As traditionally conceived, publication bias arises from selection operating on a collection of individually unbiased estimates. A canonical form of such selection across studies (SAS) is the preferential publication of affirmative studies (i.e., those with significant, positive estimates) versus nonaffirmative studies (i.e., those with…

In learning to program and understanding how a programming language controls a computer, learners develop both insights and misconceptions whilst their mental models are gradually refined. It is important that the learner is able to distinguish the different elements and roles of a computer (compiler, interpreter, memory, etc.), which novice…

A frequent criticism of exploratory factor analysis (EFA) is that it does not allow correlated residuals to be modelled, while they can be routinely specified in the confirmatory (CFA) model. In this article, we propose an EFA approach in which both the common factor solution and the residual matrix are unrestricted (i.e., the correlated residuals…

We evaluate the effectiveness of reading aloud a program code in learning programming from a neuroscientific perspective by measuring brain activity using a near-infrared spectroscopy device. The results show that when reading aloud and then reading silently, brain activity increases during reading aloud; a similar trend is observed when the…

Researchers often have hypotheses concerning the state of affairs in the population from which they sampled their data to compare group means. The classical frequentist approach provides one way of carrying out hypothesis testing using ANOVA to state the null hypothesis that there is no difference in the means and proceed with multiple comparisons…

The principles of programming language design for learning and teaching have been described and discussed for several decades. Most influential was the work of Niklaus Wirth, describing principles such as simplicity, modularity, orthogonality, and readability. So why is this still an area of fundamental disagreement among educators? Why can…

Constructing a consensus problem space from extensive qualitative data for an ill-structured real-life problem and expressing the result to a broader audience is challenging. To effectively communicate a complex problem space, visualization of that problem space must elucidate inter-causal relationships among the problem variables. In this…

R is becoming the standard for teaching statistics due to its flexibility, and open-source nature, replacing software programs like Minitab and SPSS. The main driver for reform within Scottish statistical undergraduate programs is the creation of the Scottish Qualification Authority's Higher Applications of Mathematics course which has statistics…

In this paper the author explores and demonstrates the vital role mathematics plays in technology by showing how algebra, and in particular Boolean algebra, has become an essential part of how computers and computer languages work. Both Boolean logic and algebra are core competencies in Computer Science at the university level which may encourage…

A Prolog program consists of a set of facts and rules rather than imperative statements, commonly used in most other programming languages. Therefore, the Prolog language is used to encode logic, from which the inference engine deduces logical conclusions. In this article, we argue that the use of the Prolog language can be useful to help students…

In Spring 2020, the need for redesigning online assessments to preserve integrity became a priority to many educators. Many of us found methods to proctor examinations using Zoom and proctoring software. Such examinations pose their own issues. To reduce the technical difficulties and cost, many Zoom proctored examination sessions were shortened;…

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…

With the introduction of new standards for electronic records and transcripts and other changes within higher education, a perfect storm is forming that challenges the 30 years of electronic data exchange (EDX) work. This article outlines the threat to the work and uses recent data to explore the landscape around the past, present, and future. In…

Bayesian Knowledge Tracing, a model used for cognitive mastery estimation, has been a hallmark of adaptive learning research and an integral component of deployed intelligent tutoring systems (ITS). In this paper, we provide a brief history of knowledge tracing model research and introduce pyBKT, an accessible and computationally efficient library…

Adaptive learning is an area of educational technology that consists in delivering personalized learning experiences to address the unique needs of each learner. An important subfield of adaptive learning is learning path personalization: it aims at designing systems that recommend sequences of educational activities to maximize students' learning…