Statistics Course Research Articles

The Impact of Student Engagement and Motivation in the Statistics Learning Process

The aim of the present exploratory study was to examine students’ situational engagement and motivation in the statistics classroom at Zayed University, in Dubai, United Arab Emirates (UAE). Two instruments were used for this purpose: a) experience sampling method (ESM), and b) the validated Mathematics Motivation Questionnaire (MMQ). This study employed two samples, at undergraduate level (2nd and 4th Semesters). Participants consisted of 100 students enrolled in Statistics I and Statistics II (Probability and Structure of Randomness). The results indicate that, apart from challenge and effort, emotional engagement is not significantly different across different activities. The results also indicate increases in intrinsic value and utility value and decreases in test anxiety. Finally, results indicate higher engagement and effort when social interaction is purposely planned and fostered, such as in small groups. On the contrary, individual class activities seem to generate slightly lower levels of engagement and effort. These findings have significant implications for educators and researchers who seek to enhance students' engagement and motivation in their statistics courses

PERHITUNGAN MATEMATIS KLASTERISASI NILAI MATA KULIAH MAHASISWA MENGGUNAKAN ALGORITMA K-MEANS

This research aims to conduct mathematical calculations related to the clustering of statistical course grades among students. The author utilized data from several students enrolled in the Mathematics Education Study Program at STAI Muhammadiyah Probolinggo, who took the statistics course as a case study. The clustering algorithm employed in this study is K-Means. The analysis results provide significant insights into the students' abilities in the statistics course. This research offers potential benefits to the study program in curriculum development and the design of more effective teaching strategies. The findings can be used to identify student groups in need of additional attention and to comprehend academic behavior patterns that may affect learning outcomes. In this study, only grade atributes such as assignments, mid-term, and final exam scores were utilized. Nevertheless, it is worth noting that the K-Means algorithm can be applied to cluster data with multiple grade atributes, including attendance, discipline, participation, and other atributes relevant to student learning.Keywords : mathematical calculations, identification, clustering, attributes

The mediating role of online learning readiness in the relationship between course satisfaction and self-efficacy to learn statistics in online classes

ABSTRACT The study identifies the mediating effects of online learning readiness (OLR) in the relation between course satisfaction and self-efficacy to learn online statistics. The sample comprised 121 students recruited from a large public university in a south-eastern state in the United States of America. Structural equation modelling (SEM) and correlational analysis were used to test the hypotheses. We found that self-efficacy to learn statistics is positively associated with both course satisfaction and online learning readiness in students. OLR has a significant positive association with course satisfaction. Our findings confirmed the mediational effect of OLR of students enrolled in online statistics courses in the relationships between self-efficacy to learn statistics and students’ course satisfaction. This study suggests that self-efficacy to learn statistics contributes to higher course satisfaction in online statistics learning. We suggest that educational establishments should focus on developing policies to improve the online learning readiness of students and student self-efficacy, to enhance course satisfaction.

A Rasch-model-based hierarchical framework for statistical literacy and learning

Statistical literacy has a large and important role in the teaching of statistics. Most mathematics and statistics courses are hierarchical, and the earlier material forms the foundation for later material. We construct a hierarchical structure for an introductory statistics course using Rasch analysis of the student scripts for the final examination. This forms the basis of a statistical literacy construct that has wider implications than just an undergraduate course. The world is overwhelmed with data from an exponentially increasing number of sources. Such data is of various types and contexts, ranging from social, commercial, scientific, survey and human. Statistical literacy has therefore assumed a larger and more important role.

Examining statistical literacy, attitudes toward statistics, and statistics self‐efficacy among applied linguistics research students in China

AbstractStatistics has played an increasingly important role in applied linguistics research. However, little research has been available that sheds light on statistical literacy among early‐career researchers of applied linguistics. The study reported in this article surveyed statistical literacy, attitudes toward statistics, and statistics self‐efficacy among Chinese applied linguistics research students and further examined the inter‐variable relationships. Based on analyses of the cross‐sectional survey of 211 master's students, we found that: (1) the students’ overall statistical literacy was not satisfying; (2) although they thought positively of statistics, they were not particularly confident with statistics; (3) the three experience‐related variables—the number of statistics courses taken, quantitative research orientation, and self‐training—were important predictors of statistical literacy, attitudes toward statistics, and statistics self‐efficacy; and (4) statistics self‐efficacy seemed to mediate the relationship between attitudes toward statistics and statistical literacy. We discussed these findings in relation to improving statistics courses in applied linguistics program in China and to statistics learning and teaching.

