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The principal purpose of this investigation is to study the effect of robotic cooperative learning methodologies on middle school students’ critical thinking, and STEM interest. The semi-experimental inquiry consisted of ninety four six-grade students (forty nine students in the experimental group, forty five students in the control group), chosen by their principals. A critical thinking test was administered to evaluate the cognitive skills and STEM interest of the students. Instruction was implemented in two formats: cooperative learning and problem-based learning. The experimental group utilized robotic cooperative learning while the control group utilized problem-based learning.  After four sessions of both instruction types with both groups the findings reveal that critical thinking of students is enhanced significantly by robotic cooperative learning (P<0.01).

Although self-directed learning environments are common in higher education and online learning environments, they are uncommon in secondary educational settings. This mixed-method action research study, in which the author/researcher was also the teacher, reports on the design and implementation of a self-directed learning environment for eighth-grade life science students. This study investigated the impact of this type of learning environment on the behavior and achievement of students. The findings demonstrated an increase in self-regulatory behaviors, higher performance on a state-mandated final exam, and the development of complex and robust student learning networks. Implications for teaching and learning practices and suggestions for further research are discussed.

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This pilot case study sought to investigate patterns of interactions between learners and their instructor in a teacher education course called “Computer Science for Teachers”. This course was constructed to leverage aspects of open world game design elements in order to investigate the effects of degrees of autonomy in gameplay/learning. This course was conducted in a specially built social learning platform based on Elgg software. Student interactions with the instructor and other students in this course were analyzed to determine the learning networks students constructed during each key learning activity as well as the epistemic spaces defined by these interactions. Descriptive statistics along with social network analysis (SNA) and epistemic network analysis (ENA) were used to investigate these data. The findings indicate that more traditional/less open world gaming type learning activities were associated with learning networks and epistemic spaces that were teacher-centered and narrower, while more open world gaming/high levels of autonomy (student-centric) learning activities were associated with learning networks that were highly decentralized and epistemic spaces that featured students asking and answering questions of/for one another. These findings were consistent with existing research into player behavior in open world type games and learner behavior in settings with high levels of autonomy support. Implications for further research are discussed.