ABSTRACT
In recent times, programming is increasingly taught to younger students in schools. While learning programming is known to be difficult, we can lighten the learning experience of this age group by adopting pedagogies that are common to them, but not as common in CS education. One of these pedagogies is Reading Aloud (RA), a familiar strategy when young children and beginners start learning how to read in their natural language. RA is linked with a better comprehension of text for beginner readers. We hypothesize that reading code aloud during introductory lessons will lead to better code comprehension. To this end, we design and execute a controlled experiment with the experimental group participants reading the code aloud during the lessons. The participants are 49 primary school students between 9 and 13 years old, who follow three lessons in programming in Python. The lessons are followed by a comprehension assessment based on Bloom's taxonomy. The results show that the students of the experimental group scored significantly higher in the Remembering-level questions compared to the ones in the control group. There is no significant difference between the two groups in their answers to the Understanding-level questions. Furthermore, the participants in both groups followed some of the instructed vocalizations more frequently such as the variable's assignment (is). Vocalizing the indentation spaces in a for -loop was among the least followed. Our paper suggests that using RA for teaching programming in schools will contribute to improving code comprehension with its effect on syntax remembering.
- Lorin W Anderson and David Krathwohl. 2001. A Taxonomy for Learning, Teaching, and Assessing. New York.Google Scholar
- Richard Arends. 2012. Learning to teach. McGraw-Hill.Google Scholar
- Craig Barton. 2018. How I wish I'd taught maths. John Catt Educational Ltd.Google Scholar
- Andrew Begel. {n. d.}. Programming By Voice: A Domain-specific Application of Speech Recognition. ({n. d.}).Google Scholar
- A. Begel and S.L. Graham. {n. d.}. Spoken Programs. 2005 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC'05) ({n. d.}). Google ScholarDigital Library
- A. Begel and S.L. Graham. 2006. An Assessment of a Speech-Based Programming Environment. Visual Languages and Human-Centric Computing (VL/HCC'06) (2006). Google ScholarDigital Library
- B.S. Bloom. 1956. Taxonomy of Educational Objectives: The Classification of Educational Goals. Number v. 1 in Taxonomy of Educational Objectives: The Classification of Educational Goals. D. McKay. 64012369 https://books.google.nl/books?id=hos6AAAAIAAJGoogle Scholar
- B. Du Boulay. 1986. Some Difficulties of Learning to Program. Journal of Educational Computing Research, Vol. 2, 1 (1986), 57--73. https://doi.org/10.2190/3LFX-9RRF-67T8-UVK9Google ScholarCross Ref
- Linda E. Martin and Sherry Kragler. 2011. Becoming a Self-Regulated Reader: A Study of Primary-Grade Students' Reading Strategies. Literacy Research and Instruction, Vol. 50, 2 (2011), 89--104.Google ScholarCross Ref
- Michael F. Mascolo. 2015. Neo-Piagetian Theories of Cognitive Development. International Encyclopedia of the Social & Behavioral Sciences (2015), 501--510.Google Scholar
- R. Steve McCallum, Shannon Sharp, Sherry Mee Bell, and Thomas George. 2004. Silent versus oral reading comprehension and efficiency. Psychology in the Schools, Vol. 41, 2 (2004), 241--246.Google ScholarCross Ref
- Chris Parnin. 2011. Subvocalization - Toward Hearing the Inner Thoughts of Developers. 2011 IEEE 19th International Conference on Program Comprehension (2011). Google ScholarDigital Library
- M. Perrone-Bertolotti, L. Rapin, J.-P. Lachaux, M. Baciu, and H. Lavenbruck. 2014. What is that little voice inside my head? Inner speech phenomenology, its role in cognitive performance, and its relation to self-monitoring. Behavioural Brain Research, Vol. 261 (2014), 220--239.Google ScholarCross Ref
- David E Price, DA Dahlstrom, Ben Newton, and Joseph L Zachary. 2002. Off to See the Wizard: using a "Wizard of Oz" study to learn how to design a spoken language interface for programming. In Frontiers in Education, 2002. FIE 2002. 32nd Annual, Vol. 1. IEEE, T2G--T2G.Google ScholarCross Ref
- Suzanne M Prior and Katherine A Welling. 2001. "Read in Your Head": A Vygotskian Analysis of the Transition from Oral to Silent Reading. Reading Psychology, Vol. 22, 1 (2001), 1--15.Google ScholarCross Ref
- Katherine E. Purswell and Dee C. Ray. 2014. Research With Small Samples. Counseling Outcome Research and Evaluation, Vol. 5, 2 (2014), 116--126.Google ScholarCross Ref
- Keith Rayner, Barbara R. Foorman, Charles A. Perfetti, David Pesetsky, and Mark S. Seidenberg. 2002. How Should Reading be Taught? Scientific American, Vol. 286, 3 (2002), 84--91.Google ScholarCross Ref
- Lana Edwards Santoro, David J. Chard, Lisa Howard, and Scott K. Baker. 2008. Making the Very Most of Classroom Read-Alouds to Promote Comprehension and Vocabulary. The Reading Teacher, Vol. 61, 5 (2008), 396--408.Google ScholarCross Ref
- Marcel Schmeier and Ruud Bijman. 2017. Effectief rekenonderwijs op de basisschool 1st edition ed.). Uitgeverij Pica.Google Scholar
- Lindsey Snell and Mr Jim Cunningham. 2000. An investigation into programming by voice and development of a toolkit for writing voice-controlled applications. (2000).Google Scholar
- Osamu Takeuchi, Maiko Ikeda, and Atsushi Mizumoto. 2012. Reading Aloud Activity in L2 and Cerebral Activation. RELC Journal, Vol. 43, 2 (2012), 151--167.Google ScholarCross Ref
- Donna Teague and Raymond Lister. 2014. Longitudinal Think Aloud Study of a Novice Programmer. In Proceedings of the Sixteenth Australasian Computing Education Conference - Volume 148 (ACE '14). Australian Computer Society, Inc, Darlinghurst, Australia, Australia, 41--50. http://dl.acm.org/citation.cfm?id=2667490.2667495 Google ScholarDigital Library
- Errol Thompson, Andrew Luxton-Reilly, Jacqueline L. Whalley, Minjie Hu, and Phil Robbins. 2008. Bloom's Taxonomy for CS Assessment. In Proceedings of the Tenth Conference on Australasian Computing Education - Volume 78 (ACE '08). Australian Computer Society, Inc., Darlinghurst, Australia, Australia, 155--161. http://dl.acm.org/citation.cfm?id=1379249.1379265 Google ScholarDigital Library
- Jacqueline Whalley and Nadia Kasto. 2014. A qualitative think-aloud study of novice programmers' code writing strategies. Proceedings of the 2014 conference on Innovation & technology in computer science education - ITiCSE '14 (2014). Google ScholarDigital Library
- Jacqueline L. Whalley, Raymond Lister, Errol Thompson, Tony Clear, Phil Robbins, P. K. Ajith Kumar, and Christine Prasad. 2006. An Australasian Study of Reading and Comprehension Skills in Novice Programmers, Using the Bloom and SOLO Taxonomies. In Proceedings of the 8th Australasian Conference on Computing Education - Volume 52 (ACE '06). Australian Computer Society, Inc., Darlinghurst, Australia, Australia, 243--252. http://dl.acm.org/citation.cfm?id=1151869.1151901 Google ScholarDigital Library
Index Terms
- The Effect of Reading Code Aloud on Comprehension: An Empirical Study with School Students
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