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You searched for +publisher:"Vanderbilt University" +contributor:("Douglas B. Clark"). Showing records 1 – 3 of 3 total matches.

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Vanderbilt University

1. Van Eaton, Grant Waller. Beyond Traditional Measures of Teacher Quality: Incorporating Cultural Competence to Measure Classroom Community.

Degree: PhD, Learning, Teaching and Diversity, 2017, Vanderbilt University

This study explores the necessity and validity of including cultural competence as a dimension of the construct of quality teaching and classroom community. Through an analysis of existing measures, cultural competence was found to be missing across widely-adopted measures of teacher quality; in contrast, the literature on cultural competence in education, as well studies documenting the importance and validity of including cultural competence in measures of quality medical education, point to the importance of expanding the dominant construct of teacher quality to include aspects of cultural competence. In response to this need, this dissertation analyzes a new observation rubric, the Vision for Student Learning (VfSL). The VfSL is not a traditional, evaluative measure of teacher quality; instead, it is a formative measure of classroom community that scores classrooms based on student actions, rather than teacher actions. The VfSL is grouped into three dimensions: Safe, Brave, and Equitable Classrooms; Rigorous and Culturally Relevant Learning; and Perseverance to Goals. Using exploratory factor analysis and item response theory (IRT) models, this dissertation demonstrates that the VfSL is both reliable and valid as a measure of classroom community, providing initial evidence that inclusion of cultural competence in observation rubrics is both possible and desirable when used strictly to provide formative feedback. Furthermore, the factor structure of the VfSL empirically affirms the theoretically-driven design of the first two dimensions of the measurement instrument and provides evidence that the skills of building classroom culture and enacting rigorous instruction are distinct skill sets that should be targeted to improve classroom community. Revisions to the design of the instrument are suggested based on findings from the factor and IRT analyses. Additionally, while the VfSL shows sensitivity across various demographic groups, researchers and practitioners utilizing the VfSL should be cautious to ensure that any observed differences in classroom community across lines of race and gender are not a function of rater or item bias. Advisors/Committee Members: Ilana Horn (committee member), Barbara Stengel (committee member), Sun-Joo Cho (committee member), Douglas B. Clark (Committee Chair).

Subjects/Keywords: cultural competence; teacher observation; IRT; teacher quality

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Van Eaton, G. W. (2017). Beyond Traditional Measures of Teacher Quality: Incorporating Cultural Competence to Measure Classroom Community. (Doctoral Dissertation). Vanderbilt University. Retrieved from http://hdl.handle.net/1803/14410

Chicago Manual of Style (16th Edition):

Van Eaton, Grant Waller. “Beyond Traditional Measures of Teacher Quality: Incorporating Cultural Competence to Measure Classroom Community.” 2017. Doctoral Dissertation, Vanderbilt University. Accessed November 28, 2020. http://hdl.handle.net/1803/14410.

MLA Handbook (7th Edition):

Van Eaton, Grant Waller. “Beyond Traditional Measures of Teacher Quality: Incorporating Cultural Competence to Measure Classroom Community.” 2017. Web. 28 Nov 2020.

Vancouver:

Van Eaton GW. Beyond Traditional Measures of Teacher Quality: Incorporating Cultural Competence to Measure Classroom Community. [Internet] [Doctoral dissertation]. Vanderbilt University; 2017. [cited 2020 Nov 28]. Available from: http://hdl.handle.net/1803/14410.

Council of Science Editors:

Van Eaton GW. Beyond Traditional Measures of Teacher Quality: Incorporating Cultural Competence to Measure Classroom Community. [Doctoral Dissertation]. Vanderbilt University; 2017. Available from: http://hdl.handle.net/1803/14410


Vanderbilt University

2. Martinez Garza, Mario Manuel. Coevolution of Theory and Data Analytics of Digital Game-Based Learning.

Degree: PhD, Learning, Teaching and Diversity, 2016, Vanderbilt University

Learning theory and educational data analytics can be said to coevolve, that is, to refine and improve each other reciprocally, each aspect providing a necessary element for the growth and advancement of the other. In this three-paper dissertation, I explore this process of coevolution between learning theory and data analytics in the context of digital game-based learning. From the theoretical side, I describe a framework based on a general theory of cognition (the two-system or dual-system model) that can be applied to digital game environments. The main hypothesis in this framework is that certain patterns of action in the game-space indicate the use of certain epistemic stances that have analogues within the two-system model. The proposed Two Stance/Two Model Framework (2SM) provides (a) improved explanatory power regarding intrapersonal variation in learning from games, (b) more complete theory regarding individual needs, goals, and agency, (c) a more extensive account of collaboration and community, and (d) improved perspective on knowledge-rich interactions in online affinity spaces. From the methodological side, I applied techniques of statistical computing (affinity clustering and sequence mining) to detect the stances of the 2SM as they appear in a physics learning game. The 2SM theorized that slow modes of solution would correlate to higher learning gains; students who use mainly fast iterative solution strategies did achieve lower learning gains than students who preferred slow, elaborated solutions. A second finding was that, as play progresses, students generally improve their performance in game areas that highlight physics concepts, but that this improvement is strongly moderated by their prior knowledge of physics. This dissertation further contributes to the existing knowledge of digital game-based learning by demonstrating how an analysis of the collected actions of players can be applied in a reliable and comprehensive fashion to research questions that are otherwise challenging to investigate. Advisors/Committee Members: Rogers P. Hall (committee member), Daniel T. Levin (committee member), Melissa S. Gresalfi (committee member), Douglas B. Clark (Committee Chair).

