Developing Statistical Reasoning Ability of Industrial Engineering Students Through Experiential Learning

Fardillah, Frena; Sutaagra, Ossa; Supriani, Yani; Farlina, Ehda; Priatna, Nanang

doi:10.1088/1742-6596/1179/1/012068

Cited by 4 publications

(5 citation statements)

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“…On the other hand (Yanti et al 2021) reported that the 4MAT Learning Style System is an innovative method of statistical reasoning learning implementation. Blended Learning is one of the solutions in implementing statistical reasoning learning during the pandemic, where the process was conducted face-to-face and online (Rohana and Ningsih 2020), and (Fardillah et al 2019) reported that experiential learning can improve students' statistical reasoning ability.…”

Section: Methodsmentioning

confidence: 99%

What Methods are used for Statistical Reasoning Learning?: A Systematic Literature Review

Gunadi

Juandi²

2022

JPMIPA

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A student's statistical reasoning ability is needed as a good and precise foundation, so that a teacher is demanded to use the proper methods to improve students' statistical reasoning. This research aims to know the appropriate methods used to improve students' statistical reasoning ability and the methods' steps. Systematic Literature Review (SLR) is employed in three steps. The SLR stages are carried out in three stages, namely Planning the Review, Conducting the Review, Reporting and Disseminating. Article searching by using Harzing's Publish or Perish Application and data analysis using atlas.ti with coding Histoorical Background, Context Solution, Research Questions or Objectives, Methodology, Conclusions, and Findings. The findings of statistical reasoning learning are Statistical Reasoning Learning Environment (SRLE), Experiential Learning, Blended Learning, 4MAT learning style system, and Brain-based Learning. From those methods, Statistical Reasoning Learning Environment is used primarily in the learning process.

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Section: Methodsmentioning

confidence: 99%

What Methods are used for Statistical Reasoning Learning?: A Systematic Literature Review

Gunadi

Juandi²

2022

JPMIPA

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“…Some arguments behind this proposal are that textbook examples are useful to show the routine but fail to meet basic requirements of applied statistics (modeling), and that artificial case studies might hide the complexity of applications. Some authors propose to develop the statistical reasoning of industrial-engineering students through experiential learning (Fardillah, Sutaagra, Supriani, Farnila, & Priatna, 2019). This means that students learn from active experimentation and concrete experiences, to get engaged in a reflective observation that produces an abstract conceptualization.…”

Section: The Need For Preparing the Students For The Practicementioning

confidence: 99%

Interaction Between Academia and Industry to Build Statistical Capacity Among Industrial-Engineering Students

Silva

Aguilar

2020

SERJ

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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

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“…Although it can be applied in various scientific contexts, in general statistical reasoning is a goal that must be achieved in statistical learning. Statistical reasoning contains several basic concepts regarding probability, variability, sample selection, data distribution, and normal distribution (Fardillah et al, 2019;J Garfield, 2002;Joan Garfield & Ben-Zvi, 2005;Rosidah et al, 2018) especially in the study of statistics.…”

mentioning

confidence: 99%

Differences in the Improvement of Statistical Reasoning Ability Based on Students' Self-Regulated Learning Level in Online Learning Using LMS

Jauhari,

Herman,

Juandi

et al. 2023

JTAM

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In the literature, studies on technology-supported learning, especially using LMS, have been widely carried out during a pandemic. However, little is known about LMS, which is interesting and helps to develop students' statistical reasoning abilities for online learning by considering the students' Self-Regulated Learning (SRL) levels (High, medium and low). This study aims to examine and analyze the differences in statistical reasoning abilities of students who study using LMS in terms of SRL levels (high, medium and low). This study uses a quantitative method with the type of One-group pre-test post-test design. What took sampled randomly at the University of Pasundan Bandung, totalling 54 third-level students of Pasundan University Bandung, Indonesia. Research data related to statistical reasoning abilities were collected through a test consisting of six questions. In contrast, SRL level data were collected using a questionnaire consisting of 46 question items. Paired t-test and One-way ANOVA analysis were applied to answer the research hypothesis. The results of the study concluded that students studying with LMS with High SRL obtained a higher increase in statistical reasoning ability than students studying with LMS with Medium and low SRL categories, with the criteria for improvement in the three categories being in the high and medium improvement categories. Research findings related to learning using LMS can be used as an alternative learning model in online learning situations.

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Developing Statistical Reasoning Ability of Industrial Engineering Students Through Experiential Learning

Cited by 4 publications

References 1 publication

What Methods are used for Statistical Reasoning Learning?: A Systematic Literature Review

What Methods are used for Statistical Reasoning Learning?: A Systematic Literature Review

Interaction Between Academia and Industry to Build Statistical Capacity Among Industrial-Engineering Students

Differences in the Improvement of Statistical Reasoning Ability Based on Students' Self-Regulated Learning Level in Online Learning Using LMS

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