Journal articles: 'Education – Research – Statistics'

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Jolliffe, Flavia, and Iddo Gal. "Statistics Education Research Journal." MSOR Connections 4, no. 3 (2004): 58. http://dx.doi.org/10.11120/msor.2004.04030058.

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Jollifte, Flavia. "Statistics Education Research Journal (SERJ)." MSOR Connections 2, no. 3 (2002): 5. http://dx.doi.org/10.11120/msor.2002.02030005.

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Huh, Myung-Hoe. "Law and Statistics: Education, Applications and Research." Korean Journal of Applied Statistics 23, no. 4 (2010): 725–38. http://dx.doi.org/10.5351/kjas.2010.23.4.725.

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Ograjenšek, Irena, and Iddo Gal. "Enhancing Statistics Education by Including Qualitative Research." International Statistical Review 84, no. 2 (2015): 165–78. http://dx.doi.org/10.1111/insr.12158.

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Ottaviani, Maria-Gabriella. "Research into Statistics Education as a Discipline." International Statistical Review 73, no. 2 (2007): 207–9. http://dx.doi.org/10.1111/j.1751-5823.2005.tb00272.x.

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Asher, William. "The Role of Statistics in Research." Journal of Experimental Education 61, no. 4 (1993): 388–93. http://dx.doi.org/10.1080/00220973.1993.10806599.

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Puryear, Jeffrey M. "International education statistics and research: Status and problems." International Journal of Educational Development 15, no. 1 (1995): 79–91. http://dx.doi.org/10.1016/0738-0593(94)e0015-g.

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Darmi, Mario. "Statistics in aquacultural research." Journal of Biological Education 30, no. 1 (1996): 52–56. http://dx.doi.org/10.1080/00219266.1996.9655477.

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Merrill, Ray M., Christopher A. Lindsay, Eric C. Shields, and Julianne Stoddard. "Perspective: Have the Focus and Sophistication of Research in Health Education Changed?" Health Education & Behavior 34, no. 1 (2006): 10–25. http://dx.doi.org/10.1177/1090198106288564.

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This study assessed the types of research and the statistical methods used in three representative health education journals from 1994 through 2003. Editorials, commentaries, program/practice notes, and perspectives represent 17.6% of the journals’ content. The most common types of articles are cross-sectional studies (27.5%), reviews (23.2%), and analytic studies (i.e., case-control, cohort, and experimental studies) (18.4%). The estimated annual percentage change across the study period in these types of articles was 3.3, -9.3, and 5.5, respectively. A significant increase was observed in use of descriptive statistics (estimated annual percentage change = 2.4), parametric test statistics (4.4), nonparametric test statistics (3.5), epidemiologic statistics (10.3), generalized linear models (6.8), validation statistics (6.7), and other statistics (8.2). Movement toward increasing use of cross-sectional studies, analytic study designs, and statistical methods—representing greater emphasis on needs assessment for health education, health education program development, and program evaluation—indicates the need for better quantitatively trained health educators.

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Gal, Iddo, and Irena Ograjenšek. "Official Statistics and Statistics Education: Bridging the Gap." Journal of Official Statistics 33, no. 1 (2017): 79–100. http://dx.doi.org/10.1515/jos-2017-0005.

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Abstract This article aims to challenge official statistics providers and statistics educators to ponder on how to help non-specialist adult users of statistics develop those aspects of statistical literacy that pertain to official statistics. We first document the gap in the literature in terms of the conceptual basis and educational materials needed for such an undertaking. We then review skills and competencies that may help adults to make sense of statistical information in areas of importance to society. Based on this review, we identify six elements related to official statistics about which non-specialist adult users should possess knowledge in order to be considered literate in official statistics: (1) the system of official statistics and its work principles; (2) the nature of statistics about society; (3) indicators; (4) statistical techniques and big ideas; (5) research methods and data sources; and (6) awareness and skills for citizens’ access to statistical reports. Based on this ad hoc typology, we discuss directions that official statistics providers, in cooperation with statistics educators, could take in order to (1) advance the conceptualization of skills needed to understand official statistics, and (2) expand educational activities and services, specifically by developing a collaborative digital textbook and a modular online course, to improve public capacity for understanding of official statistics.

