driven by the challenge of transferring huge data volumes between Petrobras and ANP (Brazilian National Petroleum Agency) and due to security policies that prevent the use of Globus Online. SETA provides several features like integrity checking and automatic retransmission of only corrupted blocks, transfer resume in case of data connection failure, TCP parallel data connections and scheduled transfers. SETA's advantages against traditional solutions are shown in this work.