Developing rural Chinese children’s computational thinking through ­game-based learning and parental involvement

References

• Argasinski, K., & Broom, M. (2013). Ecological theatre and the evolutionary game: How environmental and demographic factors determine payoffs in evolutionary games. Journal of Mathematical Biology, 67(4), 935–962. https://doi.org/10.1007/s00285-012-0573-2
   PubMed Web of Science ®Google Scholar
• Ascher, C. (1988). Improving the home-school connection for low-income urban parents. Urban Review, 20(1), 109–123.
   Google Scholar
• Basu, S., Rutstein, D. W., Xu, Y., Wang, H., & Shear, L. (2021). A principled approach to designing computational thinking concepts and practices assessments for upper elementary grades. Computer Science Education, 31(2), 169–198. https://doi.org/10.1080/08993408.2020.1866939
   Web of Science ®Google Scholar
• Bers, M. U., González-González, C., & Armas-Torres, M. B. (2019). Coding as a playground: Promoting positive learning experiences in childhood classrooms. Computers in Education, 138(1), 130–145. https://doi.org/10.1016/j.compedu.2019.04.013
   Web of Science ®Google Scholar
• Bocconi, S., Chioccariello, A., Kampylis, P., Dagienė, V., Wastiau, P., Engelhardt, K., Earp, J., Horvath, M. A., Jasutė, E., Malagoli, C., Masiulionytė-Dagienė, V., & Stupurienė, G. (2022). Reviewing computational thinking in compulsory education: State of play and practices from computing education. Publications Office of the European.
   Google Scholar
• Brackmann, C. P., Román-González, M., Robles, G., Moreno-León, J., Casali, A., & Barone, D. (2017). Development of computational thinking skills through unplugged activities in primary school. In Proceedings of the 12th Workshop on Primary and Secondary Computing Education (pp. 65–72). https://doi.org/10.1145/3137065.3137069
   Google Scholar
• Brummelman, E., Crocker, J., & Bushman, B. J. (2016). The praise paradox: When and why praise backfires in children with low self‐esteem. Child Development Perspectives, 10(2), 111–115. https://doi.org/10.1111/cdep.12171
   Web of Science ®Google Scholar
• Catala, A., Sylla, C. M., & Ozgur, A. G. (2021). Smart Toys++: Exploiting the social connectedness for playing and learning. Interaction Design and Children, 679–681. https://doi.org/10.1145/3459990.3460519
   Google Scholar
• Chiazzese, G., Arrigo, M., Chifari, A., Lonati, V., & Tosto, C. (2019). Educational robotics in primary school: Measuring the development of computational thinking skills with the bebras tasks. Informatics, 6(4), 43. https://doi.org/10.3390/informatics6040043
   Web of Science ®Google Scholar
• Cheairs, S. E. (2015). Perceptions of parental involvement among rural parents, teachers, and administrators [Doctoral dissertation, Walden University].
   Google Scholar
• Ching, Y. H., Hsu, Y. C., & Baldwin, S. (2018). Developing computational thinking with educational technologies for young learners. TechTrends, 62(6), 563–573. https://doi.org/10.1007/s11528-018-0292-7
   Web of Science ®Google Scholar
• Chevalier, M., Giang, C., Piatti, A., & Mondada, F. (2020). Fostering computational thinking through educational robotics: A model for creative computational problem solving. International Journal of STEM Education, 7(1), 1–18. https://doi.org/10.1186/s40594-020-00238-z
   Web of Science ®Google Scholar
• Chou, P. N. (2020). Using ScratchJr to foster young children’s computational thinking competence: A case study in a third-grade computer class. Journal of Educational Computing Research, 58(3), 570–595. https://doi.org/10.1177/0735633119872908
   Web of Science ®Google Scholar
• Czerkawski, B. C., & Lyman, E. W. (2015). Exploring issues about computational thinking in higher education. Techtrends Tech Trends, 59, 57–65. https://doi.org/10.1007/s11528-015-0840-3
   Google Scholar
• Denning, P. J., & Tedre, M. (2019). Computational thinking. Mit Press.
   Google Scholar
• Desforges, C., & Abouchaar, A. (2003). The impact of parental involvement, parental support and family education on pupil achievement and adjustment. Research Report 433. Department for Education and Skills.
   Google Scholar
• Deschryver, M. D., & Yadav, A. (2015). Creative and computational thinking in the context of new literacies: Working with teachers to scaffold complex technology mediated approaches to teaching and learning. Journal of Technology and Teacher Education, 23(3), 411–431.