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Cover, J. Daniel, J. Levin, J. A. Fox, W. C. Levin, and J. Levin. "Elementary Statistics in Social Research." Teaching Sociology 18, no. 1 (1990): 95. http://dx.doi.org/10.2307/1318246.

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Kamali, Ali, Jack Levin, and James Allen Fox. "Elementary Statistics in Social Research." Teaching Sociology 21, no. 4 (1993): 416. http://dx.doi.org/10.2307/1319094.

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Zellner, Kathleen, Connie J. Boerst, and Wil Tabb. "Statistics Used in Current Nursing Research." Journal of Nursing Education 46, no. 2 (2007): 55–59. http://dx.doi.org/10.3928/01484834-20070201-03.

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Little, Steven G., Angeleque Akin-Little, and Howard B. Lee. "Education in Statistics and Research Design in School Psychology." School Psychology International 24, no. 4 (2003): 437–48. http://dx.doi.org/10.1177/01430343030244006.

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Pallesen, Palle Bo, Torill Tverborgvik, Hanna Barbara Rasmussen, and Elsebeth Lynge. "Data on education: From population statistics to epidemiological research." Scandinavian Journal of Public Health 38, no. 2 (2010): 177–83. http://dx.doi.org/10.1177/1403494809357104.

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GROTH, RANDALL E. "DEVELOPING STATISTICAL KNOWLEDGE FOR TEACHING DURING DESIGN-BASED RESEARCH." STATISTICS EDUCATION RESEARCH JOURNAL 16, no. 2 (2017): 376–96. http://dx.doi.org/10.52041/serj.v16i2.197.

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Statistical knowledge for teaching is not precisely equivalent to statistics subject matter knowledge. Teachers must know how to make statistics understandable to others as well as understand the subject matter themselves. This dual demand on teachers calls for the development of viable teacher education models. This paper offers one such model, which relies upon engaging teachers in design-based research. Teachers collaborate with a researcher to design, implement, and analyze instruction to pursue desired statistical learning outcomes for students. The researcher allows teachers enough autonomy to make and learn from mistakes during the process. Unpacking and addressing the mistakes has value as a means of teacher learning. The model and a specific instance of its implementation are described along with reflections on how productive mistakes during design-based research provide opportunities for fostering the development of statistical knowledge for teaching.  First published November 2017 at Statistics Education Research Journal Archives

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Leech, Nancy, and Carolyn A. Haug. "Investigating Graduate Level Research and Statistics Courses in Schools of Education." International Journal of Doctoral Studies 10 (2015): 093–110. http://dx.doi.org/10.28945/2111.

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Instruction in research methods, particularly statistical training, is an essential requirement for most higher education advanced-degree students. However, results from the institutional survey reported here demonstrate that many faculty in schools of education still do not require or offer a variety of research and analysis courses to provide this training. This article will explore graduate-level requirements for research methods and data analysis courses in schools of education across the United States. Two surveys, one asking questions about research methods courses and one about statistics courses, were distributed through listservs to faculty at institutions of higher education. Twenty-eight responses, representing 28 institutions, were collected for the research course survey and 19 responses, representing 19 institutions, were collected for the statistics course survey. The number of courses offered and required and the number of credit hours for them are presented for Master’s, Ed.D., and Ph.D. students. From this study, it is evident that several universities do not offer or require many research methods or statistics courses for education graduate students. The authors intend that this information will assist faculty in rethinking what coursework is necessary to educate successful graduate students.

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Raudenbush, Stephen W., and Daniel Schwartz. "Randomized Experiments in Education, with Implications for Multilevel Causal Inference." Annual Review of Statistics and Its Application 7, no. 1 (2020): 177–208. http://dx.doi.org/10.1146/annurev-statistics-031219-041205.

