Research
Here are some featured publications on my research in learning sciences and education.
Practical Strategies for Collaboration across Discipline-Based Education Research and the Learning Sciences
Rather than pursue questions related to learning in biology from separate camps, recent calls highlight the necessity of interdisciplinary research agendas. Interdisciplinary collaborations allow for a complicated and expanded approach to questions about learning within specific science domains, such as biology. Despite its benefits, interdisciplinary work inevitably involves challenges. Some such challenges originate from differences in theoretical and methodological approaches across lines of work. Thus, aims at developing successful interdisciplinary research programs raise important considerations regarding methodologies for studying biology learning, strategies for approaching collaborations, and training of early-career scientists. Our goal here is to describe two fields important to understanding learning in biology, discipline-based education research and the learning sciences. We discuss differences between each discipline’s approach to biology education research and the benefits and challenges associated with incorporating these perspectives in a single research program. We then propose strategies for building productive interdisciplinary collaboration.
Challenges facing interdisciplinary researchers: Findings from a professional development workshop
Interdisciplinary research is the synergistic combination of two or more disciplines to achieve one research objective. Current research highlights the importance of interdisciplinary research in science education, particularly between educational experts within a particular science discipline (discipline-based education researchers) and those who study human learning in a more general sense (learning scientists). However, this type of interdisciplinary research is not common and little empirical evidence exists that identifies barriers and possible solutions. We hosted a pre-conference workshop for Discipline-Based Educational Researchers and Learning Scientists designed to support interdisciplinary collaborations. We collected evidence during our workshop regarding barriers to interdisciplinary collaborations in science education, perceptions of perceived cohesion in participants’ home university departments and professional communities, and the impact of our workshop on fostering new connections.
Based on participants’ responses, we identified three categories of barriers, Disciplinary Differences, Professional Integration, and Collaborative Practice. Using a post-conference survey, we found an inverse pattern in perceived cohesion to home departments compared to self-identified professional communities. Additionally, we found that after the workshop participants reported increased connections across disciplines. Our results provide empirical evidence regarding challenges to interdisciplinary research in science education and suggest that small professional development workshops have the potential for facilitating durable interdisciplinary networks where participants feel a sense of belonging not always available in their home departments.
Learning Analytics to Assess Beliefs about Science: Evolution of Expertise as Seen through Biological Inquiry
Epistemological beliefs about science (EBAS) or beliefs about the nature of science knowledge, and how that knowledge is generated during inquiry, are an essential yet difficult to assess component of science literacy. Leveraging learning analytics to capture and analyze student practices in simulated or game-based authentic science activities is a potential avenue for assessing EBAS. Our previous work characterized inquiry practices of experts and novices engaged in simulated authentic science inquiry and suggested that practices may reflect EBAS. Here, we extend our prior qualitative work to quantitatively examine differences in practices and EBAS between non–science majors, biology majors, and biology graduates.
We observed that inquiry practices of non–science majors and biology graduates were similar to the novice and expert practices, respectively, in our prior work. However, biology majors sometimes appeared to act like their undergraduate peers (e.g., performing fewer planning actions) but other times were more similar to biology graduates (e.g., performing complex investigations). We noted that cognitive constructs like metacognition were also important for understanding which practices were most likely to be reflective of EBAS. This work advances how to assess EBAS using learning analytics and raises questions regarding the development of cognitive processes like EBAS among aspiring biologists.
Assessing epistemological beliefs of experts and novices via practices in authentic science inquiry
Achieving science literacy requires learning disciplinary knowledge, science practices, and development of sophisticated epistemological beliefs about the nature of science and science knowledge. Although sophisticated epistemological beliefs about science are important for attaining science literacy, students’ beliefs are difficult to assess. Previous work suggested that students’ epistemological beliefs about science are best assessed in the context of engagement in science practices, such as argumentation or inquiry.
In this paper, we propose a novel method for examining students’ epistemological beliefs about science situated in authentic science inquiry or their Epistemology in Authentic Science Inquiry (EASI). As a first step towards developing this assessment, we performed a novice/expert study to characterize practices within a simulated authentic science inquiry experience provided by Science Classroom Inquiry (SCI) simulations. Our analyses indicated that experts and novices, as defined by their experience with authentic science practices, had distinct practices in SCI simulations. For example, experts, as compared to novices, spent much of their investigations seeking outside information, which is consistent with novice/expert studies in engineering. We also observed that novice practices existed on a continuum, with some appearing more-or less expert-like. Furthermore, pre-test performance on established metrics of nature of science was predictive of practices within the simulation.
Since performance on pre-test metrics of nature of science was predictive of practices, and since there were distinct expert or novice-like practices, it may be possible to use practices in simulated authentic science inquiry as a proxy for student’s epistemological beliefs. Given than novices existed on a continuum, this could facilitate the development of targeted science curriculum tailored to the needs of a particular group of students. This study indicates how educational technologies, such as simulated authentic science inquiry, can be harnessed to examine difficult to assess, but important, constructs such as epistemology.
Assessment of language in authentic science inquiry reveals putative differences in epistemology
Science epistemology, or beliefs about what it means to do science and how science knowledge is generated, is an integral part of authentic science inquiry. Although the development of a sophisticated science epistemology is critical for attaining science literacy, epistemology remains an elusive construct to precisely and quantitatively evaluate. Previous work has suggested that analysis of student practices in science inquiry, such as their use of language, may be reflective of their underlying epistemologies. Here we describe the usage of a learning analytics tool, TAALES, and keyness analysis to analyze the concluding statements made by students at the end of a computer-based authentic science inquiry experience.
Preliminary results indicate that linguistic analysis reveals differences in domain-general lexical sophistication and in domain-specific verb usage that are consistent with the expertise level of the participant. For example, experts tend to use more hedging language such as "may" and "support" during conclusions whereas novices use stronger language such as "cause." Using these differences, a simple, rule-based prediction algorithm with LOOCV achieved prediction accuracies of greater than 80%. These data underscore the potential for the use of learning analytics in simulated authentic inquiry to provide a novel and valuable method of assessing inquiry practices and related epistemologies.