   Google Scholar
• Dietz, G., Le, J. K., Tamer, N., Han, J., Gweon, H., Murnane, E. L., & Landay, J. A. (2021). StoryCoder: Teaching computational thinking concepts through storytelling in a voice-guided app for children. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems (pp. 1–15). https://doi.org/10.1145/3411764.3445039
   Google Scholar
• Edwards, R., & Alldred, P. (2000). A typology of parental involvement in education centring on children and young people: Negotiating familialisation, institutionalisation and individualisation. British Journal of Sociology of Education, 21(3), 435–455. https://doi.org/10.1080/713655358
   Web of Science ®Google Scholar
• Epstein, J. L., & Becker, H. J. (1982). Teachers’ reported practices of parent involvement: Problems and possibilities. The Elementary School Journal, 83(2), 103–113.
   Web of Science ®Google Scholar
• Epstein, J. L., & Dauber, S. L. (1991). School programs and teacher practices of parent involvement in inner-city elementary and middle schools. The Elementary School Journal, 91(3), 289–230. https://doi.org/10.1086/461656
   Web of Science ®Google Scholar
• European Council. (2006). Recommendation of the European Parliament and the Council on key competencies for lifelong learning. Official Journal of the European Union, March 2006, 10–18. Retrieved March 17, 2021, from http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2006:394:0010:0018:en:PDF
   Google Scholar
• Fantuzzo, J., Tighe, E., & Childs, S. (2000). Family involvement questionnaire: A multivariate assessment of family participation in early childhood education. Journal of Educational Psychology, 92(2), 367–376. https://doi.org/10.1037/0022-0663.92.2.367
   Web of Science ®Google Scholar
• Feldhausen, R., Weese, J. L., & Bean, N. H. (2018). Increasing student self-efficacy in computational thinking via STEM outreach programs. In Proceedings of the 49th ACM Technical Symposium on Computer Science Education (pp. 302–307). https://doi.org/10.1145/3159450.3159593
   Google Scholar
• Fowler, A., Fristce, T., & MacLauren, M. (2012). Kodu Game Lab: A programming environment. The Computer Games Journal, 1(1), 17–28. https://doi.org/10.1007/BF03392325
   Google Scholar
• Govind, M., Relkin, E., & Bers, M. U. (2020). Engaging children and parents to code together using the ScratchJr App. Visitor Studies, 23(1), 46–65. https://doi.org/10.1080/10645578.2020.1732184
   Web of Science ®Google Scholar
• Griffith, S. F., & Arnold, D. H. (2019). Home learning in the new mobile age: Parent–child interactions during joint play with educational apps in the US. Journal of Children and Media, 13(1), 1–19. https://doi.org/10.1080/17482798.2018.1489866
   Web of Science ®Google Scholar
• Gregg, K., Rugg, M., & Stoneman, Z. (2012). Building on the hopes and dreams of Latino families with young children: Findings from family member focus groups. Early Childhood Education, 40, 87–96. https://doi.org/10.1007/s10643-011-0498-1
   Google Scholar
• Harris, C. (2018). Computational Thinking Unplugged: Comparing the Impact on Confidence and Competence from Analog and Digital Resources in Computer Science Professional Development for Elementary Teachers: A Education doctoral Dissertation in Executive Leadership. Library in St. John Fisher College (Paper 374). Retrieved December 20, 2021, from https://fisherpub.sjfc.edu/education_etd/374.
   Google Scholar
• Henderson, A., & Berla, N. (1994). A new generation of evidence: The family is critical to student achievement. National Committee for Citizens in Education.
   Google Scholar
• Herbert, C. W. (2010). An introduction to programming using Alice 2. Course Technology Press.