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Education research has experienced a methodological renaissance over the past two decades, with a new focus on large-scale randomized experiments. This wave of experiments has made education research an even more exciting area for statisticians, unearthing many lessons and challenges in experimental design, causal inference, and statistics more broadly. Importantly, educational research and practice almost always occur in a multilevel setting, which makes the statistics relevant to other fields with this structure, including social policy, health services research, and clinical trials in medicine. In this article we first briefly review the history that led to this new era in education research and describe the design features that dominate the modern large-scale educational experiments. We then highlight some of the key statistical challenges in this area, including endogeneity of design, heterogeneity of treatment effects, noncompliance with treatment assignment, mediation, generalizability, and spillover. Though a secondary focus, we also touch on promising trial designs that answer more nuanced questions, such as the SMART design for studying dynamic treatment regimes and factorial designs for optimizing the components of an existing treatment.

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Harwell, Michael R., Mary Lee Herrick, Deborah Curtis, Daniel Mundfrom, and Karen Gold. "Evaluating Statistics Texts Used in Education." Journal of Educational and Behavioral Statistics 21, no. 1 (1996): 3–34. http://dx.doi.org/10.3102/10769986021001003.

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Evaluating texts is an important activity associated with teaching statistics. Surprisingly, the statistical education literature offers little guidance on how these evaluations should be conducted. This lack of guidance may be at least partly responsible for the fact that published evaluations of statistics texts almost invariably employ evaluation criteria that lack any theory-based rationale. This failing is typically compounded by a lack of empirical evidence supporting the usefulness of the criteria. This article describes the construction and piloting of instruments for evaluating statistics texts that are grounded in the statistical education and text evaluation literatures. The study is an initial step in a line of research which we hope will result in the establishment and maintenance of a database of evaluations of statistical texts. Evaluative information of this kind should assist instructors wrestling with text selection decisions and individuals charged with performing evaluations, such as journal reviewers, and should ultimately benefit the direct consumers of these texts—the students.

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Thompson, W. Burt. "Making Data Analysis Realistic: Incorporating Research into Statistics Courses." Teaching of Psychology 21, no. 1 (1994): 41–43. http://dx.doi.org/10.1207/s15328023top2101_9.

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I describe the use of a student-designed Student Information Questionnaire that generates a large data set useful for teaching a variety of statistical procedures and concepts. This questionnaire helps statistics instructors minimize the use of uninteresting artificial data in their classes. Also, students learn firsthand that data analysis is an integral part of the research process, rather than an isolated set of procedures. Evaluations of the technique suggest that students find real data more interesting than artificial data and more helpful for learning statistics.

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Mulvenon, Sean W., and Victor X. Wang. "Graduate Level Research Methods and Statistics Courses." International Journal of Adult Vocational Education and Technology 6, no. 4 (2015): 1–11. http://dx.doi.org/10.4018/ijavet.2015100101.

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The goal of an educational system or degree program is to “educate” students. This immediately raises the question of what does it mean to “educate” students. All academic institutions, degree programs and content areas are typically expected to answer this question and establish appropriate academic expectations both within the classroom and as part of their specific academic programs. The theme of this special edition is to provide insight on the challenges of improving graduation rates in both undergraduate and graduate education. As a statistics professor, on many occasions the authors have been part of both college and university committees on research methodology, statistics, and other academic requirements associated with graduate education. The purpose this article is to provide an overview of these experiences and the authors' perspective on how to improve success of students in methodology and statistics courses associated with successfully completing a graduate degree.

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Lovekamp, William E., Shane D. Soboroff, and Michael D. Gillespie. "Engaging Students in Survey Research Projects across Research Methods and Statistics Courses." Teaching Sociology 45, no. 1 (2016): 65–72. http://dx.doi.org/10.1177/0092055x16673136.

