INTERACTION BETWEEN ACADEMIA AND INDUSTRY TO BUILD STATISTICAL CAPACITY AMONG INDUSTRIAL-ENGINEERING STUDENTS

2020 ◽  
Vol 19 (1) ◽  
pp. 167-180
Author(s):  
JOSÉ LUIS ÁNGEL RODRÍGUEZ SILVA ◽  
MARIO SÁNCHEZ AGUILAR
Keyword(s):  
Applied Field ◽  
Engineering Students ◽  
Statistics Education ◽  
Teaching Experiment ◽  
Industrial Engineering ◽  
University Education ◽  
Theoretical Studies ◽  
Industrial Environment ◽  
Research Journal ◽  
Statistics Course

One of the aims of this work is to highlight the need for connecting the practice and theoretical studies of industrial engineers. One reason for this need is the fact that students tend to graduate without proper preparation for practice, spreading thus a bad reputation of statistics and its potential, and even affecting students’ dispositions and motivation towards the study and applications of statistics. This paper presents the results of a study conducted at two higher-education institutions in Mexico. The industrial engineering students who participated were introduced to a multivariate statistics course, one in a traditional way and the other through a problem-solving approach embedded within an industrial environment. The didactic intervention in both groups and the problems used to evaluate them are described. The results show that the experimental students had a significant increase in their qualifications and alower variance in their performance. From our study we can suggest that a university education in close connection with applications in an industrial environment significantly improves the students’ education. This teaching experiment provides students with opportunities to experience the genuine character of statistics as an applied field, giving meaning to the statistical techniques learnt in the classroom. It is one way to make the education in statistics more apt to the demand from outside and by the same time it enables the students to really understand statistics. First published February 2020 at Statistics Education Research Journal Archives

INTRODUCTORY STATISTICS COURSE TERTIARY STUDENTS’ UNDERSTANDING OF P-VALUES

2014 ◽  
Vol 13 (1) ◽  
pp. 53-65 ◽  
Author(s):  
ROBYN REABURN
Keyword(s):  
Null Hypothesis ◽  
Probabilistic Reasoning ◽  
Statistics Education ◽  
Introductory Statistics ◽  
P Values ◽  
Testing Procedures ◽  
Research Journal ◽  
Null Hypothesis Testing ◽  
Statistics Course ◽  
Teaching Programs

This study aimed to gain knowledge of students’ beliefs and difficulties in understanding p-values, and to use this knowledge to develop improved teaching programs. This study took place over four consecutive teaching semesters of a one-semester tertiary statistics unit. The study was cyclical, in that the results of each semester were used to inform the instructional design for the following semester. Over the semesters, the following instructional techniques were introduced: computer simulation, the introduction of hypothetical probabilistic reasoning using a familiar context, and the use of alternative representations. The students were also encouraged to write about their work. As the interventions progressed, a higher proportion of students successfully defined and used p-values in Null Hypothesis Testing procedures. First published May 2014 at Statistics Education Research Journal Archives

AN EXPLORATION OF STUDENT ATTITUDES AND SATISFACTION IN A GAISE-INFLUENCED INTRODUCTORY STATISTICS COURSE

2017 ◽  
Vol 16 (2) ◽  
pp. 487-510
Author(s):  
WARREN PAUL
Keyword(s):  
Student Attitudes ◽  
Structural Equation ◽  
Statistics Education ◽  
Student Feedback ◽  
Introductory Statistics ◽  
Group Discussions ◽  
Research Journal ◽  
Statistics Course ◽  
Attitudes Toward Statistics ◽  
Students Attitudes

We used the Survey of Attitudes Toward Statistics to (1) evaluate using pre-semester data the Students’ Attitudes Toward Statistics Model (SATS-M), and (2) test the effect on attitudes of an introductory statistics course redesigned according to the Guidelines for Assessment and Instruction in Statistics Education (GAISE) by examining the change in attitudes over the semester and, using supplementary data from an annual Student Feedback Survey, testing for a change in overall satisfaction following implementation of the redesigned course. We took an exploratory rather than confirmatory approach in both parts of this study using Bayesian networks and structural equation modelling. These results were triangulated with analysis of focus group discussions and the annual Student Feedback Survey. First published November 2017 at Statistics Education Research Journal Archives

scholarly journals ELEMENTARY PRESERVICE TEACHERS' REASONING ABOUT MODELING A “FAMILY FACTORY” WITH TINKERPLOTS – A PILOT STUDY

2017 ◽  
Vol 16 (2) ◽  
pp. 244-286
Author(s):  
ROLF BIEHLER ◽  
DANIEL FRISCHEMEIER ◽  
SUSANNE PODWORNY
Keyword(s):  
Preservice Teachers ◽  
Education Research ◽  
Pilot Study ◽  
Statistics Education ◽  
University Education ◽  
Statistics Education Research ◽  
Research Journal ◽  
Elementary Preservice Teachers ◽  
Set Up