Subjects/Keywords: data mining; learning analytics; educational games; science learning

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Martinez Garza, M. M. (2016). Coevolution of Theory and Data Analytics of Digital Game-Based Learning. (Doctoral Dissertation). Vanderbilt University. Retrieved from http://hdl.handle.net/1803/10476

Chicago Manual of Style (16th Edition):

Martinez Garza, Mario Manuel. “Coevolution of Theory and Data Analytics of Digital Game-Based Learning.” 2016. Doctoral Dissertation, Vanderbilt University. Accessed November 28, 2020. http://hdl.handle.net/1803/10476.

MLA Handbook (7th Edition):

Martinez Garza, Mario Manuel. “Coevolution of Theory and Data Analytics of Digital Game-Based Learning.” 2016. Web. 28 Nov 2020.

Vancouver:

Martinez Garza MM. Coevolution of Theory and Data Analytics of Digital Game-Based Learning. [Internet] [Doctoral dissertation]. Vanderbilt University; 2016. [cited 2020 Nov 28]. Available from: http://hdl.handle.net/1803/10476.

Council of Science Editors:

Martinez Garza MM. Coevolution of Theory and Data Analytics of Digital Game-Based Learning. [Doctoral Dissertation]. Vanderbilt University; 2016. Available from: http://hdl.handle.net/1803/10476


Vanderbilt University

3. Basu, Satabdi. Fostering Synergistic Learning of Computational Thinking and Middle School Science in Computer-based Intelligent Learning Environments.

Degree: PhD, Computer Science, 2016, Vanderbilt University

Recent advances in computing are transforming our lives at an astonishing pace. Computational Thinking (CT) is a term used to describe the representational practices and behaviors involved in formulating problems and their solutions so that the solutions can be carried out by a computer or a computing agent. Driven by the needs of a 21st century workforce, there is currently a great emphasis on teaching students to think computationally from an early age. Computer science education is gradually being incorporated into K-12 curricula, but a more feasible approach to make CT accessible to all students may be to integrate it with components of existing K-12 curricula. While CT is considered a vital ingredient of science learning, successfully leveraging the synergy between the two in middle school classrooms is non-trivial. This dissertation research presents Computational Thinking using Simulation and Modeling (CTSiM), a computer-based environment that integrates learning of CT concepts and practices with middle school science curricula. CTSiM combines the use of an agent-based visual language for conceptual and computational modeling of science topics, hypertext resources for information acquisition, and simulation tools to study and analyze the behaviors of the modeled science topics. We discuss assessments metrics developed to study the computational artifacts students build and the CT practices and learning strategies they employ in the CTSiM environment. These metrics can be used online to interpret students’ behavior and performance, and provide the framework for adaptively scaffolding students based on their observed deficiencies. Results from a classroom study with ninety-eight middle school students demonstrate the effectiveness of the CTSiM environment and the adaptive scaffolding framework. Students display better understanding of important science and CT concepts, improve their modeling performance over time, adopt useful modeling behaviors, and are able to transfer their modeling skills to new scenarios. In addition, students’ modeling performance and use of CT practices during modeling are significantly correlated with their science learning, demonstrating the synergy between CT and science learning. Advisors/Committee Members: Dr. Douglas H. Fisher (committee member), Dr. Julie Ann Adams (committee member), Dr. Douglas B. Clark (committee member), Dr. Pratim Sengupta (committee member), Dr. Gautam Biswas (Committee Chair).

Subjects/Keywords: Adaptive scaffolding; Agent based Modeling; Learning by Modeling; Science Education; Computational Thinking; Open ended Learning Environments; Learning Analytics

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Basu, S. (2016). Fostering Synergistic Learning of Computational Thinking and Middle School Science in Computer-based Intelligent Learning Environments. (Doctoral Dissertation). Vanderbilt University. Retrieved from http://hdl.handle.net/1803/11338

Chicago Manual of Style (16th Edition):

Basu, Satabdi. “Fostering Synergistic Learning of Computational Thinking and Middle School Science in Computer-based Intelligent Learning Environments.” 2016. Doctoral Dissertation, Vanderbilt University. Accessed November 28, 2020. http://hdl.handle.net/1803/11338.

MLA Handbook (7th Edition):

Basu, Satabdi. “Fostering Synergistic Learning of Computational Thinking and Middle School Science in Computer-based Intelligent Learning Environments.” 2016. Web. 28 Nov 2020.

Vancouver:

Basu S. Fostering Synergistic Learning of Computational Thinking and Middle School Science in Computer-based Intelligent Learning Environments. [Internet] [Doctoral dissertation]. Vanderbilt University; 2016. [cited 2020 Nov 28]. Available from: http://hdl.handle.net/1803/11338.

Council of Science Editors:

Basu S. Fostering Synergistic Learning of Computational Thinking and Middle School Science in Computer-based Intelligent Learning Environments. [Doctoral Dissertation]. Vanderbilt University; 2016. Available from: http://hdl.handle.net/1803/11338

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