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Journal ArticleDOI

The Influence of Teachers’ Knowledge on Student Learning in Middle School Physical Science Classrooms

01 Oct 2013-American Educational Research Journal (SAGE PublicationsSage CA: Los Angeles, CA)-Vol. 50, Iss: 5, pp 1020-1049
TL;DR: This paper examined the relationship between teacher knowledge and student learning for 9,556 students of 181 middle school physical science teachers and found that a teacher's ability to identify students' most common wrong answer on multiple-choice items, a form of pedagogical content knowledge, is an additional measure of science teacher competence.
Abstract: This study examines the relationship between teacher knowledge and student learning for 9,556 students of 181 middle school physical science teachers. Assessment instruments based on the National Science Education Standards with 20 items in common were administered several times during the school year to both students and their teachers. For items that had a very popular wrong answer, the teachers who could identify this misconception had larger classroom gains, much larger than if the teachers knew only the correct answer. On items on which students did not exhibit misconceptions, teacher subject matter knowledge alone accounted for higher student gains. This finding suggests that a teacher’s ability to identify students’ most common wrong answer on multiple-choice items, a form of pedagogical content knowledge, is an additional measure of science teacher competence.
Citations
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1,549 citations

Journal ArticleDOI
TL;DR: In this paper, the authors argue that the underlying model that the new Framework presents of science better represents contemporary understanding of nature of science as a social and cultural practice, and that adopting a framework of practices will enable better communication of meaning amongst professional science educators.
Abstract: This paper provides a rationale for the changes advocated by the Framework for K-12 Science Education and the Next Generation Science Standards. It provides an argument for why the model embedded in the Next Generation Science Standards is seen as an improvement. The Case made here is that the underlying model that the new Framework presents of science better represents contemporary understanding of nature of science as a social and cultural practice. Second, it argues that the adopting a framework of practices will enable better communication of meaning amongst professional science educators. This, in turn, will enable practice in the classroom to improve. Finally, the implications for teacher education are explored.

395 citations

01 Oct 2014
TL;DR: This paper reviewed over 200 pieces of research to identify the elements of teaching with the strongest evidence of improving attainment and found some common practices can be harmful to learning and have no grounding in research.
Abstract: This report reviews over 200 pieces of research to identify the elements of teaching with the strongest evidence of improving attainment. It finds some common practices can be harmful to learning and have no grounding in research. Specific practices which are supported by good evidence of their effectiveness are also examined and six key factors that contribute to great teaching are identified. The report also analyses different methods of evaluating teaching including: using ‘value-added’ results from student test scores; observing classroom teaching; and getting students to rate the quality of their teaching.

321 citations


Cites background from "The Influence of Teachers’ Knowledg..."

  • ...For example, Sadler et al (2013) tested a group of volunteer, experienced middle school (seventh and eighth grade) science teachers on their understanding of the content they were teaching and on the kinds of misconceptions they expected students to show....

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Journal ArticleDOI
TL;DR: It is found that students exhibit various misconceptions and other difficulties in syntactic knowledge, conceptual knowledge, and strategic knowledge and that developing and enhancing instructors’ pedagogical content knowledge (PCK), including their knowledge of students’ misconceptions and ability to apply effective instructional approaches and tools to addressStudents’ difficulties, is vital to the success of teaching introductory programming.
Abstract: Efforts to improve computer science education are underway, and teachers of computer science are challenged in introductory programming courses to help learners develop their understanding of programming and computer science. Identifying and addressing students’ misconceptions is a key part of a computer science teacher's competence. However, relevant research on this topic is not as fully developed in the computer science education field as it is in mathematics and science education. In this article, we first review relevant literature on general definitions of misconceptions and studies about students’ misconceptions and other difficulties in introductory programming. Next, we investigate the factors that contribute to the difficulties. Finally, strategies and tools to address difficulties including misconceptions are discussed.Based on the review of literature, we found that students exhibit various misconceptions and other difficulties in syntactic knowledge, conceptual knowledge, and strategic knowledge. These difficulties experienced by students are related to many factors including unfamiliarity of syntax, natural language, math knowledge, inaccurate mental models, lack of strategies, programming environments, and teachers’ knowledge and instruction. However, many sources of students’ difficulties have connections with students’ prior knowledge. To better understand and address students’ misconceptions and other difficulties, various instructional approaches and tools have been developed. Nevertheless, the dissemination of these approaches and tools has been limited. Thus, first, we suggest enhancing the dissemination of existing tools and approaches and investigating their long-term effects. Second, we recommend that computing education research move beyond documenting misconceptions to address the development of students’ (mis)conceptions by integrating conceptual change theories. Third, we believe that developing and enhancing instructors’ pedagogical content knowledge (PCK), including their knowledge of students’ misconceptions and ability to apply effective instructional approaches and tools to address students’ difficulties, is vital to the success of teaching introductory programming.

