Level Statistics Course Research Articles

Five Hands-on Experiments for a Design of Experiments Course

In many collegiate level statistics courses, the focus of the learning outcomes is often on the analysis of data after it has been collected. Students are provided with clean data sets from previous studies to practice statistical analysis, but receive little to no application as to the amount of time and effort that goes in to collecting good data. To account for these deficits at the author’s institution, a design of experiments course was created that provided students with a more hands-on learning experience to the statistical process, especially as pertains to data collection. This paper focuses on five of the experiments that students designed and implemented during the course, and some suggestions to instructors that may wish to use these experiments in their own courses.

"Constantly Working on My Attitude Towards Statistics!" Education Doctoral Students' Experiences with and Motivations for Learning Statistics.

Doctoral students in education-related fields are required to take graduate level statistics courses and often face anxiety and negative attitudes about taking these courses. Using a mixed methods survey research design (N = 95), this study explored students’ experiences with statistics anxiety and how course instructors can support them to mitigate statistics anxiety and improve attitudes. Analyses of quantitative survey data found that students who had never taken a statistics course before beginning their doctoral program, and students that had completed less doctoral coursework had higher negative attitudes towards learning statistics; and older students had higher statistics anxiety. Plans to use research in the future predicted more positive attitudes and lower statistics anxiety. Analysis of qualitative survey data found that students: (1) expressed that their attitude towards learning statistics was very important and played a big role in how they approached their coursework; (2) considered their plans to use research skills in the future as motivation to learn statistics; and (3) believed that their instructors’ attitudes and instructional practices supported learning and decreased statistics anxiety. This study has implications for how statistics and research methods courses are taught in higher education, and how the experiences of graduate students in education may have lasting implications for research use in Prek-12 education settings.

Comparing the Performance of ESL and English-Native Speaking Students in an Introductory Level Statistics Course

English as a second language (ESL) students often face more challenges than their English-Native Speaking (ENS) peers due to language and cultural barriers. The purpose of this study is to investigate the difference in performance between ESL students and ENS students in the introductory level statistics course, STAT150, at the University of Norther Colorado (UNC). Due to the dichotomous nature of the data and the large differences in sample sizes between ESN and ESL students, the Bootstrapped Logistic Regression model is used to analyze the data. Contrary to the findings of previously conducted studies, the results of this study suggest that ESL students who have been enrolled in STAT 150 at UNC are just as likely to receive a high mark in the course as their ENS counterparts. One explanation for this finding is that the level of instruction and quality of content provided throughout the course gave all students, including ESL students, all the information necessary to succeed in the course. If this explanation is accepted, the outcomecentric results found by this study reflect well upon the overall quality of instruction and English proficiency policies at UNC.

MÜHENDİSLİK ÖĞRENCİLERİNİN İSTATİSTİĞE KARŞI TUTUMLARI: ÇOKLU DURUM ÇALIŞMASI

This study investigated the attitudes toward statistics of the electrical & electronics engineering and geomatic engineering students who were enrolled in a Turkish university. Survey of Attitudes toward Statistics-36 (SATS) was used to collect data. The participants of the study were 62 Engineering students (38 male and 24 female). They were sophomore students enrolled in either electrical & electronics engineering (n=28) or geomatic engineering (n=34) departments and had not taken a university level statistics course before. Both electrical & electronics engineering students and geomatic engineering students generally had positive attitudes toward statistics; however, geomatic students tended to have more neutral attitudes at the end of the semester.

