Statistics Anxiety Research Articles

No Anxious Student Is Left Behind: Statistics Anxiety, Personality Traits, and Academic Dishonesty—Lessons from COVID-19

Scholarly studies have revealed that exposure to statistics courses affect students’ anxiety levels and that this has been associated with unethical misconduct. Thus, the present research’s main objective is to comprehend the mediating role Statistics Anxiety plays on the relationship comprising students’ personality traits and academic dishonesty as manifesting before and during the COVID-19 pandemic. Its aim is to understand this phenomenon and provide theoretical tools for fostering sustainably personalized distance learning and instruction. Data were collected from students studying for a bachelor’s degree in the social sciences at three different Israeli colleges. The sample comprises 316 participants and data were analyzed using Structural Equation Modelling (SEM). The results show a significant mediation manifested by an indirect effect between personality traits and academic dishonesty via statistics anxiety only in emergency remote teaching, although no parallel significant mediation was observed in the face-to-face course. These results could be explained by differences in delivery methods. Thus, we recommend that in the emergency remote teaching environment instructors’ presence include: (1) supportive, emphatic interaction to reduce virtual distance and (2) Social Emotional Learning (SEL) strategies, which foster students’ learning challenges and prevent anxiety and academic dishonesty.

Fear of Statistics among TEFL Postgraduate Students

Although statistics is an important compulsory course in a wide variety of disciplines, the vast majority of students including TEFL postgraduate students find it frightening and difficult to understand, and thus suffer from underachievement. As a result, a specific kind of anxiety called statistical anxiety emerges that requires immediate attention. To date, a large and growing body of research has focused on exploring different aspects and dimensions of statistics that produce fear and tension. However, the problem of fear of statistics amongst TEFL postgraduate students has received scant attention in the literature. In this study, attempts are made to assess and describe the areas of anxiety that TEFL postgraduate students experience during a statistics course. To this end, the present study employed a descriptive research design, i.e., survey research. First, a statistical anxiety questionnaire, which reflects three correlated dimensions of statistical anxiety including Examination Anxiety, Asking for Help Anxiety, and Interpretation Anxiety, was distributed among 72 TEFL postgraduate students. Then, interview sessions were held with 10 participants for the purpose of further exploration of the participants’ responses to the questionnaire items. Analysis revealed that examination anxiety has the highest frequency among other subscales, while the lowest frequency belongs to asking for help anxiety. These descriptive results together with the conceptualization of participants’ perspectives regarding their major concerns in statistics have clear implications for statistics teachers, course developers, policy makers, and TEFL postgraduate students.

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.

Teaching statistics to non-specialists: challenges and strategies for success

ABSTRACT Training in research methods is a crucial component of the student experience in further and higher education. A common set of statistical and experimental design methods are taught across a broad range of non-mathematics disciplines, spanning STEM subjects, medicine, and the social sciences. Understanding these methods is central to students’ ability to engage with their course, tutors, and the literature. It is also the key to enabling students to become not only practitioners of their chosen subject, but also statistically literate citizens, capable of understanding and evaluating everyday statistics. The first aim of this paper is to review the specific set of challenges faced by staff and students teaching and learning statistics within non-mathematics disciplines. Secondly, we review best practice and current trends in the design of motivating and effective statistics courses for non-specialists. Our findings suggest that many of the key challenges stem from negative attitudes towards statistics coupled with poor motivation to study the subject, factors which are exacerbated by statistics anxiety. Fortunately, because these challenges are so widespread, and have attracted the attention of innovative educators across broad disciplines, there is a wealth of good ideas and resources available to statistics teachers seeking ways to create effective learning experiences.

Relationship between Statistics Anxiety and Academic Dishonesty: A Comparison between Learning Environments in Social Sciences

The current research examines the impact of Statistics Anxiety on academic ethical behavior as manifesting in undergraduate social science students attending introductory statistics courses in different learning environments: Covid-19-Emergency Remote Teaching (ERT), Planned Online Environment (POE), and Face-to-Face (F2F) courses. Data were collected from students in academic institutions studying for a bachelor’s degree in the social sciences. Structural Equation Modeling (SEM) was used to examine the relationship between students’ previous academic achievements and Academic Dishonesty mediated by Statistics Anxiety. The results of multi-group analysis show that path coefficients differ between the three learning environments (POE, F2F, and ERT). Specifically, the results support a model in which previous math and academic achievements are significantly related to Academic Dishonesty mediated by Statistics Anxiety in a POE context only. Accordingly, POE statistics learning is less effective than F2F instruction and practice. Our research shows that instructors’ presence in the learning process reduces students’ anxiety levels and unethical behavior. Thus, we recommend that in POE, the instructor’s presence includes supportive, emphatic, and interpersonal interaction to reduce virtual distance. We conclude that introductory courses in statistics need to empower students experiencing Statistics Anxiety for a better sustainable statistical literacy population.

