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Teachers’ Views and Experiences on Teaching Second and Subsequent Programming Languages

Published: 17 August 2021 Publication History

Abstract

Motivation More and more high schools are teaching programming, and in many cases, teachers teach multiple programming languages to the same group of students. Objectives The goal of this paper is to explore the views of high-school teachers on second and subsequent programming languages, including their motivation for teaching multiple languages, their struggles, and their use of transfer strategies when they teach their second or third programming language. Method The study consists of semi-structured interviews with 23 high-school teachers in two European countries. Results Our findings indicate that school pupils face the same issues as university students when moving from first to subsequent languages. Furthermore, the teachers’ attitudes towards second language learning are highly variable, both positive and negative, with some supportive teaching strategies used, but many less helpful ones in evidence too. Discussion Our findings suggest that the value of second language learning needs to be highlighted in teacher professional development materials more strongly and that teachers might need more support in implementing transfer strategies.

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References

[1]
Amjad Altadmri and Neil Brown. 2015. 37 Million Compilations: Investigating Novice Programming Mistakes in Large-Scale Student Data. SIGCSE 2015 - Proceedings of the 46th ACM Technical Symposium on Computer Science Education (2015), 522–527. https://doi.org/10.1145/2676723.2677258
[2]
Michal Armoni, Orni Meerbaum-Salant, and Mordechai Ben-Ari. 2015. From scratch to “real” programming. ACM Transactions on Computing Education (TOCE) 14, 4 (2015), 1–15.
[3]
Deborah J. Armstrong and Bill C. Hardgrave. 2007. Understanding Mindshift Learning: The Transition to Object-Oriented Development. MIS Quarterly 31, 3 (2007), 453–474. http://www.jstor.org/stable/25148803
[4]
Katerine Bielaczyc, Peter L. Pirolli, and Ann L. Brown. 1995. Training in Self-Explanation and Self-Regulation Strategies: Investigating the Effects of Knowledge Acquisition Activities on Problem Solving. Cognition and instruction 13, 2 (1995), 221–252.
[5]
John B. Biggs and Kevin F. Collis. 1982. Evaluation the Quality of Learning: The SOLO Taxonomy (Structure of the Observed Learning Outcome). Academic Press.
[6]
Neil CC Brown, Sue Sentance, Tom Crick, and Simon Humphreys. 2014. Restart: The resurgence of computer science in UK schools. ACM Transactions on Computing Education (TOCE) 14, 2 (2014), 1–22.
[7]
Victoria Clarke, Virginia Braun, and Nikki Hayfield. 2015. Thematic analysis. Qualitative psychology: A practical guide to research methods (2015), 222–248.
[8]
Wanda Dann, Dennis Cosgrove, Don Slater, Dave Culyba, and Steve Cooper. 2012. Mediated transfer: Alice 3 to java. In Proceedings of the 43rd ACM technical symposium on Computer Science Education. 141–146.
[9]
Stephen Davies, Jennifer A Polack-Wahl, and Karen Anewalt. 2011. A snapshot of current practices in teaching the introductory programming sequence. In Proceedings of the 42nd ACM technical symposium on Computer science education. 625–630.
[10]
Paul Denny, Andrew Luxton-Reilly, Ewan Tempero, and Jacob Hendrickx. 2011. Understanding the syntax barrier for novices. In Proceedings of the 16th annual joint conference on Innovation and technology in computer science education. ACM, 208–212. https://doi.org/10.1145/1999747.1999807
[11]
Mary L. Gick and Keith J. Holyoak. 1983. Schema Induction and Analogical Transfer. Cognitive psychology 15, 1 (1983), 1–38.
[12]
Olivier Goletti, Kim Mens, and Felienne Hermans. 2021. Tutors’ Experiences in Using Explicit Strategies in a Problem-Based Learning Introductory Programming Course. In Proceedings of the 2021 ACM Conference on Innovation and Technology in Computer Science Education (ITiCSE ’21). ACM Press, Virtual Event, Germany. https://doi.org/10.1145/3430665.3456348 (to appear).
[13]
Michael Homer and James Noble. 2014. Combining Tiled and Textual Views of Code. In Proceedings of the Second IEEE Working Conference on Software Visualization. IEEE Computer Society, 1–10. https://doi.org/10.1109/VISSOFT.2014.11
[14]
