Teaching for Success in Computer Science: Research-Backed Strategies
Dr. Kai Dupe • December 15, 2025
Computer science has often been portrayed as a field where only a select few can succeed.
Computer science has often been portrayed as a field where only a select few can succeed. Yet decades of research in computer science education suggest something far more encouraging: student success in computing is strongly influenced by how we teach, how students are supported, and how learning environments are designed. When instruction aligns with research-based practices, student learning and persistence increase across experience levels.
One of the most consistent findings across STEM education is the effectiveness of active learning. A large meta-analysis by Freeman et al. found that students in active-learning environments performed better and were significantly less likely to fail than students in traditional lecture-only courses (Freeman et al., 2014: https://www.pnas.org/doi/10.1073/pnas.1319030111). In computer science, active learning includes structured labs, guided coding exercises, peer discussion, and opportunities for students to reason through problems. Programming is a skill developed through practice, iteration, and feedback—not passive observation.
Research also emphasizes the role of self-efficacy, or students’ belief in their ability to succeed. Albert Bandura’s foundational work shows that confidence influences persistence, motivation, and academic performance (Bandura, 1997: https://www.uky.edu/~eushe2/Bandura/BanEncy.html). In computing, studies indicate that students who believe success comes from effort and effective strategies—rather than innate talent—are more likely to continue in the major (Lewis et al., 2016: https://dl.acm.org/doi/10.1145/2839509.2844593). Early, well-scaffolded successes and explicit normalization of struggle, particularly around debugging, help reinforce this belief.
Collaborative learning further supports student success. Research on peer instruction and pair programming demonstrates improvements in conceptual understanding and student engagement, especially in introductory computer science courses (Porter et al., 2013: https://dl.acm.org/doi/10.1145/2445196.2445248). Working with peers helps students articulate their thinking, learn from alternative approaches, and develop communication skills central to professional computing practice.
From a cognitive perspective, worked examples and scaffolding are especially effective for novice programmers. Cognitive Load Theory shows that learners benefit from studying annotated or partially solved examples before tackling problems independently (Sweller, 1988: https://link.springer.com/article/10.1007/BF00375144). As students gain expertise, these supports can be gradually removed.
Finally, real-world and challenge-based projects increase motivation by helping students see computing as relevant and impactful. When students understand why their code matters, they engage more deeply and persist longer.
The message from the research is clear and hopeful: computer science students thrive when instruction is intentional, supportive, and evidence-based.
A mentor gives you advice. A sponsor creates opportunities.
Representation alone will not solve the persistent racial disparities in computing.
The truth is that most software applications exist to manage information.
Artificial intelligence has become the newest member of nearly every software development team.
The true promise of computing is not found in the machines we build, but in the human potential we unlock when knowledge becomes accessible to everyone.
One of the reasons I value the MCT program so highly is that it represents more than technical knowledge.
Software engineering is not simply coding.
Companies often promote the idea that technical skill alone determines success.
Hackathons also strengthen teamwork and communication skills.
Stepping onto the campus of Morehouse College this past weekend for Admitted Students Day was more than a visit—it was a moment of reflection. As I watched young Black men walk with purpose across the yard, I found myself asking a simple but profound question: What would it have been like for me to study computer science here? My journey into computing was shaped in environments where I was often the only Black man in the room. That reality brings with it an unspoken weight—the need to prove you belong, the awareness of being watched, and sometimes, the quiet isolation that comes with underrepresentation. Standing at Morehouse, I realized that this burden is not a given. It is a condition of the environment. At Morehouse, the environment is different by design. Here, Black men are not anomalies—they are the standard. I imagined what it would feel like to learn algorithms, data structures, and software development in a space where my identity was not questioned but affirmed. Where excellence is expected, not in spite of who you are, but because of it. As a computer science professor, I understand the academic rigor required to succeed in this field. There is no shortcut through recursion, no bypass around debugging, no substitute for disciplined problem-solving. But what struck me during my visit is how much context matters. When students are free from the psychological burden of proving they belong, they can redirect that energy toward mastering the material. They can collaborate more openly, ask questions more freely, and take intellectual risks without fear. I also thought about legacy. At Morehouse, students walk the same grounds as Martin Luther King Jr.. That kind of history does something to a person. It raises the bar—not just academically, but personally. It invites students to see their education not just as a pathway to a career, but as preparation for impact. Leaving campus, I felt inspired—but also reflective. I cannot rewrite my journey, but I can appreciate what spaces like Morehouse offer the next generation. For a Black male pursuing computer science, it is more than a degree. It is an opportunity to develop skill, confidence, and identity in alignment. And that combination is powerful.