Given sample data, how do you calculate the value of a parameter? While this question is impossible to answer, it is frequently encountered in statistics classes when students are introduced to the distinction between a sample and a population (or between a statistic and a parameter). It is not uncommon for teachers of statistics to also confuse…

Researchers strive to create learning environments where they can apply technology and different teaching methods together. Flipped learning has been a popular approach in recent years because it offers opportunities for both online and offline learning. The present study aims to conduct a thematic analysis of articles on the use of the flipped…

The study aimed to conduct a systematic literature review to identify the trends, impacts, and challenges of mobile microlearning (MML) research. Using five academic databases from the fields of social science, engineering, and medical science as search sources, 26 scholarly articles, published between 2015 and 2020, were retrieved. The study…

Purpose: This study analyzes the content of doctoral theses completed in chemistry education within the last two decades (1999-2019) after the restructuring of education faculties in Turkey. This study examines the doctoral dissertations completed in chemistry education in 1999-2019 concerning their year of publication, university, objective,…

Science education focuses on the methods of thinking about and using process skills rather than memorizing scientific facts. 5E educational model aims to learn by discovering scientific knowledge and engaging students in learning environments. The aim of this study was to examine the articles in the field of education related to the 5E educational…

Sampling distributions are fundamental to an understanding of statistical inference, yet research shows that students in introductory statistics courses tend to have multiple misconceptions of this important concept. A common instructional method used to address these misconceptions is computer simulation, often preceded by hands-on simulation…

This paper demonstrated how to apply Machine Learning (ML) techniques to analyze student interaction data collected in an online mathematics game. Using a data-driven approach, we examined 1) how different ML algorithms influenced the precision of middle-school students' (N = 359) performance (i.e. posttest math knowledge scores) prediction and 2)…

There are challenges in teaching research methodology as highlighted by many researchers. Among the challenges are strategies for putting material in context. For achieving this purpose, students' engagement in the learning process needs to be re-looked. This paper shares on a practice engaging students in a research methodology class. The…

Statistical inference involves drawing scientifically-based conclusions describing natural processes or observable phenomena from datasets with intrinsic random variation. We designed, implemented, and validated a new portable randomization-based statistical inference infrastructure (http://socr.umich.edu/HTML5/Resampling_Webapp) that blends…

This paper demonstrated how to apply Machine Learning (ML) techniques to analyze student interaction data collected in an online mathematics game. Using a data-driven approach, we examined: (1) how different ML algorithms influenced the precision of middle-school students' (N = 359) performance (i.e. posttest math knowledge scores) prediction; and…

The rapid development in the world of technology and communication has contributed directly to the teaching and learning process in schools. Therefore, a paradigm shift towards learning methods in the education system needs to be implemented to meet the educational aims of the 21st century. This is due to the current methods of delivery in…

This paper demonstrates how to apply Machine Learning (ML) techniques to analyze student interaction data collected in an online mathematics game. We examined: (1) how different ML algorithms influenced the precision of middle-school students' (N = 359) performance prediction; and (2) what types of in-game features were associated with student…

This paper presents an explorative holistic analysis of digitally-constructed gamification processes in mathematics education. The main aim of this study is to identify the key issues, intentions and trends by examining peer-reviewed publications using a combination of social network analysis (SNA), computerized lexical analysis and content…

Special educators are urged to use research findings to inform their instruction in order to improve student outcomes. However, it can be difficult to tell whether and how research findings apply to one's own students. In this article, we discuss how special educators can consider the samples and the sampling methods in studies to examine the…

While aggregate reasoning is a core aspect of statistical reasoning, its development is a key challenge in statistics education. In this study we examine how students' aggregate reasoning with samples and sampling (ARWSS) can emerge in the context of statistical modeling activities of real phenomena. We present a case study on the emergent ARWSS…