Statistical Anxiety Rating Scale Research Articles

Exploring statistics anxiety and self-efficacy in psychology undergraduate students

Statistics anxiety is experienced by a large proportion of psychology students, even though conducting statistical analyses is a fundamental skill for students to acquire. The research on statistics anxiety has tended to explore either dispositional factors (e.g. personality) or situational factors (e.g. teacher effects). One potential predictor that has not yet been considered is statistical self-efficacy; the belief that one can successfully complete statistical tasks. The present study aims to clarify whether statistical self-efficacy is a predictor of any aspects of statistics anxiety in psychology students. In this study 100 undergraduate students (89% female identifying), in the second and third (final) year of a psychology degree in the UK, completed the Statistics Anxiety Rating Scale (STARS), the Statistics Self-efficacy scale (SSE), and a measure of trait anxiety. A hierarchical regression showed a significant negative relationship between statistical self-efficacy and all aspects of statistics anxiety, showing that students who are more confident in their statistical skills experience less statistics anxiety. Findings are discussed in relation to both understanding statistics anxiety and developing interventions to alleviate statistics anxiety, such as mentoring for students with diagnosed clinical anxiety conditions or interventions that aim to improve a student’s self-efficacy.

To behave or not (un)ethically? The meditative effect of mindfulness on statistics anxiety and academic dishonesty moderated by risk aversion

Despite the growing interest in mindfulness in higher education, the literature on its relation to decision-making under risk (i.e. academic misconduct) and statistics anxiety is scarce. The present research shall fill this gap. Based on the prospect theory, we assessed the mediating effect of mindfulness on the relationship between statistics anxiety and academic dishonesty moderated by risk aversion. Data were collected from 791 undergraduate students in six Israeli academic institutions studying for bachelor’s degrees in social sciences. Questionnaires included the following measures: risk behaviour according to the prospect theory framework, Mindful Attention Awareness Scale, Statistics Anxiety Rating Scale, Academic Misconduct Scale and sociodemographic variables. Correlations among these variables were explored. The data was analysed using Structural Equation Modelling (SEM). The results indicate that the variance in academic dishonesty is explained by students' statistics anxiety with a mediation of Mindfulness moderated by Risk Aversion. Mindfulness negatively affects Academic Dishonesty, while Risk Aversion has a significant positive effect on Mindfulness. Finally, among individuals with high statistics anxiety, Risk Averse individuals show significantly higher Mindfulness than Risk Seekers. We conclude that mindfulness-based interventions might be a constructive tool to reduce risk-taking and promote ethical decision-making among individuals who experience high levels of statistics anxiety. Furthermore, developing mindful skills may help individuals with higher anxiety levels neutralize these unwanted feelings and get along with their learning tasks. Hence, avoid academic unethical behaviours.

Grasping the STARS: A comprehensive study on statistics—Anxiety levels among engineering students

Engineering students often face the challenge of comprehending and applying statistical concepts to evaluate and assess research. This research seeks to investigate the factor structure of Statistics Anxiety Rating Scale (STARs), which comprises six domains with 51 items. The questionnaire was administered to engineering students currently enrolled in a statistics class, and the data were analyzed using Statistical Package for the Social Sciences. The study sheds light on the factors that contribute to students’ statistics anxiety when taking a statistics course. The findings highlight the elements that influence statistics anxiety, educators and institutions can develop targeted interventions and support mechanisms to enhance students’ statistical competence and overall learning experience. This research not only addresses the unique challenges faced by engineering students but also holds implications for fostering statistical literacy across various disciplines.

