Knowledge tracing (KT) models have been a commonly used tool for tracking students' knowledge status. Recent advances in deep knowledge tracing (DKT) have demonstrated increased performance for knowledge tracing tasks in many datasets. However, interpreting students' states on single knowledge components (KCs) from DKT models could be challenging…

In recent years, programming education has gained recognition at various educational levels due to its increasing importance. As the need for problem-solving skills becomes more vital, researchers have emphasized the significance of developing algorithmic thinking (AT) skills to help students in program development and error debugging. Despite the…

The aim of this paper is to provide tools to teachers for monitoring student work and understanding practices in order to help student and possibly adapt exercises in the future. In the context of an online programming learning platform, we propose to study the attempts (i.e., submitted programs) of the students for each exercise by using…

The estimation of RxC ecological inference contingency tables from aggregate data is one of the most salient and challenging problems in the field of quantitative social sciences, with major solutions proposed from both the ecological regression and the mathematical programming frameworks. In recent decades, there has been a drive to find…

Explain-in-Plain-English (EiPE) questions are used by some researchers and educators to assess code reading skills. EiPE questions require students to briefly explain (in plain English) the purpose of a given piece of code, without restating what the code does line-by-line. The premise is that novices who can explain the purpose of a piece of code…

Contribution: This research illuminates information entropy's efficacy as a pivotal educational tool in programming, enabling the precise quantification of algorithmic complexity and student abstraction levels for solving problems. This approach can provide students quantitative, comparative insights into the differences between optimal and…

Knowledge Tracing (KT) models predicting student performance in intelligent tutoring systems have been successfully deployed in several educational domains. However, their usage in open-ended programming problems poses multiple challenges due to the complexity of the programming code and a complex interplay between syntax and logic requirements…

This study investigated the effect of video lecture types on the performance of students in computational problem-solving practices. A total of 19 university students participated in the computational problem-solving practices that mostly required declarative knowledge, and 22 university students participated in the computational problem-solving…

In this paper, we describe an educational activity involving the use of a digital artifact, implemented in a visual programming environment, for mediating the learning of axial symmetry in primary school through algorithmics and computer programming. The educational activity was designed with the aim of bringing out increasingly…

This study aims to examine the views of fourth-grade primary school students on coding education given through the Scratch program by determining the students' skills in using the program and algorithmic thinking skills. The study was conducted as a one-group study with an embedded mixed design. The study group consisted of 32 students attending…

This study examined the developmental process of children's computational thinking using block-based programming tools, specifically algorithmic thinking and debugging skills. With this aim, a group of children (N = 191) from two primary schools were studied for two years beginning from the fourth grade, as they engaged in our block-based…

When the new programming language Pascal was developed in the 1970's, Walter Gander did not like it because because many features which he appreciated in prior programming languages were missing in Pascal. For example the block structure was gone, there were no dynamical arrays, no functions or procedures were allowed as parameters of a procedure,…

Background and Context: We replicated and expanded on previous work about how well students learn dynamic programming, a difficult topic for students in algorithms class. Their study interviewed a number of students at one university in a single term. We recruited a larger sample size of students, over several terms, in both large public and…

Computational thinking (CT) is becoming increasingly important as a learning content. Subject-integrated approaches aim to develop CT within other subjects like mathematics. The question is how exactly CT can be integrated and learned in mathematics classrooms. In a case study involving 12 sixth-grade learners, CT activities were explored that…

The study investigates the potential of anxiety clusters in predicting programming performance in two distinct coding environments. Participants comprised 83 second-year programming students who were randomly assigned to either a block-based or a text-based group. Anxiety-induced behaviors were assessed using physiological measures (Apple Watch…