scholarly journals EVALUATING TWO MODELS OF COLLABORATIVE TESTS IN AN ONLINE INTRODUCTORY STATISTICS COURSE

2015 ◽  
Vol 14 (1) ◽  
pp. 36-59
Author(s):  
AUÐBJÖRG BJÖRNSDÓTTIR ◽  
JOAN GARFIELD ◽  
MICHELLE EVERSON
Keyword(s):  
Quantitative Methods ◽  
Statistics Education ◽  
Introductory Statistics ◽  
Qualitative And Quantitative Methods ◽  
Noticeable Increase ◽  
Research Journal ◽  
Significant Difference ◽  
Statistics Course ◽  
Students Attitudes ◽  
Collaborative Tests

This study explored the use of two different types of collaborative tests in an online introductory statistics course. A study was designed and carried out to investigate three research questions: (1) What is the difference in students’ learning between using consensus and non-consensus collaborative tests in the online environment?, (2) What is the effect of using consensus and non-consensus collaborative tests on students’ attitudes towards statistics?, and (3) How does using a required consensus vs. a non-consensus approach on collaborative tests affect group discussions? Qualitative and quantitative methods were used for data analysis. While no significant difference was found between groups using the two collaborative testing formats, there was a noticeable increase in students’ attitudes across both formats towards learning statistics. This supports prior research on the benefits of using collaborative tests in face-to-face courses. First published May 2015 at Statistics Education Research Journal Archives

AN EXPLORATION OF STUDENT ATTITUDES AND SATISFACTION IN A GAISE-INFLUENCED INTRODUCTORY STATISTICS COURSE

2017 ◽  
Vol 16 (2) ◽  
pp. 487-510
Author(s):  
WARREN PAUL
Keyword(s):  
Student Attitudes ◽  
Structural Equation ◽  
Statistics Education ◽  
Student Feedback ◽  
Introductory Statistics ◽  
Group Discussions ◽  
Research Journal ◽  
Statistics Course ◽  
Attitudes Toward Statistics ◽  
Students Attitudes

We used the Survey of Attitudes Toward Statistics to (1) evaluate using pre-semester data the Students’ Attitudes Toward Statistics Model (SATS-M), and (2) test the effect on attitudes of an introductory statistics course redesigned according to the Guidelines for Assessment and Instruction in Statistics Education (GAISE) by examining the change in attitudes over the semester and, using supplementary data from an annual Student Feedback Survey, testing for a change in overall satisfaction following implementation of the redesigned course. We took an exploratory rather than confirmatory approach in both parts of this study using Bayesian networks and structural equation modelling. These results were triangulated with analysis of focus group discussions and the annual Student Feedback Survey. First published November 2017 at Statistics Education Research Journal Archives

CONFIRMING THE STRUCTURE OF THE SURVEY OF ATTITUDES TOWARD STATISTICS (SATS-36) BY SWEDISH STUDENTS

2019 ◽  
Vol 18 (1) ◽  
pp. 83-93
Author(s):  
INGER PERSSON ◽  
KATRIN KRAUS ◽  
LISBETH HANSSON ◽  
FAN YANG WALLENTIN
Keyword(s):  
Statistics Education ◽  
Original Model ◽  
Introductory Statistics ◽  
Model Structure ◽  
Research Journal ◽  
Statistics Course ◽  
Confirmatory Factor ◽  
Attitudes Toward Statistics ◽  
Students Attitudes ◽  
Analyze Data

Research on students’ attitudes toward statistics has attracted many statistics instructors and statistics education researchers. In this study, we use confirmatory factor analysis to analyze data collected from an introductory statistics course using the Survey of Attitudes toward Statistics. The results suggest that the items and six factors are conceptually relevant, confirming the six-factor structure of the pretest version of SATS-36 on this sample of Swedish students, with a few suggested modifications of the original model structure. Two items are excluded from the Difficulty component, two items on the Affect component are allowed to correlate, and two items on the Cognitive competence component are also allowed to correlate. First published May 2019 at Statistics Education Research Journal Archives

scholarly journals WHEN DO STUDENTS’ ATTITUDES CHANGE? INVESTIGATING STUDENT ATTITUDES AT MIDTERM

2017 ◽  
Vol 16 (2) ◽  
pp. 476-486
Author(s):  
APRIL T. KERBY ◽  
JACQUELINE R. WROUGHTON
Keyword(s):  
Education Research ◽  
Student Attitudes ◽  
Statistics Education ◽  
Student Attitude ◽  
Introductory Statistics ◽  
Individual Student ◽  
Statistics Education Research ◽  
Research Journal ◽  
Statistics Course ◽  
Students Attitudes

Statistics educators have been investigating how students’ attitudes change in the introductory statistics course for many years. Typically, an overall decrease in mean attitudes over the course has been noted. However, when and how do students’ attitudes change during the term? Do they steadily decrease or is there a point when students’ attitudes might actually be increasing? If so, can instructors use this to their advantage? This research introduced a mid-semester survey of attitudes. We found that students’ attitudes are not necessarily strictly declining from the beginning to the end of the semester. We also found it might be advantageous to follow individual student attitude trends throughout the semester instead of just looking at aggregate mean scores for the different surveys. First published November 2017 at Statistics Education Research Journal Archives