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One innovative way to help students make sense of survey research has been to create a multifaceted, collaborative assignment that promotes critical thinking, comparative analysis, self-reflection, and statistical literacy. We use a short questionnaire adapted from the Higher Education Research Institute’s Cooperative Institutional Research Program’s Freshman Survey. In our Research Methods course, students begin by administering the brief questionnaire to a small, nonrandom sample of students at our university. They analyze the data descriptively and compare their “results” to the national trends as part of their required course homework. These data are then quantitatively analyzed throughout all homework exercises the next semester during their statistics course. This collaborative effort bridges methods, statistics, and capstone courses, helping students connect the courses and develop a deeper understanding, awareness and appreciation of the utility of preestablished instruments for collecting primary data and for assessing the meaning of secondary data.

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Et. al., Ibnatul Jalilah Yusof,. "Assessing Statistical Literacy Level of Postgraduate Education Research Students in Malaysian Research Universities." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 5 (2021): 1318–24. http://dx.doi.org/10.17762/turcomat.v12i5.1800.

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Statistical literacy is an essential component of research literacy demanded for the research students to master as they are required to read, comprehend, and evaluate research articles. Misinterpretations of data and research findings are among the unfavorable results in the lack of research literacy. Consequently, it will affect the quality of their research and eventually leads to ripple impact on other researchers. However, this study is still under researched especially among postgraduate research students. Therefore, this paper examined statistical literacy level among postgraduate research students. This study was a survey conducted with a sample of 236 education postgraduate research students by using a set of statistical literacy items. The data were analysed using Rasch Analysis approach which includes item and person measures. Findings suggested that postgraduate students‘ statistical literacy level is at Moderate Low level. The findings also revealed that the hardest items to be answered by the students are related to hypothesis testing (significant value). In order for students to improve their statistical literacy, this study suggested that the instructors and institutions to reexamine and to explore new methods of teaching and learning statistics.

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Domański, Czesław. "Challenges to statistical education of the society." Wiadomości Statystyczne. The Polish Statistician 61, no. 9 (2016): 109–15. http://dx.doi.org/10.5604/01.3001.0014.1099.

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The article discusses the latest challenges of research and teaching related to statistical education of the society. The technological revolution change the economic and social life radically. They require a transformation of the way of thinking and acting. Society need statistics that provides information about the country and its neighbors. Through statistics citizens can actively participate in democratic processes. These new conditions define the tasks set for the statisticians — to develop statistics skills and adapt statistical information to the needs of citizens.

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Park,Sang-Hee, 이선재, Sungdoo Hong, and Kim Nam Soon. "Methodological Implications of Bayesian Statistics for Research about Special Education." Journal of Special Children Education 11, no. 3 (2009): 341–56. http://dx.doi.org/10.21075/kacsn.2009.11.3.341.

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Resnik, David B. "Statistics, ethics, and research: An agenda for education and reform." Accountability in Research 8, no. 1-2 (2000): 163–88. http://dx.doi.org/10.1080/08989620008573971.

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DELMAS, ROBERT, and PETER PETOCZ. "CALL FOR PAPERS: A GLOBAL VIEW OF STATISTICS EDUCATION RESEARCH." STATISTICS EDUCATION RESEARCH JOURNAL 11, no. 1 (2012): 45–47. http://dx.doi.org/10.52041/serj.v11i1.342.

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RESTON, ENRIQUETA, SARAS KRISHNAN, and NORAINI IDRIS. "STATISTICS EDUCATION RESEARCH IN MALAYSIA AND THE PHILIPPINES: A COMPARATIVE ANALYSIS." STATISTICS EDUCATION RESEARCH JOURNAL 13, no. 2 (2014): 218–31. http://dx.doi.org/10.52041/serj.v13i2.292.

