title: Explicating the value of standardized educational achievement data and a protocol for collaborative analysis of this data

authors: Cowie, Bronwen

subjects: data literacy

abstract: Governments expect teachers to be able to make sense of and take action on data at various levels of aggregation. In our research we collaborated with 13 teachers from six primary schools and one intermediate school to use a Data Conversation Protocol to analyze and act on mathematics assessment data generated through a standardized assessment tool—the Progressive Achievement Test (PAT). Our intention was to optimize teacher use of this data for pedagogical decision making and action. At team meetings, the teachers co-constructed then refined a taken-as-shared definition for teacher data literacy for instructional action, which acted to inform and anchor our collaborative research. Data were collected in all teacher meetings and via interviews. Initial findings indicate that a ‘Data Conversation Protocol’ is helping teachers to slow down the process of considering, interpreting and making a judgement about their students’ understanding thereby opening up a space for deeper consideration of the range of possible reasons for student responses to assessment items. Students responded positively to teachers’ data informed small group teaching, gaining in understanding and confidence. Teachers considered this confidence translated to more positive engagement with mathematical ideas. Patterns and trends in student responses emerging from the teachers’ collaborative analysis of standard data supported a shift from viewing student responses as linked to student or school characteristics to critical analysis of how their teaching approaches might have contributed to student answers/misunderstandings. This finding has implications for how we might challenge assumptions about students through a willingness to engage critically with student achievement data. The importance of teachers having a rich pedagogical content knowledge as a basis for this was clearly evident.

text: Explicating the value of standardized educational achievement data and a protocol for collaborative analysis of this data Governments expect teachers to be able to make sense of and take action on data at various levels of aggregation. In our research we collaborated with 13 teachers from six primary schools and one intermediate school to use a Data Conversation Protocol to analyze and act on mathematics assessment data generated through a standardized assessment tool—the Progressive Achievement Test (PAT). Our intention was to optimize teacher use of this data for pedagogical decision making and action. At team meetings, the teachers co-constructed then refined a taken-as-shared definition for teacher data literacy for instructional action, which acted to inform and anchor our collaborative research. Data were collected in all teacher meetings and via interviews. Initial findings indicate that a ‘Data Conversation Protocol’ is helping teachers to slow down the process of considering, interpreting and making a judgement about their students’ understanding thereby opening up a space for deeper consideration of the range of possible reasons for student responses to assessment items. Students responded positively to teachers’ data informed small group teaching, gaining in understanding and confidence. Teachers considered this confidence translated to more positive engagement with mathematical ideas. Patterns and trends in student responses emerging from the teachers’ collaborative analysis of standard data supported a shift from viewing student responses as linked to student or school characteristics to critical analysis of how their teaching approaches might have contributed to student answers/misunderstandings. This finding has implications for how we might challenge assumptions about students through a willingness to engage critically with student achievement data. The importance of teachers having a rich pedagogical content knowledge as a basis for this was clearly evident.

year: 2021

title: Pace Regression

authors: Wang, Yong

subjects: Linear regression

abstract: This paper articulates a new method of linear regression, “pace regression”, that addresses many drawbacks of standard regression reported in the literature-particularly the subset selection problem. Pace regression improves on classical ordinary least squares (OLS) regression by evaluating the effect of each variable and using a clustering analysis to improve the statistical basis for estimating their contribution to the overall regression. As well as outperforming OLS, it also outperforms-in a remarkably general sense-other linear modeling techniques in the literature, including subset selection procedures, which seek a reduction in dimensionality that falls out as a natural byproduct of pace regression. The paper defines six procedures that share the fundamental idea of pace regression, all of which are theoretically justified in terms of asymptotic performance. Experiments confirm the performance improvement over other techniques.

text: Pace Regression This paper articulates a new method of linear regression, “pace regression”, that addresses many drawbacks of standard regression reported in the literature-particularly the subset selection problem. Pace regression improves on classical ordinary least squares (OLS) regression by evaluating the effect of each variable and using a clustering analysis to improve the statistical basis for estimating their contribution to the overall regression. As well as outperforming OLS, it also outperforms-in a remarkably general sense-other linear modeling techniques in the literature, including subset selection procedures, which seek a reduction in dimensionality that falls out as a natural byproduct of pace regression. The paper defines six procedures that share the fundamental idea of pace regression, all of which are theoretically justified in terms of asymptotic performance. Experiments confirm the performance improvement over other techniques.

year: 1999-09

title: Biological flora of New Zealand 11. Eleochairs spacelata, kuta, paopao, bamboo spike sedge.

authors: Kapa, Mieke M

subjects: cultural

abstract: Information relevant to the ecology and morphology of Eleocharis sphacelata (Cyperaceae) available through published and unpublished sources is assembled and reviewed. Eleocharis sphacelata is a freshwater wetland sedge found growing at the edge of lake margins, swamps, lagoons, and bogs within New Zealand, Australia, and Papua New Guinea. It is a perennial rhizomatous herb, with tall green cylindrical culms rising from submerged rhizomes generally buried under water in aerobic soils. A tendency to dominate the deepwater margins makes E. sphacelata crucial to the ecology of this habitat as a source of food, shelter, and protection for invertebrates, birds, and fish. Eleocharis sphacelata is commonly named giant spike-rush, kuta, or paopao. Māori have traditionally used the plant for clothing and warm coverings within whare (houses). Recent interest comes from its use in restoration plantings and constructed wetlands.

text: Biological flora of New Zealand 11. Eleochairs spacelata, kuta, paopao, bamboo spike sedge. Information relevant to the ecology and morphology of Eleocharis sphacelata (Cyperaceae) available through published and unpublished sources is assembled and reviewed. Eleocharis sphacelata is a freshwater wetland sedge found growing at the edge of lake margins, swamps, lagoons, and bogs within New Zealand, Australia, and Papua New Guinea. It is a perennial rhizomatous herb, with tall green cylindrical culms rising from submerged rhizomes generally buried under water in aerobic soils. A tendency to dominate the deepwater margins makes E. sphacelata crucial to the ecology of this habitat as a source of food, shelter, and protection for invertebrates, birds, and fish. Eleocharis sphacelata is commonly named giant spike-rush, kuta, or paopao. Māori have traditionally used the plant for clothing and warm coverings within whare (houses). Recent interest comes from its use in restoration plantings and constructed wetlands.

year: 2009