316 citations


Cites background from "The Influence of Teachers’ Knowledg..."

  • ...Teachers’ knowledge of student misconceptions and/or ability to assess students and reveal their misconceptions is thought to be important to effective teaching (Sadler et al. 2013)....

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  • ...In addition, teachers’ poor content knowledge may also lead to students’ misconceptions (Sadler et al. 2013)....

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References
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Book
01 Dec 1969
TL;DR: The concepts of power analysis are discussed in this paper, where Chi-square Tests for Goodness of Fit and Contingency Tables, t-Test for Means, and Sign Test are used.
Abstract: Contents: Prefaces. The Concepts of Power Analysis. The t-Test for Means. The Significance of a Product Moment rs (subscript s). Differences Between Correlation Coefficients. The Test That a Proportion is .50 and the Sign Test. Differences Between Proportions. Chi-Square Tests for Goodness of Fit and Contingency Tables. The Analysis of Variance and Covariance. Multiple Regression and Correlation Analysis. Set Correlation and Multivariate Methods. Some Issues in Power Analysis. Computational Procedures.

115,069 citations


"The Influence of Teachers’ Knowledg..." refers background in this paper

  • ...While gains appear relatively small (Table 2), it is more useful to express them as effect size, or gain calculated in units of standard deviation of the pretest score (Cohen, 1969)....

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Book
01 Jan 1989
TL;DR: Hosmer and Lemeshow as discussed by the authors provide an accessible introduction to the logistic regression model while incorporating advances of the last decade, including a variety of software packages for the analysis of data sets.
Abstract: From the reviews of the First Edition. "An interesting, useful, and well-written book on logistic regression models... Hosmer and Lemeshow have used very little mathematics, have presented difficult concepts heuristically and through illustrative examples, and have included references."- Choice "Well written, clearly organized, and comprehensive... the authors carefully walk the reader through the estimation of interpretation of coefficients from a wide variety of logistic regression models . . . their careful explication of the quantitative re-expression of coefficients from these various models is excellent." - Contemporary Sociology "An extremely well-written book that will certainly prove an invaluable acquisition to the practicing statistician who finds other literature on analysis of discrete data hard to follow or heavily theoretical."-The Statistician In this revised and updated edition of their popular book, David Hosmer and Stanley Lemeshow continue to provide an amazingly accessible introduction to the logistic regression model while incorporating advances of the last decade, including a variety of software packages for the analysis of data sets. Hosmer and Lemeshow extend the discussion from biostatistics and epidemiology to cutting-edge applications in data mining and machine learning, guiding readers step-by-step through the use of modeling techniques for dichotomous data in diverse fields. Ample new topics and expanded discussions of existing material are accompanied by a wealth of real-world examples-with extensive data sets available over the Internet.

