Learning basic concept of computer programming with path-finding task in ar and its properties

This paper designs and develops a computer programming learning system for total beginners and those who have no programming experience. The traditional computer programming learning systems require prior knowledge about variables, their types, operators for arithmetic calculations and relational ca...

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Published in:	Education and information technologies Vol. 27; no. 1; pp. 719 - 742
Main Authors:	Ishihara, Makio, Rattanachinalai, Pongpun
Format:	Journal Article
Language:	English
Published:	New York Springer US 01.01.2022 Springer Springer Nature B.V
Subjects:	Artificial Intelligence Augmented reality Codes Coding Computer Appl. in Social and Behavioral Sciences Computer programming Computer Science Computer Science Education Computers Computers and Education Difficulty Level Education Educational Technology Information Systems Applications (incl.Internet) Learner Engagement Novices Prior Learning Programming Scores Sequential Learning Special Issue on: The frontiers of augmented and mixed reality in all levels of education Student Motivation Task Analysis User interface User Interfaces and Human Computer Interaction Path-finding task Computer programming Education Tangible user interface Augmented reality
ISSN:	1360-2357, 1573-7608
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Abstract	This paper designs and develops a computer programming learning system for total beginners and those who have no programming experience. The traditional computer programming learning systems require prior knowledge about variables, their types, operators for arithmetic calculations and relational calculations etc., for adopting a wide range of representation of program codes, leading to the burden to them. The proposed system focuses on learning the three basic flows of control: sequential, conditional and iterative controls, for not requiring the prior knowledge, and exploits a path-finding task for confining representation of program codes to a specific task, which is a navigation task where students are asked to organize a sequence of orders for an avatar to move from a given start to a given end on a Manhattan grid map. The previous work employs the path-finding task to foster understanding of the sequence of orders by encouraging students to perform self-tracing process while our proposed system employs it to include that property of understanding for the three basic flows of control which are not covered in the previous work. To add high interactivity and tangibility for student motivation and engagement to learning, the proposed system also employs AR capability. An experiment on feasibility of our system for education is conducted and the results show that our system has the potential for improving students’ understanding of how to make program codes by decrease of the ratio of program codes’ length made by beginners to experts, which is from 2.186 to 1.267, regardless of AR capability such that the ratio decreased from 2.481 to 1.346 without AR capability and it was from 1.974 to 1.206 with it. The results also show that our system significantly leverages their motivation of learning by increase of beginners’ score from 5.00 without AR capability to 6.67 with it for interest and it is from 5.67 to 7.00 for amusement, and even if sacrificing a wide range of representation of program codes that the traditional systems take, a certain stress is significantly given on spending time thinking and building up a program code in proportion to its difficulty and complexity.
AbstractList	This paper designs and develops a computer programming learning system for total beginners and those who have no programming experience. The traditional computer programming learning systems require prior knowledge about variables, their types, operators for arithmetic calculations and relational calculations etc., for adopting a wide range of representation of program codes, leading to the burden to them. The proposed system focuses on learning the three basic flows of control: sequential, conditional and iterative controls, for not requiring the prior knowledge, and exploits a path-finding task for confining representation of program codes to a specific task, which is a navigation task where students are asked to organize a sequence of orders for an avatar to move from a given start to a given end on a Manhattan grid map. The previous work employs the path-finding task to foster understanding of the sequence of orders by encouraging students to perform self-tracing process while our proposed system employs it to include that property of understanding for the three basic flows of control which are not covered in the previous work. To add high interactivity and tangibility for student motivation and engagement to learning, the proposed system also employs AR capability. An experiment on feasibility of our system for education is conducted and the results show that our system has the potential for improving students’ understanding of how to make program codes by decrease of the ratio of program codes’ length made by beginners to experts, which is from 2.186 to 1.267, regardless of AR capability such that the ratio decreased from 2.481 to 1.346 without AR capability and it was from 1.974 to 1.206 with it. The results also show that our system significantly leverages their motivation of learning by increase of beginners’ score from 5.00 without AR capability to 6.67 with it for interest and it is from 5.67 to 7.00 for amusement, and even if sacrificing a wide range of representation of program codes that the traditional systems take, a certain stress is significantly given on spending time thinking and building up a program code in proportion to its difficulty and complexity.