Cruz Izu, Amali Weerasinghe, and Cheryl Pope. 2016. A Study of Code Design Skills in Novice Programmers Using the SOLO Taxonomy. In Proceedings of the 2016 ACM Conference on International Computing Education Research. ACM, Melbourne VIC Australia, 251–259. https://doi.org/10.1145/2960310.2960324
[15]
Nan Jiang. 2000. Lexical Representation and Development in a Second Language. Applied Linguistics 21 (03 2000). https://doi.org/10.1093/applin/21.1.47
[16]
KN King. 1992. The evolution of the programming languages course. In Proceedings of the twenty-third SIGCSE technical symposium on Computer science education. 213–219.
[17]
David Klahr and Sharon McCoy Carver. 1988. Cognitive Objectives in a LOGO Debugging Curriculum: Instruction, Learning, and Transfer. Cognitive Psychology 20, 3 (July 1988), 362–404. https://doi.org/10.1016/0010-0285(88)90004-7
[18]
Michael Kölling, Neil CC Brown, and Amjad Altadmri. 2015. Frame-based editing: Easing the transition from blocks to text-based programming. In Proceedings of the Workshop in Primary and Secondary Computing Education. ACM, 29–38.
[19]
Divna Krpan, Saša Mladenović, and Goran Zaharija. 2017. Mediated transfer from visual to high-level programming language. In 2017 40th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO). IEEE, 800–805.
[20]
David J Malan and Henry H Leitner. 2007. Scratch for budding computer scientists. ACM Sigcse Bulletin 39, 1 (2007), 223–227.
[21]
Lauren E. Margulieux, Mark Guzdial, and Richard Catrambone. 2012. Subgoal-Labeled Instructional Material Improves Performance and Transfer in Learning to Develop Mobile Applications. In Proceedings of the Ninth Annual International Conference on International Computing Education Research(ICER ’12). Association for Computing Machinery, New York, NY, USA, 71–78. https://doi.org/10.1145/2361276.2361291
[22]
Cindy Marling and David Juedes. 2016. CS0 for Computer Science Majors at Ohio University. In Proceedings of the 47th ACM Technical Symposium on Computing Science Education. 138–143.
[23]
Monika Mladenović, Žana Žanko, and Andrina Granić. 2021. Mediated transfer: From text to blocks and back. International Journal of Child-Computer Interaction (2021), 100279.
[24]
I. T. Chan Mow. 2008. Issues and Difficulties in Teaching Novice Computer Programming. In Innovative Techniques in Instruction Technology, E-learning, E-assessment, and Education.
[25]
Dale Parsons and Patricia Haden. 2007. Programming osmosis: Knowledge transfer from imperative to visual programming environments. In Procedings of The Twentieth Annual NACCQ Conference. 209–215.
[26]
Elizabeth Patitsas, Michelle Craig, and Steve Easterbrook. 2013. Comparing and Contrasting Different Algorithms Leads to Increased Student Learning. In Proceedings of the Ninth Annual International ACM Conference on International Computing Education Research - ICER ’13. ACM Press, San Diego, San California, USA, 145. https://doi.org/10.1145/2493394.2493409
[27]
David Perkins and Fay Martin. 1985. Fragile Knowledge and Neglected Strategies in Novice Programmers. IR85-22.(1985).
[28]
David N Perkins, Gavriel Salomon, 1992. Transfer of learning. International encyclopedia of education 2 (1992), 6452–6457.
[29]
Martinha Piteira and Carlos Costa. 2013. Learning Computer Programming: Study of Difficulties in Learning Programming. In Proceedings of the 2013 International Conference on Information Systems and Design of Communication(ISDOC ’13). Association for Computing Machinery, New York, NY, USA, 75–80. https://doi.org/10.1145/2503859.2503871 event-place: Lisboa, Portugal.
[30]
Kris Powers, Stacey Ecott, and Leanne M Hirshfield. 2007. Through the looking glass: teaching CS0 with Alice. In Proceedings of the 38th SIGCSE technical symposium on Computer science education. 213–217.
[31]
Igor Moreno Santos, Matthias Hauswirth, and Nathaniel Nystrom. 2019. Experiences in bridging from functional to object-oriented programming. In Proceedings of the 2019 ACM SIGPLAN Symposium on SPLASH-E. 36–40.
[32]
Jean Scholtz. 1996. Adaptation of programming plans in transfer between programming languages: a developmental approach. In Empirical studies of programmers: Sixth workshop. Intellect Books, 233.
[33]
Jean Scholtz and Susan Wiedenbeck. 1990. Learning second and subsequent programming languages: A problem of transfer. International Journal of Human-Computer Interaction 2, 1(1990), 51–72.
[34]
