The aim of this study is to investigate the impact of interactive and demonstration (non-interactive) video tutorials for software training on the effectiveness of procedural learning and student satisfaction. An analysis of signalling made by instructional designers was carried out to develop high-quality instructional video materials. These…

Background and Context: Recursion in binary trees has proven to be a hard topic. There was not much research on enhancing student understanding of this topic. Objective: We present a tutorial to enhance learning through practice of recursive operations in binary trees, as it is typically taught post-CS2. Method: We identified the misconceptions…

Self-evaluation of one's competences is considered a core factor in various domains of human functioning, including learning and instruction, as well as academic and vocational choices. Researchers from the fields of metacognition and learning, as well as motivation and learning have thus intensively investigated issues related to the…

Recursion is one of the most important and hardest topics in lower division computer science courses. As it is an advanced programming skill, the best way to learn it is through targeted practice exercises. But the best practice problems are time consuming to manually grade by an instructor. As a consequence, students historically have completed…

Virtual agents have been shown to be more effective when incorporating social factors such as trust into task action selection. However, there has been less work on how virtual tutoring agents can incorporate social factors into pedagogical action selection. We propose and evaluate how a socially-conditioned task reasoner for a virtual pedagogical…

Sharing user information between systems is an area of interest for every field involving personalization. Recommender Systems are more advanced in this aspect than Intelligent Tutoring Systems (ITSs) and Intelligent Learning Environments (ILEs). A reason for this is that the user models of Intelligent Tutoring Systems and Intelligent Learning…