Skip to main content
Log in

ARCS approach to PTA-based programming language practice sessions: Factors influencing Programming Problem-Solving Skills

  • Published:
Education and Information Technologies Aims and scope Submit manuscript

Abstract

This study used the ARCS approach to investigate the effects of university students’ motivation, including attention, relevance, confidence, and satisfaction, to use the Programming Teaching Assistant (PTA) on their Programming Problem-Solving Skills (PPSS). Previous studies have shown that PTA features enhance learners’ programming performance, but relevant studies have not empirically evaluated the factors influencing learners’ problem-solving skills in PTA-based programming language practice. Thus, the current study used the ARCS model to investigate the effects of its core factors, Attention (A), Relevance (R), Confidence (C), and Satisfaction (S), on the learners’ PPSS. A total of 99 students major in computer science and engineering (CSE) participated in this study. Multiple linear regression analysis was conducted and the results indicated that these motivational factors influenced learners’ PPSS in PTA-based programming language practice. The PTA has proven to be a motivating platform for programming language practice. Finally, relevant implications are offered.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig.5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

Data availability

Data available on request.

References

  • Adesanya, A. O., Sotayo, O. A. T., & Bolarinwa, F. B. (2022). Relevance of secretaries’ problem-solving skills for improved job performance in ogul state public service. Journal of the Business of Education, 3(1), 39–45.

    Google Scholar 

  • Amalia, P. R., Sukestiyarno, Y. L., & Cahyono, A. N. (2022). Problem-solving skill based on learning independence through assistance in independent learning with entrepreneurial-nuanced modules. Unnes Journal of Mathematics Education Research, 11(1), 102–108.

    Google Scholar 

  • Araiza-Alba, P., Keane, T., Chen, W. S., & Kaufman, J. (2021). Immersive virtual reality as a tool to learn problem-solving skills. Computers & Education, 164, 104121. https://doi.org/10.1016/j.compedu.2020.104121

    Article  Google Scholar 

  • Arianto, F., Mustaji, & Bachri, B. S. (2021). Metacognitive strategy and science problem-solving abilities in elementary school students. International Journal of Social Science and Human Research, 4(9), 2571–2574. https://doi.org/10.47191/ijsshr/v4-i9-42

  • Astuti, F. N., Suranto, S., & Masykuri, M. (2019). Augmented reality for teaching science: Students’ problem solving skill, motivation, and learning outcomes. JPBI (jurnal Pendidikan Biologi Indonesia), 5(2), 305–312. https://doi.org/10.22219/jpbi.v5i2.8455

    Article  Google Scholar 

  • Baars, M., Wijnia, L., & Paas, F. (2017). The association between motivation, affect, and self-regulated learning when solving problems. Frontiers in Psychology, 8, 1346. https://doi.org/10.3389/fpsyg.2017.01346

    Article  Google Scholar 

  • Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review, 84(2), 191. https://doi.org/10.1037/0033-295X.84.2.191

    Article  Google Scholar 

  • Bandura, A. (1983). Self-efficacy determinants of anticipated fears and calamities. Journal of Personality and Social Psychology, 45(2), 464.

    Article  Google Scholar 

  • Cecchinato, G., Papa, R., & Foschi, L. C. (2019). Bringing game elements to the classroom: The role of challenge and technology. Italian Journal of Educational Technology, 27(2), 158–173. https://doi.org/10.17471/2499-4324/1078

    Article  Google Scholar 

  • Chen, L. Q., Wu, M. T., Pan, L. F., & Zheng, R. B. (2021). Grade prediction in blended learning using multisource data. Scientific Programming, 1–15. https://doi.org/10.1155/2021/4513610

  • Chen, T. L., Hsiao, T. C., Kang, T. C., Wu, T. Y., & Chen, C. C. (2020). Learning programming language in higher education for sustainable development: Point-earning bidding method. Sustainability, 12(11), 4489. https://doi.org/10.3390/su12114489

    Article  Google Scholar 

  • Crockett, L., Jukes, I., & Churches, A. (2011). Literacy is not enough: 21st century fluencies for the digital age. Corwin Press.

