The Effect of Data Acquisition-Probeware and Digital Video Analysis on Accurate Graphical Representation of Kinetics in a High School Physics Class

Struck, William A.; Yerrick, Randy

doi:10.1007/s10956-009-9194-y

Cited by 15 publications

(11 citation statements)

References 22 publications

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“…When authors mention the real-world context as a mediating factor, they refer to experiences of the students with the real world (e.g., Boyd and Rubin 1996;Carrejo and Marshall 2007;Heck and Uylings 2006;Struck and Yerrick 2010;Wilhelm and Confrey 2003). Mitnik et al (2009) gave students the opportunity to study the motion of a robot in the real world, by making the environment more explorative and immersive.…”

Section: Real-world Contextmentioning

confidence: 99%

“…In some instances, authors primarily focus on how the learning environment provided this linkage between motion and graph (e.g., Metcalf and Tinker 2004;Stylianou et al 2005;Svec 1999), while other authors focus more on how students were engaged in connecting the graph to the motion (e.g., Heck and Uylings 2006). A few authors emphasize how this linkage might facilitate a corresponding linking in memory, whereas the information in the graph is a direct result of students' own motion (e.g., Brasell 1987;Brungardt and Zollman 1995;Kozhevnikov and Thornton 2006;Mokros and Tinker 1987;Struck and Yerrick 2010). While in almost all learning environments the linkage between an actual (or simulated) motion and the corresponding graph is explicit, some authors also refer to linking motion to graph at a more abstract level (e.g., Boyd and Rubin 1996;Espinoza 2015;Ferrara 2014;Holbert and Wilensky 2014;Robutti 2006;Thornton and Sokoloff 1990).…”

Section: Linking Motion To Graphmentioning

confidence: 99%

“…The mediating factor student control explicitly refers to students being in control in the learning environment allowing them to manipulate either the motion event or its graphical representation. Most of these articles refer to student control as being in control of the (physical) motion (e.g., Anderson and Wall 2016;Struck and Yerrick 2010). In this respect, students are able to directly manipulate the visual display .…”

Section: Student Controlmentioning

confidence: 99%

See 2 more Smart Citations

Embodied Learning Environments for Graphing Motion: a Systematic Literature Review

et al. 2019

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Embodied learning environments have a substantial share in teaching interventions and research for enhancing learning in science, technology, engineering, and mathematics (STEM) education. In these learning environments, students' bodily experiences are an essential part of the learning activities and hence, of the learning. In this systematic review, we focused on embodied learning environments supporting students' understanding of graphing change in the context of modeling motion. Our goal was to deepen the theoretical understanding of what aspects of these embodied learning environments are important for teaching and learning. We specified four embodied configurations by juxtaposing embodied learning environments on the degree of bodily involvement (own and others/objects' motion) and immediacy (immediate and non-immediate) resulting in four classes of embodied learning environments. Our review included 44 articles (comprising 62 learning environments) and uncovered eight mediating factors, as described by the authors of the reviewed articles: realworld context, multimodality, linking motion to graph, multiple representations, semiotics, student control, attention capturing, and cognitive conflict. Different combinations of mediating factors were identified in each class of embodied learning environments. Additionally, we found that learning environments making use of students' own motion immediately linked to its representation were most effective in terms of learning outcomes. Implications of this review for future research and the design of embodied learning environments are discussed.

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Section: Real-world Contextmentioning

confidence: 99%

Section: Linking Motion To Graphmentioning

confidence: 99%

Section: Student Controlmentioning

confidence: 99%

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Embodied Learning Environments for Graphing Motion: a Systematic Literature Review

et al. 2019

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“…This interest in sensors as learning technologies has continued into current day (e.g., Struck and Yerrick 2010;Zucker et al 2008). For example, a recent report prepared by the National Science Foundation Task Force on Cyberlearning placed repeated emphasis on sensor technologies as a key area for future educational technology research and development (Borgman et al 2008).…”

Section: Introductionmentioning

confidence: 99%

Integrating physical activity data technologies into elementary school classrooms

Lee

Thomas

2011

Education Tech Research Dev

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Mindfulness is a critical dimension in current school physical activity programs (e.g., physical education, intramural, and interscholastic physical activities). School physical activity programs are a key vehicle used in developing healthy active lifestyles among children and youth; however, the absence of mindfulness in these programs has given rise to numerous problems (such as body-mind dualism and stress) that interfere with attaining program objectives. This paper discusses what mindfulness is, why it is needed, and how mindfulness can be integrated into school physical activity programming. The integration of mindfulness can help develop a healthy lifestyle for a whole child; in turn, our school physical activity programs can be re-conceptualized and transformed to deliver this objective on a perpetual basis.

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“…Originally called 'microcomputer-based laboratories' and later 'probeware,' sensor-based learning emerged in the 1980s to help children explore, experiment with, and analyze physical phenomena in new ways (e.g., kinematics [41], electricity [77]). While most prior work has focused on learning benefits with older students in high-school and college (e.g., [50,64,65,71,73]), three studies with younger children-our focus-also showed benefits [13,53,77]. Researchers suggest that it is the tight coupling between activity and the computer-based visualization that accounts for gains in understanding and engagement [13,53].…”

Section: Sensor-based Learningmentioning

confidence: 99%

SharedPhys

Kang

Norooz

Oguamanam

et al. 2016

Proceedings of the the 15th International Conference on Interaction Design and Children

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We present and evaluate a new mixed-reality tool called SharedPhys, which tightly integrates real-time physiological sensing, whole-body interaction, and responsive large-screen visualizations to support new forms of embodied interaction and collaborative learning. While our primary content area is the human body, we use the body and physical activity as a pathway to other STEM areas such as biology, health, and mathematics. We describe our participatory design process with 20 elementary school teachers, the development of three contrasting SharedPhys prototypes, and results from six exploratory evaluations in two after-school programs. Our findings suggest that the tight coupling between physical interaction, sensing, and visualization in a multiuser environment helps promote engagement, allows children to easily explore cause-and-effect relationships, supports and shapes social interactions, and promotes playful experiences.

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The Effect of Data Acquisition-Probeware and Digital Video Analysis on Accurate Graphical Representation of Kinetics in a High School Physics Class

Cited by 15 publications

References 22 publications

Embodied Learning Environments for Graphing Motion: a Systematic Literature Review

Embodied Learning Environments for Graphing Motion: a Systematic Literature Review

Integrating physical activity data technologies into elementary school classrooms

SharedPhys

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