This editorial brings together the insights of fourteen members of the journal’s editorial board to critically examine the evolving landscape of educational computing. In an era marked by rapid technological advancements; from generative artificial intelligence to extended reality, this editorial explores the multidimensional challenges and opportunities these developments present for education. Drawing from multidisciplinary perspectives, the contributors collectively identify four thematic areas that demand sustained scholarly attention: (1) Equity, Inclusion, and the Digital Divide; (2) Ethics, Social Sustainability, and Well-being; (3) Instructional Design; and (4) Human-Computer Interaction in Educational Technologies. Each theme reflects a convergence of urgent concerns and transformative potential and is accompanied by forward-looking research questions that aim to shape the future agenda of the field. Together, the contributions highlight critical tensions and possibilities, offering a roadmap for researchers, practitioners, and policymakers committed to harnessing educational computing technologies in socially responsible, pedagogically sound, and human-centred ways.

Even though there are various source code plagiarism detection approaches, most of them only concern with low-level plagiarism attack with an assumption that plagiarism is only conducted by students who are not proficient in programming. However, plagiarism is often conducted not only due to student incapability, but also because of bad time management. Thus, high-level plagiarism attack should be detected and evaluated. This paper proposes source code plagiarism detection approach which can detect most introductory-programming-course plagiarism attacks at any level by utilizing low-level instructions instead of source code tokens. Several mechanisms are also introduced to improve its effectiveness such as instruction generalization, instruction reinterpretation, method-based comparison, and method linearization. Since low-level instruction is a language-dependent feature, Java is selected as target programming language with bytecode as its low-level instruction. Based on evaluation, it can be concluded that our approach is more effective to detect most plagiarism attack types than raw source code approach on introductory programming course. This evaluation is based on plagiarism attack types that are collected through controlled experiment.

Historically, computing instructors and researchers have developed a wide variety of tools to support teaching and educational research, including exam and code testing suites and data collection solutions. However, these tools often find limited adoption beyond their creators. As a result, it is common for many of the same functionalities to be re-implemented by different instructional groups within the Computing Education community. We hypothesise that this is due in part to discoverability, availability, and adaptability challenges. Further, instructors often face institutional barriers to deployment, which can include hesitance of institutions to rely on community developed solutions that often lack a centralised authority and may be community or individually maintained. To this end, our working group explored what solutions are currently available, what instructors needed, and the reasons behind the above-mentioned phenomenon. To do so, we reviewed existing literature and surveyed the community to identify the tools that have been developed by the community; the solutions that are currently available and in use by instructors; what features are needed moving forward for classroom and research use; what support for extensions is needed to support further Computing Education research; and what institutional challenges instructors and researchers are currently facing or have faced in using community software solutions. Finally, the working group identified factors that limited adoption of solutions. This work proposes ways to integrate and improve the availability, discoverability, and dissemination of existing community projects, as well as ways to manage and overcome institutional challenges.