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…

In this paper, several research topics are presented that provide productive avenues of exploration for students in an undergraduate cryptography course. The topics are intended for a variety of skill levels and interests. In some cases, a student might be inspired to try to solve the proposed problem or write computer code. Other topics might…

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…

The use of a pedagogical approach mediated transfer with the bridging method has been successful in facilitating the transitions from block-based to text-based programming languages. Nevertheless, there is a lack of research addressing the impact of this transfer on programming misconceptions during the transition. The way programming concepts are…

Physics education researchers are interested in using the tools of machine learning and natural language processing to make quantitative claims from natural language and text data, such as open-ended responses to survey questions. The aspiration is that this form of machine coding may be more efficient and consistent than human coding, allowing…

In the digital age, it's crucial to equip children with twenty-first-century skills, including programming and other competencies such as creativity, analytical thinking, and collaboration. This study introduces an integrated STEM (Science, Technology, Engineering, and Mathematics) curriculum focused on computer science for educators. It explores…

Studies examining students' learning behavior predominantly employed rich video data as their main source of information due to the limited knowledge of computer vision and deep learning algorithms. However, one of the challenges faced during such observation is the strenuous task of coding large amounts of video data through repeated viewings. In…

Previous studies on writing and understanding programs presented evidence that programmers beyond a novice stage utilize plans or plan-like structures. Other studies on code composition showed that learners have difficulties with writing, reading, and debugging code where interacting plans are merged into a short piece of code. In this article, we…

This study investigates the potential of automated classification using prompt-based learning approaches with transformer models (large language models trained in an unsupervised manner) for a domain-specific classification task. Prompt-based learning with zero or few shots has the potential to (1) make use of artificial intelligence without…

This study was carried out to develop a test to assess algorithmic thinking skills. To this end, the twelve steps suggested by Downing (2006) were adopted. Throughout the test development, 24 middle school sixth-grade students and eight experts in different areas took part as needed in the tasks on the project. The test was given to 252 students…

A majority of research in Computational Thinking (CT) mainly focuses on teaching coding to school students. However, CT involves more than just coding and includes other skills like algorithmic thinking. The current study developed an Online Inquiry-based Learning Platform for Computational Thinking (CT-ONLINQ) that follows Inquiry-Based Learning…

Digital education has recently become a mainstream education model. Despite digital education's increasing popularity, there remain issues when it comes to teacher-student interactions in digital space, which have made it impossible for this model to achieve the same teaching quality as traditional in-person education. Compared with other academic…

This research was triggered by the identified need in literature for large-scale studies about the kinds of designs that teachers create for mobile learning (m-learning). These studies require analyses of large datasets of learning designs. The common approach followed by researchers when analyzing designs has been to manually classify them…

Presents a class of distortion controlled vector quantizers that are capable of compressing images so they comply with certain distortion requirements. Highlights include tree-structured vector quantizers; multiresolution vector quantization; error coding vector quantizer; error coding multiresolution algorithm; and Huffman coding of the quad-tree…

Analyzes the computational complexity of optimal binary tree pruning for tree-structured vector quantization. Topics discussed include the combinatorial nature of the optimization problem; the complexity of optimal tree pruning; and finding a minimal size pruned tree. (11 references) (LRW)