   Google Scholar
• Hooshyar, D., Pedaste, M., Yang, Y., Malva, L., Hwang, G. J., Wang, M., Lim, H., & Delev, D. (2021). From gaming to computational thinking: An adaptive educational computer game-based learning approach. Journal of Educational Computing Research, 59(3), 383–409. https://doi.org/10.1177/0735633120965919
   Web of Science ®Google Scholar
• Hutchins, N. M., Biswas, G., Maróti, M., Lédeczi, Á., Grover, S., Wolf, R., Pilner Blair, K., Chin, D., Conlin, L., Basu, S., & McElhaney, K. (2020). C2STEM: A system for synergistic learning of physics and computational thinking. Journal of Science Education and Technology, 29(1), 83–100. https://doi.org/10.1007/s10956-019-09804-9
   Web of Science ®Google Scholar
• IQTE CASS. (2021). Survey and analysis report on digital literacy in rural China under the background of rural revitalization strategy. Retrieved October 20, 2021, from http://iqte.cssn.cn/yjjg/fstyjzx/xxhyjzx/xsdt/202103/P020210311318247184884.pdf
   Google Scholar
• Jeon, I., & Song, K. S. (2019). The Effect of learning analytics system towards learner’s computational thinking capabilities. In Proceedings of the 2019 11th International Conference on Computer and Automation Engineering (pp. 12–16.). https://doi.org/10.1145/3313991.3314017
   Google Scholar
• Jeynes, W. H. (2003). A meta-analysis: The effects of parental involvement on minority children’s academic achievement. Education and Urban Society, 35, 202–218.
   Web of Science ®Google Scholar
• Jeynes, W. H. (2005). A meta-analysis of the relation of parental involvement to urban elementary school student academic achievement. Urban Education, 40, 237–269. https://doi.org/10.1177/0042085905274540
   Web of Science ®Google Scholar
• Jeynes, W. H. (2007). A meta analysis the relationship between parental involvement and urban secondary school student academic achievement. Urban Education, 42(1), 82–110.
   Web of Science ®Google Scholar
• Kale, U., Akcaoglu, M., Cullen, T., & Goh, D. (2018). Contextual factors influencing access to teaching computational thinking. Computers in the Schools, 35(2), 69–87. https://doi.org/10.1080/07380569.2018.1462630
   Web of Science ®Google Scholar
• Kalelioglu, F., Gülbahar, Y., & Kukul, V. (2016). A framework for computational thinking based on a systematic research review. Baltic Journal of Modern Computing, 4(3), 583–596.
   Web of Science ®Google Scholar
• K-12 Computer Science Framework. (2016). Retrieved November 21, 2021, from http://www.k12cs.org
   Google Scholar
• Kjällander, S., Mannila, L., Åkerfeldt, A., & Heintz, F. (2021). Elementary students’ first approach to computational thinking and programming. Education Sciences, 11(2), 80. https://doi.org/10.3390/educsci11020080
   Web of Science ®Google Scholar
• Kuo, W. C., & Hsu, T. C. (2020). Learning computational thinking without a computer: How computational participation happens in a computational thinking board game. The Asia-Pacific Education Researcher, 29, 67–83. https://doi.org/10.1007/s40299-019-00479-9
   Web of Science ®Google Scholar
• Kong, S. C., Lai, M., & Sun, D. (2020). Teacher development in computational thinking: Design and learning outcomes of programming concepts, practices and pedagogy. Computers in Education, 151, 103872. https://doi.org/10.1016/j.compedu.2020.103872
   Web of Science ®Google Scholar
• Kong, S. C., Chiu, M. M., & Lai, M. (2018). A study of primary school students’ interest, collaboration attitude, and programming empowerment in computational thinking education. Computers & Education, 127, 178–189. https://doi.org/10.1016/j.compedu.2018.08.026
   Web of Science ®Google Scholar
• Kong, S. C., & Wang, Y. Q. (2021). Item response analysis of computational thinking practices: Test characteristics and students’ learning abilities in visual programming contexts. Computers in Human Behavior, 122, 106836. https://doi.org/10.1016/j.chb.2021.106836
   Web of Science ®Google Scholar
• Koslowski, J. (1980). Density dependence, the logistic equation, and r-and K-selection: A critique and an alternative approach. Evolutionary Theory, 5(2), 89–101.
