In Modeling Theory in Science Education, Halloun (2004) adopts the word ‘paradigm’, but his use of the term is radically different from that of Kuhn. In this paper,
I explore some of the differences between Kuhn’s paradigms and Halloun’s paradigms. Where Kuhn’s paradigms are public, community-defining
exemplars of practice, Halloun’s paradigms are private, individualized ways of thinking. Where Kuhn writes of the paradigm
shift as a revolutionary, vision-altering conversion experience, Halloun writes of a gradual evolution from one way of thinking
to another and an easy back-and-forth switch between paradigms. Since Kuhn’s paradigms are self-enclosed and incommensurable,
there is no objective standard by which one paradigm can be shown to be superior to the other. But Halloun uses ‘viability’
as a standard for paradigm choice. Underlying all of this is the more basic question of whether the history of science is
an appropriate metaphor for student progress in the classroom. I conclude with some brief thoughts on this question. 相似文献
INTRODUCTION Tracing a planar implicit curve f(x, y)=0 on a rectangular region [xl, xr]×[yb, yt] is of great interest in Computer-Aided Design and Computer Graphics. While parametric curves are easy to plot, plotting implicit curves is a challenging problem. Planar im- plicit curve plotting method can be classified into two categories (Shou et al., 2005; Martin et al., 2002; Lopes et al., 2002). In the first category are subdivi- sion methods (Shou et al., 2005; Martin et al., 2002) … 相似文献
The impact of misspecifying covariance matrices at the second and third levels of the three-level model is evaluated. Results indicate that ignoring existing covariance has no effect on the treatment effect estimate. In addition, the between-case variance estimates are unbiased when covariance is either modeled or ignored. If the research interest lies in the between-study variance estimate, including at least 30 studies is warranted. Modeling covariance does not result in less biased between-study variance estimates as the between-study covariance estimate is biased. When the research interest lies in the between-case covariance, the model including covariance results in unbiased between-case variance estimates. The three-level model appears to be less appropriate for estimating between-study variance if fewer than 30 studies are included. 相似文献
This study examines the organizational characteristics of 51 higher education institutions in relationship to student performance and growth. The study first finds that organizational measures of mission, size, wealth, complexity, and selectivity are statistically represented by the 2-year versus 4-year college mission. Findings indicate that 2-year and 4-year campuses indeed do exert significantly different influences on undergraduate GPA and self-reported intellectual growth. Next, the study uses both OLS regression and HLM to examine these influences. High school percentile rank and college classroom experiences are better predictors of Cum GPA at 4-year institutions, while student effort is a better predictor of GPA at 2-year institutions. Whereas the most important predictors of Cum GPA include precollege measures such as high school percentile rank and SAT score, the most influential predictors of student intellectual growth are campus experiences including classroom vitality, peer support, student effort, commitment, and involvement. Controlling for all other variables, students at 2-year institutions receive higher grades, and students at 4-year campuses experience more growth. 相似文献
Background: Reading is an interactive and constructive process of making meaning by engaging a variety of materials and sources and by participating in reading communities at school or in daily life.
Aim: The purpose of this study was to explore the factors affecting digital reading literacy among upper-elementary school students.
Method: A 3-stage stratified cluster sampling was implemented that resulted in a sample of 592 upper-elementary students from 29 classes in 7 schools. Self-Regulated Learning Strategies Assessment (S-RLSA), Digital Reading Literacy Assessment (DRLA), and student reports of their parents’ education backgrounds were used to collect data on the outcome and predictor variables. Interpretation of these data involved two highly regarded statistical techniques. First, structural equation modeling was used to explore relationships amongst the constructs. Second, multi-group invariance (MI) analyses were used to assess the influence of parental education and self-regulated learning strategies on students’ digital reading literacy.
Results: Enriching students’ family learning resources and strengthening their self-regulated learning abilities could have very important influences on promoting upper-elementary school students' digital reading literacy -webpage information retrieval, reading and communication abilities.
Conclusions: This study also provides information on how teachers can address student resources to improve digital reading literacy and self-regulated strategies. 相似文献
