Statistics Course Research Articles

Undergraduate Research in an Applied Probability & Statistics Course

The author modified a course entitled Applied Probability and Statistics to engage students in performing their own hypothesis tests in a course-based undergraduate research experience (CURE). This paper discusses the structure of the course, what it does to encourage undergraduate research, and changes one could make to tailor this experience to their own institutional needs.

PSYCHOMETRIC EVALUATION OF THE STUDENTS’ ATTITUDES TOWARD STATISTICS AND TECHNOLOGY SCALE (SASTSc)

The current study sought to evaluate the SASTSc in two samples of students taking a statistics course that incorporates statistical software. The SASTSc was given at two time points, once at the beginning of the semester and then again at the end of the semester. Our evaluation included examining competing factor analytic models, examining convergent validity, test-retest reliability, and assessing internal consistency. Our results in both samples replicate the scale’s proposed factor structure; however, not all items were useful and we propose some changes to the wording of items to improve the scale. Data, analysis scripts, and results are publicly available at https://osf.io/rv64m/?view_only=6dfbf883f0d841b69c238773cee6e62e.

An exploration of course and cohort communication spaces in Discord, Teams, and Moodle

This research examined the impact of supplementing a learning management system, Moodle, with communication tools, Discord and Teams, to support communication in blended and distance undergraduate courses in computer science, information technology, mathematics and statistics at a New Zealand university with well-established use of Moodle. Nineteen students participated in semi-structured interviews. Findings show that adding Discord or Teams increases information and knowledge exchange and helps students to connect with peers and teachers in their courses. Teams was beneficial particularly in settings with formal group work. Discord, which enables both students and staff to set up additional communication channels that are not restricted to course enrolments, was instrumental in connecting students across year levels with peers and alumni. This enabled discussions on course selection, career options and disciplinary topics beyond the course curriculum. Importantly, these beyond-course communication spaces nurtured belonging to wider discipline and study communities. The research establishes the importance of the increased levels of communication by highlighting the effects on student learning and connections to others. Looking beyond the specific tools, the level of formality and the degree of student co-ownership are identified as key factors in supporting the within- and beyond-course communication spaces. Implications for practice or policy: Learning management systems provide valuable course support but do not meet all learning and teaching communication needs, partly due to their formal and university-controlled nature. Educators and students benefit from using strong chat tools with improved information and knowledge exchange. Both educators and students experience enhanced belonging when using collaboration and chat tools. Students value Discord’s informality and student-led characteristics. Educators who use Teams to support formal group work must carefully manage integration with Moodle.

Creativity in Deriving The Fermi-Dirac Equation Through STEAM Approaches

This research is motivated by statistical physics learning in deriving the Fermi-Dirac equation conceptually from lecturers to students or by rote and low creativity of students. This study aims to explore student learning creativity in deriving the Fermi-Dirac equation through the STEAM approach. This study uses a didactic design that includes the stages of prospective analysis, didactic metapedia analysis, and prospective re-analysis, which is applied to the sixth-semester physics tadris student of UIN Sulthan Thahah Saifuddin Jambi. The research instrument used is a description test and a non-test through observation sheets and interviews. The results showed that the implementation of STEAM could increase the creativity of statistical physics with an achievement level of 87% asking questions, 78% learning outcomes, 75% reflection, and 75% analysis on the material of the Fermi-Dirac equation by adhering to student activities starting with phenomena that are easy to digest with the realistic situation during online lectures, which shows that the STEAM approach is quite well used in deriving the Fermi-Dirac equation in the online statistical physics course.

Can Gender and Major Explain College Students’ Performance in Business Statistics?

Recent discussions in education, industry, and government have focused on the need for growth and diversity in STEM fields. STEM education and practice directly contribute to the economic vitality of a nation and benefit its citizens. Yet, STEM education and employment growth seem lopsided concerning both gender and diversity. While researchers have studied various dimensions of this phenomenon, this paper seeks to add to the knowledge base by analyzing the effects of gender and college major on performance and attitudes in statistics-related courses. T-tests, one-way analysis of variance, and multiple regression were used to investigate the effects of gender, major, and attitude on performance in business statistics courses. Results indicate that, in the business statistics course, there were no significant differences between the average score of male students and female students in 2 of 3 semesters. In the marketing research course, where similar statistical concepts as taught in the business statistics course were adopted, results were similar. However, there were differences in the students’ scores when their academic majors were considered. Findings from this study can contribute to developing effective and innovative pedagogical methodologies to teach statistics and related subjects.

