Bibliography: the digital-skills evidence base

The consolidated, annotated sources for the digital-skills pillar; every work is cited in the library, grouped by the claim it carries. Method notes: how we grade · reading research critically.

Typing and the keyboard

• Feit, A. M., Weir, D., & Oulasvirta, A. (2016). How we type. CHI 2016. Everyday typists measured — technique matters more than finger-count dogma; home row, honestly.
• Dhakal, V., Feit, A. M., Kristensson, P. O., & Oulasvirta, A. (2018). Observations on typing from 136 million keystrokes. CHI 2018. The large-scale speed/accuracy dataset — benchmarks and norms.
• Connelly, V., Gee, D., & Walsh, E. (2007). BJEP, 77(2). Uninstructed children type slower than they write — the instruction gap.
• Card, S. K., Moran, T. P., & Newell, A. (1983). The Psychology of Human-Computer Interaction. The keystroke-level model — shortcuts' arithmetic and par's license.
• Lane, D. M., Napier, H. A., Peres, S. C., & Sándor, A. (2005). IJHCI, 18(2) and Carroll, J. M., & Rosson, M. B. (1987). Paradox of the active user. Why efficient methods go unadopted — the shortcut-teaching case.
• Fitts, P. M. (1954). JEP, 47(6). Pointing has lawful costs — cited from shortcuts to accommodations.

Search, evaluation, misinformation

• Wineburg, S., & McGrew, S. (2019). Lateral reading and the nature of expertise. Teachers College Record, 121(11). Fact-checkers leave the page — the method.
• Breakstone, J., Smith, M., Wineburg, S., et al. (2021). Educational Researcher, 50(8). Students' civic online reasoning, measured — after the checklist era.
• Bilal, D. (2000–2002). Yahooligans! studies. JASIS(T) and Druin, A., Foss, E., et al. (2010). CHI 2010. How children actually search — query formulation.
• Ofcom. Children and Parents: Media Use and Attitudes (annual). The ad-recognition and under-age-account data — sponsored results, age verification.
• Roozenbeek, J., & van der Linden, S. (2019). Palgrave Communications, 5; (2022). Science Advances, 8(34); Maertens, R., et al. (2021). JEP: Applied, 27(1). Inoculation works and decays — prebunking.
• Lewandowsky, S., et al. (2012). Psychological Science in the Public Interest, 13(3). Corrections chase misinformation — the case for acting first.

Programming education

• Weintrop, D., & Wilensky, U. (2017). ACM TOCE, 18(1). Blocks vs text, measured — the transition evidence.
• Kölling, M., Brown, N. C. C., & Altadmri, A. (2015). Frame-based editing. WiPSCE. The scaffold-removal middle ground.
• Sorva, J. (2013). ACM TOCE, 13(2) and du Boulay, B. (1986). JECR, 2(1). The misconception catalogues — the constructs ladder.
• Grover, S., & Pea, R. (2013). Educational Researcher, 42(1) and Papert, S. (1980). Mindstorms. Computational thinking's case and origin — graded honestly.
• McCauley, R., et al. (2008). Debugging: a review. Computer Science Education, 18(2). Debugging as taught skill — the pedagogy.

Writing technology

• Graham, S., & Perin, D. (2007). Writing Next. Word processing helps struggling writers most — the progression's anchor.
• Bangert-Drowns, R. L. (1993). RER, 63(1) and Morphy, P., & Graham, S. (2012). Reading and Writing, 25(3). The word-processing meta-analytic line.
• Berninger, V. W., et al. — the transcription research program. Transcription load gates composition — cited from typing readiness to dyslexia.
• MacArthur, C. A. (2009). LDRP, 24(2). Technology for struggling writers.

AI and detection

• Liang, W., et al. (2023). GPT detectors are biased against non-native English writers. Patterns, 4(7) and Weber-Wulff, D., et al. (2023). IJEI, 19. Why detectors can't carry integrity.

Sibling lists: learning science · online safety.

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