Jean Scholtz and Susan Wiedenbeck. 1991. Learning a new programming language: a model of the planning process. In Proceedings of the Twenty-Fourth Annual Hawaii International Conference on System Sciences, Vol. 2. IEEE, 3–12.
[35]
Jean Scholtz and Susan Wiedenbeck. 1993. Using unfamiliar programming languages: the effects on expertise. Interacting with Computers 5, 1 (1993), 13–30.
[36]
Linda Seiter. 2015. Using SOLO to Classify the Programming Responses of Primary Grade Students. In Proceedings of the 46th ACM Technical Symposium on Computer Science Education. ACM, Kansas City Missouri USA, 540–545. https://doi.org/10.1145/2676723.2677244
[37]
Andreas Stefik and Susanna Siebert. 2013. An Empirical Investigation into Programming Language Syntax. Trans. Comput. Educ. 13, 4 (Nov. 2013), 19:1–19:40. https://doi.org/10.1145/2534973
[38]
Andreas Stefik and Susanna Siebert. 2013. An empirical investigation into programming language syntax. ACM Transactions on Computing Education (TOCE) 13, 4 (2013), 1–40.
[39]
Nour Tabet, Huda Gedawy, Hanan Alshikhabobakr, and Saquib Razak. 2016. From alice to python. Introducing text-based programming in middle schools. In Proceedings of the 2016 ACM Conference on Innovation and Technology in Computer Science Education. 124–129.
[40]
E. L. Thorndike and Robert S. Woodworth. 1901. The Influence of Improvement in One Mental Function upon the Efficiency of Other Functions.(I).Psychological review 8, 3 (1901), 247.
[41]
Ethel Tshukudu and Quintin Cutts. 2020. Semantic Transfer in Programming Languages: Exploratory Study of Relative Novices. In Proceedings of the 2020 ACM Conference on Innovation and Technology in Computer Science Education. 307–313.
[42]
Ethel Tshukudu and Quintin Cutts. 2020. Understanding Conceptual Transfer for Students Learning New Programming Languages. In Proceedings of the 2020 ACM Conference on International Computing Education Research. 227–237.
[43]
Ethel Tshukudu and Siri Annethe Moe Jensen. 2020. The Role of Explicit Instruction on Students Learning their Second Programming Language. In United Kingdom & Ireland Computing Education Research conference.10–16.
[44]
TUG 2016. K–12 Computer Science Framework. Retrieved January 20, 2021 from http://www.k12cs.org
[45]
Karen P Walker and Stephen R Schach. 1996. Obstacles to learning a second programming language: An empirical study. Computer Science Education 7, 1 (1996), 1–20.
[46]
David Weintrop and Uri Wilensky. 2018. How block-based, text-based, and hybrid block/text modalities shape novice programming practices. International Journal of Child-Computer Interaction 17 (2018), 83–92. https://doi.org/10.1016/j.ijcci.2018.04.005
[47]
David Weintrop and Uri Wilensky. 2019. Transitioning from introductory block-based and text-based environments to professional programming languages in high school computer science classrooms. Computers & Education 142 (2019), 103646.
[48]
Susan Wiedenbeck. 1993. An analysis of novice programmers learning a second language. In Empirical studies of programmers: Fifth Workshop: Papers presented at the Fifth Workshop on empirical studies of programmers, December 3-5, 1993, Palo Alto, CA. Intellect Books, 187.
[49]
Ursula Wolz, Henry H Leitner, David J Malan, and John Maloney. 2009. Starting with scratch in CS 1. In Proceedings of the 40th ACM technical symposium on Computer science education. 2–3.
[50]
Quanfeng Wu and John R Anderson. 1990. Problem-solving transfer among programming languages. Technical Report. CARNEGIE-MELLON UNIV PITTSBURGH PA ARTIFICIAL INTELLIGENCE AND PSYCHOLOGY ….

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cover image ACM Conferences
ICER 2021: Proceedings of the 17th ACM Conference on International Computing Education Research
August 2021
451 pages
ISBN:9781450383264
DOI:10.1145/3446871
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 17 August 2021

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Author Tags

  1. K12
  2. code comprehension
  3. conceptual development
  4. programming languages
  5. semantics
  6. syntax
  7. transfer

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  • (2024)Meet MicroCode: a Live and Portable Programming Tool for the BBC micro:bitProceedings of the 23rd Annual ACM Interaction Design and Children Conference10.1145/3628516.3656995(355-370)Online publication date: 17-Jun-2024
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