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This paper presents a comparative analysis of statistics education research in Malaysia and the Philippines by modes of dissemination, research areas, and trends. An electronic search for published research papers in the area of statistics education from 2000–2012 yielded 20 for Malaysia and 19 for the Philippines. Analysis of these papers showed that most were primarily empirical research published in national refereed journals or in conference proceedings. Statistics education research in Malaysia has focused on integration of technology and on affective aspects of statistics learning. In the Philippines, studies have investigated university-level statistics pedagogy, statistics academic programs and teachers’ professional development. Implications for future statistics education research and teaching practice in these two countries are identified. First published November 2014 at Statistics Education Research Journal Archives

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GREEN, JENNIFER L., WENDY M. SMITH, APRIL T. KERBY, ERIN E. BLANKENSHIP, KENDRA K. SCHMID, and MARY ALICE CARLSON. "INTRODUCTORY STATISTICS: PREPARING IN-SERVICE MIDDLE-LEVEL MATHEMATICS TEACHERS FOR CLASSROOM RESEARCH." STATISTICS EDUCATION RESEARCH JOURNAL 17, no. 2 (2018): 216–38. http://dx.doi.org/10.52041/serj.v17i2.167.

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In this study, we examined how in-service middle-level mathematics teachers used statistics in their own classroom research. Using an embedded single-case design, we analyzed a purposefully selected sample of nine teachers’ classroom research papers, identifying several themes within each phase of the statistical problem solving process to summarize how teachers 1) planned studies and collected data, 2) analyzed data, and 3) interpreted results. The results illustrate the varying ways in which teachers used statistics to make data-based decisions about their classrooms, revealing teachers’ early development in their statistical thinking and suggesting that teachers’ required knowledge of statistics is multi-faceted, requiring both a pedagogical component and statistical knowledge for the teaching profession. Such findings have important implications for how we, as teacher educators, can best meet teachers’ professional needs. First published November 2018 at Statistics Education Research Journal Archives

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Garfield, Joan, and Andrew Ahlgren. "Difficulties in Learning Basic Concepts in Probability and Statistics: Implications for Research." Journal for Research in Mathematics Education 19, no. 1 (1988): 44–63. http://dx.doi.org/10.5951/jresematheduc.19.1.0044.

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There is a growing movement to introduce elements of statistics and probability into the secondary and even the elementary school curriculum, as part of basic literacy in mathematics. Although many articles in the education literature recommend how to teach statistics better, there is little published research on how students actually learn statistics concepts. The experience of psychologists, educators, and statisticians alike is that a large proportion of students, even in college, do not understand many of the basic statistical concepts they have studied.

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Veilleux, Jennifer C., and Kate M. Chapman. "Development of a Research Methods and Statistics Concept Inventory." Teaching of Psychology 44, no. 3 (2017): 203–11. http://dx.doi.org/10.1177/0098628317711287.

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Research methods and statistics are core courses in the undergraduate psychology major. To assess learning outcomes, it would be useful to have a measure that assesses research methods and statistical literacy beyond course grades. In two studies, we developed and provided initial validation results for a research methods and statistical knowledge concept inventory for eventual use in further scholarship of teaching and learning. In Study 1, we created vignettes and administered open-ended questions to psychology subject pool students. In Study 2, we refined the vignettes and created multiple-choice items using participant responses from Study 1. After administering the measure to psychology subject pool students and a community-based sample of Amazon Mechanical Turk workers, we used item response theory to select 20 items to compose the final Psychological Research Inventory of Concepts.

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Beins, Bernard. "Teaching the Relevance of Statistics through Consumer-Oriented Research." Teaching of Psychology 12, no. 3 (1985): 168–69. http://dx.doi.org/10.1207/s15328023top1203_16.

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Students in a small experimental design class obtained information about statistical and research applications concerning a variety of products advertised by different companies. The resulting data were perceived to have several advantages for the students: (a) it made collecting and interpreting data more interesting and less mysterious, (b) it helped them to understand how research design and statistics are used in real-life situations, and (c) it helped them to make more discerning judgments about advertisers' claims for their products.

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Leppink, Jimmie. "Statistics for N = 1." Scientia Medica 30, no. 1 (2020): e38066. http://dx.doi.org/10.15448/1980-6108.2020.1.38066.