   Google Scholar
• Lee, T. Y., Mauriello, M. L., Ahn, J., & Bederson, B. B. (2014). CTArcade: Computational thinking with games in school age children. International Journal of Child-Computer Interaction, 2(1), 26–33. https://doi.org/10.1016/j.ijcci.2014.06.003
   Google Scholar
• Leonard, J., Mitchell, M., Barnes-Johnson, J., Unertl, A., Outka-Hill, J., Robinson, R., & Hester-Croff, C. (2018). Preparing teachers to engage rural students in computational thinking through robotics, game design, and culturally responsive teaching. Journal of Teacher Education, 69(4), 386–407. https://doi.org/10.1177/0022487117732317
   Web of Science ®Google Scholar
• Malliarakis, C., Satratzemi, M., & Xinogalos, S. (2016). CMX: The effects of an educational MMORPG on learning and teaching computer programming. IEEE Transactions on Learning Technologies, 10(2), 219–235. https://doi.org/10.1109/TLT.2016.2556666
   Web of Science ®Google Scholar
• Mason, S. L., & Rich, P. J. (2020). Development and analysis of the elementary student coding attitudes survey. Computers & Education, 153, 103898. https://doi.org/10.1016/j.compedu.2020.103898
   Web of Science ®Google Scholar
• McKight, P. E., & Najab, J. (2010). Kruskal‐wallis test. The Corsini Encyclopedia of Psychology, vol. 10, 1–10.
   Google Scholar
• Ministry of Education of the People’s Republic of China. (2020 May 13). Notice of the Ministry of Education on printing and distributing the curriculum standards for general high school curriculum programs and subjects such as language (revised in the 2017 edition and 2020). Retrieved October 7, 2021, from http://www.moe.gov.cn/srcsite/A26/s8001/202006/t20200603_462199.html
   Google Scholar
• National Research Council. (2012). A framework for K-12 science education: Practices, crosscutting concepts, and core ideas. The National Academies Press.
   Google Scholar
• Nieminen, P., & Kaur, J. (2019). Reporting of data analysis methods in psychiatric journals: Trends from 1996 to 2018. International Journal of Methods in Psychiatric Research, 28(3), e1784. https://doi.org/10.1002/mpr.1784
   PubMed Web of Science ®Google Scholar
• Olszewski-Kubilius, P. (2018). The role of the family in talent development. In Steven I. Pfeiffer (Ed), Handbook of giftedness in children (pp. 129–147). Springer. https://doi.org/10.1037/0000038-030
   Google Scholar
• Papastergiou, M. (2009). Digital game-based learning in high school computer science education: Impact on educational effectiveness and student motivation. Computers & Education, 52(1), 1–12. https://doi.org/10.1016/j.compedu.2008.06.004
   Web of Science ®Google Scholar
• Papert, S. (1980). Mindstorms. Basic Books.
   Google Scholar
• Plass, J. L., Homer, B. D., & Kinzer, C. K. (2015). Foundations of game-based learning. Educational Psychologist, 50, 258–283. https://doi.org/10.1080/00461520.2015.1122533
   Web of Science ®Google Scholar
• Li, Y., & Ranieri, M. (2013). Educational and social correlates of the digital divide for rural and urban children: A study on primary school students in a provincial city of China. Computers and Education, 60, 197–209. https://doi.org/10.1016/j.compedu.2012.08.001
   Web of Science ®Google Scholar
• Relkin, E., Govind, M., Tsiang, J., & Bers, M. (2020). How parents support children’s informal learning experiences with robots. Journal of Research in STEM Education, 6(1), 39–51. https://doi.org/10.51355/jstem.2020.87
   Google Scholar
• Rich, P. J., Browning, S. F., Perkins, M., Shoop, T., Yoshikawa, E., & Belikov, O. M. (2019). Coding in K-8: International trends in teaching elementary/primary computing. TechTrends, 63(3), 311–329. https://doi.org/10.1007/s11528-018-0295-4
   Web of Science ®Google Scholar
• Richardson, S. A. (2009). Principal’s perceptions of parental involvement in the “big 8” urban districts of Ohio. Research in the Schools, 16(1), 1–12
   Google Scholar
• Román-González, M., Pérez-González, J. C., Moreno-León, J., & Robles, G. (2018). Can computational talent be detected? Predictive validity of the Computational Thinking Test. International Journal of Child-Computer Interaction, 18, 47–58. https://doi.org/10.1016/j.ijcci.2018.06.004
   Google Scholar
• Roman-Gonzalez, M., Prez-Gonzalez, J.-C., & Jimnez-Fernandez, C. (2017). Which cognitive abilities underlie computational thinking? Criterion validity of the Computational Thinking Test. Computers in Human Behavior, 72(72), 678–691. https://doi.org/10.1016/j.chb.2016.08.047
   Web of Science ®Google Scholar
• Sampson, W. A. (2002). Black student achievement: How much do family and school really matter? Scarecrow Press.
   Google Scholar
• Sanders, M. G., & Sheldon, S. B. (2009). Principals matter: A guide to school, family, and community partnerships. A SAGE Company.