    Google Scholar 

  • Di Serio, Á., Ibáñez, M. B., & Kloos, C. D. (2013). Impact of an augmented reality system on students’ motivation for a visual art course. Computers & Education, 68, 586–596. https://doi.org/10.1016/j.compedu.2012.03.002

    Article  Google Scholar 

  • Flegg, J., Mallet, D., & Lupton, M. (2012). Students’ perceptions of the relevance of mathematics in engineering. International Journal of Mathematical Education in Science and Technology, 43(6), 717–732. https://doi.org/10.1080/0020739X.2011.644333

    Article  Google Scholar 

  • Gao, Z., Zhang, Y., Zhang, R., Sun, X., & Feng, J. (2022). Do gender or major influence the performance in programming learning? Teaching mode decision based on exercise series analysis. Computational Intelligence and Neuroscience, 1–10. https://doi.org/10.1155/2022/7450669

  • Garnjost, P., & Lawter, L. (2019). Undergraduates’ satisfaction and perceptions of learning outcomes across teacher-and learner-focused pedagogies. The International Journal of Management Education, 17(2), 267–275. https://doi.org/10.1016/j.ijme.2019.03.004

    Article  Google Scholar 

  • Guo, X. Y., Wen, S. T., & Liu, Y. G. (2017) Towards Improving the Practical Ability by Teaching Mode Reform of Courses of Programming. In International Conference on Advanced Education and Management (AEMS 2017), 214–218.

  • Hadeed, S. A. (2019). The Validity and Reliability of an Adapted Problem-Solving Inventory (PSI): The Exploration of Paradoxical Problem-Solving as a Means to Manage Organizational Conflict (Doctoral dissertation, Florida International University).

  • Heppner, P. (1988). The problem solving inventory. Consulting Psychologists Press.

    Google Scholar 

  • Heppner, P. P., & Baker, C. E. (1997). Applications of the problem solving inventory. Measurement and Evaluation in Counseling and Development, 29(4), 229–241. https://doi.org/10.1080/07481756.1997.12068907

    Article  Google Scholar 

  • Huang, S. Y., Kuo, Y. H., & Chen, H. C. (2020). Applying digital escape rooms infused with science teaching in elementary school: Learning performance, learning motivation, and problem-solving ability. Thinking Skills and Creativity, 37, 100681. https://doi.org/10.1016/j.tsc.2020.100681

    Article  Google Scholar 

  • Iqbal Malik, S., Mathew, R., Tawafak, R. M., & Alfarsi, G. (2021). A web-based model to enhance algorithmic thinking for novice programmers. E-Learning and Digital Media, 18(6), 616–633. https://doi.org/10.1177/20427530211026988

    Article  Google Scholar 

  • Keller, J. M. (1979). Motivation and instructional design: A theoretical perspective. Journal of Instructional Development, 2(4), 26–34.

    Article  Google Scholar 

  • Keller, J. M. (1987). Development and use of the ARCS model of instructional design. Journal of Instructional Development, 10(3), 2–10. https://doi.org/10.1007/BF02905780

    Article  MathSciNet  Google Scholar 

  • Keller, J. M. (2010). Motivational design for learning and performance: The ARCS model approach (1st ed.). Springer.

    Book  Google Scholar 

  • Kim, M. Y., & Byun, E. K. (2019). Influence of academic self-efficacy, critical thinking disposition, and learning motivation on problem solving ability in nursing students. Journal of the Korea Academia-Industrial Cooperation Society, 20(1), 376–383. https://doi.org/10.5762/KAIS.2019.20.1.376

    Article  Google Scholar 

  • Lau, Y., Fang, L., Cheng, L. J., & Kwong, H. K. D. (2019). Volunteer motivation, social problem solving, self-efficacy, and mental health: A structural equation model approach. Educational Psychology, 39(1), 112–132. https://doi.org/10.1080/01443410.2018.1514102

    Article  Google Scholar 

  • Li, K., & Moore, D. R. (2018). Motivating students in massive open online courses (MOOCs) using the attention, relevance, confidence, satisfaction (arcs) model. Journal of Formative Design in Learning, 2(2), 102–113. https://doi.org/10.1007/s41686-018-0021-9