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Research in education is often associated with comparing group averages and linear relations in sufficiently large samples and evidence-based practice is about using the outcomes of that research in the practice of education. However, there are questions that are important for the practice of education that cannot really be addressed by comparisons of group averages and linear relations, no matter how large the samples. Besides, different types of constraints including logistic, financial, and ethical ones may make larger-sample research unfeasible or at least questionable. What has remained less known in many fields is that there are study designs and statistical methods for research involving small samples or even individuals that allow us to address questions of importance for the practice of education. This article discusses one type of such situations and provides a simple coherent statistical approach that provides point and interval estimates of differences of interest regardless of the type of the outcome variable and that is of use in other types of studies involving large samples, small samples, and single individuals.

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Magee, Gregory. "Education Reduces Recidivism." Technium Social Sciences Journal 16 (February 10, 2021): 175–82. http://dx.doi.org/10.47577/tssj.v16i1.2668.

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The research addresses how and why formal education lowers recidivism rates. Formal education means much of the learning comes from a book or other learning material delivered by a trained teacher. The two types of formal education discussed are academic and vocational education. Statistics for lowered recidivism rates resulting from education are essential to support this topic. How education, either academic or vocational, can prevent crime was the first avenue of the research topic that is explored. There are countless opportunities higher education provides to individuals. Next, a direct correlation between education and crime was looked at from a statistical view regarding the recidivism rate. The progress education has on the prison system exposes the results. A simple examination of statistics regarding the recidivism rate of the selected participants involved in the prison education system will resemble what success or effectiveness has come from education being implemented.

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Powers, Jeanne M., and Peter W. Cookson. "The Politics of School Choice Research: Fact, Fiction, and Statistics." Educational Policy 13, no. 1 (1999): 104–22. http://dx.doi.org/10.1177/0895904899131009.

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STERN, DAVID, ROGER STERN, DANNY PARSONS, JAMES MUSYOKA, FRANCIS TORGBOR, and ZACH MBASU. "ENVISIONING CHANGE IN THE STATISTICS-EDUCATION CLIMATE." STATISTICS EDUCATION RESEARCH JOURNAL 19, no. 1 (2020): 206–25. http://dx.doi.org/10.52041/serj.v19i1.131.

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The African Data Initiative started as a crowd-sourced campaign to improve the teaching of statistics in African universities. The analysis of climate data provides one suitable context to illustrate ideas that lead to a radical new form of teaching. The problem within the context comes first, the technicalities are largely reduced – mathematics is supported by meta knowledge and backed up by modelling; calculations are reduced by user-friendly software that is also used by experts. The problems are treated similarly to research questions and the results are often easier to interpret, making sense as potential answers in their context. The criteria of this approach are compared to the framework proposed by W. G. Cobb to reform statistics education in the light of the latest developments in statistics, driven by the huge increase of data. Implementation details are presented around three components: case studies, data, and the required skills. Together, these three components describe an alternative education pathway centred around statistical problem solving. The focus on interpretations of results within a real context enables software, mathematical thinking and modelling to play a supportive role, which flattens the prerequisites of complex methods and encourages their use across all levels of education. First published February 2020 at Statistics Education Research Journal Archives

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RAMIREZ, CAROLINE, CANDACE SCHAU, and ESMA EMMİOĞLU. "THE IMPORTANCE OF ATTITUDES IN STATISTICS EDUCATION." STATISTICS EDUCATION RESEARCH JOURNAL 11, no. 2 (2012): 57–71. http://dx.doi.org/10.52041/serj.v11i2.329.

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People forget what they do not use. But attitudes “stick.” Our article emphasizes the importance of students’ attitudes toward statistics. We examine 15 surveys that purport to assess these attitudes and then describe the Survey of Attitudes Toward Statistics, a commonly used attitude survey. We present our conceptual model of Students’ Attitudes Toward Statistics (SATS-M), which is congruent with Eccles and colleagues’ Expectancy-Value Theory (Eccles’ EVT), as well as others. The SATS-M includes three broad constructs that impact Statistics Course Outcomes: Student Characteristics, Previous Achievement-Related Experiences, and Statistics Attitudes. We briefly describe Eccles’ EVT and other theories that support our SATS-M. We relate findings from research using the SATS to our model and end with implications for statistics education. First published November 2012 at Statistics Education Research Journal: Archives

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Maguire, Thomas, and Glenn Rowley. "Roles for Inferential Statistics in Educational Research." Educational Philosophy and Theory 24, no. 2 (1992): 56–77. http://dx.doi.org/10.1111/j.1469-5812.1992.tb00225.x.