   Google Scholar
• Sato, Y., Gosho, M., Nagashima, K., Takahashi, S., Ware, J. H., & Laird, N. M. (2017). Statistical methods in the journal—An update. New England Journal of Medicine, 376(11), 1086–1087. https://doi.org/10.1056/NEJMc1616211
   PubMed Web of Science ®Google Scholar
• Scott, C. L. (2015). The futures of learning 2: What kind of learning for the 21st century? UNESCO. Education Research and Foresight. [ERF Working Papers Series 14]
   Google Scholar
• Sheehan, K. J., Pila, S., Lauricella, A. R., & Wartella, E. A. (2019). Parent-child interaction and children’s learning from a coding application. Computers & Education, 140, 103601. https://doi.org/10.1016/j.compedu.2019.103601
   Web of Science ®Google Scholar
• Sheldon, S. B. (2009). In school, family, and community partnerships: Your handbook for action (3rd ed.). Corwin Press.
   Google Scholar
• Shute, V. J., Sun, C., & Asbell-Clarke, J. (2017). Demystifying computational thinking. Educational Research Review, 22, 142–158. https://doi.org/10.1016/j.edurev.2017.09.003
   Web of Science ®Google Scholar
• Druga, S., Ball, T., & Ko, A. (2022). How families design and program games: A qualitative analysis of a 4-week online in-home study. Interaction Design and Children, 237–252. https://doi.org/10.1145/3501712.3529724
   Google Scholar
• Tikva, C., & Tambouris, E. (2021). Mapping computational thinking through programming in K-12 education: A conceptual model based on a systematic literature review. Computers & Education, 162. https://doi.org/10.1016/j.compedu.2020.104083
   Web of Science ®Google Scholar
• Tsarava, K., Moeller, K., Pinkwart, N., Butz, M., Trautwein, U., & Ninaus, M. (2017). Training computational thinking: Game-based unplugged and plugged-in activities in primary school. In Pivec, M. et al (Eds.), European conference on games based learning (pp. 687–695) Academic Conferences International Limited.
   Google Scholar
• Turchi, T., Fogli, D., & Malizia, A. (2019). Fostering computational thinking through collaborative game-based learning. Multimedia Tools and Applications, 78(10), 13649–13673. https://doi.org/10.1007/s11042-019-7229-9
   Web of Science ®Google Scholar
• UNESCO. (2016). Enrollment by level of education. UNESCO Institute for Statistics. Retrieved October 15, 2021, from http://data.uis.unesco.org/Index.aspx
   Google Scholar
• UNESCO. (2021). UNESCO prepares teachers and learners for 21st century challenges. Retrieved October 15, 2021, from https://en.unesco.org/news/unesco-prepares-teachers-and-learners-21st-century-challenges
   Google Scholar
• United Nations, Department of Economic and Social Affairs, Population Division. (2015). World urbanization prospects: The 2014 revision. United Nations.
   Google Scholar
• Weintrop, D., Holbert, N., Horn, M. S., & Wilensky, U. (2016). Computational thinking in constructionist video games. International Journal of Game-Based Learning (IJGBL), 6(1), 1–17. https://doi.org/10.4018/IJGBL.2016010101
   Google Scholar
• Wing, J. M. (2006). Computational thinking. Communications of the ACM, 49(3), 33–35. https://doi.org/10.1145/1118178.1118215
   Web of Science ®Google Scholar
• Wing, J. (2011). Research notebook: Computational thinking—What and why. The Link Magazine, 6, 20–23.
   Google Scholar
• Zagal, J. P., Rick, J., & Hsi, I. (2006). Collaborative games: Lessons learned from board games. Simulation & Gaming, 37(1), 24–40. https://doi.org/10.1177/1046878105282279
   Google Scholar
• Zaibon, S. B., & Yunus, E. (2022). The effectiveness of game-based learning application integrated with computational thinking concept for improving student’s problem-solving skills. In Y. H. Sheikh, I. A. Rai, & A. D. Bakar (Eds.), e-infrastructure and e-services for developing countries. AFRICOMM 2021. Lecture notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering (Vol. 443), 429–442. Springer. https://doi.org/10.1007/978-3-031-06374-9_28
   Google Scholar
• Zhong, B., Zhu, F., & Xia, L. (2021). Is there a digital divide between urban students and migrant students in China? SAGE Open, 11(2) https://doi.org/10.1177/21582440211016387
   Web of Science ®Google Scholar