Trends in the Salience of Data Collected in a Multi User Virtual Environment: an Exploratory Study

In this study, by exploring patterns in the degree of physical salience of the data the students collected, I investigated the relationship between the level of students’ tendency to frame explanations in terms of complex patterns and evidence of how they attend to and select data in support of their developing understandings of causal relationships. I accomplished this by analyzing longitudinal data collected as part of a larger study of 143 7th grade students (clustered within 36 teams, 5 teachers, and 2 schools in the same Northeastern school district) as they navigated and collected data in an ecosystems-based multi-user virtual environment curriculum known as the EcoMUVE Pond module (Metcalf, Kamarainen, Tutwiler, Grotzer, Dede, 2011) . Using individual growth modeling (Singer & Willett, 2003) I found no direct link between student pre-intervention tendency to offer explanations containing complex causal components and patterns of physical salience-driven data collection (average physical salience level, number of low physical salience data points collected, and proportion of low physical salience data points collected), though prior science content knowledge did affect the initial status and rate of change of outcomes in the average physical salience level and proportion of low physical salience data collected over time. The findings of this study suggest two issues for consideration about the use of MUVEs to study student data collection behaviors in complex spaces. Firstly, the structure of the curriculum in which the MUVE is embedded might have a direct effect on what types of data students choose to collect. This undercuts our ability to make inferences about student-driven decisions to collect specific types of data, and suggests that a more open-ended curricular model might be better suited to this type of inquiry. Secondly, differences between teachers’ choices in how to facilitate the units likely contribute to the variance in student data collection behaviors between students with different teachers. This foreshadows external validity issues in studies that use behaviors of students within a single class to develop “detectors” of student latent traits (e.g., Baker, Corbett, Roll, Koedinger, 2008)

Simplifying Causal Complexity: How Interactions Between Modes of Causal Induction and Information Availability Lead to Heuristic-Driven Reasoning

This article considers a set of well-researched default assumptions that people make in reasoning about complex causality and argues that, in part, they result from the forms of causal induction that we engage in and the type of information available in complex environments. It considers how information often falls outside our attentional frame such that covariation falls short, mechanisms can be nonobvious, and the testimony that others offer is typically subject to the same constraints as our own perceptions. It underscores the importance of multiple modes of causal induction used in support of one another when discerning and teaching about causal complexity. It considers the importance of higher order reflection on the nature of causality that recognizes the challenging features of complex causality and how it interacts with human causal cognition

Science learning and inquiry with technology

When implemented effectively, technology has great potential to positively connect with learning, assessment, and motivation in the context of K-12 science education and inquiry. Written by leading experts on technology-enhanced science learning and educational research, this book situates the topic within the broader context of educational psychology research and theory and brings it to a wider audience. With chapters on the fundamentals of science learning and assessment, integration of technology into classrooms, and examples of specific technologies, this concise volume is designed for any course on science learning that includes technology use in the curriculum. It will be indispensable for student researchers and both pre- and in-service teachers alike

Engaging middle school students in scientific practice with a collaborative mobile game

Previous research using collaborative mobile augmented reality games in science education revealed that such games can be used to promote learner engagement and have found that engagement in such mobile games is related to flow. This study investigated whether player\u27s flow experience differed by achievement track, gender, or gender composition of working groups. In an urban school district, 202 students from two eighth-grade science classes participated in a collaborative mobile science game. Data included a self-report survey collected after the game that measured player\u27s flow experience. Using a regression model, the relationship of flow experience with achievement track and gender was explored while controlling for group composition and teacher effects. The study found that gender was related to flow experience; specifically, girls reported higher flow experience scores (d = 0.30). Flow experience did not have a statistically significant relationship with achievement track showing that the activity engaged all observed students similarly