Pengaruh Minat Belajar dan Motivasi Belajar terhadap Prestasi Belajar Mahasiswa Program Studi Matematika pada Mata Kuliah Statistika Deskriptif

Pengaruh Minat Belajar dan Motivasi Belajar terhadap Prestasi Belajar Mahasiswa Program Studi Matematika pada Mata Kuliah Statistika Deskriptif

Covid in Italy: Comparison between Models

The text aims to address the topic of the SARS-CoV-2 pandemic from the point of view of mathematical models. Numerous studies refer to the impact of COVID-19 on student behavior, the use of e-learning, and harm reduction policies. The analysis presented in the text has a different objective: to develop, among students, knowledge of some mathematical models starting from data detected in a phenomenon of notable impact. In this case, the focus is on the aspects that could be covered in the last class of some upper secondary school courses or the first year of university in mathematics and statistics courses. The data refers to the Italian case, and the analysis considers data from 02/24/2020 to 5/5/2023, the date the WHO declared the end of the pandemic.

The Impact of Research Methodology and Statistics Mastery on the Quality of Student Theses in Elementary School Teacher Education Department

Thesis is one of the biggest challenges for students. This is because students often do not understand the method of writing a thesis as a scientific paper. This research was carried out to examine the mastery of research methodology and statistics on the quality of student thesis. The research method used in this study is quantitative research. The results of this study then found a positive and very significant relationship between mastery of educational research methodology material and the quality of the thesis. Then a positive and very significant relationship was also found between the level of student mastery of the statistics course material and thesis quality. Finally, the hypothesis testing concluded that between the variables of student mastery of research methodology material and statistics course material, there was a positive and very significant relationship with the thesis quality of university students.

First‐year undergraduate students’ statistical problem‐solving skills

AbstractThis study investigated first‐year undergraduate statistics students’ statistical problem‐solving skills on the probability of the union of two events, conditional probability, binomial probability distribution, probabilities for x‐limits using the z‐distribution, x‐limit associated with a given probability for a normal distribution, estimating the y‐value using a regression equation, and hypothesis testing for a single population mean when a population standard deviation is unknown. The study was a descriptive case study and employed a mixed‐method research approach. Data were collected through content analysis of a statistics course examination script of 120 first‐year undergraduate students of statistics in an open distance‐learning university in South Africa. Polya's Model of Problem Solving was used as the framework of analysis. The study revealed that the students, in general, had poor statistical problem‐solving skills.

Culturally Relevant Data in Teaching Statistics and Data Science Courses

In this article, we consider how to make data more meaningful to students through the choice of data and the activities we use them in drawing upon students lived experiences more in the teaching of statistics and data science courses. In translating scholarship around culturally relevant pedagogy from the fields of education and mathematics education we develop the idea of culturally relevant data. We see this development as a key ingredient to implementing culturally relevant pedagogy in teaching data-intensive courses leveraging the centrality of context through data in both statistics and data science to engage students particularly from historically marginalized groups in STEM. We provide suggestions as to ways of finding or creating culturally relevant data and using them in implementing culturally relevant pedagogy to support the learning and flourishing of students in statistics and data science courses. We also present findings from pilot work we have done in implementing these data in statistics courses. Finally, we discuss lingering questions and possible next steps for research in this area. Supplementary materials for this article are available online.

Exploring Achievement Behaviors in Non-Major Statistics Course: An Expectancy-Value Perspective and Thoughts for Practice

Statistics education is increasingly important to our society with enrolment increases of 16% in introductory statistics courses and 85% in upper-level statistics courses. Research has demonstrated many factors related to students’ behaviors and outcomes in statistics courses such as past achievement, attitudes, and effort. We sought to model these factors together to better understand how introductory statistics students’ attitudes were related to students' achievement behaviors and what student characteristics mediated such relationships. Structural equation modeling with data from N=301 students in an introductory statistics course for psychology majors revealed that majors with higher GPAs had more interest, enjoyment as well as utility value for statistics, and these variables were in turn related to expectations for success or achievement behaviors. Females had lower interest in statistics, and this was related to lower expectations of success. The findings highlight the need to increase interest and enjoyment and utility value for non-majors studying statistics. Recommendations for how to adapt the statistics classroom to that end are discussed.