A meta-analysis of the relation between math anxiety and math achievement.

Meta-analyses from the 1990s previously have established a significant, small-to-moderate, and negative correlation between math achievement and math anxiety. Since these publications, research has continued to investigate this relation with more diverse samples and measures. Thus, the goal of the present meta-analysis was to provide an update of the math anxiety-math achievement relation and its moderators. Analyzing 747 effect sizes accumulated from research conducted between 1992 and 2018, we found a small-to-moderate, negative, and statistically significant correlation (r = -.28) between math anxiety and math achievement. The relation was significant for all moderator subgroups, with the exception of the relation between math anxiety and assessments measuring the approximate number system. Grade level, math ability level, adolescent/adult math anxiety scales, math topic of anxiety scale, and math assessments were significant moderators of this relation. There is also a tendency for published studies to report significantly stronger correlations than unpublished studies, but overall, large, negative effect sizes are underreported. Our results are consistent with previous findings of a significant relation between math anxiety and math achievement. This association starts in childhood, remains significant through adulthood, is smaller for students in Grades 3 through 5 and postsecondary school, is larger for math anxiety than for statistics anxiety and for certain math anxiety scales, and is smaller for math exam grades and samples selected for low math ability. This work supports future research efforts to determine effective math achievement and math anxiety interventions, which may be most helpful to implement during childhood. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Validation of an Adapted Version of the Statistical Anxiety Scale in English and Its Relationship to Attitudes Toward Statistics

The aims of this study were to validate an instrument that measured statistics anxiety and to examine how attitudes toward statistics predict statistics anxiety using the Attitudes Toward Statistics (ATS) Scale for a sample of 323 undergraduate social science majors enrolled in colleges and universities in the United States. A confirmatory factor analysis suggested retaining a revised two-factor model of the Statistical Anxiety Scale (SAS) to measure statistics anxiety, namely, help and interpretation anxiety ([Formula: see text] = 49.37, df = 38.13, p = .105, comparative fit index [CFI] = .959, standardized root mean square residual [SRMR] = .035, root mean square error of approximation [RMSEA] = .076). An examination of discriminant validity of the scores of the SAS with scores of the ATS subscales revealed that statistics anxiety and attitudes toward statistics are distinct constructs. Structural equational modeling was used to determine whether attitude toward course and attitude toward field were predictors of examination anxiety and asking for help anxiety. Of the two factors of the ATS scale, attitudes toward field and attitudes toward course, the latter predicted examination anxiety better than the former did, although both were moderate predictors of examination anxiety. We recommend that statistics educators consider the role of statistics anxiety as well as attitudes toward statistics and the field when designing their pedagogical approach.

Statistical anxiety and attitudes towards statistics: Criterion-related construct validity of the HFS-R questionnaire revisited using Rasch models

In 2018, Nielsen and Kreiner provided evidence that the Attitudes and Relationship to Statistics—Revised (HFS-R) questionnaire provides essentially valid, objective, and reliable measurement of thr...

Pengaruh Kecemasan Statistik Terhadap Berpikir Literasi Statistis Mahasiswa Bimbingan Konseling IAIN Batusangkar

The importance of statistical literacy for students has a new impact on anxiety in statistics. This study aims to determine the impact of statistical anxiety to statistical literacy ablitity for 43 Guidance and Counseling students. This study uses simple linear regression to analyze the effect of statistical anxiety variables on students' statistical literacy ability. In addition, multiple linear regression is also used to analyze the effect of each construct of statistical anxiety variables partially. The results of the study showed that there was a significant influence between statistical anxiety variables on students’ statistical literacy ability. As many as 36.1% of students' statistical literacy ability variables were contributed by statistical learning anxiety variables. Based on the result, it takes a serious effort from statistics lecturer to reduce student anxiety.

