scholarly journals COGNITIVE AND NON-COGNITIVE FACTORS RELATED TO STUDENTS’ STATISTICS ACHIEVEMENT

2010 ◽  
Vol 9 (1) ◽  
pp. 6-26
Author(s):  
FRANCESCA CHIESI ◽  
CATERINA PRIMI
Keyword(s):  
Education Research ◽  
Statistics Education ◽  
Cognitive Factors ◽  
Introductory Statistics ◽  
Cognitive Variables ◽  
Cognitive Variable ◽  
Research Journal ◽  
Statistics Course ◽  
Course Achievement ◽  
Attitudes Toward Statistics

The aim of this study was to investigate students’ achievement in introductory statistics courses taking into account the relationships between cognitive and non-cognitive factors. It was hypothesised that achievement was related to background in mathematics (a cognitive variable), as well as to attitudes toward statistics and anxiety (non-cognitive variables). Students were presented with measures assessing their attitudes, mathematical competence, and anxiety toward courses and examinations at the beginning and at the end of their statistics course. Achievement was assessed by tasks assigned during the course, as well as by students’ final grades and the number of exam failures. The results reveal the reationships between cognitive and non-cognitive factors, their changes during the course, and how both interact in predicting achievement. First published May 2010 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

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

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

STUDENTS’ PERCEPTIONS OF THE FUTURE RELEVANCE OF STATISTICS AFTER COMPLETING AN ONLINE INTRODUCTORY STATISTICS COURSE

2018 ◽  
Vol 17 (2) ◽  
pp. 120-140
Author(s):  
EMMANUEL SONGSORE ◽  
BETHANY J. G. WHITE
Keyword(s):  
Education Research ◽  
Undergraduate Students ◽  
Statistics Education ◽  
Thinking Skills ◽  
Introductory Statistics ◽  
First Year ◽  
Student Interest ◽  
Introductory Courses ◽  
Research Journal ◽  
Statistics Course

Statistics educators have long recognized the importance of empowering students with statistical thinking skills that could be applied beyond the classroom. However, there is a dearth of research on how students deem statistical topics as having practical future relevance after they complete introductory courses. Focusing on student interest in and perceived value of statistics, this study reports findings from a qualitative study that examined students’ written reflections to explore the nature and extent of the perceived future relevance of statistics among undergraduate students who completed a first-year introductory statistics course online. Findings show that students deemed statistics topics as important if they could be applied to their everyday lives or their academic- and career-related interests. We conclude with recommendations for instructors of introductory statistics courses that enroll students with diverse interests and goals. First published November 2018 at Statistics Education Research Journal Archives

COMPARISON OF FUTURE COURSE ENROLLMENT AMONG STUDENTS COMPLETING ONE OF FOUR DIFFERENT INTRODUCTORY STATISTICS COURSES

2021 ◽  
Vol 19 (3) ◽  
Author(s):  
VALERIE NAZZARO ◽  
JENNIFER ROSE ◽  
LISA DIERKER
Keyword(s):  
Education Research ◽  
Statistics Education ◽  
Introductory Statistics ◽  
Course Enrollment ◽  
Research Journal ◽  
Statistics Course ◽  
Potential Impact ◽  
Statistics Courses ◽  
Subsequent Selection ◽  
Selection Of

A central challenge of introductory statistics is the development of curricula that not only serve diverse students, but also leave them wanting more. To evaluate the potential impact of a multidisciplinary, project-based introductory statistics course, students’ future course decisions were compared against traditional statistics courses using administrative data from the fall 2009 through spring 2018 semesters. Results indicated that the project-based course helped promote continued interest in the field of statistics and data analysis based on subsequent selection of courses in the field. First published December 2020 at Statistics Education Research Journal: Archives

scholarly journals THE IMPORTANCE OF ATTITUDES IN STATISTICS EDUCATION

2012 ◽  
Vol 11 (2) ◽  
pp. 57-71
Author(s):  
CAROLINE RAMIREZ ◽  
CANDACE SCHAU ◽  
ESMA EMMİOĞLU
Keyword(s):  
Education Research ◽  
Statistics Education ◽  
Value Theory ◽  
Expectancy Value Theory ◽  
Expectancy Value ◽  
Research Journal ◽  
Statistics Course ◽  
Attitudes Toward Statistics ◽  
Students Attitudes ◽  
Course Outcomes

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

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

PAINT-BY-NUMBER OR PICASSO? A GROUNDED THEORY PHENOMENOGRAPHICAL STUDY OF STUDENTS’ CONCEPTIONS OF STATISTICS

2021 ◽  
Vol 19 (2) ◽  
pp. 76-102
Author(s):  
NICOLA JUSTICE ◽  
SAMANTHA MORRIS ◽  
VERONIQUE HENRY ◽  
ELIZABETH BRONDOS FRY
Keyword(s):  
Education Research ◽  
Grounded Theory ◽  
Undergraduate Students ◽  
Statistics Education ◽  
Qualitative Approach ◽  
Introductory Statistics ◽  
Preliminary Results ◽  
Research Journal ◽  
Survey Responses

Statistics students’ conceptions of the work of statisticians and the discipline of statistics may play an important role in the topics to which they attend and their interest in pursuing further study. To learn about students’ conceptions, we collected open-ended survey responses from 44 undergraduate students who had completed introductory statistics courses. We used a grounded theory phenomenographical qualitative approach to identify several themes in students’ conceptions. In addition to the test-and-procedure conception, we offer several other themes, such as acknowledgement of variation and the role of ethical integrity. We use a metaphor of painting styles to compare to experts’ conceptions of statistics. By identifying “seeds” of what may be developed into expert conceptions, these preliminary results set possible foundations to explore trajectories that may help shape students’ conceptions of statistics. First published June 2020 at Statistics Education Research Journal Archives

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