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dc.contributor.authorLin, Yu-Ju
dc.date.accessioned2016-09-01T14:36:57Z
dc.date.available2016-09-01T14:36:57Z
dc.date.issued2015-08
dc.identifier.otherlin_yu-ju_201508_phd
dc.identifier.urihttp://purl.galileo.usg.edu/uga_etd/lin_yu-ju_201508_phd
dc.identifier.urihttp://hdl.handle.net/10724/35759
dc.description.abstractPersonalization in education has played an important role in supporting learning as well as instruction and has been conceptually classified into personalized learning and instruction. Personalized learning refers to student unique ways of learning determined by their individual needs (Carolan & Guinn, 2007; Carroll, 1975; Johnson, Adams, & Cummins, 2012; Keefe & Jenkins, 2008; Miller, 2010). Teachers implement personalized instruction by contextualizing teaching practices to accommodate student needs. However, teachers may hesitate to implement personalized instruction, due to three constrains: 1) time, 2) continuous support, and 3) the required knowledge for personalized instruction (Lin & Kim, 2013). Modeling (Bandura, 1986; Schunk, 2008) determines the development of social learning environment involving the factors of people, behaviors, and environments, and thus formed a theoretical framework of this study. A peer modeling process perceived as the environmental factor can overcome the barriers caused by the lack of time and required knowledge for personalized instruction.Appropriate use of open educational resources viewed as the behavioral and environmental factors can resolve the concern caused by the lack of continuous support including a supportive culture of openness for reuse and reproduction and the growing availability of resources. Students enrolled in introductory statistics courses tent to have different prior knowledge and background for statistics learning. The personal factors influencing students' statistic learning include, but not limited to prior knowledge (Leppink, Broers, Imbos, van der Vleuten, & Berger, 2012), technical access (Neumann & Hood, 2009), competence (Boyle et al., 2014), motivation (Ejei, Weisani, Siadat, & Khezriazar, 2011; Lavasani, Weisani, & Ejei, 2011), and statistics learning anxiety (Lavasani, et al., 2011; Macher, Paechter, Papousek, & Ruggeri, 2012). Accordingly, a developmental model to support personalized instruction as well as to promote personalized learning was proposed. The purpose of this study was to evaluate if triadic reciprocal interaction among personal, behavioral, and environmental factors occurred in the developmental model, and thus promote personalized statistics learning in terms of improved achievement, increased motivation, and decreased statistics learning anxiety.
dc.languageeng
dc.publisheruga
dc.rightsOn Campus Only Until 2017-08-01
dc.subjectPersonalized Learning
dc.subjectPersonalized Instruction
dc.subjectIntroductory Statistics
dc.subjectPeer Modeling
dc.subjectOpen Educational Resources
dc.titleThe effect of motivation and learning anxiety on achievement by modeling problem solving skills and using open educational resources
dc.typeDissertation
dc.description.degreePhD
dc.description.departmentEducational Psychology and Instructional Technology
dc.description.majorInstructional Technology
dc.description.advisorRobert Branch
dc.description.committeeRobert Branch
dc.description.committeeLloyd Rieber
dc.description.committeeMichael Orey
dc.description.committeeZhenqiu Lu


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