Relying on shared tasks and stimuli to conduct research can enhance the replicability of findings and allow a community of researchers to collect large data sets across multiple experiments. This approach is particularly relevant for experiments in spatial navigation, which often require the development of unfamiliar large-scale virtual…

We investigate three 8th-grade students' mathematical meanings developed in the context of using linked representations to generate animations of figural models tuned in musical rhythm in "MaLT2," a programmable Turtle Geometry in 3D resource affording dynamic manipulation of variable values. We adopted a modified version of the UDGS…

NoSQL databases have been used in organizations for decades. Few database textbooks on the market, however, have suitable materials about NoSQL beyond general introductions for typical business students. In fact, users of the typical NoSQL systems on the software market need to have certain computer programming skills. This teaching tip introduces…

This research aims to examine the effect of coding education on the analytical thinking skills of gifted students. The participants are 18 students, 11 to 12 years old. An embedded experimental mixed design was used in the research. The data collection was carried out with the Analytical Thinking Skill Scale to determine the difference in the…

Mathematics achievement is positively associated with coding in the classroom. By making mathematical relationships visible to students as they code, teachers leverage rich connections between block-based computer programming and mathematical sense making. In this article, the authors describe strategies for adapting a Code.org lesson integrating…

The fields of augmented reality (AR) and virtual reality (VR) have seen massive growth in recent years. Numerous degree programs have started to redesign their curricula to meet the high market demand for people qualified to fill related job positions. In this paper, the authors perform a content analysis of online job postings hosted on…

The problem-based learning model via cloud technology (PBL model via cloud technology) is a research tool fabricated with the concepts of problem-based learning management, in which students are stimulated and enabled to foresee the problems that will arise. Also, in this learning style, teachers will define the problem situations and encourage…

Computational thinking (CT) is an essential skill required for every individual in the digital era to become creative problem solvers. The purpose of this research is to investigate the relationships between computational thinking skills, the Big Five personality factors, and learning motivation using structural equation modeling (SEM). The…

Programming languages have been used and developed in the field of education. Python programming was employed in this study. The goal of this study is to see whether there is an effect of using Pydroid in mathematics learning on students' problem-solving abilities and to see if this software satisfies or does not match the criteria for mathematics…

The GEN10S Portugal project offered 15-hour face-to-face Scratch programming courses to groups of students and two or more teachers from each class, from schools that were project members. Two Scratch teachers per class, hired by the project, participated in 12 of these 15 hours, supporting the activities. When the schools' face-to-face activities…

Laboratory automation and data science are valuable new skills for all chemists, but most pedagogical activities involving automation to date have focused on upper-level coursework. Herein, we describe a combined computational and experimental lab suitable for a first-year undergraduate general chemistry course, in which these topics are…

An understanding of statistical concepts is necessary for a chemist with a complete education. Here, statistical tests were taught using the R Commander and the Factoshiny packages. These packages run on R software and have a graphical user interface (GUI), which allows students to do statistical tests quickly and easily. These packages were…

We report an educational tool for the upper level undergraduate quantum chemistry or quantum physics course that uses a symbolic approach via the PySyComp Python library. The tool covers both time-independent and time-dependent quantum chemistry, with the latter rarely considered in the foundations course due to topic complexity. We use quantized…

Traditionally, statistical computing courses have taught the syntax of a particular programming language or specific statistical computation methods. Since Nolan and Temple Lang's seminal paper, we have seen a greater emphasis on data wrangling, reproducible research, and visualization. This shift better prepares students for careers working with…

As students learn how to program, both their programming code and their understanding of it evolves over time. In this work, we present a general data-driven approach, named "Temporal-ASTNN" for modeling student learning progression in open-ended programming domains. Temporal-ASTNN combines a novel neural network model based on abstract…