    Article  Google Scholar 

  • Lin, C. Y., & Cho, S. (2011). Predicting creative problem-solving in math from a dynamic system model of creative problem solving ability. Creativity Research Journal, 23(3), 255–261. https://doi.org/10.1080/10400419.2011.595986

    Article  Google Scholar 

  • Lin, P. H., & Chen, S. Y. (2020). Design and evaluation of a deep learning recommendation based augmented reality system for teaching programming and computational thinking. IEEE Access, 8, 45689–45699. https://doi.org/10.1109/ACCESS.2020.2977679

    Article  Google Scholar 

  • Lin, X., Ma, Y., Ma, W., Liu, Y., & Tang, W. (2021). Using peer code review to improve computational thinking in a blended learning environment: A randomized control trial. Computer Applications in Engineering Education, 29(6), 1825–1835. https://doi.org/10.1002/cae.22425

    Article  Google Scholar 

  • Mayer, R. E. (2001). Cognitive, metacognitive, and motivational aspects of problem solving. Metacognition in Learning and Instruction: Theory, Research and Practice, 19, 87–101. https://doi.org/10.1007/978-94-017-2243-8_5

    Article  Google Scholar 

  • Öztürk, M. (2022). The effect of self-regulated programming learning on undergraduate students’ academic performance and motivation. Interactive Technology and Smart Education, 19(3), 319–337.

    Article  Google Scholar 

  • Palau-Saumell, R., Forgas-Coll, S., Sánchez-García, J., & Robres, E. (2019). User acceptance of mobile apps for restaurants: An expanded and extended UTAUT-2. Sustainability, 11(4), 1210. https://doi.org/10.3390/su11041210

    Article  Google Scholar 

  • Palavan, Ö., Çelik, D., & Yücel, I. (2022). An assessment of university students’ book reading levels and problem solving skills. The European Journal of Social & Behavioural Sciences, 31(1), 35–48. https://doi.org/10.15405/ejsbs.310

    Article  Google Scholar 

  • Papanastasiou, G., Drigas, A., Skianis, C., Lytras, M., & Papanastasiou, E. (2019). Virtual and augmented reality effects on K-12, higher and tertiary education students’ twenty-first century skills. Virtual Reality, 23(4), 425–436. https://doi.org/10.1007/s10055-018-0363-2

    Article  Google Scholar 

  • Pohan, A. M., Asmin, A., & Menanti, A. (2020). The effect of problem based learning and learning motivation of Mathematical problem solving skills of class 5 students at SDN 0407 Mondang. Budapest International Research and Critics in Linguistics and Education (BirLE), 3(1), 531–539. https://doi.org/10.33258/birle.v3i1.850

    Article  Google Scholar 

  • Prince, T., Snowden, E., & Matthews, B. (2010). Utilising peer coaching as a tool to improve student-teacher confidence and support the development of classroom practice. Literacy Information and Computer Education Journal (LICEJ), 1(1), 49–51.

    Google Scholar 

  • Putra, R. W. P. (2021). Improving the students’ motivation in learning English through google meet during the online learning. English Learning Innovation, 2(1), 35–42. https://doi.org/10.22219/englie.v2i1.14605

    Article  Google Scholar 

  • Rahman, M. (2019). 21st century skill “problem solving”: Defining the concept. Asian Journal of Interdisciplinary Research, 2(1), 64–74. https://doi.org/10.34256/ajir1917

  • Ramos Salazar, L., & Hayward, S. L. (2018). An examination of college students’ problem-solving self-efficacy, academic self-efficacy, motivation, test performance, and expected grade in introductory-level economics courses. Decision Sciences Journal of Innovative Education, 16(3), 217–240. https://doi.org/10.1111/dsji.12161

    Article  Google Scholar 

  • Rose, S. E., Lamont, A. M., & Reyland, N. (2021). Watching television in a home environment: Effects on children’s attention, problem solving and comprehension. Media Psychology, 25(2), 208–233. https://doi.org/10.1080/15213269.2021.1901744

  • Samson, P. L. (2015). Fostering student engagement: Creative problem-solving in small group facilitations. Collected Essays on Learning and Teaching, 8, 153–164. https://doi.org/10.22329/celt.v8i0.4227

    Article  Google Scholar 

  • Tarmizi, R. A., & Sweller, J. (1988). Guidance during mathematical problem solving. Journal of Educational Psychology, 80(4), 424. https://doi.org/10.1037/0022-0663.80.4.424

    Article  Google Scholar 

  • Timor, A. R., Ambiyar, A., Dakhi, O., Verawadina, U., & Zagoto, M. M. (2021). Effectiveness of problem-based model learning on learning outcomes and student learning motivation in basic electronic subjects. International Journal of Multi Science, 1(10), 1–8.