Rasch rating scale analysis of the survey of attitudes toward statistics

Students in every discipline in higher education take at least one course in statistics. Therefore, it is necessary to enhance students’ understanding of statistics and their achievement in such courses by considering several factors that might contribute to this enhancement. Students’ attitudes toward statistics are a critical factor that influences their performance in statistics courses, and thus an accurate measurement of attitudes is needed. The survey of attitudes toward statistics (SATS-36) is widely used in measuring attitudes toward statistics; thus, it is important to ensure that its items accurately assess this construct. Therefore, the purpose of the current study was to validate this survey when administered to a convenience sample of 423 university students. Using the Rasch rating scale model, the current study examined the dimensionality, item fit to the Rasch model, item and person reliabilities, functionality of response categories, and distribution of the SATS-36 items along the attitudes toward statistics continuum.<br /> The findings revealed excellent item and person reliabilities (greater than 0.90) and the uni-dimensionality of the survey. Additionally, all items were closely aligned with the respondents, and the response categories were well-functioning as each category had more than 10 observations and outfit statistics were all low. However, some improvements were suggested. All items on the effect subscale and some others from different subscales need to be altered in content, deleting three items (two from the value subscale and one from the difficulty subscale) and adding more items to have a better distribution of items along the continuum. Finally, the number of response categories is recommended to be reduced to five instead of seven to have a more efficient rating scale. The findings of the current study imply that even though great care has been taken in the development of this survey, examining the quality of its items and the utility of its rating scale in new settings, and using different validation approaches is necessary.

Supplemental Material for Online Versus Face-to-Face Learning in an Undergraduate Psychology Statistics Course

Supplemental Material for Online Versus Face-to-Face Learning in an Undergraduate Psychology Statistics Course

Project-Based Learning Promotes Students’ Perceived Relevance in an Engineering Statistics Course: A Comparison of Learning in Synchronous and Online Learning Environments

Understanding statistics is essential for engineers. However, statistics courses remain challenging for many students, as they find them rigid, abstract, and demanding. Prior research has indicated that using project-based learning (PjBL) to demonstrate the relevance of statistics to students can have a significant effect on learning in these courses. Consequently, this study sought to explore the impact of a PjBL intervention on student perceptions of the relevance of engineering and statistics. The purpose of the intervention was to help students understand the connection between statistics and their academic majors, lives, and future careers. Four mini-projects connecting statistics to students’ experiences and future careers were designed and implemented during a 16-week course and students’ perceptions were compared to those of students who took a traditional statistics course. Students enrolled in the experimental group (a synchronous learning experience) and the control group (an online learning experience) were sent the same survey at the end of the semester. The survey results suggest that the PjBL intervention could potentially increase students’ understanding of the usefulness of statistics and effectively enhance their perceptions of belonging to the engineering community. This study summarizes the results of this PjBL intervention, the limitations of the research design, and suggests implications for improving future statistics courses in the context of engineering.

Student Concerns and Perceived Challenges in Introductory Statistics, How the Frequency Shifted during COVID-19, and How They Differ by Subgroups of Students

ABSTRACT The COVID-19 pandemic and shift to remote instruction disrupted students’ learning and well-being. This study explored undergraduates’ incoming course concerns and later perceived challenges in an introductory statistics course. We explored how the frequency of concerns changed with the onset of COVID-19 (1417) and, during COVID-19, how incoming concerns compared to later perceived challenges (524). Students were most concerned about R coding, understanding concepts, workload, prior knowledge, time management, and performance, with each of these concerns mentioned less frequently during than before COVID-19. Concerns most directly related to the pandemic—virtual learning and inaccessibility of resources—showed an increase in frequency. The frequency of concerns differed by gender and URM status. The most frequently mentioned challenges were course workload, virtual learning, R coding, and understanding concepts, with significant differences by URM status. Concerns about understanding concepts, lack of prior knowledge, performance, and time management declined from the beginning to the end of the term. Workload had the highest rate of both consistency and emergence across the term. Because students’ perceptions have an impact on their experiences and expectations, understanding and addressing concerns and challenges could help guide instructional designers and policymakers as they develop interventions.

Development of a Revised Version of the Statistical Anxiety Scale.

Statistics anxiety is a common problem in students taking statistics courses in the social sciences. It is most widely measured by the statistical anxiety scale. The various adaptations of this instrument have shown certain problems in the replication of its factorial structure and do not have a system to control possible response bias effects. The objective of our study was to propose a short test to measure statistical anxiety that also includes a scale to control social desirability bias. We developed a revised version of the statistical anxiety scale using procedures for controlling response biases and examined its factorial structure using exploratory and confirmatory analysis in a sample of 531 students. The revised version showed a clear four-factor structure in exploratory and confirmatory factor analyses with the expected three content factors plus one social desirability factor. The scales showed no acquiescence effects and moderate social desirability effects, and had a clear relationship with academic success. The revised version of the statistical anxiety scale improves on the psychometric properties of the original version and may overcome the problems detected in some adaptations of the previous version.

