In this research paper, we conducted a comparative study to measure the effectiveness of the provided technical support in computing project-based learning (PjBL) courses. Students learn much better by solving authentic real-world problems through PjBL. PjBL in computing education has proven to boost student motivation and engagement while enhancing academic performance. Crucial to PjBL in computing is the technical support that the instructors can provide to students, which is required for sustained, successful learning during project tasks. Without adequate support, PjBL will fall short of accomplishing its goals, leading to a rise in student frustration, a loss of motivation and engagement, and compromised learning outcomes. Measuring the impacts and effectiveness of the provided support is imperative for fostering continuous improvement, informed decision-making, and student success. It enables instructors to assess the impacts of their strategies, improve their approaches, and utilize their resources more effectively. To measure the impacts of technical support on students during PjBL, we performed a comparative study on two undergraduate computing courses in Spring 2024, Fundamentals of Software Engineering and Database Systems. In both courses, students work on two assigned projects, one with little and inadequate support and the other with adequate support. We administered a post-survey after each project was completed. We analyzed students' selfreflection responses across four sub-scales, support satisfaction, motivation, self-efficacy, and project satisfaction. The results show a statistically significant increase in the supported project in the Fundamentals of Software Engineering course and no difference in the Database Systems course. This finding is likely due to other differences between the two projects for the Database Systems course beyond support, such as project scale. Qualitative analysis of students' responses also indicates the need for support by students in the less supported projects. Based on our experience, we reflect on the question of what would constitute a good design for studies that seek to compare two different student learning experiences.

In this research paper, drawing from our own and other computing instructors' experiences, we highlight common technical challenges faced by students in software engineering project-based learning (PjBL) and discuss ways in which instructors can support students in overcoming them so that motivation is summoned and sustained. Through the use of practical hands-on experiences, PjBL has been shown to be an effective educational approach. However, unless projects are intentionally designed and supported in a way that summons and sustains student motivation, PjBL is likely to fail to accomplish its goals. Several factors influence student motivation, including their perception of the project's value and how confident they are in their ability to complete it. In particular, challenges that students perceive as insurmountable during the project can significantly weaken their motivation. On the other hand, supporting students to overcome such hurdles can be troublesome, especially in large classes as well as classes with diversity in student backgrounds. To generalize from our own experience, we designed a questionnaire targeted at PjBL computing instructors that contained closed and open questions on technical challenges faced by students, support instructors provided to overcome such challenges, and lessons learned by instructors on the effectiveness of their support. A total of 47 responses were collected from instructors with diverse backgrounds in terms of courses taught, students' years, and class sizes. We categorized the technical challenges into three main categories, namely (a) challenges in installing and configuring software packaged tools, (b) lack of prerequisite knowledge, and (c) challenges while completing project tasks. In this paper, we present the survey results from the three categories of technical challenges, their frequencies, importance, and effective support strategies instructors use to alleviate them.

Teaching students complex problem-solving skills using large-scale, real-world problems is challenging for both students and teachers alike. As a result, most courses use small, well-specified, toy-like problems, which are not representative of what students will encounter in the workforce. One approach that allows teachers to use large-scale problems in class is by introducing scaffolding. Scaffolding breaks a larger problem into smaller steps, which students can solve independently, while deemphasizing tangential concepts such as the complex configuration files needed to compile open-source software systems. Strong scaffolding supports student learning, preventing them from getting bogged down with unnecessary tasks or overwhelmed by complexity. This work investigates a scaffolded problem-based-learning module for computing courses, using a realistically-sized project with characteristics representative of the industry. The project was implemented in a computer science course with roughly 100 students, and the results speak to the importance of scaffolding for student success. In fact, there were two student assignments that lacked sufficient scaffolding, compared with other tasks, and the reduction in student scoring and persistence shows that project scaffolding is necessary when implementing these types of assignments. Most students felt the project helped prepare them for a job in their chosen field.

This qualitative research performs a thematic analysis of the learning objectives in existing project-based undergraduate software engineering courses to align them with the competency model defined in the Computing Curricula 2020 reports (CC2020). This study identifies the trends, strengths, and gaps in how the reviewed course learning objectives cover the knowledge, skill, and disposition components of the CC2020 competency model. The learning objectives were categorized according to knowledge elements, skills, and dispositions as defined in the CC2020 competency model. Our analysis shows that 54% of knowledge elements from the reviewed learning objectives do not have any skill level specified and overall, only two out of the eleven dispositions in CC2020 are specified (“Collaboration” and “Professional”). We also find that technical knowledge elements from the software development category (e.g., software process, software design, and software quality, verification & validation) and systems modeling category (e.g., systems analysis & design, and requirements analysis and specification), probably unsurprisingly, are covered the most often. Similarly, collaboration & teamwork, and oral & written communication are unsurprisingly the most common professional & foundational knowledge elements in the reviewed course's learning objectives as they are essential to project-based learning. Although they are essential for the completion of a successful software project, knowledge elements such as time management, security technology & implementation, and user experience design are rarely mentioned. We discuss the implications of our findings on course design.