Prevalence and predictors of statistics anxiety among sociology and social work students

Anxiety in the context of quantitative reasoning courses is a complex and highly prevalent problem, particularly among students majoring in the arts, humanities, and social sciences. Gaining an accurate understanding of the anxiety levels experienced by students enrolling in statistics courses can be regarded as one of the most important factors affecting students’ learning and achievement in these courses. In the current study, the Statistical Anxiety Rating Scale was applied to explore the prevalence and predictors of statistics anxiety among sociology and social work undergraduate students at Sultan Qaboos University (n=142). The results show that almost 71% of the examined students had experienced some aspects of statistics anxiety, with sociology students scoring noticeably higher than social work students. The leading predictors of higher statistics anxiety levels found in this study were as follows: test and class anxiety (80.2%) and interpretation anxiety (79.1%). Moreover, Welch’s test results show significant gender differences, with female students reporting higher levels of anxiety across all subscales than their male counterparts. Finally, some practical strategies of reducing statistics anxiety are discussed.
 Keywords: Statistics anxiety, gender differences, sociology, social work, Oman

Profiling teacher pedagogical behaviours in plummeting postgraduate students’ anxiety in statistics

The indispensable relationship between Research and Statistics makes the teaching of both courses crucial in all postgraduate programmes. However, over the years, postgraduate students have displayed a high level of anxiety in studying Statistics. Therefore, exploiting the descriptive case study strategy knitted within the sequential explanatory design, a Statistics teacher was studied in one of Ghana’s outstanding universities and the reported pedagogical behaviours were profiled. Primary data were obtained from 99 postgraduate students (reading various postgraduate programmes on regular, sandwich and distance modes of education) on their level of anxiety in Statistics (using the Statistics Anxiety Rating Scale) and their experiences with their teacher’s pedagogical behaviours. Also, 12 of the postgraduate students were interviewed about the pedagogical behaviours of their teacher that reduced their anxiety in Statistics. To triangulate the primary data, secondary results on the teacher’s teaching practices were obtained from the Directorate of Academic Planning and Quality Assurance Unit of the university (originally gathered through a statistical academic support scale). Descriptive (mean and standard deviation) and inferential (one-way ANOVA and SEM) statistics were used to analyse the quantitative data and the qualitative data were analysed into themes. Consequently, the study found 17 teacher pedagogical behaviours under teacher characteristics (cognitive and affective factors) and pedagogical practices that reduced postgraduate students’ statistical anxiety and heightened positive attitudes towards the study of Statistics. Therefore, a recognition of these pedagogical behaviours and their open display during the teaching of Statistics will go a long way in reducing postgraduate students’ high statistical anxiety.

The association of self-efficacy, anxiety sensitivity, and perfectionism with statistics and math anxiety

Statistics and math anxiety are pervasive problems for post-secondary students. We hypothesized that self-efficacy would be negatively related to math/statistics anxiety, and that anxiety sensitivity and perfectionism would be positively related to math/statistics anxiety, even when controlling for gender, university program, and education level. Method: Graduate and undergraduate students (N = 447, after exclusions) completed an online self-report questionnaire, including an abbreviated version of the Statistics Anxiety Rating Scale (STARS), math anxiety, self-efficacy, anxiety sensitivity, perfectionism, and demographics. Results: Exploratory factor analysis supported a six-factor structure for statistics anxiety. Self-efficacy was negatively associated with math/statistics anxiety, whereas anxiety sensitivity and perfectionism were positively associated with math/statistics anxiety. Relationships ranged from small-to-moderate, and most relationships persisted after adding covariates. Discussion: Our study suggests the feasibility of a short-form version of the STARS. Moreover, it provides important information on how personality is associated with domain-specific anxiety that can impede statistics education.

A Multi-Level Analysis of the Effects of Statistics Anxiety/Attitudes on Trajectories of Exam Scores

This study explores three understudied facets—quadratic effects, change over time, and gender as a moderator—of the otherwise well-documented relationships between statistics anxiety and academic performance. Using pre- and post- course survey data among a sample of 111 undergraduate students in Social Statistics courses at a U.S. Midwestern university, we employ hierarchical linear modeling (HLM) to test for relationships between change in the six dimensions of the Statistics Anxiety Rating Scale (STARS) and exam grades over the course of the semester. We find that exam grades decreased over time, but at different rates across gender and the six STARS dimensions. We also identify a quadratic relationship between self-concept and final exam grades, as well as several gender interactions. This study highlights the multifaceted and dynamic nature of statistics anxiety/attitudes, as its relationship with academic performance is not always negative, linear, stable over time, or uniform across gender. Supplementary materials for this article are available online.