Third Time’s a Charm: A Tripartite Approach for Teaching Project Organization to Students

Collaborative statisticians are instrumental to maintaining the rigor and reproducibility of multidisciplinary projects on which they collaborate. Clear, complete, well-annotated records of data, its revising, analysis, interpretation, and presentation are essential. Many students do not know how to systematically and consistently organize their digital files and cannot reliably replicate (or find!) work that may have been performed on a collaborative project. This article describes a newly developed and required one semester collaborative statistics course that includes the explicit teaching of project organization in lecture, emphasis of these skills on linked homework assignments, and their closely supervised practice through a mentored collaborative project with multidisciplinary researchers. The tripartite design provided exposure to project organization concepts during the course, encouraged straightforward implementation through homework assignments, and then challenged students with a real-world experience during a collaborative project. Supplementary materials for this article are available online.

An Empirical Analysis of the Impact of Continuous Assessment on the Final Exam Mark

Since the Bologna Process was adopted, continuous assessment has been a cornerstone in the curriculum of most of the courses in the different degrees offered by the Spanish Universities. Continuous assessment plays an important role in both students’ and lecturers’ academic lives. In this study, we analyze the effect of the continuous assessment on the performance of the students in their final exams in courses of Statistics at the University of Almería. Specifically, we study if the performance of a student in the continuous assessment determines the score obtained in the final exam of the course in such a way that this score can be predicted in advance using the continuous assessment performance as an explanatory variable. After using and comparing some powerful statistical procedures, such as linear, quantile and logistic regression, artificial neural networks and Bayesian networks, we conclude that, while the fact that a student passes or fails the final exam can be properly predicted, a more detailed forecast about the grade obtained is not possible.

A Randomized Study to Evaluate the Effect of a Nudge via Weekly E-mails on Students’ Attitudes Toward Statistics

Can a “nudge” toward engaging, fun, and useful material improve student attitudes toward statistics? We report on the results of a randomized study to assess the effect of a “nudge” delivered via a weekly E-mail digest on the attitudes of students enrolled in a large introductory statistics course taught in both flipped and fully online formats. Students were randomized to receive either a personalized weekly E-mail digest with course information and a “nudge” to read and explore interesting applications of statistics relevant to the weekly course material, or a generic course E-mail digest with the same course information, and no “nudge.” Our study found no evidence that “nudging” students to read and explore interesting applications of statistics resulted in better attitudes toward statistics. Supplementary materials for this article are available online.

Threshold Concepts Theory in Higher Education—Introductory Statistics Courses as an Example

The purpose of this research was to identify “threshold” concepts in introductory statistics courses by surveying engineering students. Threshold concepts are those ideas that bind a subject together and are fundamental to the thinking and practice within a discipline. In this exploratory study, the aim was to answer the following questions: What are the learners’ assessments of the proposed threshold concepts? Based on the learners’ assessments, which of the four threshold characteristics best describes the selected threshold concepts? What are the final proposed threshold concepts that incorporate the learners’ perspectives? What is the perception held by learners about the theory’s impact on the learning and teaching processes? Using qualitative and quantitative exploratory analysis to answer these questions, all students in the College of Engineering and Applied Science who took one of the 29 sections of the course Introductory Statistics offered at the University of Colorado at Boulder were surveyed. The findings reveal there are differences in threshold concepts identified by instructors and learners. The learners added 11 concepts to the 18 proposed by the instructors as threshold concepts. Based on these inputs, a list of potential threshold concepts incorporating the two perspectives—that of instructor and that of learner—was created, and a framework of knowledge to support curriculum design was developed. An important suggestion for future research is to explore how to incorporate these threshold concepts in redesigning the syllabi of such courses, depending on the proposed framework.

Math Attitudes, Engagement, and Performance of High School Students on High and Low-stakes Tests of Statistics Knowledge

Understanding the extent engagement and math attitudes predict performance in statistics courses could inform educational interventions in this subject area, which has growing demand. We examined direct and indirect associations between course engagement-related constructs, math attitudes, and learning outcomes. Confirmatory factor analysis was used to validate scores from measures of these constructs with a sample of high school students enrolled in Advanced Placement (AP) statistics (N = 720, mean age = 16.8 years, SD = 0.82). Structural equation models were fitted to the data to examine relations between these constructs on a subsample (N = 220). A greater proportion of variation was explained in a high-stakes learning outcome (R2 = 0.54) than a low-stakes learning outcome (R2 = 0.24). We found some evidence of indirect effects of academic procrastination and course engagement on the learning outcome by way of math attitudes. The findings shed light on opportunities for intervention on academic maladaptive behaviors, such as procrastination, which could lessen negative effects on math attitudes and learning. These findings highlight the importance of testing stakes when examining associations between engagement, math attitudes, and learning, particularly in the context of high school statistics, a growing and yet understudied STEM learning context.