35,847 citations

Journal ArticleDOI
TL;DR: Applied Logistic Regression, Third Edition provides an easily accessible introduction to the logistic regression model and highlights the power of this model by examining the relationship between a dichotomous outcome and a set of covariables.
Abstract: \"A new edition of the definitive guide to logistic regression modeling for health science and other applicationsThis thoroughly expanded Third Edition provides an easily accessible introduction to the logistic regression (LR) model and highlights the power of this model by examining the relationship between a dichotomous outcome and a set of covariables. Applied Logistic Regression, Third Edition emphasizes applications in the health sciences and handpicks topics that best suit the use of modern statistical software. The book provides readers with state-of-the-art techniques for building, interpreting, and assessing the performance of LR models. New and updated features include: A chapter on the analysis of correlated outcome data. A wealth of additional material for topics ranging from Bayesian methods to assessing model fit Rich data sets from real-world studies that demonstrate each method under discussion. Detailed examples and interpretation of the presented results as well as exercises throughout Applied Logistic Regression, Third Edition is a must-have guide for professionals and researchers who need to model nominal or ordinal scaled outcome variables in public health, medicine, and the social sciences as well as a wide range of other fields and disciplines\"--

30,190 citations


"The Influence of Teachers’ Knowledg..." refers background in this paper

  • ...Here, in the logistic realm, statisticians have developed a whole range of goodness-of-fit measures, and debate continues about their relative strengths and weaknesses (Allen & Le, 2008; Hosmer & Lemeshow, 1989; Menard, 2000)....

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Journal ArticleDOI
TL;DR: In this paper, Shulman observa la historia de evaluaciones docentes, noting that the evaluación docente parecia preocuparse tanto por los conocimientos, como el siglo anterior se preoccupaba por la pedagogia.
Abstract: Este articulo fue un discurso presidencial en la reunion de America Educational Research Association de Chicago el ano 1985. -- Curioso sobre el por que el publico a menudo tiene una baja opinion sobre el conocimiento de los profesores, Shulman observa la historia de evaluaciones docentes. En la segunda mitad del 1800, las evaluaciones para quienes deseaban ensenar se basaban casi por completo en contenido. Para el ano en que el autor escribe el articulo, en 1985, la evaluacion era completamente distinta. En lugar de enfocarse en contenido, se enfocaba en topicos como planificacion de clases, sensibilizacion cultural, y otros aspectos de la conducta docente. Mientras los topicos usualmente tenian raices en la investigacion, claramente no representan el amplio espectro de habilidades y conocimientos que un docente necesita para ser efectivo. Mas especificamente, para los anos 80', la evaluacion docente parecia preocuparse tanto por los conocimientos, como el siglo anterior se preocupaba por la pedagogia.

15,740 citations


"The Influence of Teachers’ Knowledg..." refers background in this paper

  • ...SMK is defined as the general conceptual understanding of a subject area possessed by a teacher, which is obtained by completing the required coursework (Shulman, 1986)....

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Book
01 Jan 2003
TL;DR: In this paper, a framework for investigating change over time is presented, where the multilevel model for change is introduced and a framework is presented for investigating event occurrence over time.
Abstract: PART I 1. A framework for investigating change over time 2. Exploring Longitudinal Data on Change 3. Introducing the multilevel model for change 4. Doing data analysis with the multilevel mode for change 5. Treating TIME more flexibly 6. Modelling discontinuous and nonlinear change 7. Examining the multilevel model's error covariance structure 8. Modelling change using covariance structure analysis PART II 9. A Framework for Investigating Event Occurrence 10. Describing discrete-time event occurrence data 11. Fitting basic Discrete-Time Hazard Models 12. Extending the Discrete-Time Hazard Model 13. Describing Continuous-Time Event Occurrence Data 14. Fitting Cox Regression Models 15. Extending the Cox Regression Model

8,435 citations


"The Influence of Teachers’ Knowledg..." refers background or methods in this paper

  • ...…for the goodness of fit of the estimated model (intuitively interpretable as the proportion of variance in the dependent variable that is explained by the model), measuring goodness of fit becomes more complicated for hierarchical models that partition the overall variance (Singer & Willett, 2003)....

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  • ...We chose a pseudo-R2 that consists of the squared correlation between the observed and the predicted values (Singer & Willett, 2003, p. 102)....

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