The modeling of rates of biochemical reactions--fluxes--in metabolic networks is widely used for both basic biological research and biotechnological applications. A number of different modeling methods have been developed to estimate and predict fluxes, including kinetic and constraint-based (Metabolic Flux Analysis and flux balance analysis)…

As vast amounts of data have become available in business in recent years, the demand for data scientists has been rising. The author of this article provides a tutorial on how one entry-level machine learning competition from Kaggle, an online community for data scientists, can be integrated into an undergraduate econometrics course as an…

Programming ability is the core ability of this era and can be obtained and improved through practice. In this paper, an Automated Programming Assessment system based on Mastery learning and Peer competition (APAMP) was proposed and developed. APAMP allows students to practice repeatedly by providing immediate feedback after their programs are…

The thriving developer community has a significant impact on the widespread use of R software. To better understand this community, we conducted a study analyzing all R packages available on CRAN. We identified the most popular topics of R packages by text mining the package descriptions. Additionally, using network centrality measures, we…

This study highlights the importance of an educational design that includes robotics and programming through a visual programming language as a means to enable students to improve substantially their understanding of the elements of logic and mathematics. Gaining an understanding of computational concepts as well as a high degree of student…

As a programmer when solving a problem, a number of conscious and unconscious cognitive operations are being performed. Problem-solving is a gradual and cyclic activity; as the mind is adjusting the problem to its schemas formed by its previous experiences, the programmer gets closer and closer to understanding and defining the problem. The…

Learning computer programming for students of the age of 14-18 is difficult and requires endurance and engagement. Being familiar with the syntax of a computer language and writing programs in it are challenges for youngsters, not to mention that understanding algorithms is also a big challenge. To help students in the learning process, teachers…

In this paper we present a model for designing professional courses in a blended learning context as a tool to help the interaction between students, teachers and learning resources. This model aims to promote new concepts, new approaches and new strategies that have been changing the paradigm of teaching and learning. To develop a course based on…

The study investigated the effect of Game Development-Based Learning (GDBL) on the ability of IT undergraduates in Jordanian universities to define the concepts of computer programming and Object-Oriented Programming (OOP) and their ability to program in C++. An instruction was designed for an eight-week-long online course to allow the…

In this research project we describe the legacy software landscape, its current state, and challenges associated with aging information systems and access to its data. We briefly describe the popularity of dynamic languages and how a specific dynamic programming language, Ruby on Rails (RoR or Rails), is used to create a system to extract data…

This study presents a 13-year (2006-2018) systematic literature review related to the way that computational thinking (CT) has grown in elementary level education students (K-6) with the intention to: (a) present an overview of the educational context/setting where CT has been implemented, (b) identify the learning context that CT is used in…

Computing technology is reshaping the way in which professionals in the architecture, engineering, and construction industries conduct their business. The execution of construction tasks is changing from traditional 2D to 3D building information modeling (BIM)-based concepts. The use of BIM is expanded and enriched by the introduction of advanced…

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…

The COVID-19 pandemic, an unprecedented global health crisis, has not only significantly impacted public health but has also caused substantial disruptions to conventional education systems. In response to these challenges, our institution has undertaken innovative measures within the realm of education. A pivotal aspect of our response involves…

In this paper is proposed a straightforward model selection approach that indicates the most suitable count regression model based on relevant data characteristics. The proposed selection approach includes four of the most popular count regression models (i.e. Poisson, negative binomial, and respective zero-inflated frameworks). Moreover, it…