Implementation of Alternative Grading Methods in a Mathematical Statistics Course

Alternative grading methods, such as standards-based grading, provide students multiple opportunities to demonstrate their understanding of the learning outcomes in a course. These grading methods allow for more flexibility and help promote a growth mindset by embracing constructive failure for students. Implementation of these alternative grading methods requires developing specific, transparent, and assessable standards. Moving away from traditional methods also requires a mindset shift for how both students and instructors approach assessment. While providing multiple opportunities is important for learning in any course, these methods are particularly relevant to an upper level mathematical statistics course where topics covered often provide an additional challenge for students as they lie at the intersection of both theory and application. By providing multiple opportunities, students have the space for constructive failure as they tackle learning both a conceptual understanding of statistics and the supporting mathematical theory. In this article we share our experiences—including both challenges and benefits for students and instructors—in implementing standards-based grading in the first semester of a mathematical statistics course (i.e., focus primarily on probability). Supplementary materials for this article are available online.

Peer leader perspectives from a PLTL implementation in a Hispanic-serving institution.

Peer-Led Team Learning (PLTL) is a pedagogical approach that has been shown to benefit all students, especially underrepresented minority students and peer leaders in Science, Technology, Engineering, and Mathematics (STEM) disciplines. In this work, we present results from our study of the impact of PLTL on our peer leaders from a controlled implementation in general biology, general chemistry, and statistics courses at a Hispanic-serving, minority-serving institution. More specifically, we have measured our PLTL program's impact on our peer leaders' skill development, engagement with the subject material, and sense of belonging as peer leaders. Weekly peer leader reflections analyzed using the Dreyfus model exhibited a consistent set of skills, while those analyzed using the Pazos model revealed a consistent type of student-peer leader interactions, allowing for peer leaders to be assigned to specific levels in the hierarchy of each of the models. Analysis of eight skill-based Likert-scale questions on the SALG survey showed an overall positive shift at the highest level. Independent of the skill or interaction level of the peer leader, we observed several instances of peer leaders acknowledging development in their communication skills, sincere attempts at creating an engaging classroom, and a deep investment in their student's success. Peer leaders also reported improvements in understanding of the subjects they were teaching, wanting to persevere and solve problems independently, and feeling passionate about helping other students.

Empathy through Data? Student Exploration of Elements of Diversity through Projects in an Introductory Statistics Course

A project involving data related to socioeconomic indicators was administered in an introductory statistics course. As part of this project, student groups investigated a data set from the United States Department of Agriculture Food and Nutrition Service website with information on recipients of Supplemental Nutrition Assistance Program (SNAP) benefits. Pre/post data from the Miville-Guzman Universality-Diversity Scale (M-GUDS) short form were collected to measure changes in diversity awareness. The survey administered also included demographic information and open-ended questions. Based on study results (n = 48), there was moderate evidence of a change in the diversity of contact subscale of the M-GUDS short form. Written feedback indicated that students demonstrated empathy for individuals with potentially different lived experiences. The focus of this paper is to describe the study results and provide information on the importance of incorporating elements of diversity into curriculum.

A Review of the Use of Investigative Projects in Statistics and Data Science Courses

An investigative project can engage the learner in all aspects of a statistical investigation, including developing a question or issue of interest, gathering needed information, exploring the data, and communicating the results. This article summarizes the available literature regarding the implementation of investigative projects, including the potential benefits of projects, how projects have been used in a variety of settings, advice for those looking to implement projects, and future research avenues.

