The study is built on attribution theory, a framework with roots in Fritz Heider’s mid-century work on interpersonal perception and Bernard Weiner’s later formalization of achievement motivation. The core idea is deceptively simple: when people succeed or fail, they instinctively explain why, and the shape of that explanation matters enormously. Attributions vary along three dimensions — locus, whether the cause is internal to the person or external in the world; stability, whether the cause is permanent or fleeting; and controllability, whether the person could have done anything about it. A student who blames failure on low innate ability has made a stable, internal, uncontrollable attribution, which is motivational poison. A student who blames a missing lab session has made an unstable, external one, which leaves room for hope. Zakariya wanted to know which stories Nigeria’s future CS teachers tell themselves.

To find out, he turned to phenomenology — a qualitative methodology designed to capture lived experience in rich detail rather than to count variables. He conducted in-depth individual interviews with eight final-year preservice computer science teachers at a Nigerian university, then subjected the transcripts to thematic analysis, the systematic coding procedure developed by Virginia Braun and Victoria Clarke. Eight is a small number, and the study makes no claim to statistical generalization; what it offers instead is depth, a portrait of how underachievement actually feels and gets rationalized from the inside. The ethical scaffolding was careful: informed consent was obtained, the protocol was approved by the university’s ethics committee under reference ABUCUHSR/2026/033, and participants were anonymized with pseudonyms.

The analysis converged on seven distinct drivers of underachievement, and the first is one that will resonate with computer scientists everywhere: the curriculum is obsolete. Students described course content that had fallen years behind the state of the discipline, teaching them material that neither reflects modern practice nor prepares them for the classrooms they will soon run. This is not a uniquely Nigerian problem — curriculum lag plagues computer science education globally, because the field moves faster than accreditation cycles — but its severity in this context is compounded by history. Nigeria’s national computer education policy dates back to 1988, and researchers have documented gaps between policy and classroom practice for decades.

The second driver is infrastructure, or rather the absence of it. Preservice teachers reported inadequate digital facilities: insufficient computers, unreliable power, and limited internet access that made hands-on practice a scarce commodity rather than a routine expectation. For a discipline whose entire epistemology is built on building, running, and debugging real systems, learning computer science without reliable machines is like studying chemistry without a lab. The third and fourth drivers are pedagogical: students described ineffective teaching methods — lecture-heavy, transmission-style instruction at odds with the active-learning approaches that a growing body of evidence links to better outcomes in computing — and a striking lack of formative feedback. Without regular, low-stakes assessment that tells students where they stand and how to improve, they navigate their degrees by guesswork, discovering their weaknesses only when it is too late to fix them.

The remaining three drivers shift the lens from the classroom to the institution and the individual. Students cited insufficient institutional support, from administrative indifference to the absence of academic advising structures that might catch struggling learners early. They acknowledged limited self-regulatory learning strategies on their own side of the desk — weak planning, poor time management, underdeveloped study habits — and finally, the absence of any recognition mechanism, no awards, no celebration of excellence, nothing to make achievement feel visible and worth pursuing. That last finding is quietly devastating: motivation research has long shown that recognition functions as a signal that effort matters, and its absence teaches students the opposite lesson.

What makes the study more than a catalogue of grievances is how the attributions distribute. The students did not simply externalize everything. While they located most of their struggles in systemic and pedagogical constraints — external, often stable, largely uncontrollable factors — they also recognized the role of their own effort, planning, and peer collaboration in shaping outcomes. This split matters because it maps onto the classic motivational finding that the healthiest attributional profile blends accountability with realism. Students who believe nothing is their fault stop trying; students who believe everything is their fault stop hoping. These preservice teachers, remarkably, held both truths at once, which suggests the raw material for resilience is present even where the system around it is not.

The stakes extend well beyond one cohort of students. These are future teachers, and teacher quality is the single most powerful school-level predictor of student achievement. A preservice computer science teacher who graduates with shallow practical skills, no experience of formative feedback, and a demoralized attributional style does not simply underperform personally — they reproduce the entire dysfunctional pattern in their own classrooms a few years later. Nigeria’s National Digital Economy Policy and Strategy for 2020 to 2030 bets heavily on digital skills as an engine of growth, but the study’s evidence suggests the human infrastructure layer, the teachers themselves, is being built on foundations that cannot yet bear the weight.

Zakariya’s prescriptions are correspondingly structural. He calls for urgent curriculum modernization to drag course content into the current decade, faculty retraining in digital pedagogy so that teaching methods match the subject matter, serious infrastructural investment in computing facilities and connectivity, and learner-centred reform of assessment and motivation systems — formative feedback loops, recognition programs, and supports that catch struggling students before they fail. None of these are exotic interventions. The notable thing is how ordinary they are: the study essentially argues that the fastest way to improve computer science education in Nigeria is to do the unglamorous basics competently, at scale, consistently.

There is also a methodological lesson here for education research more broadly. Quantitative studies can tell you that underachievement exists and correlate it with any number of factors, but they cannot tell you what failure means to the person living it — and meaning is where motivation lives. By listening to eight students describe their own struggles in their own words, this study surfaces mechanisms that a regression coefficient would never reveal: the demoralizing silence after an exam, the absurdity of learning programming without a working machine, the quiet erosion of ambition when excellence goes unnoticed. For a field racing to staff classrooms with digitally competent teachers worldwide, the message travels well beyond Nigeria. Systems that want high achievement cannot merely demand it; they have to build the conditions, curricular, infrastructural, pedagogical, and motivational, under which achievement becomes the rational, rewarded, expected outcome. Until they do, the students closest to the problem will keep telling the truth about it — and the truth, as this study shows, is that they know exactly what is broken.

Subject of Research: Academic underachievement among preservice computer science teachers in Nigeria

Article Title: Unpacking the challenges: investigating the drivers of academic underachievement among preservice computer science teachers in Nigeria

Article References: Zakariya, Y. F. (2026). Unpacking the challenges: investigating the drivers of academic underachievement among preservice computer science teachers in Nigeria. SN Social Sciences, 6(8), Article 349. https://doi.org/10.1007/s43545-026-01640-0

Image Credits: AI Generated

DOI: 10.1007/s43545-026-01640-0

Keywords: computer science education, preservice teachers, academic underachievement, attribution theory, Nigeria, teacher education, qualitative research, phenomenology, thematic analysis, STEM education, digital infrastructure, curriculum reform