Connecting data and chance is fundamental in statistics curricula. The use of software like TinkerPlots can bridge both worlds because the TinkerPlots Sampler supports learners in expressive modeling. We conducted a study with elementary preservice teachers with a basic university education in statistics. They were asked to set up and evaluate their own models with TinkerPlots by using a real and open dataset they were given. In this article we present students’ processes of setting up and evaluating their models and focus on their reasoning during this process. First published November 2017 at Statistics Education Research Journal Archives

scholarly journals CONCEPTUAL ISSUES IN QUANTIFYING UNUSUALNESS AND CONCEIVING STOCHASTIC EXPERIMENTS: INSIGHTS FROM STUDENTS’ EXPERIENCES IN DESIGNING SAMPLING SIMULATIONS

2016 ◽  
Vol 15 (2) ◽  
pp. 81-105
Author(s):  
LUIS SALDANHA
Keyword(s):  
High School Students ◽  
Statistics Education ◽  
Teaching Experiment ◽  
Simulation Design ◽  
School Students ◽  
Research Journal ◽  
Computer Microworld ◽  
Long Run ◽  
Design Activities ◽  
Repeated Sampling

This article reports on a classroom teaching experiment that engaged a group of high school students in designing sampling simulations within a computer microworld. The simulation-design activities aimed to foster students’ abilities to conceive of contextual situations as stochastic experiments, and to engage them with the logic of hypothesis testing. This scheme of ideas involves imagining a population and a sample drawn from it, and an image of repeated sampling as a basis for quantifying a sampling outcome’s unusualness in terms of long-run relative frequency under an assumption about the population’s composition. The study highlights challenges that students experienced, and sheds light on aspects of conceiving stochastic experiments and conceiving a sampling outcome’s unusualness as a probabilistic quantity. First published November 2016 at Statistics Education Research Journal Archives

scholarly journals EVALUATING TWO MODELS OF COLLABORATIVE TESTS IN AN ONLINE INTRODUCTORY STATISTICS COURSE

2015 ◽  
Vol 14 (1) ◽  
pp. 36-59
Author(s):  
AUÐBJÖRG BJÖRNSDÓTTIR ◽  
JOAN GARFIELD ◽  
MICHELLE EVERSON
Keyword(s):  
Quantitative Methods ◽  
Statistics Education ◽  
Introductory Statistics ◽  
Qualitative And Quantitative Methods ◽  
Noticeable Increase ◽  
Research Journal ◽  
Significant Difference ◽  
Statistics Course ◽  
Students Attitudes ◽  
Collaborative Tests

This study explored the use of two different types of collaborative tests in an online introductory statistics course. A study was designed and carried out to investigate three research questions: (1) What is the difference in students’ learning between using consensus and non-consensus collaborative tests in the online environment?, (2) What is the effect of using consensus and non-consensus collaborative tests on students’ attitudes towards statistics?, and (3) How does using a required consensus vs. a non-consensus approach on collaborative tests affect group discussions? Qualitative and quantitative methods were used for data analysis. While no significant difference was found between groups using the two collaborative testing formats, there was a noticeable increase in students’ attitudes across both formats towards learning statistics. This supports prior research on the benefits of using collaborative tests in face-to-face courses. First published May 2015 at Statistics Education Research Journal Archives

scholarly journals COGNITIVE TRANSFER OUTCOMES FOR A SIMULATION-BASED INTRODUCTORY STATISTICS CURRICULUM

2017 ◽  
Vol 16 (2) ◽  
pp. 419-440
Author(s):  
MATTHEW D. BECKMAN ◽  
ROBERT C. DELMAS ◽  
JOAN GARFIELD
Keyword(s):  
Learning Outcomes ◽  
Statistics Education ◽  
Assessment Instrument ◽  
Introductory Statistics ◽  
Far Transfer ◽  
Research Journal ◽  
Cognitive Transfer ◽  
Simulation Based ◽  
Statistics Course ◽  
New Applications

Cognitive transfer is the ability to apply learned skills and knowledge to new applications and contexts. This investigation evaluates cognitive transfer outcomes for a tertiary-level introductory statistics course using the CATALST curriculum, which exclusively used simulation-based methods to develop foundations of statistical inference. A common assessment instrument administered at the end of each course measured learning outcomes for students. CATALST students showed evidence of both near and far transfer outcomes while scoring as high, or higher than, on the assessed learning objectives when compared with peers enrolled in similar courses that emphasized parametric inferential methods (e.g., the t-test). First published November 2017 at Statistics Education Research Journal Archives

scholarly journals RETENTION OF STATISTICAL CONCEPTS IN A PRELIMINARY RANDOMIZATION-BASED INTRODUCTORY STATISTICS CURRICULUM

