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Drawing on data from about 300 fourth- and fifth-grade mathematics teachers, the article links experience, instructional and noninstructional effort, subject/course participation, and knowledge to student outcomes, while revealing imbalances in these teacher traits across student populations. The findings inform hiring and training decisions.",{"@graph":14,"@context":73},[15,34,56],{"@type":16,"itemListElement":17},"BreadcrumbList",[18,23,27,31],{"item":19,"name":20,"@type":21,"position":22},"https://docshare.wps.com","Home","ListItem",1,{"item":24,"name":25,"@type":21,"position":26},"https://docshare.wps.com/document/","Document",2,{"item":28,"name":29,"@type":21,"position":30},"https://docshare.wps.com/document/research-report/","Research & 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Vol. 33(7) 1103–1134 © The Author(s) 2018  \nArticle reuse guidelines: [sagepub.com/journals-permissions](sagepub.com/journals-permissions)[ ](sagepub.com/journals-permissions)[DOI: 10.1177/0895904818755468](DOI: 10.1177/0895904818755468)  \n[journals.sagepub.com/home/epx](journals.sagepub.com/home/epx)  \nHeather C. Hill 1, Charalambos Y. Charalambous2, and Mark J. Chin 1  \nAbstract  \nDiverse stakeholders have an interest in understanding how teacher characteristics—their preparation and experience, knowledge, and mindsets and habits—relate to students’ outcomes in mathematics. Past research has extensively explored this issue but often examined each characteristic in isolation. Drawing on data from roughly 300 fourth-and fifth-grade teachers, we attend to multiple teacher characteristics and find that experience, knowledge, effort invested in noninstructional activities, and participation in mathematics content/methods courses predict student outcomes. We also find imbalances in key teacher characteristics across student populations. We discuss the implications of these findings for hiring and training mathematics teachers.  \nKeywords  \nachievement, mathematics education, teacher quality, teacher qualifications  \n1 Harvard University, Cambridge, MA, USA  \n2University of Cyprus, Nicosia, Cyprus  \nCorresponding Author:  \nMark J. Chin, Center for Education Policy Research, 50 Church Street, 4th Floor, Cambridge, MA 02138, USA.  \n[Email: mark_chin@g.harvard.edu](Email: mark_chin@g.harvard.edu)  \nIdentifying effective teachers has become a pressing need for many state and district policy makers. Federal legislation, such as No Child Left Behind and Race to the Top, required local educational agencies (LEAs) to both measure teacher quality and take action to dismiss or remediate those that fall below a bar for sufficient quality. LEAs themselves may wish to better identify effective and ineffective teachers, as past research has shown teacher quality to be one of the strongest institutional-level predictors of student outcomes (e.g., Chetty, Friedman, & Rockoff, 2014) . Yet for LEAs interested in improving the quality of teacher candidates at entry into their system, and in improving the quality of the many teachers without student test scores and/or classroom observations, determining teacher quality can be challenging. The same is true for LEAs interested in strategically placing new teachers in certain schools to more equitably distribute teacher quality.  \nSuch LEAs might turn to the literature on the relationship between teacher characteristics and student outcomes. The factors tested by this literature fall into three broad categories, including the preparation and experiences hypothesized to be important to teachers (e.g., postsecondary mathematics coursework, degrees, teaching experience, certification type; Clotfelter, Ladd, & Vigdor, 2007; Harris & Sass, 2011; Monk, 1994); teacher knowledge (e.g., mathematical knowledge for teaching, knowledge of students’ mathematical abilities and misconceptions; Bell, Wilson, Higgins, & McCoach, 2010; Carpenter, Fennema, Peterson, & Carey, 1988; Hill, Rowan, & Ball, 2005); and teacher mind-sets and habits (e.g., efficacy, locus of control, effort invested in teaching; Bandura, 1997; Tschannen-Moran & Hoy, 2001). Across these categories, researchers have measured and tested numerous variables against student learning on standardized assessments.  \nWhile many of the studies noted above show small positive associations between measured characteristics and student outcomes, results for specific variables are decidedly mixed across the field as a whole, making the job of practitioners who want to take lessons from this literature difficult. Furthermore, most studies in this genre tend to specialize in only one category, restricting the number and type of variables tested and th","cbCaild8YzAkDUUt","https://ap.wps.com/l/cbCaild8YzAkDUUt","pdf",489025,32,"English","# Abstract\n# Introduction and Policy Need\n## Teacher Quality Measurement Challenges\n## Prior Research on Teacher Characteristics\n# Study Purpose and Data Source\n## Comprehensive Comparison Framework\n## Distribution Across Students and Schools","[{\"question\":\"What teacher characteristics are examined in the study?\",\"answer\":\"The study focuses on teacher preparation and experience, teacher knowledge, and teacher mindsets and habits, relating each set to mathematics student outcomes.\"},{\"question\":\"What factors predict student outcomes in mathematics?\",\"answer\":\"Results indicate that experience, knowledge, effort invested in noninstructional activities, and participation in mathematics content/methods courses predict student outcomes.\"},{\"question\":\"How do the findings affect hiring and training mathematics teachers?\",\"answer\":\"The study discusses implications for hiring and training by identifying which teacher characteristics are linked to outcomes and noting disparities across student populations that matter for equitable staffing.\"}]","Teacher Characteristics and Student Learning in Mathematics - A Comprehensive Assessment | PDF",1792095137,81]