How students find, evaluate and utilize peer-collected annotated multimedia data in science inquiry with zydeco

Abstract

Scientific inquiry can be more authentic and meaningful to students when using personal and peer-collected data. The challenges of organizing and evaluating a potentially large amount of data can be overcome through the use of annotations (title, tags, and audio notes). We created Zydeco, a multi-component system that students use to collect annotated multimedia data from a museum (using a smartphone app), and then create a scientific explanation with their personal and peers' data (using a tablet app). We ran a classroom study with 54 students (ages 11-13) investigating how students searched for, evaluated, and used annotated data to construct a scientific explanation. We found that tags supported data interpretation, while title searching and panning through the unfiltered data set supported finding and using data.

The Benefits and Limitations of Educative Curriculum Materials

“…Several studies focus on how various technology tools can support preservice teachers in promoting inquiry (Bell & Trundle, 2008;Crawford et al, 2005); however, these studies do not discuss how to support in-service teachers in implementing technology in their classrooms to support student learning. The U.S. Department of Education's (2010) report on the national technology plan highlighted the benefits of technology for supporting the development of content with inquiry, and in the past two decades many studies have explored the use of technology to improve students' ability to engage in inquiry (Kuhn et al, 2012;Maldonado & Pea, 2010;Sandoval & Reiser, 2004;Songer, 2006;Suthers, 1998); however, these studies have ignored the impact on teachers' practices.…”

Verbatim and Semantic Imitation in Indexing Resources on the Web: A Fuzzy‐trace Account of Social Tagging

“…Particularly, social tags are not only cues supporting information search or leading to simple swarm-like imitation (Ley & Seitlinger, 2011) but seem to externalize individual thoughts that in turn evoke associated ideas and reflections of other students. Considered in this light, it becomes clearer why the simple tagging functionality of collaborative learning environments proves to support learning processes among students (e.g., Kuhn et al, 2012). As a tool that interconnects both external (e.g., learning objects) and internal representations (e.g., gist traces), ST has the potential to foster the exchange of learning experiences in constructivist and technology-enhanced learning settings.…”

What Do Students’ Explanations Look Like When They Use Second-Hand Data?

“…The data students collected were similar to their peers' data, since they all collected data from the same museum. Students primarily preferred using second-hand data in their explanations, but the authors did not compare the quality of student explanations when they used second-hand data (Kuhn et al, 2012). What is interesting here is that it is data collected in the same site.…”

“…To answer this question, we analyzed the quality of students' explanations after visiting WP. When analyzing these explanations, we focused on how students justify their claims by using evidence (Kuhn et al, 2012;McNeill et al, 2006;Novak & Treagust, 2013;Sandoval & Millwood, 2005;Simon et al, 2006). When analyzing the health of WP, students also had access to the data collected by their peers in the same day from WP.…”

“…Creating Data Pool for Examining Second-Hand Data Kuhn et al (2012) created a data organization tool to combine peers' data and the students' own data in the same data pool. Students collected data to observe traits in a natural history museum.…”