This work-in-progress paper is part of a larger research project that aims to study how a digital game-based math program affects middle school students' perceptions of their math learning. We present preliminary results related to how a story-based game environment supports students' perceived math learning experience and affective outcomes. We first compare survey outcomes between treatment and business-as-usual control groups. We then analyze various in-game activity metrics to explore how students' gameplay behaviors relate to these perceptions and affective outcomes. Preliminary results suggest that embedding math learning in a narrative-supported context may shape middle school students' engagement with and perceived understanding of math learning. This work also offers a novel method for analyzing the impacts of digital game-based math programs using students' gameplay behavior metrics.

As demand for data scientists has increased to inform decision-making across multiple fields of societal importance, postsecondary institutions have expanded data science course offerings. Despite such growth, educators struggle to teach students all the skills central to data science. They focus on programming and statistical tools and lack time for mentoring students in data storytelling. This working paper reviewed literature and interviewed experts to model the domain knowledge of data storytelling to inform the design of intelligent technology to support data storytelling instruction at scale. The paper closes with a recommendation of two ways that artificial intelligence tools can support the development of students' data storytelling knowledge and skills: ''direct'' feedback to students on routine data science tasks and ''facilitated'' summaries of students' data story progress to inform instructors' feedback. We intend to apply these insights to the design of intelligent coaching in an online platform to support the development of storytelling competency at scale.

The "Computer Science for All" initiative advocates for universal access to computer science (CS) instruction. A key strategy toward this end has been to establish CS content standards outlining what all students should have the opportunity to learn. Standards can support curriculum quality and access to quality CS instruction, but only if they are used to inform curriculum design and instructional practice. Professional learning offered to teachers of CS has typically focused on learning to implement a specific curriculum, rather than deepening understanding of CS concepts. We set out to develop a set of educative resources, formative assessment tools and teacher professional development (PD) sessions to support middle school CS teachers' knowledge of CS standards and standards-aligned formative assessment literacy. Our PD and associated resources focus on five CS standards in the Algorithm and Programming strand and are meant to support teachers using any CS curriculum or programming language. In this experience report, we share what we learned from implementing our standards-based PD with four middle school CS teachers. Teachers initially perceived standards as irrelevant to their teaching but they came to appreciate how a deeper understanding of CS concepts could enhance their instructional practice. Analysis of PD observations and exit surveys, teacher interviews, and teacher responses to a survey assessing CS pedagogical content knowledge demonstrated the complexity of using content standards as a driver of high-quality CS instruction at the middle school level, and reinforced our position that more standards-focused PD is needed.

Self-regulated learning (SRL) is critical for student success in online postsecondary education. Many technology-based interventions have been studied to improve SRL skills, but few were situated in broad-access institutions that disproportionately serve systemically marginalized student populations in STEM fields. This study presents preliminary findings from a rapid-cycle evaluation that tests two technology-supported instructional strategies (videos and prompts) designed to improve SRL in online learning. Using fine-grained clickstream data from 141 students across ten sections of five courses taught at a minority-serving community college, we generate measures of SRL behavior and correlate them with students' exposure to tested strategies. Our results indicate modestly positive relationships between both videos and prompts and SRL behavior. In addition, prompts are more strongly correlated with SRL behavior for first-generation and female students than for their peers. These initial findings reveal the promise and complexity of implementing effective and equitable technology-supported interventions to develop SRL skills and mindsets among diverse student populations in online STEM education.

The development of the CS content standards underscores the importance of curricula aligned with the standards, ensuring equitable coverage of CS concepts for all students. Because standards are broad, we emphasize the need for CS curricula to specify not only the standards they align with but also which aspects of the standards they align with and how. We map one common middle school CS curriculum to a few standards to demonstrate this need.

Our work-in-progress paper explores students' role-changing patterns while working on science tasks in small groups. Grounded on the Collaboration Conceptual Model, we examined how members in 15 middle school student groups changed their roles throughout the entire collaborative activities. We annotated students' role changes at a one-minute segment, as well as the overall group collaboration quality at the individual task level for each student group. Our analytical approach involved hierarchical cluster analysis and non-parametric statistical tests to identify the relationships between students' role-changing patterns and collaboration outcomes. Preliminary results identified two distinct group types that showed different patterns of role changes and manifested different group collaboration qualities and performances. We discuss how this work is of interest to the [email protected] community in promoting effective collaboration at scale in authentic classroom settings.

The rapid expansion of K-12 CS education has made it critical to support CS teachers, many of whom are new to teaching CS, with the necessary resources and training to strengthen their understanding of CS concepts and how to effectively teach CS. CS teachers are often tasked with teaching different curricula using different programming languages in different grades or during different school years, and tend to receive different professional development (PD) for each curriculum they are required to teach. This often leads to a lack of deep understanding of the underlying CS concepts and how different curricula address the same concepts in different ways. Empowering teachers to develop a deep understanding of CS standards, and use formative assessments to recognize common student challenges associated with the standards, will enable teachers to provide more effective CS instruction, irrespective of the curriculum and/or programming language they are tasked with using. This position paper advocates supporting CS teacher professional learning by supplementing existing curriculum-specific teacher PD with standards-aligned PD that focuses on teachers' conceptual understanding of CS standards and ability to adapt instruction based on student understanding of concepts underlying the CS standards. We share concrete examples of how to design standards-aligned educative resources and instructionally supportive tools that promote teachers' understanding of CS standards and common student challenges and develop teachers' formative assessment literacy, all essential components of CS pedagogical content knowledge.