Investigating the Predictive Power of Student Characteristics on
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Investigating the Predictive Power of Student Characteristics on
STARTSUniversity of Central FloridaSTARSElectronic Theses and Dissertations, 2004-20192016Investigating the Predictive Power of student Characteristic Investigating the Predictive Power of Student Characteristics oncs on Success in Studio-mode, Algebra-based Introductory Physics CoursesJarrad PondUniversity of Central Florida& Part of the Physics CommonsFind similar works at: https://stars.library.ucf.edu/etdUniversity of Central Florida Libraries http://library.ucf.eduThis Doctoral Dissertation (Open Access) Investigating the Predictive Power of Student Characteristics onis brought to you for free and open access by STARS. It has been accepted for inclusion in E ectronic Theses and Dissertations. 2004-2019 by an authorInvestigating the Predictive Power of Student Characteristics on
ized administrator of STARS. For more information, please contact STARS@ucf.edu.STARS CitationPond. Jarrad, "Investigating the Predictive Power of stuSTARTSUniversity of Central FloridaSTARSElectronic Theses and Dissertations, 2004-20192016Investigating the Predictive Power of student Characteristic Investigating the Predictive Power of Student Characteristics on98.https://stars.library.ucf.edu/etd/5098fc......»ỉ', <:< central ■ •* \ ' »Florida.♦ _♦ ♦ ♦ ♦ ♦ : .STATES♦Showdicaf tot, Archives, RcsMrch & Schctarihlp ■INVESTIGATING THE PREDICTIVE POWER OF STUDENT CHARACTERSITICS ON SUCCESS IN STUDIO-MODE. ALGEBRA-BASED INTRODUCTORY PHYSICS COURSESbyJARRAD WILLI Investigating the Predictive Power of Student Characteristics onAM THOMAS POND B.S. University of Central Florida. 2009A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor ofInvestigating the Predictive Power of Student Characteristics on
Philosophy in the Department of Physics in the College of Sciences at the University of Central Florida Orlando. FloridaSummer Term2016Major ProfessoSTARTSUniversity of Central FloridaSTARSElectronic Theses and Dissertations, 2004-20192016Investigating the Predictive Power of student Characteristic Investigating the Predictive Power of Student Characteristics on implementations of the studio-mode of physics instruction, the objective of this work is to investigate the characteristics of students enrolled in algebra-based, studio-mode introductory physics courses at various universities in order to evaluate what effects these characteristics have on differe Investigating the Predictive Power of Student Characteristics onnt measures of student success, such as gains in conceptual knowledge, shifts to more favorable attitudes toward physics, and final course grades. LnInvestigating the Predictive Power of Student Characteristics on
my analysis. I explore the strategic self-regulatory, motivational, and demographic characteristics of students in algebra-based, studio-mode physics STARTSUniversity of Central FloridaSTARSElectronic Theses and Dissertations, 2004-20192016Investigating the Predictive Power of student Characteristic Investigating the Predictive Power of Student Characteristics on these institutions possesses varying student populations and differing levels of success in their studio-mode physics courses, as measured by students’ overall average conceptual learning gains.In order to collect information about the students at each institution. I compiled questions from several Investigating the Predictive Power of Student Characteristics on existing questionnaires designed to measure student characteristics such as study strategies and motivations for learning physics, and organization oInvestigating the Predictive Power of Student Characteristics on
f scientific knowledge. I also gathered student demographic information. This compiled survey, named the Student Characteristics Survey (SCS) was giveSTARTSUniversity of Central FloridaSTARSElectronic Theses and Dissertations, 2004-20192016Investigating the Predictive Power of student Characteristic Investigating the Predictive Power of Student Characteristics on. 2015; Schwinger. Steinmayr. & Spinath. 2012; Shell & Busman. 2008; Shell & Soh. 2013; Tuominen-Soini. Salmela-Aro. & Niemivirta, 2011; Vansteenkiste, Soenens. Sierens. Luyckx, & Lens. 2009) have identified distinct learning profiles across varying student populations. Using aiiiperson-centered app Investigating the Predictive Power of Student Characteristics onroach, I used model-based cluster analysis methods (Gan, Ma, & Wu, 2007) to organize students into distinct groups. From this analysis. I identified fInvestigating the Predictive Power of Student Characteristics on
ive distinct learning profiles in the population of physics students, similar to those found in previous research. In addition, student outcome informSTARTSUniversity of Central FloridaSTARSElectronic Theses and Dissertations, 2004-20192016Investigating the Predictive Power of student Characteristic Investigating the Predictive Power of Student Characteristics on grades were gathered at UCF. No student outcome data was gathered at GW: thus. GW is represented in analyses involving information compiled solely from the scs, but GW is not represented in analyses involving student outcome information. Investigating the Predictive Power of Student Characteristics onSTARTSUniversity of Central FloridaSTARSElectronic Theses and Dissertations, 2004-20192016Investigating the Predictive Power of student CharacteristicGọi ngay
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