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Integrating online partial pair programming and socially shared metacognitive regulation for the improvement of students’ learning

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Chia-Wen Tsai
Chia-Wen Tsai
Michael Yu-Ching Lin
Michael Yu-Ching Lin
Michael Yu-Ching Lin
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Yih-Ping Cheng
Yih-Ping Cheng
Yih-Ping Cheng
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Lynne Lee
Lynne Lee
Lynne Lee
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Abstract and Figures

Many universities around the world were forced to lock down and students had to continue their learning in online environments in response to the COVID-19 pandemic. Teachers thus had to adopt effective and appropriate online teaching pedagogy integrated with related educational technologies to help their students achieve satisfactory learning outcomes in these courses. In addition, the world-wide problems of high failure level and dropout rates in programming courses challenge both teachers and students. Aiming to develop students’ practical programming skills, commitment to learning, and reduce learning disengagement, the researchers behind this study adopted two teaching approaches, integrating online partial pair programming (PPP) and socially shared metacognitive regulation (SSMR), to explore their effects on students’ learning performance in an online programming course. A quasi-experiment was implemented to explore the effects of online PPP and SSMR. The participants comprised three classes of students, all from non-information or non-computer departments taking a compulsory course titled ‘Programming Design’. The experimental groups included the first class (G1) simultaneously receiving the online PPP and SSMR intervention and the second class (G2) receiving only the online SSMR intervention. The third class (G3) received a traditional teaching method (non-PPP and non-SSMR) delivered online and served as the control group. Both quantitative and qualitative data were collected and analyzed. Experimental results show that the SSMR group (G2) demonstrated significantly better development of programming skills and commitment to learning than the control group (G3). However, the expected effects of online PPP on improving students’ learning were not found. The implications of designing pedagogies with PPP and SSMR in an online programming course for decision-makers in governments and universities, researchers, and teachers implementing online courses, particularly programming courses, are provided and discussed.
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https://doi.org/10.1007/s10209-024-01127-w
LONG PAPER
Integrating online partial pair programming andsocially shared
metacognitive regulation fortheimprovement ofstudents’ learning
Chia‑WenTsai1· MichaelYu‑ChingLin2· Yih‑PingCheng3· LynneLee4· Chih‑HsienLin5· Jian‑WeiLin6·
Min‑LingHung7· Wen‑YuChen8
Accepted: 29 May 2024
© The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024
Abstract
Many universities around the world were forced to lock down and students had to continue their learning in online environ-
ments in response to the COVID-19 pandemic. Teachers thus had to adopt effective and appropriate online teaching peda-
gogy integrated with related educational technologies to help their students achieve satisfactory learning outcomes in these
courses. In addition, the world-wide problems of high failure level and dropout rates in programming courses challenge
both teachers and students. Aiming to develop students’ practical programming skills, commitment to learning, and reduce
learning disengagement, the researchers behind this study adopted two teaching approaches, integrating online partial pair
programming (PPP) and socially shared metacognitive regulation (SSMR), to explore their effects on students’ learning
performance in an online programming course. A quasi-experiment was implemented to explore the effects of online PPP
and SSMR. The participants comprised three classes of students, all from non-information or non-computer departments
taking a compulsory course titled ‘Programming Design’. The experimental groups included the first class (G1) simultane-
ously receiving the online PPP and SSMR intervention and the second class (G2) receiving only the online SSMR interven-
tion. The third class (G3) received a traditional teaching method (non-PPP and non-SSMR) delivered online and served
as the control group. Both quantitative and qualitative data were collected and analyzed. Experimental results show that
the SSMR group (G2) demonstrated significantly better development of programming skills and commitment to learning
than the control group (G3). However, the expected effects of online PPP on improving students’ learning were not found.
The implications of designing pedagogies with PPP and SSMR in an online programming course for decision-makers in
governments and universities, researchers, and teachers implementing online courses, particularly programming courses,
are provided and discussed.
