Reflection and metacognition are central to the creative user experience. However, most HCI research on reflection focuses on clear, task-oriented goals such as to reflect on personal data or pedagogical outcomes. This contrasts with the open-ended and challenging to articulate goals of creative user experiences. For the first time, this workshop brings together interdisciplinary researchers, designers, educators, and artists across HCI, Cognitive Science, Design, AI, Learning Sciences, and Digital Art to examine reflection in creative interaction. The workshop will discuss themes, drawn from earlier discussions with HCI researchers and artists, on: how best to capture reflection in creative contexts, how to leverage the arts to support reflection for ethical change, and how to design creative AI that enhances – not hinders – critical thinking. By bringing interdisciplinary perspectives on reflection into discussion, the workshop will develop a guiding taxonomy for reflection in creative interaction to inform future creative practice and tool development.

Curiosity is the inherent human drive to learn and understand the unknown. This poster presents the design and implementation of nine Curiosity Portals: intentionally designed invitations in everyday spaces that spark curiosity through hands-on, sensory-rich experiences. We provide empirical evidence of how designers operationalize attributes from the existing Curiosity Portal framework into practice. Eleven graduate students studying design participated in a course where they created curiosity portals, and temporarily deployed them in diverse public settings. We illustrate how designers embodied their curiosities through the artifacts they created from early ideation to implementation to deployment. Our findings reveal four cross-cutting implementation strategies designers employed to operationalize curiosity portals. We also identified critical tensions designers must navigate in real-world situations. These findings expand the curiosity portal framework from a designer-centered perspective, providing practical insights on how to invite curiosity through physical design in everyday spaces.

Human-Computer Interaction (HCI) and education researchers have applied Augmented Reality (AR) to support spatial thinking in K-12 education. However, fewer studies support spatial thinking through spatial exploration. Room-scale AR, a recent technology development, brings new opportunities not yet researched. We developed NetLogo AR, an AR authoring toolkit, that allows children to play with, design, and create room-scale AR experiences that combine AR with computational models. To acquire a deeper and more nuanced understanding of children’s interactions with this new technology, we conducted eight-week participatory design sessions with seven children aged 11-13. We analyzed 48 hours of video data, interview transcripts, and design artifacts. Children were enthusiastic and engaged in spatial thinking activities. We affirmed room-scale AR’s role in spatial exploration by comparing it with other supported modalities. Building on existing studies, we propose a new AR design framework around spatial movement and exploration that could help inform design decisions.

Although enrollments in introductory computing courses are rising, many students still struggle to learn programming. Previous research has found that students’ perceptions of the programming process may be one factor that contributes to this problem. Students often assess their own programming abilities overly harshly when experiencing low-level programming moments that are considered normal and expected parts of learning to program. For example, many students think they are doing poorly if they need to stop coding to plan. Research has also shown that students who self-assess negatively in these moments tend to have lower self-efficacy, defined as one’s belief in their ability to achieve a particular outcome. In turn, students with lower self-efficacy tend not to persist in their computing studies. While the criteria that students use to assess their ability have been studied extensively, we have a limited understanding of the origins of these criteria and students’ reasons for adopting them. To address this gap, we conducted a total of 36 interviews with seven introductory computer science students throughout an academic quarter. In each interview, we asked students to think aloud and explain their reasoning while filling out a self-assessment survey. Through a qualitative analysis of the data, we identified the most common reasons students gave for negatively assessing their performance, including having high expectations for their abilities and feeling like they cannot overcome a struggle. We also identified common reasons why students do not negatively assess their ability in these moments, including believing an experience is “normal” or feeling like they can learn from or overcome a struggle. These findings contribute valuable new knowledge about the underpinnings of students’ self-assessments of ability, and suggest that interventions that explicitly emphasize best practices and normalize struggles in the programming learning process are needed to increase student self-efficacy and persistence in computing.

Introductory computer science for non-majors, often referred to as CS0, is a course that is designed to be more accessible and less intimidating than CS1, with the goal of alleviating barriers and fears associated with learning computer science (CS). However, despite this intention, many students still struggle in CS0 and these courses do not always successfully prepare students for future CS learning experiences. In this paper, we study the experiences of CS0 students with a particular focus on the intersection of their metacognition, affect, and behaviors. To study students’ daily learning experiences, we collected data from 20 participants who completed structured daily diaries and retrospective interviews over the course of a single homework assignment. Through a thematic analysis of the diaries and interviews, we identified three distinct patterns of engagement that highlight the importance of metacognitive knowledge of strategies, or a students’ understanding of when, why, and how to effectively use regulation and disciplinary strategies while working on tasks. The three patterns of engagement include: (1) avoidance behaviors resulting from negative emotions, negative judgements, and a lack of metacognitive knowledge of strategies, (2) persistence or re-engagement behaviors despite negative emotions and judgements aided by metacognitive knowledge of strategies, and (3) persistence behaviors with evidence that metacognitive knowledge of strategies prevented students from forming negative judgements in the first place. We contribute an initial model of the interplay of metacognition, affect, and behaviors in CS learning, showing the role of metacognitive knowledge of strategies in helping students persist in the face of struggle. In our discussion, we advocate for explicit interventions that support students in developing metacognitive knowledge of strategies while also supporting their sometimes challenging emotional experiences.

Robot technologies have been introduced to computing education to engage learners. This study introduces the concept of co-creation with a robot agent into culturally-responsive computing (CRC). Co-creation with computer agents has previously focused on creating external artifacts. Our work differs by making the robot agent itself the co-created product. Through participatory design activities, we positioned adolescent girls and an agentic social robot as co-creators of the robot’s identity. Taking a thematic analysis approach, we examined how girls embody the role of creator and co-creator in this space. We identified themes surrounding who has the power to make decisions, what decisions are made, and how to maintain social relationship. Our findings suggest that co-creation with robot technology is a promising implementation vehicle for realizing CRC.

Traditional methods of learning conditional statements follow lecture-based instruction, which focuses on teaching concepts and definitions. While this traditional method of instruction is the dominant teaching style in Computer Science (CS) education, it has also been identified to be one of the least effective methods for teaching and engaging students [3]. The existing limitations of traditional methods include low engagement, disconnection from the real-world applications, a lack of valuable artifacts to evaluate the learning outcomes. To improve the learning methods of conditional statements stated above, we asked the following two questions: RQ1: Can storytelling logic, an early development logic, be a viable tool that translates the concept of condition followed by a consequence to the logic of conditional statements? RQ2: In what approaches can we apply the isomorphic relationship between the two logics to the learning of conditional statements?