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Giesbrecht, N., Y. Sell, C. Scialfa, L. Sandals, and P. Ehlers. "Essential Topics in Introductory Statistics and Methodology Courses." Teaching of Psychology 24, no. 4 (1997): 242–46. http://dx.doi.org/10.1207/s15328023top2404_2.

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The purpose of this research is to assess interdisciplinary agreement about the content of an introductory course in statistics and research methods. We compiled a set of methodological and statistical topics from relevant research, introductory textbooks, and course descriptions. Eighteen professors in the natural sciences, social sciences, and education assessed the importance of these topics for a hypothetical introductory statistics and research methods course. Results indicate agreement across disciplines on the relative importance of 97% of the statistical topics, with 75% of these topics deemed to be important. In contrast, there is agreement on the relative importance of only 48% of the research methods topics. The results are useful in the evaluation of existing statistics courses and texts. In addition, the data provide support for interdisciplinary introductory statistics instruction but also raise questions regarding the apparent discipline-specific nature of instruction in methodology.

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BOROVCNIK, MANFRED, LEANDRO DE OLIVEIRA SOUZA, MAUREN PORCIÚNCULA, LUCÍA ZAPATA-CARDONA, and AUDY SALCEDO. "CALL FOR PAPERS: STATISTICS EDUCATION RESEARCH FROM A LATIN AMERICAN PERSPECTIVE." STATISTICS EDUCATION RESEARCH JOURNAL 18, no. 1 (2019): 6–7. http://dx.doi.org/10.52041/serj.v18i1.146.

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DELMAS, ROBERT, and PETER PETOCZ. "CALL FOR NOMINATIONS FOR NEW CO-EDITOR: STATISTICS EDUCATION RESEARCH JOURNAL." STATISTICS EDUCATION RESEARCH JOURNAL 10, no. 2 (2011): 3–4. http://dx.doi.org/10.52041/serj.v10i2.344.

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Groth, Randall E. "Research Commentary: Working at the Boundaries of Mathematics Education and Statistics Education Communities of Practice." Journal for Research in Mathematics Education 46, no. 1 (2015): 4–16. http://dx.doi.org/10.5951/jresematheduc.46.1.0004.

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Statistics education has begun to mature as a discipline distinct from mathematics education, creating new perspectives on the teaching and learning of statistics. This commentary emphasizes the importance of coordinating perspectives from statistics education and mathematics education through boundary interactions between the two communities of practice. I argue that such interactions are particularly vital in shared problem spaces related to the teaching and learning of measurement, variability, and contextualized problems. Collaborative work within these shared problem spaces can contribute to the vitality of each discipline. Neglect of the shared problem spaces may contribute to insularity and have negative consequences for research and school curricula. Challenges of working at the boundaries are considered, and strategies for overcoming the challenges are proposed.

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Castro Sotos, Ana Elisa, Stijn Vanhoof, Wim Van den Noortgate, and Patrick Onghena. "Students’ misconceptions of statistical inference: A review of the empirical evidence from research on statistics education." Educational Research Review 2, no. 2 (2007): 98–113. http://dx.doi.org/10.1016/j.edurev.2007.04.001.

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Bebermeier, Sarah, and Anne Hagemann. "Creating Statistics Exercises on the Basis of Research Articles." Teaching of Psychology 46, no. 3 (2019): 240–45. http://dx.doi.org/10.1177/0098628319853938.

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Markert, R. J. "A research methods and statistics journal club for residents." Academic Medicine 64, no. 4 (1989): 223–4. http://dx.doi.org/10.1097/00001888-198904000-00014.