Probing Scaffolding Self-Regulated Learning Responses, Resources Contribution and Target Achievements of University Students in Statistics Course

Scaffolding self-regulated learning is an emerging research agenda in higher education. However, scaffolding self-regulated learning in a relatively complex subject such as statistics is still understudied. The present study addresses this matter by observing university students’ engagement in scaffolding self-regulated learning in a statistics course focusing on their scaffolding responses, resources contribution and target achievements. It was an exploratory case study with the participation of 26 private university students who are enrolled in the fifth semester as their third-year studies. The results indicate that university students are aware of statistics learning goals but overtargeting achievements, as they were less likely to achieve their decided targets. Students prefer to write a self-reflection than take notes. The different duration of watching videos and reading modules does not vary in quiz performance. The current findings add a novel understanding that self-regulated statistics learning requires advanced scaffolds to promote higher outcomes because of its characteristics as a complex and abstract subject.

Integrating Diversity into Psychology Statistics Courses: Advice, Reflections, and Special Considerations

Introduction In an increasingly diverse world, there has been a call for psychology educators to make efforts to integrate diversity into the psychology curriculum. Statement of the Problem Researchers who have surveyed psychology faculty have found the amount of time devoted to diversity content in nondiversity-focused courses is limited, with faculty citing barriers to integration such as a lack of relevance and time constraints. Literature Review Educators who have worked to incorporate diversity topics into their courses have found positive outcomes. Teaching Implications We describe our approach to integrating diversity into an introductory statistics course, highlight lessons learned, and provide special considerations for psychology educators. Conclusion Integrating diversity-related content into statistics is challenging; however, the effort is worth it, particularly if integrating diversity content into required courses may be the only exposure to diversity students get.

How does one's “mindset” contribute to statistical learning? A moderated mediation model of growth mindset of statistical ability on statistical learning outcomes

The purpose of this study is to investigate whether “growth mindset” contributes to statistical learning in the social sciences, and to address the controversy whether growth mindset is positively associated with academic achievement. Students enrolled in a statistics course were invited to participate in a two-stage online questionnaire, resulting in cross-sectional data (including only the first-wave data) and longitudinal data (two-wave data). Both cross-sectional and longitudinal data show that compared with general growth mindset, statistical growth mindset has a significant indirect effect on academic achievement in statistics courses acting through academic engagement, which supports the idea of “domain specificity”. Perceived difficulty moderated the effect of the statistical growth mindset and academic engagement, only in cross-sectional data. This study provides empirical evidence for the application of a statistical growth mindset to statistical learning and partially addresses the controversy over the predictive effect of growth mindset.

The effect of students’ attitudes and concerns on statistical concepts performance: A SEM approach

The purpose of this study was to investigate how the attitudes and concerns of higher learning students made an impact on their performance in the fundamental concepts of the statistics course. Despite being classified as one of the important areas of scientific, industrial, or social problems, students generally perceive statistics as a challenging course to understand. This negative perception leads to a set of complex emotional reactions that may cause great discomfort, resulting in negative consequences, such as anxiety. A sample of 248 UiTM Pahang Branch students, enrolled in a basic statistics course, was randomly selected using a stratified sampling technique. This study employed Structural Equation Modeling (SEM) method to assess the linear relationship model between students' attitudes and concerns, and their performance in statistics examinations. The findings indicated that both students' attitudes and concerns showed a significant negative influence on their performance in statistics examinations, resulting in poor academic performance. Hence, to foster students' academic success in statistics courses, it is essential to cultivate a positive attitude and enhance their confidence levels.

Creating simulation applets to teach statistics

The purpose of this study is whether the use of software for simulating concepts of statistics and probability theory during a semester introductory statistics course ensured greater success in the final exam of the course for students who used it, compared to students who used general statistical software. The simulation software used was created for this purpose based on the average level of understanding of the students who attended the course. The students who attended the course were divided into two groups in a way that ensured that the two groups had proportionally about the same level of statistical knowledge, mathematical background, and about the same number of students in terms of origin and gender. One group used simulation software throughout the semester, while the other used general statistical software. The simulation software used in this survey was created for this purpose based on the average level of understanding of the students who attended the course. At the end of the semester after the final exam, various factors were considered and students' final exam performance (success rates), were compared based on these factors. It appeared that success in the final exam when it comes to similar populations as the two groups of students who attended the course has a strong dependence on the factor of using simulation software.