INTRODUCTORY STATISTICS COURSE TERTIARY STUDENTS’ UNDERSTANDING OF P-VALUES

2014 ◽  
Vol 13 (1) ◽  
pp. 53-65 ◽  
Author(s):  
ROBYN REABURN
Keyword(s):  
Null Hypothesis ◽  
Probabilistic Reasoning ◽  
Statistics Education ◽  
Introductory Statistics ◽  
P Values ◽  
Testing Procedures ◽  
Research Journal ◽  
Null Hypothesis Testing ◽  
Statistics Course ◽  
Teaching Programs

This study aimed to gain knowledge of students’ beliefs and difficulties in understanding p-values, and to use this knowledge to develop improved teaching programs. This study took place over four consecutive teaching semesters of a one-semester tertiary statistics unit. The study was cyclical, in that the results of each semester were used to inform the instructional design for the following semester. Over the semesters, the following instructional techniques were introduced: computer simulation, the introduction of hypothetical probabilistic reasoning using a familiar context, and the use of alternative representations. The students were also encouraged to write about their work. As the interventions progressed, a higher proportion of students successfully defined and used p-values in Null Hypothesis Testing procedures. First published May 2014 at Statistics Education Research Journal Archives

scholarly journals QUALITATIVE RESEARCH: AN ESSENTIAL PART OF STATISTICAL COGNITION RESEARCH

2010 ◽  
Vol 9 (2) ◽  
pp. 22-34
Author(s):  
PAV KALINOWSKI ◽  
JERRY LAI ◽  
FIONA FIDLER ◽  
GEOFF CUMMING
Keyword(s):  
Quantitative Research ◽  
Quantitative Methods ◽  
Statistics Education ◽  
Statistical Tests ◽  
Reporting Practices ◽  
Qualitative And Quantitative ◽  
Qualitative And Quantitative Methods ◽  
Research Journal ◽  
New Directions ◽  
Method Approach

Our research in statistical cognition uses both qualitative and quantitative methods. A mixed method approach makes our research more comprehensive, and provides us with new directions, unexpected insights, and alternative explanations for previously established concepts. In this paper, we review four statistical cognition studies that used mixed methods and explain the contributions of both the quantitative and qualitative components. The four studies investigated concern statistical reporting practices in medical journals, an intervention aimed at improving psychologists’ interpretations of statistical tests, the extent to which interpretations improve when results are presented with confidence intervals (CIs) rather than p-values, and graduate students’ misconceptions about CIs. Finally, we discuss the concept of scientific rigour and outline guidelines for maintaining rigour that should apply equally to qualitative and quantitative research. First published November 2010 at Statistics Education Research Journal: Archives

scholarly journals COGNITIVE TRANSFER OUTCOMES FOR A SIMULATION-BASED INTRODUCTORY STATISTICS CURRICULUM

2017 ◽  
Vol 16 (2) ◽  
pp. 419-440
Author(s):  
MATTHEW D. BECKMAN ◽  
ROBERT C. DELMAS ◽  
JOAN GARFIELD
Keyword(s):  
Learning Outcomes ◽  
Statistics Education ◽  
Assessment Instrument ◽  
Introductory Statistics ◽  
Far Transfer ◽  
Research Journal ◽  
Cognitive Transfer ◽  
Simulation Based ◽  
Statistics Course ◽  
New Applications

Cognitive transfer is the ability to apply learned skills and knowledge to new applications and contexts. This investigation evaluates cognitive transfer outcomes for a tertiary-level introductory statistics course using the CATALST curriculum, which exclusively used simulation-based methods to develop foundations of statistical inference. A common assessment instrument administered at the end of each course measured learning outcomes for students. CATALST students showed evidence of both near and far transfer outcomes while scoring as high, or higher than, on the assessed learning objectives when compared with peers enrolled in similar courses that emphasized parametric inferential methods (e.g., the t-test). First published November 2017 at Statistics Education Research Journal Archives

scholarly journals RETENTION OF STATISTICAL CONCEPTS IN A PRELIMINARY RANDOMIZATION-BASED INTRODUCTORY STATISTICS CURRICULUM

2012 ◽  
Vol 11 (1) ◽  
pp. 21-40 ◽  
Author(s):  
NATHAN TINTLE ◽  
KYLIE TOPLIFF ◽  
JILL VANDERSTOEP ◽  
VICKI-LYNN HOLMES ◽  
TODD SWANSON
Keyword(s):  
Education Research ◽  
Student Learning ◽  
Conceptual Understanding ◽  
Statistics Education ◽  
Introductory Statistics ◽  
Research Journal ◽  
Statistics Course ◽  
Additional Support ◽  
Improve Student Learning ◽  
Statistics Curriculum