Statistical Anxiety and Achievement among University Students

Statistics is a critical subject for university students. Their achievement has been negatively impacted by statistical anxiety and the obligation to pass the statistics course. By predicting the achievement of 199 students from one of local higher educational institutions students using statistical anxiety, study mode, gender and programme specialization. A survey was used to select respondents from a variety of programs at a local university. A random sampling technique was applied in administering the questionnaire of Statistical Anxiety Rating Scale. The questionnaire consists of 51 items which has six factors that can be answered using Google form. The descriptive and inferential statistics were used to analyze the data. Statistics anxiety, age, gender, study mode, and program specialization all account for 27 percent of the variation in their achievement. It is possible to improve statistics teaching and learning among university students, despite the fact that the percentage is relatively small. Academic background and previous work experience are important factors to consider when conducting future research with profound statistical understanding.

COMPARATIVE STUDY OF THE ATTITUDES OF SCIENCE AND NON-SCIENCE STUDENTS TOWARDS STATISTICS: THE ROLE OF STATISTIC ANXIETY

Statistics is an essential part of the curriculum in Nigerias education landscape taught in the science and non-science classrooms. However, there has been a growing concern about the students attitudes towards statistics across every level. The present study aimed to determine whether there would be a difference between science and non-science students attitudes towards statistics and whether statistics anxiety contributes to the variations in students attitudes towards statistics in the tertiary education level in Nigeria. A convenience sample of two hundred and twenty-two first-year students pooled from three public tertiary institutions in the Kogi State of Nigeria participated in the study. A cross-sectional survey design was adopted. The participants completed a self-report measure of Survey of Attitude toward Statistics (SATS-36),initially developed by Schau (2003), and a modified version of the Statistics Anxiety Rating Scale (SARS) developed initially by Baloǧlu (2002). An independent t-test performed on the data established a statistically significant difference in the attitudes of the science and non-science students towards statistics at MD = 1.78, t (200) = 13.632, P< = .05. The result of a regression analysis performed on the data revealed that statistics anxiety positively predicted attitudes towards anxiety. It was concluded that the variation between the attitude of science students and non-science students towards the teaching and learning of statistics is moderated by statistics anxiety. The study recommends that robust attitude change strategies be adopted to reshape the attitudes of the non-science students towards statistics.

Investigation of the Statistical Anxiety Rating Scale Psychometric Properties with a Sample of Greek Students

The purpose of this study was to adapt the Statistics Anxiety Rating Scale (STARS) for a Greek student population. The STARS was administered to 890 Tertiary Education students in two Greek universities. It was performed a cross-validation study to examine the factorial structure and the psychometric properties with a series of confirmatory factor analyses. Results revealed a correlated six first-order factor model which provided the best fit to the data compared to a six-factor model with one superordinate factor. All six factors of the Greek version of the STARS presented convergent and discriminant validity and were internally consistent. Implications and limitations are discussed.

Predict or describe? How learning analytics dashboard design influences motivation and statistics anxiety in an online statistics course.

Based on the achievement goal theory, this experimental study explored the influence of predictive and descriptive learning analytics dashboards on graduate students’ motivation and statistics anxiety in an online graduate-level statistics course. Participants were randomly assigned into one of three groups: (a) predictive dashboard, (b) descriptive dashboard, or (c) control (i.e., no dashboard). Measures of motivation and statistical anxiety were collected in the beginning and the end of the semester via the Motivated Strategies for Learning Questionnaire and Statistical Anxiety Rating Scale. Individual semi-structured interviews were used to understand learners’ perceptions of the course and whether the use of the dashboards influenced the meaning of their learning experiences. Results indicate that, compared to the control group, the predictive dashboard significantly reduced learners’ interpretation anxiety and had an effect on intrinsic goal orientation that depended on learners’ lower or higher initial levels of intrinsic goal orientation. In comparison to the control group, both predictive and descriptive dashboards reduced worth of anxiety (negative attitudes towards statistics) for learners who started the course with higher levels of worth anxiety. Thematic analysis revealed that learners who adopted a more performance-avoidance goal orientation approach demonstrated higher levels of anxiety regardless of the dashboard used.Supplementary InformationThe online version contains supplementary material available at 10.1007/s11423-021-09998-z.

