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With the emergence of self-tracking devices that collect and produce real-time personal data, it is becoming increasingly necessary to innovate data literacy frameworks and student curricula to address new competencies in data handling, visualization, and use. We examine the evolution of data literacy frameworks across the past 7 years, specifically focusing on the inclusion of self-data competencies. We analyzed existing data literacy frameworks to identify common phases of data engagement. A scoping review of published data literacy frameworks was conducted, and 23 studies were included for analysis. Results from this scoping review demonstrate the existence of at least eight sequential phases of data engagement to develop data literacy. Two of these phases address personal or self-data competencies. We then describe a curriculum that addresses these eight phases of data engagement by pairing biometric devices with online tools and educational materials to scaffold self-data knowledge, skills, and attitudes. Based on this, we conclude with the need to propose holistic data literacy education programmes, considering the curriculum as a model to guide similar materials aimed at fostering emerging data competencies. 

As a creative endeavor, scientific research requires inspiration, innovation, exploration, and divergent thinking. Yet, in K-12 settings, it is often viewed as rigid and formulaic. MindHive is a web-based platform designed to facilitate student-teacher-scientist partnerships in research on human behavior. Features support research phases (e.g., question finding, study design, peer review, iteration), and their creative dimensions, including exploration, expressiveness, collaboration, and enjoyment. Interviews with teachers and students who used MindHive show how learners describe their experiences as creative agents. This work illustrates how educational technologies can broaden STEM participation by being authentic to methodical and creative aspects of STEM research. 

Citizen science programs offer opportunities for K-12 students to engage in authentic science inquiry. However, these programs often fall short of including learners as agents in the entire process, and thus contrast with the growing open science movement within scientific communities. Notably, study ideation and peer review, which are central to the making of science, are typically reserved for professional scientists. This study describes the implementation of an open science curriculum that engages high school students in a full cycle of scientific inquiry. We explored the focus and quality of students’ study designs and peer reviews, and their perceptions of open science based on their participation in the program. Specifically, we implemented a human brain and behavior citizen science unit in 6 classrooms across 3 high schools. After learning about open science and citizen science, students (N = 104) participated in scientist-initiated research studies, and then collaboratively proposed their own studies to investigate personally interesting questions about human behavior and the brain. Students then peer reviewed proposals of students from other schools. Based on a qualitative and quantitative analysis of students’ artifacts created in-unit and on a pre and posttest, we describe their interests, abilities, and self-reported experiences with study design and peer review. Our findings suggest that participation in open science in a human brain and behavior research context can engage students with critical aspects of experiment design, as well as with issues that are unique to human subjects research, such as research ethics. Meanwhile, the quality of students’ study designs and reviews changed in notable, but mixed, ways: While students improved in justifying the importance of research studies, they did not improve in their abilities to align methods to their research questions. In terms of peer review, students generally reported that their peers' feedback was helpful, but our analysis showed that student reviewers struggled to articulate concrete recommendations for improvement. In light of these findings, we discuss the need for curricula that support the development of research and review abilities by building on students’ interests, while also guiding students in transferring these abilities across a range of research foci. 

We explored the COVID-19 pandemic as a context for learning about the role of science in a global health crisis. In spring 2020, at the beginning of the first pandemic-related lockdown, we worked with a high school teacher to design and implement a unit on human brain and behavior science. The unit guided her 17 students in creating studies that explored personally relevant questions about the pandemic to contribute to a citizen science platform. Pre-/postsurveys, student artifacts, and student and teacher interviews showed increases in students’ fascination with science—a driver of engagement and career preference—and sense of agency as citizen scientists. Students approached science as a tool for addressing their pandemic-related concerns but were hampered by the challenges of remote schooling. These findings highlight both the opportunities of learning from a global crisis, and the need to consider how that crisis is still affecting learners. 

Abstract The bulk of social neuroscience takes a ‘stimulus-brain’ approach, typically comparing brain responses to different types of social stimuli, but most of the time in the absence of direct social interaction. Over the last two decades, a growing number of researchers have adopted a ‘brain-to-brain’ approach, exploring similarities between brain patterns across participants as a novel way to gain insight into the social brain. This methodological shift has facilitated the introduction of naturalistic social stimuli into the study design (e.g. movies) and, crucially, has spurred the development of new tools to directly study social interaction, both in controlled experimental settings and in more ecologically valid environments. Specifically, ‘hyperscanning’ setups, which allow the simultaneous recording of brain activity from two or more individuals during social tasks, has gained popularity in recent years. However, currently, there is no agreed-upon approach to carry out such ‘inter-brain connectivity analysis’, resulting in a scattered landscape of analysis techniques. To accommodate a growing demand to standardize analysis approaches in this fast-growing research field, we have developed Hyperscanning Python Pipeline, a comprehensive and easy open-source software package that allows (social) neuroscientists to carry-out and to interpret inter-brain connectivity analyses.