Research synthesis · Computing education

Computing education: computational thinking, functional programming and technology acceptance

Vajjhala and colleagues study how computing is taught and accepted — functional programming with Haskell, computational thinking across disciplines, blockchain within cybersecurity curricula, and student acceptance of mandatory learning technology.

A short narrative review of research by Narasimha Rao Vajjhala and co-authors in this area. Every claim carries an APA citation that links to the publication’s own page (abstract, key findings, DOI); the full references are listed at the end. Updated .

Synthesis

Narasimha Rao Vajjhala’s computing education research asks how programming, computational thinking and security should be taught, and how students accept the technologies used to teach them.

On programming, Fonkam and Vajjhala (2026) systematically reviewed 28 empirical studies published between 2015 and 2025 on functional programming taught with Haskell. They found mixed but promising outcomes: integrated approaches that combine functional programming with broader programming principles outperformed purely functional courses, benefits for mathematical reasoning and abstract thinking were consistent, and transfer to mainstream object-oriented languages was selective. Beyond programming, Fonkam and Vajjhala edited a volume that reframes computational thinking, logic and problem solving as discipline-independent skills and offers lesson plans, case studies and tools for embedding them in subjects ranging from educational robotics to digital marketing and literature (Fonkam & Vajjhala, 2024).

On security education, Strang et al. (2020a) found only five peer-reviewed papers on teaching blockchain in higher education, contrasted its treatment as a managerial decision topic for business students with application design and programming for computing students, and proposed a two-dimensional teaching typology spanning stakeholder role and teaching ideology.

On acceptance, Strang and Vajjhala (2017) studied 65 senior supply chain students required to use a new learning management system. Perceived usefulness, enjoyment, voluntariness and results demonstrability explained 52.3% of behavioral intention, and behavioral intention predicted students’ actual course grades — evidence that Technology Acceptance Model 3 predicts performance, not only self-reported intention. Related consumer studies found that satisfaction and happiness predicted young Indian consumers’ online purchase intention (Vajjhala & Strang, 2018a), and that trust — not gender, age or income — predicted young US and Indian consumers’ online smartphone purchase decisions (Vajjhala & Strang, 2019).

Together these studies support teaching programming paradigms in an integrated way, treating computational thinking as a cross-disciplinary literacy, teaching security to both technical and managerial audiences, and attending to how students experience the platforms they are required to use.

Key claims with sources

  1. Functional programming taught with Haskell brings consistent benefits for mathematical reasoning and abstract thinking, with selective transfer to object-oriented languages (Fonkam & Vajjhala, 2026).
  2. Among students required to use a new learning management system, behavioral intention predicted actual course grade (Strang & Vajjhala, 2017).
  3. Blockchain can be taught along two dimensions — stakeholder role and teaching ideology (Strang et al., 2020a).

References

How to cite this synthesis

Please cite the original publications above for specific findings. To cite this overview itself:

Vajjhala, N. R. (2026, September 25). Computing education: computational thinking, functional programming and technology acceptance. Narasimha Rao Vajjhala. https://www.narasimharao.net/research/focus-areas/computing-education-technology-acceptance/

Markdown version