Computational thinking (CT) is a necessary skill that must be learned in today's tech-focused world, especially within K-12 education, where early learning of problem-solving skills and algorithmic thinking is beneficial in everyday life. Various ways have been used to cultivate this skill in these early education phases [6]. Our approach was to use an unplugged gamified coding activity that involved creating a learning environment that required hands-on participation and critical computational thinking. This study examines the impact of a gamified coding activity on computational thinking (CT) skills of K-12 students in a public stem event setting where each student has around 30 minutes of solving time. This study also observes the influence of the short-term intervention on algorithmic thinking and problem solving abilities by incorporating a before-and-after survey, in which students were asked to write down the steps to brush their teeth before and after the activity. This data was used to evaluate improvements in student procedural thinking and logical structure. The findings suggest that gamification enhances engagement and helps students develop clearer and more structured algorithms. These results contribute to research on effective teaching strategies for CT in K-12 education and to improving the learning environment.
Yacc and Lex provide a powerful tool to automate finding implicit structure hidden within a flat sequence of symbols. However, Yacc is fragile in that it can easily fail with obscure messages. We learn LR Parsing to fix these.
Teaching large classes, particularly in computer science (CS), presents notable challenges that can hinder student learning. Common issues include low student participation, often due to students feeling hesitant or uncomfortable speaking up in large groups, and difficulties in providing timely feedback. To address these challenges, this study introduces a straightforward and practical solution: a dual-component quiz system integrated into laboratory sessions. In this approach, students first complete a quiz individually, followed by a collaborative phase where they retake the same quiz in small groups. This structure promotes peer feedback and reinforces understanding. The grading scheme allocates 60% of the total score to individual performance and 40% to group performance, encouraging both personal accountability and collaborative engagement. To assess the effectiveness of this method, a comparative analysis was performed using course evaluations from five sections of CS 132 at Boston University. Two sections, serving as the baseline, did not include the quiz component, while three sections implemented the new system. The results of the Welch Statistical Test (WST) revealed that the collaborative quiz system significantly improved student participation, promptness of feedback, and quality of feedback to students.
In this paper, some common difficulties that students experience with proofs by induction are discussed. These are used to form design goals for a WebApp to help students understand induction better. A WebApp implementing those goals is presented. Finally, results from a self reflection survey of students rating their understanding of induction are presented.
Dr. Michael B. Flinn is Professor, Chair, and Disrupter-in-Residence (unofficial title, very official energy) in the Department of Computer Science and Information Technologies at Frostburg State University, where he also coordinates the Master of Applied Computer Science program. With nearly 25 years in computing education, Dr. Flinn challenges the status quo by asking one big question: How do we truly engage students in a world flooded with AI agents, infinite scroll, and attention-hacking algorithms?