Gamify Online Courses with Tools Built into Your Learning Management System (LMS) to Enhance Self-Determined and Active Learning

“Gamified” active learning has been shown to increase students’ academic performance, engagement, and make more social connections than standard course settings. However, the costs to use an educational game design with efficient delivery of the game/course plan can be problematic. Our first objective was to evaluate the effectiveness of gamification by using existing techniques (e.g., simple HTML-based games) and readily available collaborative tools (e.g., Wikis) from a typical learning management system (LMS) such as Blackboard. Moreover, our second objective was to examine students’ attitudes towards gamification (e.g., usefulness). Data were collected from 2015 to 2017 (n = 80) at a Midwestern university in the United State using a mixed methods approach. For the quantitative method, online surveys were conducted in an experimental group (class with implementation of gamification) and control group (class without any gamified activities) that were randomly selected from graduate level statistics courses. For the qualitative method, the researcher conducted semi-structured interviews with subjects who addressed their interests to be interviewed during the online survey. A Welch’s independent t-test revealed a significant difference (p < 0.001) in the mean exam scores of experiment and control groups. A difference favored the classes with gamification. More than 70 % of students agreed that gamified activities were either extremely or highly useful in helping them review and/or understand fundamental concepts. In conclusion, using built-in LMS tools to design gamified learning activities may enhance students’ learning outcome/effectiveness, provide more diversified learning methods and motivation, and offer easy modifications for different learning needs.

A Mixed Method Investigation of Social Science Graduate Students’ Statistics Anxiety Conditions Before and After the Introductory Statistics Course

Research frequently uses quantitative approach to explore undergraduates’ statistics anxiety conditions. However, few studies of adults’ statistics anxiety use qualitative method or focus solely on graduate students. Moreover, even less studies focus on comparing adults’ anxiety levels before and after the introductory statistics course. This line of study is important to pursue since the introductory statistics course should play the very important roles of both preparing students’ the foundation knowledge of higher level statistics course, and inspiring students’ interests for higher level course. In addition, graduate students tend to have different backgrounds, learning motivations, and learning habits compared to their undergraduate counterparts. Overall, limited mixed research method is available on social sciences graduate students’ (1) statistics anxiety before and after the introductory statistics course and (2) actions taken to decrease the anxiety. This study seeks to fill this gap by incorporating a mixed research method to explore social sciences graduate students’ statistics learning processes. Findings suggest that the social sciences graduate students’ anxiety levels diminished after the introductory statistics course, even though they also experienced severe statistics anxiety at the very beginning. These findings became essential for institutions, higher education instructors, and social sciences statistics learners to consider.

Service-Learning Project in a First-Year Seminar: A Social Network Analysis

Understanding the effects of a service-learning component on the classroom culture, socially and academically, brings a novel perspective to designing, executing, and assessing these types of active-learning projects. This paper evaluates the success of a service-learning project from a perspective of social networks by investigating the question: How does a service-learning project affect friendship and academic collaborations in the classroom? We believe that the benefits of service-learning involvement extend beyond helping students' academic success. Especially in a first-year seminar course, building a support system for the incoming student in order to ease the translation to a college setting is beneficial to students and to colleges. Here we use social network analysis tools to analyze relational data where relations are described as friendships or academic collaborations among classmates. Our results show that a group-based service learning project in an introductory level Statistics course has different effects on the evolution of friendship and academic collaboration networks among classmates.

SOCRAnalyses: Implementation and Demonstration of a New Graphical Statistics Educational Toolkit

The web-based, Java-written SOCR (Statistical Online Computational Resource) tools have been utilized in many undergraduate and graduate level statistics courses for seven years now (Dinov 2006; Dinov et al. 2008b). It has been proven that these resources can successfully improve students' learning (Dinov et al. 2008b). Being first published online in 2005, SOCR Analyses is a somewhat new component and it concentrate on data modeling for both parametric and non-parametric data analyses with graphical model diagnostics. One of the main purposes of SOCR Analyses is to facilitate statistical learning for high school and undergraduate students. As we have already implemented SOCR Distributions and Experiments, SOCR Analyses and Charts fulfill the rest of a standard statistics curricula. Currently, there are four core components of SOCR Analyses. Linear models included in SOCR Analyses are simple linear regression, multiple linear regression, one-way and two-way ANOVA. Tests for sample comparisons include t-test in the parametric category. Some examples of SOCR Analyses' in the non-parametric category are Wilcoxon rank sum test, Kruskal-Wallis test, Friedman's test, Kolmogorov-Smirnoff test and Fligner-Killeen test. Hypothesis testing models include contingency table, Friedman's test and Fisher's exact test. The last component of Analyses is a utility for computing sample sizes for normal distribution. In this article, we present the design framework, computational implementation and the utilization of SOCR Analyses.