Audience	Academic
Author	Ishihara, Makio Rattanachinalai, Pongpun
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References_xml	– reference: Hattori, K., & Hirai, T. (2019). An intuitive and educational programming tool with tangible blocks and ar. In ACM SIGGRAPH 2019 Posters, SIGGRAPH ’19. Association for computing machinery, New York, NY, USA.https://doi.org/10.1145/3306214.3338570. – reference: Horn, M.S., Solovey, E.T., Crouser, R.J., & Jacob, R.J. (2009). Comparing the use of tangible and graphical programming languages for informal science education. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, CHI09, pp 975–984, Association for Computing Machinery, New York, NY, USA.https://doi.org/10.1145/1518701.1518851. – reference: NishidaTHaradaANakamuraRMiyamotoYMatsuuraTImplementation and evaluation of pen: The programming environment for novicesIPSJ Journal200748827362747https://ci.nii.ac.jp/naid/110006386503/en/ – reference: Ruhe, G., Bagert, D.J., Edwards, H., Ryan, M., Mead, N.R., & Saiedian, H. (2000). Shortages of qualified software engineering faculty and practitioners (panel session): Challenges in breaking the cycle. In Proceedings of the 22nd international conference on software engineering, ICSE00, pp 665–668, Association for Computing Machinery, New York, NY, USA.https://doi.org/10.1145/337180.337504. – reference: Chandramouli, M, Zahraee, M, & Winer, C. (2014). A fun-learning approach to programming: an adaptive virtual reality (vr) platform to teach programming to engineering students. In IEEE International conference on electro/information technology, pp 581–586. – reference: WuHKLeeSWYChangHYLiangJCCurrent status, opportunities and challenges of augmented reality in educationComputers and Education201362414910.1016/j.compedu.2012.10.024https://doi.org/10.1016/j.compedu.2012.10.024. http://www.sciencedirect.com/science/article/pii/S0360131512002527 – reference: Papert, S. (1972). On making a theorem for a child. In Proceedings of the ACM annual conference - Volume 1, ACM ’72, pp 345–349. Association for Computing Machinery, New York, NY, USA.https://doi.org/10.1145/800193.569942. – reference: MaloneyJResnickMRuskNSilvermanBEastmondEThe scratch programming language and environmentACM Trans. Comput. Educ20101041510.1145/1868358.1868363 – reference: Kim, J., Agarwal, S., Marotta, K., Li, S., Leo, J., & Chau, D.H. (2019). Mixed reality for learning programming. In Proceedings of the 18th ACM international conference on interaction design and children, IDC ’19, pp 574–579, Association for Computing Machinery, New York, NY, USA.https://doi.org/10.1145/3311927.3325335. – reference: Sakamoto, R., & Ohshima, T. (2019). Code weaver: a tangible programming learning tool with mixed reality interface. In SIGGRAPH Asia 2019 posters, SA’19. Association for computing machinery, New York, NY, USA.https://doi.org/10.1145/3355056.3364561. – reference: Dahl, O.J., Dijkstra, E.W., & Hoare, C.A.R. (eds.) (1972). Structured Programming. Academic Press Ltd.,GBR. – reference: Teng, C., & Chen, J. (2012). An augmented reality environment for learning opengl programming. In 2012 9Th international conference on ubiquitous intelligence and computing and 9th international conference on autonomic and trusted computing, pp 996–1001. – reference: Gomes, A., & Mendes, A. (2007). Learning to program - difficulties and solutions. 283–287. – volume: 48 start-page: 2736 issue: 8 year: 2007 ident: 10416_CR8 publication-title: IPSJ Journal – ident: 10416_CR10 doi: 10.1145/337180.337504 – ident: 10416_CR6 doi: 10.1145/3311927.3325335 – volume: 62 start-page: 41 year: 2013 ident: 10416_CR13 publication-title: Computers and Education doi: 10.1016/j.compedu.2012.10.024 – ident: 10416_CR5 doi: 10.1145/1518701.1518851 – ident: 10416_CR11 doi: 10.1145/3355056.3364561 – ident: 10416_CR12 doi: 10.1109/UIC-ATC.2012.57 – volume: 10 start-page: 15 issue: 4 year: 2010 ident: 10416_CR7 publication-title: ACM Trans. Comput. Educ doi: 10.1145/1868358.1868363 – ident: 10416_CR1 doi: 10.1109/EIT.2014.6871829 – ident: 10416_CR4 doi: 10.1145/3306214.3338570 – ident: 10416_CR3 – ident: 10416_CR2 – ident: 10416_CR9 doi: 10.1145/800193.569942
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SubjectTerms	Artificial Intelligence Augmented reality Codes Coding Computer Appl. in Social and Behavioral Sciences Computer programming Computer Science Computer Science Education Computers Computers and Education Difficulty Level Education Educational Technology Information Systems Applications (incl.Internet) Learner Engagement Novices Prior Learning Programming Scores Sequential Learning Special Issue on: The frontiers of augmented and mixed reality in all levels of education Student Motivation Task Analysis User interface User Interfaces and Human Computer Interaction
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Title	Learning basic concept of computer programming with path-finding task in ar and its properties
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