2012 ◽  
Vol 11 (1) ◽  
pp. 21-40 ◽  
Author(s):  
NATHAN TINTLE ◽  
KYLIE TOPLIFF ◽  
JILL VANDERSTOEP ◽  
VICKI-LYNN HOLMES ◽  
TODD SWANSON
Keyword(s):  
Education Research ◽  
Student Learning ◽  
Conceptual Understanding ◽  
Statistics Education ◽  
Introductory Statistics ◽  
Research Journal ◽  
Statistics Course ◽  
Additional Support ◽  
Improve Student Learning ◽  
Statistics Curriculum

Previous research suggests that a randomization-based introductory statistics course may improve student learning compared to the consensus curriculum. However, it is unclear whether these gains are retained by students post-course. We compared the conceptual understanding of a cohort of students who took a randomization-based curriculum (n = 76) to a cohort of students who used the consensus curriculum (n = 79). Overall, students taking the randomization-based curriculum showed higher conceptual retention in areas emphasized in the curriculum, with no significant decrease in conceptual retention in other areas. This study provides additional support for the use of randomization-methods in teaching introductory statistics courses. First published May 2012 at Statistics Education Research Journal: Archives

INVESTIGATING STUDENTS’ REASONING ABOUT SAMPLING DISTRIBUTIONS THROUGH A RESOURCE PERSPECTIVE

2019 ◽  
Vol 18 (1) ◽  
pp. 26-45
Author(s):  
KELLY FINDLEY ◽  
ALEXANDER LYFORD
Keyword(s):  
Education Research ◽  
Grounded Theory ◽  
Undergraduate Students ◽  
Statistics Education ◽  
Introductory Statistics ◽  
Research Journal ◽  
Sampling Distributions ◽  
Statistics Course ◽  
Resource Perspective ◽  
Problem Setting

Researchers have documented many misconceptions students hold about sampling variability. This study takes a different approach—instead of identifying shortcomings, we consider the productive reasoning pieces students construct as they reason about sampling distributions. We interviewed eight undergraduate students newly enrolled in an introductory statistics course. Taking a grounded theory style approach, we identified 10 resources that students used when reasoning about the sampling distribution for the average within two contexts: penny years and dice rolls. Students had varied success in their responses as they made choices about how to represent their resources in their constructions. Successful constructions exemplified careful blending of resources, while less  successful constructions reflected disjoint perceptions and tensions between seemingly conflicting resources. Our findings stress the importance of framing students as capable reasoning agents by describing student resources that were used while solving tasks related to sampling distributions. We also discuss the influence of context and problem setting in students’ reasoning and resource elicitation. First published May 2019 at Statistics Education Research Journal Archives

TAKING PROJECT-BASED STATISTICS ABROAD: LEARNING EXPERIENCES AND OUTCOMES OF A PROJECT-BASED STATISTICS COURSE IN WEST AFRICA

2021 ◽  
Vol 19 (3) ◽  
Author(s):  
REBECCA AWUAH ◽  
KRISTEL M. GALLAGHER ◽  
LISA C. DIERKER
Keyword(s):  
West Africa ◽  
Undergraduate Students ◽  
Statistics Education ◽  
Positive Impact ◽  
Learning Experiences ◽  
Introductory Statistics ◽  
Research Journal ◽  
Statistics Course ◽  
The Impact

To evaluate the impact of a multidisciplinary, project-based course in introductory statistics, this exploratory study examined learning experiences, feelings of confidence, and interest in future experiences with data for undergraduate students in Ghana, West Africa. Students completed a one-semester, introductory statistics course utilizing the Passion-driven Statistics curriculum. Results showed more than half of the students put more effort into the course and found the material more challenging compared to other courses, while nearly three-quarters reported interest in one or more follow-up courses. Importantly, students also reported increased confidence in a variety of applied statistical skills. These findings demonstrate the positive impact of a multidisciplinary, project-based curriculum on undergraduate students in Ghana, West Africa and demonstrate the potential for its global portability. First published December 2020 at Statistics Education Research Journal: Archives

scholarly journals DEVELOPING A STATISTICAL LITERACY ASSESSMENT FOR THE MODERN INTRODUCTORY STATISTICS COURSE

2018 ◽  
Vol 17 (2) ◽  
pp. 161-178
Author(s):  
LAURA ZIEGLER ◽  
JOAN GARFIELD
Keyword(s):  
Statistics Education ◽  
Reliability And Validity ◽  
Introductory Statistics ◽  
Literacy Assessment ◽  
Statistical Literacy ◽  
Research Journal ◽  
Simulation Based ◽  
Statistics Course ◽  
Students First ◽  
Definition Of

The purpose of this study was to develop the Basic Literacy In Statistics (BLIS) assessment for students in an introductory statistics course, at the postsecondary level, that includes, to some extent, simulation-based methods. The definition of statistical literacy used in the development of the assessment was the ability to read, understand, and communicate statistical information. Multiple instruments were available to assess students in introductory statistics courses; however, there were no assessments available that focused on statistical literacy. Evidence of reliability and validity were collected during the development of the assessment. Evidence of reliability and validity was high; however, more items with high difficulty levels could increase the precision in estimating ability estimates for higher achieving students. First published November 2018 at Statistics Education Research Journal Archives

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