Graphing Calculator Programs for Instructional Data Diagnostics and Statistical Inference

A number of programs written for the TI-83 Plus calculator are demonstrated in this article to illustrate this graphing calculator's surprisingly advanced statistical capabilities. Examples include residual plots for analysis of variance, pairwise comparison in one-factor experimental design, statistical inference for simple linear regression and confidence intervals for contrasts used in experimental design. These and a number of other programs are available for download. Advances in graphing calculator statistical programs, such as those described in this article, allow instructors and students in introductory applied graduate level statistics courses to perform sophisticated statistical data diagnostic and inference procedures during class time in an ordinary class room.

TEACHING STATISTICS VIA DISTANCE: DUPLICATING THE CLASSROOM EXPERIENCE

This paper presents the results of developing technology mediated instructional material (TMIM) for a graduate level statistics courses presented to a mixed audience—students at the local site as well as students at distance sites. Over the past five years our pedagogical approach has included numerous software and hardware solutions to address educational demands. These experiences admit useful lists of successes and failures that will benefit other interested course designers. Most useful is highlighting combinations of software and hardware that address the technological components of duplicating the classroom experience. As course design considerations are a result of content and pedagogy, we identify motivational sources in the details of actually conducting a course with a distance education component. Simultaneously, we emphasize our experience that the local students are prime beneficiaries of TMIM strategies and we employ our methods regardless of any distance education requirements.

Cooperative Learning in Statistics

Summary The formal use of cooperative learning techniques developed originally in primary and secondary education proved effective in improving student performance and retention in a college freshman level statistics course. Lectures interspersed with group activities proved effective in increasing conceptual understanding and overall class performance.

Gender Differences in Performance on Variables Related to Achievement in Graduate-Level Educational Statistics

To assess gender differences in performance in three graduate level courses in educational statistics, responses from students to a question concerning gender, mathematics pre- and posttests, cloze pre- and posttests, and final exams in statistics were analyzed. Males performed slightly better on the mathematics pretest. When gender and mathematics and cloze pretests were used in multiple regression analyses to predict final examination performance, gender was not a significant predictor for any course. However, the interaction between gender and cloze pretest performance was significant for the Ph.D. level course on multiple regression. Mathematics pretest performance was the primary predictor for performance in the Master's level statistics course; both cloze test and mathematics test performance influenced scores on posttest measure in the Ph.D. level courses. Apparently the influence of entering mathematics ability, comprehension of statistical terminology, and gender varies by the primary emphasis of the course taken. While mathematical ability is most important in basic statistics, it is less important in higher level courses in which an adequate mathematics background is assumed by instructors. In consequence, the importance of comprehension of concepts increases from the Master's level to the advanced Ph.D. level in the educational statistics courses analyzed in this study.

Teaching a computer-based college level statistics course in a secondary school

This paper discusses experiences in utilizing an HP-2000 system as the framework for teaching computer programming and statistics. The statistical approach relies upon the binary model; this model is developed by each student using the random function generator. Although empirically heuristic, such an approach provides a useful intellectual base for developing all other statistical notions more formally. Student experiences in researching the role of computer science and/or statistics in their career choices led three students to select Computer Science as a major at California State University, Northridge.

Teaching a computer-based college level statistics course in a secondary school

This paper discusses experiences in utilizing an HP-2000 system as the framework for teaching computer programming and statistics. The statistical approach relies upon the binary model; this model is developed by each student using the random function generator. Although empirically heuristic, such an approach provides a useful intellectual base for developing all other statistical notions more formally. Student experiences in researching the role of computer science and/or statistics in their career choices led three students to select Computer Science as a major at California State University, Northridge.