Objectives: Java is a popular programming language for use in computing education, but it is difficult to get a wide picture of the issues that it presents for novices; most studies look only at the types or frequency of errors. In this observational study, we aim to learn how novices use different features of the Java language. Participants:…

Contribution: In this article, the authors present findings and insights on the efficacy of using an educational block-based programming (BBP) environment--Blocks4DS, to teach the binary search tree (BST). Background: For a decade, BBP environments have been a hot topic in the computer science education (CSEd) community to promote interactive…

The automatic code generation is the process of generating source code snippets from a program, i.e., code for generating code. Its importance lies in facilitating software development, particularly important is helping in the implementation of software designs such as engineering diagrams, in such a case, automatic code generation copes with the…

This short paper presents an educational approach to teaching three popular methods for encoding DNA sequences: one-hot encoding, binary encoding, and integer encoding. Aimed at bioinformatics and computational biology students, our learning intervention focuses on developing practical skills in implementing these essential techniques for…

Biochemistry is a data-heavy discipline, yet teaching students to work with large datasets is absent from many undergraduate Biochemistry programs. Ensuring that future generations of students are confident in tackling problems using big data first requires that educators become comfortable teaching big data skills. The activity described herein…

Learning analytics (LA) is a significant field of study to examine and identify difficulties the novice programmers face while learning how to program. Despite producing notable research by the community in the specified area, rare work is observed to synthesize these research efforts and discover the dimensions that guide the future research of…

Understanding data structures is fundamental for mastering algorithms. In order to solve problems and tasks, students must be able to choose the most appropriate data structure in which the data is stored and that helps in the process of the solution. Of course, there is no single correct solution, but in many cases, it is an important step to…

In using software to write a scientific, technical, or other scholarly document, authors have essentially two options. They can either write it in a 'what you see is what you get' (WYSIWYG) editor such as a word processor, or write it in a text editor using a markup language such as HTML, LATEX, Markdown, or AsciiDoc. This paper gives an overview…

This article is presented in two parts: in the first part we discuss the use of R and R-related tools when implementing a data science curriculum in the classroom and direct readers to helpful R resources in education, and in the second part, we demonstrate the use of R in exploring COVID-19 data. In particular, we explore ethnic/racial…

The rapid development of big data technology has attracted a variety of sectors, including tertiary education. The purpose of this paper is to construct a precision teaching mode based on big data technology in order to improve teaching quality and further promote education and teaching reform. The proposed mode, based on the theory of precision…

Data and its applications are increasingly ubiquitous in the rapidly digitizing world and consequently, students across different disciplines face increasing demand to develop skills to answer both academia's and businesses' increasing need to collect, manage, evaluate, apply and extract knowledge from data and critically reflect upon the derived…

Feedback on how students progress through completing subgoals can improve students' learning and motivation in programming. Detecting subgoal completion is a challenging task, and most learning environments do so either with "expert-authored" models or with "data-driven" models. Both models have advantages that are…

For undergraduate students to be prepared for graduate school and industry, it is imperative that they understand how to merge the theoretical insights gleaned through their undergraduate education with the raw data sets acquired through materials analysis. Thus, the ability to implement data analysis is a vital skill that students should develop.…

The explosion in availability and variety of data requires learning experiences that reveal more of the data world faster and develop practical skills with digital technologies. Key high-level goals of the International Data Science in Schools Project (IDSSP) include having students continually immersed in the cycle of learning from data, and data…

This edited volume presents the latest research focussing on current challenges on the deployment of smart technologies and pedagogies for supporting teaching and learning in the post-covid19 era. This is at the core of studying the evolution of the learning process, the role of technology-supported pedagogical approaches, and the progress of…