scholarly journals STUDENTS’ ATTITUDES TOWARD STATISTICS ACROSS THE DISCIPLINES: A MIXED-METHODS APPROACH

2012 ◽  
Vol 11 (2) ◽  
pp. 45-56
Author(s):  
JAMES D. GRIFFITH ◽  
LEA T. ADAMS ◽  
LUCY L. GU ◽  
CHRISTIAN L. HART ◽  
PENNEY NICHOLS-WHITEHEAD
Keyword(s):  
Mixed Methods ◽  
Undergraduate Students ◽  
Qualitative Methodology ◽  
Statistics Education ◽  
Business Majors ◽  
Negative Attitudes ◽  
Mixed Methods Approach ◽  
Research Journal ◽  
Attitudes Toward Statistics ◽  
Students Attitudes

Students’ attitudes toward statistics were investigated using a mixed-methods approach including a discovery-oriented qualitative methodology among 684 undergraduate students across business, criminal justice, and psychology majors where at least one course in statistics was required. Students were asked about their attitudes toward statistics and the reasons for their attitudes. Five categories resulted for those with positive and negative attitudes and were separated on the basis of discipline. Approximately 63% of students indicated a positive attitude toward statistics. Business majors were most positive and were more likely to believe statistics would be used in their future career. Multiple methodological approaches have now provided data on the various domains of attitudes toward statistics and those implications are discussed. First published November 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

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

MEASURING STATISTICS ATTITUDES: STRUCTURE OF THE SURVEY OF ATTITUDES TOWARD STATISTICS (SATS-36)

2011 ◽  
Vol 10 (1) ◽  
pp. 35-51
Author(s):  
STIJN VANHOOF ◽  
SOFIE KUPPENS ◽  
ANA ELISA CASTRO SOTOS ◽  
LIEVEN VERSCHAFFEL ◽  
PATRICK ONGHENA
Keyword(s):  
Factor Analysis ◽  
Education Research ◽  
Confirmatory Factor Analysis ◽  
Statistics Education ◽  
Individual Item ◽  
Research Journal ◽  
Item Functioning ◽  
Confirmatory Factor ◽  
Attitudes Toward Statistics ◽  
Students Attitudes

Although a number of instruments for assessing attitudes toward statistics have been developed, several questions with regard to the structure and item functioning remain unresolved. In this study, the structure of the Survey of Attitudes Toward Statistics (SATS-36), a widely used questionnaire to measure six aspects of students’ attitudes toward statistics, is investigated. This study addresses the previously unexplored issue of individual item functioning. Based on confirmatory factor analysis using individual items, the results suggest that the SATS-36 can be improved by removing some poorly functioning items and that depending on the goals of a specific study either six subscales could be used or three of them (Affect, Cognitive Competence, and Difficulty) can be combined into one subscale without losing much information. First published May 2011 at Statistics Education Research Journal: Archives

scholarly journals SURVEYS ASSESSING STUDENTS’ ATTITUDES TOWARD STATISTICS: A SYSTEMATIC REVIEW OF VALIDITY AND RELIABILITY

2012 ◽  
Vol 11 (2) ◽  
pp. 103-123
Author(s):  
MEAGHAN M. NOLAN ◽  
TANYA BERAN ◽  
KENT G. HECKER
Keyword(s):  
Systematic Review ◽  
Education Research ◽  
Statistics Education ◽  
Final Analysis ◽  
Attitude Scale ◽  
Validity And Reliability ◽  
Research Journal ◽  
Positive Attitudes ◽  
Attitudes Toward Statistics ◽  
Students Attitudes

Students with positive attitudes toward statistics are likely to show strong academic performance in statistics courses. Multiple surveys measuring students’ attitudes toward statistics exist; however, a comparison of the validity and reliability of interpretations based on their scores is needed. A systematic review of relevant electronic databases yielded 532 citations, 78 of which were reviewed, and 35 included in a final analysis. Fifteen instruments were identified; however, evidence of validity and reliability has only accumulated for the Statistics Attitude Scale, Attitudes Toward Statistics Scale, and Survey of Attitudes Toward Statistics (two versions). In conclusion, a number of surveys exist, but there is a paucity of peer-reviewed validity and reliability evidence. First published November 2012 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 ATTITUDES TOWARD STATISTICS AND ACHIEVEMENT: BETWEEN STUDENTS OF SCIENCE AND SOCIAL FIELDS

2018 ◽  
Vol 7 (2) ◽  
pp. 173
Author(s):  
Dian Cahyawati ◽  
Wahyudin Wahyudin ◽  
Sufyani Prabawanto
Keyword(s):  
Undergraduate Students ◽  
Student Attitudes ◽  
Statistical Tests ◽  
Descriptive Analysis ◽  
Negative Attitudes ◽  
Social Fields ◽  
Affective Value ◽  
Attitudes Toward Statistics ◽  
The Difference ◽  
Students Attitudes

The purpose of this study was to explore students' attitudes toward statistics (ATS) based on the beginning and the end of learning, based on differences in fields of study, and examine its relationship with statistical acheivement. ATS was measured by an attitude instrument, namely The Survey of Attitudes toward Statistics (SATS) which consists of six dimensions (affective, cognitive competence, difficulty, value, interest, effort). Research respondents were undergraduate students who took lectures on statistical recognition that came from at one of the universities in South Sumatra. The results of the descriptive analysis showed the variation of ATS in each dimension of attitudes classified into positive, neutral, or negative attitudes. Although there are variations in the response of student attitudes in each dimension, but the results of statistical tests have not been able to show differences in attitudes between the beginning and the end of learning in each dimension. The differences in attitudes between the beginning and the end of learning that are statistically significant are in the dimensions of affective, value, and effort. The difference in the field of student science shows the difference in ATS, but only in the dimension of value. This study does not have enough evidence to state that there is a significant relationship between student attitudes to statistics and the results of learning statistics.

scholarly journals CALL FOR PAPERS: STUDENTS’ ATTITUDES TOWARD STATISTICS

2011 ◽  
Vol 10 (1) ◽  
Author(s):  
ROBERT DELMAS ◽  
PETER PETOCZ
Keyword(s):  
Education Research ◽  
Statistics Education ◽  
Statistics Education Research ◽  
Research Journal ◽  
Attitudes Toward Statistics ◽  
Students Attitudes

First published May 2011 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

scholarly journals ASSESSING LEARNING OUTCOMES: AN ANALYSIS OF THE GOALS-2 INSTRUMENT

2015 ◽  
Vol 14 (2) ◽  
pp. 93-116
Author(s):  
ANELISE GUIMARAES SABBAG ◽  
ANDREW ZIEFFLER
Keyword(s):  
Undergraduate Students ◽  
Mixed Model ◽  
Factor Model ◽  
Statistics Education ◽  
The United States ◽  
Measurement Models ◽  
Test Information ◽  
Research Journal ◽  
Graded Response ◽  
Two Parameter

The test instrument GOALS-2 was designed primarily to evaluate the effectiveness of the CATALST curriculum. The purpose of this study was to perform a psychometric analysis of this instrument. Undergraduate students from six universities in the United States (n=289) were administered the instrument. Three measurement models were fit and compared: the two-parameter logistic model, the mixed model (comprised of both the two-parameter logistic and the graded-response model), and the bi-factor model. The mixed model was found to most appropriately model students’ responses. The results suggested the revision of some items and the addition of more discriminating items to improve total test information. First published November 2015 at Statistics Education Research Journal Archives

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