Improving Quantitative Abilities and Attitudes in Clinical Psychology Courses: Longitudinal Assessment of a Blended Learning Intervention

Background: Many students report negative attitudes toward research methods and statistics (RMS), and these attitudes are associated with impaired performance. Student interest in clinical psychology suggests that clinical courses may provide a promising venue for integrating RMS instruction. This approach may be particularly valuable for students from underrepresented groups in psychology. Objective: We evaluated whether integrating core RMS concepts into undergraduate clinical psychology courses using a blended learning intervention improved students’ quantitative knowledge and attitudes. Exploratory analyses assessed whether the intervention had differential efficacy for students from underrepresented groups. Method: Students completed pre- and post-course assessments of content knowledge, perceived RMS competence, implicit theories of quantitative skills, and statistics anxiety. We compared changes in student outcomes before ( n = 101) and after ( n = 91) implementing the blended learning intervention. Results: Overall, the intervention did not result in greater improvements in content knowledge, perceived RMS competence, or statistics anxiety. However, exploratory analyses suggested that the intervention was more effective for first-generation and racial/ethnic minority students. Change in endorsement of a growth-oriented mindset for quantitative skills was marginally stronger among students in courses implementing the blended learning intervention. Conclusion: These findings suggest that integrating RMS content in clinical psychology courses may confer modest benefits for students’ knowledge and attitudes toward quantitative skills, especially among students from underrepresented groups.

Identifying the Causative Factors for Statistical Anxiety among Undergraduates (With Special Reference to General Sir John Kotelawala Defence University)

Identifying the Causative Factors for Statistical Anxiety among Undergraduates (With Special Reference to General Sir John Kotelawala Defence University)

Exploring social work students’ attitudes toward research courses: comparing students in Australia and Switzerland

ABSTRACT Several studies have confirmed social work students’ reluctance about research courses. However, there remains little understanding of the determinants of students’ interest in research courses. This study aimed to contribute to a more robust understanding of underlying dynamics influencing students’ feelings regarding research courses through a comparison of students entering a BSW programme in Australia and Switzerland. We hypothesized that a) students’ interest in research courses was predicted by students’ fear of research courses and research orientation, b) their research orientation was determined by their fear of research courses, and c) their fear was predicted by their statistics anxiety and general self-efficacy. For data collection, we used an anonymous self-administered online questionnaire. Data were analysed using descriptive statistics, multivariate analyses and structural equation modelling. The sample included 165 Australian and 245 Swiss students (N=410). In both student groups, interest in research courses was predicted by students’ fear of research courses and their research orientation. Fear of research courses was predicted by general self-efficacy and statistics anxiety. Fear of research courses did not determine research orientation. Regardless of the diverse contexts, in both groups the predictors of research interest proved to be the same.

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.

Design, Development, and Evaluation of an Online Statistics Course for Educational Technology Doctoral Students: a Design and Development Case

The purpose of this design and development case is to document the design, development, and evaluation of a statistics course tailored for educational technology doctoral students in an online program. The course is intended to prepare online doctoral students to both consume and produce quantitative research in the field of educational technology using relevant and authentic learning experiences. This paper first outlined the course features used to engage students in the learning materials. Twenty doctoral students enrolled in this online statistics course provided relevant data on three occasions (pre-, mid-, and post-surveys) during a 16-week academic semester. Drawing from both quantitative and qualitative data sources, this paper demonstrates that the use of authentic and relevant datasets based on peer-reviewed publications from the field of educational technology coupled with engaging practice assignments, designed for students to exercise the use of various statistical techniques using SPSS, was a successful strategy. Students found learning about analysis of covariance (ANCOVA) along with factorial and repeated measures analysis of variance (ANOVA) in the same module overwhelming. Results showed that students’ level of statistics anxiety significantly decreased in three key areas. The discussion provides interpretations of the findings as well as our lessons learned.

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.

