This paper presents the design and development of LINEAR: Road to INFINITY, a digital educational game created to help students aged 10–14 learn linear algebra in an engaging and interactive way. The game uses the LADDER framework, which starts with learning content and focuses on making the game both educational and enjoyable. To support deeper learning, the design also incorporates educational theories such as Constructivist Learning Theory, Experiential Learning Theory, and Flow Theory. These help create a learning environment where students can actively explore, practice, and improve their algebra skills. The goal is to offer a tool that teachers can use in class or students can use independently to make learning algebra more fun and effective.

In point cloud data processing, preprocessing is a critical step, particularly for addressing incomplete data caused by occlusions or limited visibility during acquisition. To enhance the completeness of point cloud models, this paper proposes a method for reconstructing missing regions using approximation curves. The approach begins by deriving control points from the existing point cloud, which are used to construct curves that closely conform to the surface geometry. Control points are computed through triangulation and spatial analysis, ensuring that the generated curves align with the local structure of the data. Uniform sampling is then applied along each curve to produce a set of points that effectively fill the missing regions. Experimental results demonstrate that the proposed method can successfully reconstruct surface segments with consistent spacing and high accuracy, making the data suitable for downstream applications such as 3D modeling, object classification, and structural analysis.

Linked lists are among the most fundamental yet challenging data structures for novice learners because of their noncontiguous memory organization and complex pointer manipulation. To address these learning barriers, this paper proposes "RAILLINK," a digital educational puzzle game designed using the LADDER model, aimed at enhancing conceptual understanding of basic singly linked list operations for students aged 15–22. This game-based learning tool transforms operations, such as traversal, insertion, deletion, and reordering into interactive missions embedded in a railway logistics simulation. To support deeper learning, the design also incorporates educational theories such as the Constructivist Learning Theory, Experiential Learning Theory, Flow Theory, and Zone of Proximal Development Theory. RAILLINK leverages narrative elements, constraint-based tasks, and real-time feedback to foster conceptual clarity and engagement.

This study systematically details the development and implementation of a digital educational game for genetic algorithm learning, guided by the Analysis, Design, Development, Implementation, and Evaluation (ADDIE) model. The game is tailored to educate users on genetic algorithms, integrating a range of game mechanics, including quizzes, simulations, and challenges, to create an immersive and enjoyable educational environment. In the Analysis and Design phases, learning objectives, target audience characteristics, potential challenges, and game mechanics were meticulously designed. The subsequent Development phase involved integrating genetic algorithm concepts into the game's components. The game was then deployed for testing with students, employing assessments to gauge user satisfaction and game effectiveness. Preliminary results indicate positive user feedback and an enhanced understanding of genetic algorithms, highlighting the ADDIE model's potential in guiding the creation of effective digital educational games. This research contributes valuable insights into the application of instructional design models for developing educational games that foster meaningful learning experiences.

Boolean algebra is an important study for the analysis and simplification of logic circuit. There are many methods that can simplify Boolean algebra expression quickly. However, simplification Boolean algebra expression by applying Boolean algebra laws was commonly taught in the class. The teacher or student must spend a lot of time on checking the correctness of this method line by line with bare eyes. This paper proposed the software to helps them by automatically find error locations from image of handwritten Boolean expression derivation. The image was segmented into the lines before characters would be extracted from each line. After that, the characters were recognise and rewriting into the text form. The expression of each line was simplified by the system, then it will be compared to the next line. Finally, the system returns the result in format of input image overlayed with a result from finding error process.