Keywords Online partial pair programming· Online socially shared metacognitive regulation· Programming course·
Programming skills· Commitment to learning· Learning disengagement· Cloud classroom
1 Introduction
Computing and programming has been (re)integrated into
basic education curricula in many nations, as understand-
ing the concepts of programming code, computing, and
programming is critical for agentic citizenship in modern
education and society [78]. Although there are many educa-
tors indicating the importance of computing and program-
ming education, students’ dropout rate from programming
courses is very high as many find it quite difficult to learn
and understand programming [88]. In addition, many uni-
versities were forced to lock down and students had to learn
in online environments because of the COVID-19 pandemic
restrictions [38]. This may increase the difficulty of teach-
ing programming, as learning in online environments may
result in students having a sense of isolation [19, 107] and
distraction [109]. Thus, adopting and integrating effective
teaching methods with educational technologies is necessary
to facilitate students attaining better learning outcomes in
online or blended programming courses.
1.1 The need formeans ofovercoming learning
challenges
In recent years, the keenness to learn programming has been
increasing as modern society and workplaces have greatly
Extended author information available on the last page of the article
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... [15] 2021 A gamified web-based system for computer programming learning 6 [16] 2024 Integrating online meta-cognitive learning strategy and team regulation to develop students 7 [17] 2023 Applying an evidence-based learning analytics intervention to support computer programming 8 [18] 2024 Students' perspectives on using digital tools in programming courses 9 [19] 2024 A Rule-Based Chatbot Offering Personalized Guidance in Computer Programming Education 10 [20] 2024 A study of factors influencing programming anxiety among non-computer students 11 [21] 2024 Experience Teaching Non-Computer Science Majors Computer Programming 12 [22] 2023 An enhanced career prospect prediction system for non-computer stream students in software companies 13 [23] 2021 A Phenomenographic Analysis of College Students' conceptions of and approaches to 14 [24] 2024 Interdisciplinary integration of computational thinking in K-12 education 15 [25] 2024 An Interactive Tool for Improving Python Syntax Mastery in Non-Computing Students 16 [26] 2024 Using Accessibility Awareness Interventions to Improve Computing Education 17 [27] 2024 Professional Development in Computational Thinking: A Systematic Literature Review 18 [28] 2024 Digital Game Making and Game Templates Promote Learner Engagement in Noncomputing Classroom Teaching. 19 [29] 2021 Designing IDE interventions to promote social interaction and improved programming outcomes in early computing courses 20 [30] 2024 Integrating online partial pair programming & socially shared metacognitive regulation for the improvement of students' learning 21 [31] 2022 Analysis of factors contributing to the difficulties in learning computer programming among non-computer science students 22 [32] [34] 2022 Increasing programming self-efficacy (PSE) through a problem-based gamification digital learning ecosystem (DLE) model 25 [35] 2024 Coding attitudes of fourth-grade Latinx students during distance learning 26 [36] 2021 Collaborating learning in an educational robotics environment 27 [37] 2024 Programming education and learner motivation in an age of generative AI: student and educator perspective 28 [38] 2024 An AI-driven virtual tutor for computer science education 29 [39] 2023 Effectiveness of flipped classroom pedagogy in programming education: A meta-analysis ...
... Collaboration and data-driven approaches are recurring themes in most of the papers. A study such as integrating pair programming (PP) with metacognitive regulation [30] and IDE interventions promoting social interaction [29] Demonstrates the value of teamwork and peer learning. Evidence-based learning analytics [17] and systematic reviews of professional development programs for computational thinking [27] Underline the importance of data-driven decisionmaking and educator support in improving outcomes. ...
... Another issue discussed here is that students do not have a collaborative learning programming environment. [30], so they cannot handle multiple programming problems simultaneously [18]. (lack of resources and tools) another challenge is students' limited access to wellneeded resources such as educational tools and e-learning/distance learning materials [35]. ...
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