Gender Influence on Statistics Anxiety among Graduate Students

The present study was conducted to further explore gender-based differences in the experience of statistics anxiety among graduate students. A sample of 75 graduate students from a mid-sized research university in the southeastern United States were recruited to participate in a survey concerning statistics anxiety. Data were analyzed using multivariate analysis of covariance and discriminant analysis. Using the Statistics Anxiety Rating Scale, students’ statistics anxiety was measured. After accounting for age, the findings revealed a significant gender difference in statistics anxiety. A significant covariate effect of age indicated that older graduate students reported experiencing higher levels of anxiety as compared to their younger peers. Age accounted for 21% of variance in the combined statistics anxiety subscales. Analysis further revealed that males experienced higher levels of anxiety when seeking statistics help from a fellow student or a professor than did females. Implications for the design of statistics courses are discussed.

Mokken Scale Analysis: Discussion and Application

This article presents a discussion and illustration of Mokken scale analysis (MSA), a nonparametric form of item response theory (IRT), in relation to common IRT models such as Rasch and Guttman scaling. The procedure can be used for dichotomous and ordinal polytomous data commonly used with questionnaires. The assumptions of MSA are discussed as well as characteristics that differentiate a Mokken scale from a Guttman scale. MSA is illustrated using the mokken package with R Studio and a data set that included over 3,340 responses to a modified version of the Statistical Anxiety Rating Scale. Issues addressed in the illustration include monotonicity, scalability, and invariant ordering. The R script for the illustration is included.

That Old Devil Called ‘Statistics’: Statistics Anxiety in University Students and Related Factors

The present study investigated relationships between statistics anxiety (SA), trait anxiety, attitudes towards mathematics and statistics, and academic achievement among university students who had at least one study course related to statistics in their study programme. Five hundred and twelve students from the University of Ljubljana completed the Statistics Anxiety Rating Scale (STARS), State-Trait Anxiety Inventory, and answered questions about their perceptions of mathematics and statistics. The results showed below-average mean scores on the STARS dimensions, except for the Test and Class Anxiety with the average score around the midpoint of the scale. Female students reported higher levels of SA than male students did. The highest levels of SA were reported by students who perceived mathematics and statistics as a threat. The subscales of the STARS correlated positively with students’ trait anxiety. Students who reported less enjoyment in mathematics in high school perceived statistics to be a less worthy subject and had a lower computation self-concept. Students who had better mathematics performance in high school and higher average study grades also reported a higher computation self-concept. In the present study, we translated the STARS questionnaire into Slovenian and confirmed the six-factor structure of the questionnaire. The results provide a basis for further research on statistics anxiety and further validation of the STARS questionnaire. The results can also aid statistics teachers in better understanding students’ worries, fears, and attitudes towards statistics and in learning about the factors that affect students’ statistics anxiety and their work in the course.

Anxiety and Attitudes Toward Statistics and Research Among Younger and Older Nontraditional Adult Learners

Individuals who are 50 years or older are the largest growing demographic among adult learners. However, we still are in the initial stages of investigating their attitudes and anxieties regarding specific areas of study. The current study explored differences between 92 younger (26–49 years) and older (50+ years) nontraditional-aged, degree-seeking undergraduate and graduate students’ attitudes and anxieties regarding statistics and research. The Attitudes Toward Research (ATR) and Statistics Anxiety Rating Scale (STARS) scales were completed via an online survey. Younger nontraditional-aged students generally expressed significantly higher anxiety and more negative beliefs regarding both statistics and research than their older counterparts. Differences were not explained by level of study nor by related experience. Results are discussed in relation to further consideration of student- and cohort-centered applications of andragogical and heutagogical principles for targeted educational practices.

Assessing the Statistical Anxiety Rating Scale as applied to prospective teachers in an Israeli Teacher-Training College

Statistics literacy is a growing part of our lives. However, around 75% of social science undergraduate students experience moderate to high levels of statistics anxiety, characterized by troubling thoughts, stress and an aversion to statistical content or to learning situations using statistics. The aims of the study were to examine the psychometric properties of the Hebrew version of the Statistical Anxiety Rating Scale, and to unfold the underlying structure of the construct as perceived by 163 pre-service teachers in an Israeli college of education. Multidimensional scaling analysis (MDS) confirms the confirmatory factor analysis (CFA) findings but highlights the importance of identifying the context of anxiety (statistics course vs. statistics as a distinct discipline) and the locus of anxiety (internal vs. external). The findings can help teacher educators better monitor their students’ statistics anxiety and assist them in implementing appropriate ways of reducing it.