Previous research suggests that a randomization-based introductory statistics course may improve student learning compared to the consensus curriculum. However, it is unclear whether these gains are retained by students post-course. We compared the conceptual understanding of a cohort of students who took a randomization-based curriculum (n = 76) to a cohort of students who used the consensus curriculum (n = 79). Overall, students taking the randomization-based curriculum showed higher conceptual retention in areas emphasized in the curriculum, with no significant decrease in conceptual retention in other areas. This study provides additional support for the use of randomization-methods in teaching introductory statistics courses. First published May 2012 at Statistics Education Research Journal: Archives

STUDENTS’ PERCEPTIONS OF STATISTICS: AN EXPLORATION OF ATTITUDES, CONCEPTUALIZATIONS, AND CONTENT KNOWLEDGE OF STATISTICS

2012 ◽  
Vol 11 (2) ◽  
pp. 6-25
Author(s):  
MARJORIE E. BOND ◽  
SUSAN N. PERKINS ◽  
CAROLINE RAMIREZ
Keyword(s):  
Education Research ◽  
Content Knowledge ◽  
Undergraduate Students ◽  
Statistics Education ◽  
Basic Knowledge ◽  
Statistics Education Research ◽  
Research Journal ◽  
Significant Difference ◽  
Attitudes Toward Statistics ◽  
Students Attitudes

Although statistics education research has focused on students’ learning and conceptual understanding of statistics, researchers have only recently begun investigating students’ perceptions of statistics. The term perception describes the overlap between cognitive and non-cognitive factors. In this mixed-methods study, undergraduate students provided their perceptions of statistics and completed the Survey of Students’ Attitudes Toward Statistics-36 (SATS-36). The qualitative data suggest students had basic knowledge of what the word statistics meant, but with varying depths of understanding and conceptualization of statistics. Quantitative analysis also examined the relationship between students’ perceptions of statistics and attitudes toward statistics. We found no significant difference in mean pre- or post-SATS scores across conceptualization and content knowledge categories. The implications of these findings for education and research are discussed. First published November 2012 at Statistics Education Research Journal: Archives

INVESTIGATING STUDENTS’ REASONING ABOUT SAMPLING DISTRIBUTIONS THROUGH A RESOURCE PERSPECTIVE

2019 ◽  
Vol 18 (1) ◽  
pp. 26-45
Author(s):  
KELLY FINDLEY ◽  
ALEXANDER LYFORD
Keyword(s):  
Education Research ◽  
Grounded Theory ◽  
Undergraduate Students ◽  
Statistics Education ◽  
Introductory Statistics ◽  
Research Journal ◽  
Sampling Distributions ◽  
Statistics Course ◽  
Resource Perspective ◽  
Problem Setting

Researchers have documented many misconceptions students hold about sampling variability. This study takes a different approach—instead of identifying shortcomings, we consider the productive reasoning pieces students construct as they reason about sampling distributions. We interviewed eight undergraduate students newly enrolled in an introductory statistics course. Taking a grounded theory style approach, we identified 10 resources that students used when reasoning about the sampling distribution for the average within two contexts: penny years and dice rolls. Students had varied success in their responses as they made choices about how to represent their resources in their constructions. Successful constructions exemplified careful blending of resources, while less  successful constructions reflected disjoint perceptions and tensions between seemingly conflicting resources. Our findings stress the importance of framing students as capable reasoning agents by describing student resources that were used while solving tasks related to sampling distributions. We also discuss the influence of context and problem setting in students’ reasoning and resource elicitation. First published May 2019 at Statistics Education Research Journal Archives

TAKING PROJECT-BASED STATISTICS ABROAD: LEARNING EXPERIENCES AND OUTCOMES OF A PROJECT-BASED STATISTICS COURSE IN WEST AFRICA

2021 ◽  
Vol 19 (3) ◽  
Author(s):  
REBECCA AWUAH ◽  
KRISTEL M. GALLAGHER ◽  
LISA C. DIERKER
Keyword(s):  
West Africa ◽  
Undergraduate Students ◽  
Statistics Education ◽  
Positive Impact ◽  
Learning Experiences ◽  
Introductory Statistics ◽  
Research Journal ◽  
Statistics Course ◽  
The Impact

To evaluate the impact of a multidisciplinary, project-based course in introductory statistics, this exploratory study examined learning experiences, feelings of confidence, and interest in future experiences with data for undergraduate students in Ghana, West Africa. Students completed a one-semester, introductory statistics course utilizing the Passion-driven Statistics curriculum. Results showed more than half of the students put more effort into the course and found the material more challenging compared to other courses, while nearly three-quarters reported interest in one or more follow-up courses. Importantly, students also reported increased confidence in a variety of applied statistical skills. These findings demonstrate the positive impact of a multidisciplinary, project-based curriculum on undergraduate students in Ghana, West Africa and demonstrate the potential for its global portability. First published December 2020 at Statistics Education Research Journal: Archives

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