Quantitative literacy is necessary to keep pace with the exponentially increasing magnitude of biological data and the complexity of statistical tools. However, statistical programming can cause anxiety in new learners and educators alike. In order to produce graduates that are well-prepared for quantitative research, overcoming the initial…

Dimensionality reduction techniques are essential in analyzing large 'omics' datasets in biochemistry and molecular biology. Principal component analysis, t-distributed stochastic neighbor embedding, and uniform manifold approximation and projection are commonly used for data visualization. However, these methods can be challenging for students…

Concurrency is a complex to learn topic that is becoming more and more relevant, such that many undergraduate Computer Science curricula are introducing it in introductory programming courses. This paper investigates the combined use of Sonic Pi and Team-Based Learning to mitigate the difficulties in early exposure to concurrency. Sonic Pi, a…

Rough set theory (RST) was proposed by Zdzistaw Pawlak (Pawlak,1982) as a methodology for data analysis using the notion of discernibility of objects based on their attribute values. The main advantage of using RST approach is that it does not need additional assumptions--like data distribution in statistical analysis. Besides, it provides…

Applying Herzberg's motivation-hygiene theory, we studied the determinants of student satisfaction in using R in a Decision Support Systems course that previously used Excel to teach Data Mining and Business Analytics (DMBA). The course is a degree requirement, and prior programming experience is not a prerequisite. We hypothesized that motivators…

This study tried to design a WhatsApp bot to be implemented in English language vocabulary learning context in Oman. 150 Omani English as a Foreign Language (EFL) students from three different proficiency levels were selected based on random sampling. To measure the effectiveness of the treatment, pretests, posttests, and delayed posttests were…

Simulation modeling is an effective tool for solving problems that cannot be explained analytically or when data cannot be collected. This is done by simulating the observed behavior of a problem under study using a computer program. In math education, this can develop knowledge and fundamental competencies of simulation modeling at a higher level…

R and Python are commonly used software languages for data analytics. Using these languages as the course software for the introductory course gives students practical skills for applying statistical concepts to data analysis. However, the reliance upon the command line is perceived by the typical nontechnical introductory student as sufficiently…

Data science surrounds us in contexts as diverse as climate change, air pollution, route-finding, genomics, market manipulation, and movie recommendations. To open the "data-science-black-box" for lower secondary school students, we developed a data science teaching unit focusing on the analysis of environmental data, which we embedded…

The choice of the first programming language (FPL) has been a controversial issue for several decades. Nearly everyone agrees that the FPL is important and affects students' subsequent education on programming. The study presented in this article investigates the suitability of various C-like and Pascal-like programming languages as a FPL.…

The advance of pervasive technologies such as mobile technologies and various mobile devices has brought opportunities for educators to design and perform interactive learning activities and has also enabled educationalists to access the virtual learning environment anytime and anywhere without restrictions of time or place and without too much…

The continuous technological development nowadays acts ancillary and supportively in student-centered learning, in both formal and informal education settings. Effective learning environments, such as the AppInventor software, could spark the students' interest and allow them to develop programming skills and strengthen their algorithmic…

Individual based models (IBMs) are up-to-date tools both in research and educational areas. Here we introduce an IBM built on NetLogo platform that simulates a top-down trophic cascade controlled by the pressure exerted by two model predators (web-building spiders and ground runner spiders) on a model pest (the olive fruit fly) within a…

This paper analyzed Scratch projects developed by undergraduate students. The sample consisted of 22 child development students (18 women and four men) in the 2018-2019 academic year. The study adopted an action research design within the scope of a course titled "Teaching Science and Mathematics in Preschool Education." The research was…

In psychology departments in South Africa, the Statistical Package for the Social Sciences (SPSS) is routinely used for quantitative analysis. While SPSS has a user-friendly interface, it does not permit application of some of the more sophisticated analytic approaches and therefore has limited functionality. The programming language R can perform…