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Dunn, Dana S. "Collaborative Writing in a Statistics and Research Methods Course." Teaching of Psychology 23, no. 1 (1996): 38–40. http://dx.doi.org/10.1207/s15328023top2301_8.

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I apply two writing techniques—collaborative writing and peer review—to an experimental project in a statistics and research methods course. Student reactions to the collaboration and peer exercise are discussed.

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Afrizon, Renol, and Wahyuni Satria Dewi. "Kepraktisan Bahan Ajar Statistika Pendidikan Fisika Bermuatan Model Cooperative Problem Solving." JURNAL EKSAKTA PENDIDIKAN (JEP) 3, no. 1 (2019): 26. http://dx.doi.org/10.24036/jep/vol3-iss1/311.

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The statistics of physics education are compulsory course with a lot of material descriptions so the lectures must be assisted by the use of teaching materials. The lectures of statistics of physics education that took place in the July-December 2017 semester illustrates that: 1) teaching materials are less attractive to students, 2) the assignments given are quite clear and sufficient in accordance with the level of thinking of students, 3) materials delivered by the lecturer is in accordance with the targets in the syllabus with some material is still abstract, 4) the lecture have been pursued in accordance with the syllabus but the methods used have not varied and 5) students learn material of statistic of physics education only from the lecturer explanation so that only a few students can answer statistical problems quickly and correctly. This indicates that it is need provided teaching materials with a cooperative problem solving model. The author has tried to design teaching materials of statistic of physics education with cooperative problem solving models with very valid criteria according to the assessment of six experts with educational qualifications of statistics and physics education. However, this teaching material has not been tested at normal conditions in the lectures so that the level of practicality has not been revealed. The aim of this study was to determine the practicality level of educational statistical teaching materials containing cooperative problem solving models according to users, namely lecturers and students who listed in the course. Type of research is research and devel-opment with the ADDIE model. The ADDIE model stands for Analyze, Design, Develop, Implement and Evaluation. This research is part of the Implementation stage where development products are implemented in real terms so that the level of practicality can be measured with indicators of ease of use, attractiveness and efficiency. Data collection used student response questionnaires and lecturer response questionnaires with a Likert scale. Data analysis used descriptive statistic analysis techniques. The results showed that teaching materials of physics education statistics had very practical criteria (lecturers opinion) and practical (students opinion). The conclusion of this study is the teaching materials of statistic of physics education with cooperative problem solving model has been practically used in lectures

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SHARMA, SASHI. "INFLUENCE OF CULTURE ON SECONDARY SCHOOL STUDENTS’ UNDERSTANDING OF STATISTICS: A FIJIAN PERSPECTIVE." STATISTICS EDUCATION RESEARCH JOURNAL 13, no. 2 (2014): 104–17. http://dx.doi.org/10.52041/serj.v13i2.284.

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Although we use statistical notions daily in making decisions, research in statistics education has focused mostly on formal statistics. Further, everyday culture may influence informal ideas of statistics. Yet, there appears to be minimal literature that deals with the educational implications of the role of culture. This paper will discuss the interaction between statistical cognition and culture, reporting on the effects of culture on secondary students’ statistical ideas. It will draw on examples from my work and that of a few others who have studied cultural influences on statistical ideas to explain how statistics is tied to cultural practices. The paper will consider the issues arising out of the literature and offer suggestions for meeting the challenges. First published November 2014 at Statistics Education Research Journal Archives

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Adams, Thomas W., Evelyn Hatch, and Hossein Farhady. "Research Design and Statistics for Applied Linguistics." TESOL Quarterly 19, no. 1 (1985): 155. http://dx.doi.org/10.2307/3586777.

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Spyridakis, Jan H., Michael J. Wenger, and Sarah H. Andrew. "The Technical Communicator's Guide to Understanding Statistics and Research Design." Journal of Technical Writing and Communication 21, no. 3 (1991): 207–19. http://dx.doi.org/10.2190/3qvp-fcyf-gc74-eq2q.

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Journal articles on the topic 'Education – Research – Statistics'

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