Reducing the influence of perfectionism and statistics anxiety on college student performance in statistics courses.

The influence of perfectionism and statistics anxiety on academic performance (AP) in statistics courses was investigated using a multidimensional perfectionism scale and a statistics anxiety rating scale. For perfectionism, the factor of personal standards (PS) had a significant direct positive effect on AP, while the factor of parental expectations (PE) was significantly negatively correlated with AP. Other factors (concern over mistakes, organization, and doubts about actions) did not significantly influence AP. For statistics anxiety, the two factors (test and class anxiety and computation self-concept) significantly impaired AP. These results indicated a need for innovation in classroom instruction and the reform of statistics course content and presentation to reduce statistics anxiety and improve PS. There is also a need to ensure that students better internalize PE and to revise instructional design techniques to enhance students’ independent learning ability.

Penugasan Tutor Sebaya dengan Metode Pinalti

This research focuses on the assignment of peer tutors in the Mathematics Study Program, Mathematics Department, FMIPA Unpatti. The purpose of this study was to obtain the completion of peer tutor assignments with the penalty method. The penalty method is a method used to solve the problem of unbalanced assignments. The processed two parts, namely finding the initial solution and finding the optimal solution. The column penalty method or the row penalty method is used to get the initial solution. In this study, the row penalty method is used because the number of rows is less than the number of columns, and the optimal solution is sought. The data used are student names, courses, and final grades. The results obtained using the Penalty method are that David becomes a tutor in the Statistical Method course, Alfito becomes a tutor in the Operations Research course, Christin becomes a tutor in the Linear Program course, Gabriella becomes a tutor in the Analytical Geometry course and Navila becomes a tutor in the course Elementary Statistics.

Investigating Problem Solving and Mathematical Connections in Solving the Fermi-Dirac Equation

This study aimed to describe the problem-solving abilities and mathematical connections of the sixth-semester students of Physics Tadris in the Statistical Physics course, especially the Bose-Einstein Equation Material. This type of research is quantitative descriptive research. Data collection in this study used a cognitive test technique in the form of a description test to measure students' mathematical abilities, which amounted to 8 questions, of which four were used to measure problem-solving abilities, and four were used to measure students' mathematical connections. Data analysis was carried out descriptively to determine the profile of students' mathematical abilities and the distribution of predicate achievement on the ability of problem fractions and students' mathematical connections. The results showed that students' average problem-solving ability and mathematical connection were in the Pretty Good category.

An Investigation of Students’ Difficulties in Statistics Learning on Online Based Learning at Universitas Terbuka Taiwan

This study aims to determine the students’ difficulties in online learning. Online learning is one solution offered by several parties such as the government, universities, and teachers. However, this has not been fully able to help students understand the statistics well. This study investigates students’ difficulties in terms of topics, learning processes, and assignments. The students have taken statistics courses for one semester. The data collection techniques with open questionnaires via google Forms and online interviews. The number of participants for open questionnaires was 25 students and 6 students were taken to be interviewed. Based on the questionnaires and interviews conducted with students, the results of the study are that students still have difficulty in understanding the material itself because of complicated calculations, complicated formulas, and Unrealistic. While the difficulties of students in online learning are limited time, network problems, explanations and examples of questions are not written in detail in online learning, the strategies used in online learning make some students negligent in learning, and the number of online meetings is still lacking, online learning can be helpful but not maximized. Moreover, students’ difficulties with assignments such as the formula are very much, the book has several errors, students do not understand the stages in solving problems, difficulty in determining the symbols used in the story problem, difficulty in calculating it, difficulty in imagining the application of the formula into real life. The recommendation from this study is the statistics teacher can choose the appropriate learning model for statistics courses.
 Keywords: Students’ Difficulties, Statistics Learning, Online Learning

Impacts of the COVID-19 Transition to Remote Instruction for University Students

At a public university in March 2020, 234 students (78% female; 63% second year, 28% third year) enrolled in a psychological statistics course described their experiences during the first week of the transition to remote instruction in response to coronavirus disease 2019. Qualitative responses indicated 13 common concerns in the following domains: financial, housing, and food security; social life; emotional health; sleep; and academic performance. Students with lower socioeconomic status were more likely to experience financial instability, food insecurity, and academic challenges.