    Google Scholar 

  • Tzohar-Rozen, M., & Kramarski, B. (2014). Metacognition, motivation and emotions: Contribution of self-regulated learning to solving mathematical problems. Global Education Review, 1(4), 76–95.

    Google Scholar 

  • Vatansever, Ö., & BaltacıGöktalay, Ş. (2018). How does teaching programming through scratch affect problem-solving skills of 5th and 6th grade middle school students. International Journal of Eurasia Social Sciences, 9(33), 1778–1801. https://doi.org/10.15405/ejsbs.310

    Article  Google Scholar 

  • Victoria State Government. (2020). Teach with digital technologies. In Victoria state government (pp. 1–6). https://www.education.vic.gov.au/school/teachers/teachingresources/digital/Pages/teach.aspx. Accessed 3 Mar 2022

  • Watanobe, Y., Rahman, M. M., Matsumoto, T., Rage, U. K., & Ravikumar, P. (2022). Online judge system: Requirements, architecture, and experiences. International Journal of Software Engineering and Knowledge Engineering, 32(06), 917–946.

    Article  Google Scholar 

  • Yang, B., & Wang, G. (2018). PTA Scoring Analysis Based on Statistical Method in a MOOC. In 2018 9th International Conference on Information Technology in Medicine and Education (ITME), 545–548. IEEE. https://doi.org/10.1109/ITME.2018.00126

  • Yang, B., Song, C., Zhang, W., & Sun, X. (2020). Discussion on Online and Offline Teaching Mode of Data Structure. In 2020 The 4th International Conference on Digital Technology in Education, 32–35. https://doi.org/10.1145/3429630.3429634

  • Yang, J. C., & Chen, S. Y. (2020). An investigation of game behavior in the context of digital game-based learning: An individual difference perspective. Computers in Human Behavior, 112, 106432.

    Article  Google Scholar 

  • Yildiz Durak, H. (2020). The effects of using different tools in programming teaching of secondary school students on engagement, computational thinking and reflective thinking skills for problem solving. Technology, Knowledge and Learning, 25, 179–195.

    Article  Google Scholar 

  • Yilmaz Ince, E. (2021). Students’ perceptions on learning programming with CodinGame. International Journal of Technology in Teaching and Learning, 17(1), 38–46.

    Google Scholar 

  • Yunus, M., Setyosari, P., Utaya, S., & Kuswandi, D. (2021). The influence of online project collaborative learning and achievement motivation on problem-solving ability. European Journal of Educational Research, 10(2), 813–823. https://doi.org/10.12973/eu-jer.10.2.813

    Article  Google Scholar 

  • Zeng, J., Zhang, Q., Xie, N., & Yang, B. (2021). Application of deep self-attention in knowledge tracing. arXiv preprint arXiv:2105.07909. https://doi.org/10.48550/arXiv.2105.07909

  • Zhang, X., Zhou, F., & Yan, Y. (2022). Multi-Collaborative C++ Language Experimental Teaching Reformation Based on PTA. In Proceedings of the 2022 6th International Conference on E-Education, E-Business and E-Technology, 15–21. https://doi.org/10.1145/3549843.3549846

Download references

Acknowledgements

We acknowledged Mr. Shuvo Md Touhidul Islam for his technical supports.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Benazir Quadir.

Ethics declarations

Conflict of interest

No conflict of interest.

Additional information

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendix

Appendix

Table 4

Table 4 Descriptive statistics of the questionnaire items

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Quadir, B., Mostafa, K., Yang, J.C. et al. ARCS approach to PTA-based programming language practice sessions: Factors influencing Programming Problem-Solving Skills. Educ Inf Technol 28, 13713–13735 (2023). https://doi.org/10.1007/s10639-023-11740-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10639-023-11740-6

Keywords

Navigation