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Open-ended learning environments (OELEs) involve high learner agency in defining learning goals and multiple pathways to achieve those goals. These tasks involve learners transitioning through self-regulated learning (SRL) phases by actively setting goals, applying different strategies for those goals, and monitoring performance to update their strategies. However, because of the flexibility, how learners react to impasses and errors has a critical influence on their learning. An intelligent pedagogical agent (IPA) continuously modeling learner activities could help support learners in these environments. However, this continuous comprehension of behaviors and strategies is difficult in OELEs with evolving goals, ill-defined problem structures, and learning sequences. In this paper, we draw from the literature on SRL phases and cognitive states to investigate the utility of two different methods, Sequence Mapping, and Hidden Markov Models, in building learner activity models from log data collected from a summer camp with 14 middle school girls in an open-design environment. We evaluate the effectiveness of these models separately, and combined, in identifying 7 states: Forethought, Engaged Concentration, Acting, Monitoring, Wheel Spinning, Mind Wandering, and Reflect and Repair. Lastly, we recommend dialogue intervention strategies for an IPA to support learning in OELEs. 

One of the keys to the success of collaborative learning is balanced participation by all learners, but this does not always happen naturally. Pedagogical robots have the potential to facilitate balance. However, it remains unclear what participation balance robots should aim at; various metrics have been proposed, but it is still an open question whether we should balance human participation in human-human interactions (HHI) or human-robot interactions (HRI) and whether we should consider robots' participation in collaborative learning involving multiple humans and a robot. This paper examines collaborative learning between a pair of students and a teachable robot that acts as a peer tutee to answer the aforementioned question. Through an exploratory study, we hypothesize which balance metrics in the literature and which portions of dialogues (including vs. excluding robots' participation and human participation in HHI vs. HRI) will better predict learning as a group. We test the hypotheses with another study and replicate them with automatically obtained units of participation to simulate the information available to robots when they adaptively fix imbalances in real-time. Finally, we discuss recommendations on which metrics learning science researchers should choose when trying to understand how to facilitate collaboration. 

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. 

Culturally responsive STEM and computing initiatives aim to engage and embolden a diverse range of learners, center their identity and experiences in curriculum, and connect learners to each other and their communities. With an abrupt pivot to online learning at the beginning of 2020, more educational experiences have taken place virtually. We ran a virtual synchronous culturally responsive computing camp and saw that establishing the right environment online to support a good sense of connectedness was challenging. To investigate this further, we interviewed eight K-12 instructors of culturally responsive STEM and computing programs. Three themes emerged on defining and cultivating connectedness in learning experiences, the role of equity in supporting community online, and affordances of being online specific to culturally responsive perspectives. We support our thematic findings with vignettes from the camp data. In this study, we address K-12 culturally responsive STEM and computing instructors' beliefs, experiences, and approaches regarding cultivating connectedness online. This work fills a gap in understanding instructor perspectives on building in-program and broader community connections online from a culturally responsive STEM and computing lens.

 

Computing education is important for K-12 learners, but not all learners resonate with common educational practices. Culturally responsive computing initiatives center and empower learners from diverse and historically excluded backgrounds. Recently, a number of educational programs have been developed and curated for an online experience. In this paper, we describe an online synchronous culturally responsive computing (CRC) camp for middle school girls (ages 11-14 years old) and report on challenges and successes from running the camp curriculum four times over the course of a year. We also describe core iterative changes we made between our runs. We then discuss lessons learned related to building rapport and connection among learners, centering learners of different backgrounds in an online synchronous environment, and facilitating reflection on power and identity aimed at positioning learners as techno-social change agents. Lastly, we offer recommendations for running online CRC experiences. 

The inclusion of community voices in research is important. Over the years, research training programs have continued to emphasize that engagement with communities at the focus of research can promote thoughtful, sensitive designs ( Rivera et al., 2004 ). In this paper, we discuss a method for youth participation in the research process. In an attempt to move beyond “staged and superficial” participation in gathering youth perspectives, we advocate for including co-researchers in the development and modification of fundamental aspects of the research process, from data analysis to the development of additional research questions and collection methods ( Guishard & Tuck, 2013 ). In the course of a study designed to enroll middle school students in participatory co-design sessions ( Cahill, 2007 ) to aid in the development of educational technologies, it became apparent that our youth participants, as co-researchers, could also aid in the development, analysis, and coding of anonymized interview transcripts; development of themes; and creation of models for behaviors found in the transcripts ( Docan-Morgan, 2010 ; Luchtenberg et al., 2020 ). Thus, this paper presents a practical example of a co-research process that includes youth participants, with an emphasis on training in qualitative coding and the fundamentals of research design.