Contribution of statistical anxiety to student learning outcomes: Study in Universitas Negeri Padang

The purpose of this study is to describe the statistical anxiety contribution to student learning outcomes. The sample of the study was 368 students of Universitas Negeri Padang, who attended Statistical courses in the semester of January-June 2018. Statistical anxiety data were collected through statistical anxiety rating scale (STARS) which analyzed descriptively. The results showed that there was a statistical anxiety contribution to the student statistical learning outcomes, with a contribution value of 10.4 %. Implications are discussed further for learning process in higher education.

USING ATTITUDES AND ANXIETIES TO PREDICT END-OF-COURSE OUTCOMES IN ONLINE AND FACE-TO-FACE INTRODUCTORY STATISTICS COURSES

An abbreviated form of the Statistics Anxiety Rating Scale (STARS) was administered to online and face-to-face introductory statistics students. Subscale scores were used to predict final exam grades and successful course completion. In predicting final exam scores, self-concept, and worth of statistics were found to be statistically significant with no significant difference by campus (online versus face-to-face). Logistic regression and random forests were used to predict successful course completion, with campus being the only significant predictor in the logistic model and face-to-face students being more likely to successfully complete the course. The random forest model indicated that self-concept and test anxiety were overall the best predictors, whereas separately test anxiety was the best predictor in the online group and self-concept was the best predictor in the face-to-face group. First published November 2018 at Statistics Education Research Journal Archives

Statistics Self-Efficacy And Learning Styles As Predictor Of Statistics Anxiety

The study investigated statistics self-efficacy and learning styles as predictors of statistics anxiety among graduate students in University of Port Harcourt. Seven research questions and six null hypotheses were formulated to guide the study. The participants in the study were 150 (male = 86, female 64) graduate students drawn through stratified random sampling technique. Three valid instrument titled; statistical anxiety rating scale (STARS), current statistics self-efficacy scale (CSSES), and Grasham Reichann student learning style scales(GRSLSC) was used for data collection. The validity of the instrument was determined using multivariate statistical method of factor analysis. The reliability indices of the instrument were estimated using the Cronbach alpha with coefficients values for statistics anxiety rating scale. .916 and sub scales of .884.71, .80, .70, .63, .60. Current statistics self-efficacy r = .623, and .56, 52, 53, 54, 51, 60 coefficients for the Grasha-Riechmann student learning style scales sub scales. Research question 1, was answered using descriptive statistics of mean and standard deviation, while 2, 3, 4 and 5 was answered using simple and multiple regression. The null hypothesis tested at 0.05 level of significance with ANOVA associated with multiple regression and t – test associated with simple regression was used for providing answers to the null hypothesis. The result revealed that the statistics anxiety level of graduated student was high, Statistics self-efficacy and learning styles both individual and jointly was seen to predict statistics anxiety. It was recommended that psychological and educational intervention be carried out in the context of increasing statistics self-efficacy and reducing statistics anxiety. Based on findings implications were made and suggestions for further studies.

An examination of the internal consistency and structure of the Statistical Anxiety Rating Scale (STARS).

The purpose of the current study was to examine the internal consistency and structure of the English version of the Statistical Anxiety Rating Scale (STARS). Participants were 202 (79% females) psychology undergraduates was recruited from James Cook University’s Singapore (71%) and Australia (29%) campuses. Acceptable internal consistency reliabilities, ranging from .81 to .94, were found in this sample. Approximate fit indices suggest that a correlated six first-order factor model best describes the data in contrast to theoretical considerations suggesting that a six factor model with two correlated superordinate factors (i.e., statistics anxiety and attitudes toward statistics) best describes the data. Researchers are recommended to use part one of the STARS to assess statistics anxiety and part two to assess attitudes toward statistics.