From competence to customization: examining digital personalized learning through a moderated mediation model

• In Event: International Perspectives on Digital Platforms: Challenges, Customization, and Institutional Adaptation

Proposal

Personalized learning (PL) is now a key goal and reform initiative in today's education system (Zhang et al., 2020). It addresses the varied and ongoing learning needs of students in the era of universal higher education, while also promoting more equitable and inclusive educational opportunities. Nowadays, digital technology, with its convenience, ability to analyze and customize massive resources, and real-time interactivity, is gradually transforming PL. This evolution enables PL to become more extensive, universal, and lifelong. However, it also introduces challenges like digital distraction and technological dependence, highlighting the need for learners' abilities and commitment. Thus, we will focus on leveraging students' individual potential to harness technology's dual nature and facilitate effective PL. This aligns closely with the conference theme, “Envisioning Education in a Digital Society”, which explores the potential of education within a digital culture and the necessary actions for advancement.
Currently, PL in the digital age is still emerging in both practice and research (Shemshack & Spector, 2020). While there is agreement that PL can improve learning outcomes and perceptions across various subjects (Zheng et al., 2022), there is limited understanding of the factors that effectively promote PL. Some studies have identified technology advancement as an important prerequisite for PL. However, most of these studies rely on theoretical explanations and case studies, lacking large-sample empirical testing, which may limit the generalizability and replicability of their findings. Additionally, existing research predominantly examines how teachers and schools can implement personalized instruction in group settings through the choice of teaching methods and the effective use of related technologies (Alamri et al., 2020; Garrett, 2020; Kallio & Halverson,2020). Less attention has been paid to the informal learning in higher education and students' experiences with PL, ignoring the pivotal role of university students. This is crucial in the age of technological boom, as it pertains to the lifelong learning and sustainable development of university students.
In order to respond to the call of the digital age and fill gaps in existing research, we propose a moderated mediation model based on the self-regulated learning (SRL) theory. This model emphasizes learners' self-awareness and their ability to transform mental capacities into academic skills by adjusting their behavior, resources, and environment to activate, modify, and sustain specific learning practices (Zimmerman, 2002). Based on SRL, our aim is to explore how mechanisms and boundary conditions affect the digital personalized learning (DPL) in the informal settings from the perspective of university students. The research questions are:
(a) Does digital competence (DC) affect university students' DPL?
(b) How does DC indirectly affect university students' DPL through the mediating role of digital technology usage (DTU)?
(c) To what extent does digital self-directed learning (DSL) reinforce the effect of DC on university students' DTU and the indirect impact of DC on DPL through DTU?
To this end, we pose the following hypothesis:
H1: Digital competence positively predicts students' digital technology usage during learning. Zimmerman (2002) argues self-regulated learning is not a socially isolated methods, but rather requires rationally seeking external help based on self-competence. Therefore, we argue that DC, encompassing both digital skills and technological literacy, enables university students to understand the operational processes, applicable scenarios, and functional attributes of various digital technologies. This competence also aids in identifying and managing potential technological risks, thus enhancing their use of digital technology in learning.
H2: Digital technology usage positively predicts students' digital personalized learning. SRL theory suggests learners use self-regulation strategies such as self-assessment, information seeking, recording and monitoring to enhance their personal functioning, academic behavior, and learning environment, contributing to academic success (Zimmerman, 1989). The comprehensive capabilities of digital technology support students implement these strategies, thus facilitating the DPL.
H3: Digital technology usage mediates the relationship between students' digital competence and digital personalized learning. As previously discussed, DC lays the foundation for students’ DTU in the learning, and thus contributes to DPL.
H4: Digital self-directed learning moderates the positive effect of students’ digital competence on the digital technology usage. DSL retains the fundamental qualities of self-directed learning, emphasizing learners' self-empowerment and self-determination (Knowles, 1975). It complements DC by facilitating rational and purposeful DTU by university students. This positive relationship is more pronounced for students with high levels of DSL than low.
H5: Digital self-directed learning moderates the indirect relationship between students' digital competencies and digital personalized learning via digital technology usage. According to SRL theory, learner spontaneity and initiative are increasingly important in informal learning (Zimmerman, 2002). Higher levels of DSL, increase the likelihood that students will effectively utilize their DC across various areas, enhance their ability to recognize and implement learning actions, and manage the negative effects of complex information and technology. This, in turn, helps meet their learning needs and interests, contributing to DPL.
A total of 15748 samples of Chinese university students was collected through online questionnaires. We utilize SPSS software to conduct reliability test, descriptive statistics and correlation analysis. Then we employ path analyses to test research hypotheses, which are conducted using MPLUS software. Specifically, we constructed two models: Model 1, a mediation model, to test Hypotheses 1, 2, and 3; and Model 2, a moderated mediation model, to test Hypotheses 4 and 5. The results show all the above hypotheses are supported.
Drawing on a large-scale empirical survey from China, this study makes three theoretical contributions. Firstly, our research highlights the significant influence of university students' DC on enhancing DPL. This extends beyond the traditional focus on either teachers' roles or technology's impact alone, underscoring the crucial role of individual digital capabilities in shaping their educational outcomes. Secondly, we reveal the mediating process whereby students convert their DC into DPL through DTU. This contribution opens the "black box" of the transforming process, providing a framework to explore how digital tools can be strategically employed to bridge the gap between digital competence to learning results. Finally, we exam the moderating role of university students' DSL, highlighting the boundary conditions affecting DPL and enhancing our understanding of the increased focus on student autonomy in informal learning within higher education.

Authors

• Jia Ren, Xiamen University

• Yirong Jessica GUO, Xiamen University

• Yifan Song