Researcher Intention to Use Statistical Software

The present study seeks to analyse researchers' willingness and intention to use statistical software packages by using the framework of the technology acceptance model. A sample of 380 researchers was taken from various academic institutions using convenience sampling. Data was collected using a structured questionnaire and respondents were asked to respond on five-point Likert scale. The findings of the study support the applicability of the technology acceptance model in explaining and predicting researchers' intention to use statistical software packages in their data analysis process. External variables such as statistical efficacy, computer attitude, statistical anxiety, perceived enjoyment and accessibility were found to have a significant relationship with the researchers' intention to use statistical software. The study provides some interesting and meaningful implications for researchers and marketing professionals involved in the development of statistical software; these are detailed in the article.

Anxious women or complacent men? Anxiety of statistics in a sample of UK sociology undergraduates

ABSTRACT One of the most commonly identified obstacles in the learning-teaching of quantitative material is statistics anxiety. Of the factors analysed in relation to statistics anxiety, age and gender have received a substantial proportion of the research focus. Yet there is limited work that systematically examines the possibility of an interrelationship, or interaction, between age and gender and reported statistics anxiety. This article aims to directly address this gap in the research by examining this interaction. A secondary analysis of data gathered from across 34 institutions in the UK is undertaken. The research presented is the first to examine this issue using a multivariate-modelling framework in a UK context. Although the international literature tends to indicate that women disproportionately experience statistics anxiety, the findings here show women have a moderate likelihood of reporting anxiety. There is a group of unworried young men who are likely to require pedagogical attention. Indeed, it may be that the existence a group of complacent young men have women seem anxious by comparison.

Integrating an Online Statistics Course With a Graduate Nursing Research Course for Enhanced Learning.

Exploration for innovative pedagogical techniques to teach statistics led to examination of the Open and Free Courses offered through the Carnegie Mellon University Online Learning Initiative (CMU OLI). This study examined the impact of the CMU OLI statistics course on graduate nursing students' course grades and course evaluations. This retrospective study of a hybrid course compared three teaching modalities for statistics: 1) face-to-face workshop, 2) CMU OLI course, and 3) CMU OLI course plus online discussions. Mean grade point averages increased sequentially and significantly. Individual students' grades improved and student evaluations of instruction mean scores for critical thinking, teaching effectiveness, overall course rating, and overall learning increased significantly (p < .01). Future studies are needed that build knowledge of how open and free online courses can be used in nursing education to facilitate retention of content, allay statistics anxiety, and increase student motivation toward research. [J Nurs Educ. 2020;59(4):227-230.].

DEVELOPING STATISTICAL UNDERSTANDING AND OVERCOMING ANXIETY VIA DROP-IN CONSULTATIONS

Students in many Australian universities start their studies mathematically underprepared as there are no prerequisites for mathematics, and assumed knowledge requirements are often overlooked. Many degrees include at least one statistics subject for which students require a reasonable level of mathematical ability to successfully complete. Students’ efforts to grasp quantitative skills often lead to feelings of anxiety, stress, and lack of self-confidence. The Mathematics Education Support Hub (MESH) at WSU provides free support in mathematics and statistics to all students, both undergraduate and postgraduate, to increase their engagement, understanding, and abilities in statistics as well as to overcome their anxiety. In this paper we focus on the drop-in consultation service, which provides “just in time” help in campus libraries. Data is collected for every consultation, which enabling an investigation in relation to the mathematics background of students and the problematic topics in statistics. Text mining is used to examine students’ queries to identify the topics in statistics subjects that students struggle most with. Outcomes of this analysis can be used by statistics instructors and mathematics support centres to improve students’ experience in learning and to help to reduce statistics anxiety in future generations of statistics students.&#x0D; First published February 2020 at Statistics Education Research Journal Archives

Pre-registration in the undergraduate dissertation: A critical discussion

Over recent years, psychology has become increasingly concerned with reproducibility and replicability of research findings (Munafò et al., 2017). One method of ensuring that research is hypothesis driven, as opposed to data driven, is the process of publicly pre-registering a study’s hypotheses, data analysis plan, and procedure prior to data collection (Nosek et al., 2018). This paper discusses the potential benefits of introducing pre-registration to the undergraduate dissertation. The utility of pre-registration as a pedagogic practice within dissertation supervision is also critically appraised, with reference to open science literature. Here, it is proposed that encouraging pre-registration of undergraduate dissertation work may alleviate some pedagogic challenges, such as statistics anxiety, questionable research practices, and research clarity and structure. Perceived barriers, such as time and resource constraints, are also discussed.