Determinants of College Students’ Online Fragmented Learning Effect: An Analysis of Teaching Courses on Scientific Research Software on the Bilibili Platform

Abstract

In the era of mobile Internet, online fragmented learning has become one of the mainstream ways for college students to study independently. Analyzing the online fragmented learning effect (OFLE) has essential reference value for guiding the online learning behavior of college students and optimizing the allocation of online learning platform resources. It also provides sustainable solutions for enhancing college students’ online independent learning effect. For this paper, we took college students who have studied teaching courses on scientific research software (TCSRS) on Bilibili as our research subjects, constructed a theoretical model of college students’ OFLE based on the theory of online learning and fragmented learning, verified the model through using questionnaire data, and analyzed the determinants of college students’ OFLE and its mechanisms. Our results indicate the following: (1) Most college students spend a dispersed amount of time learning TCSRS, showing the characteristics of “fragmentation”. (2) Learning motivation (LM), self-efficacy (SE), and fragmented time utilization (FTU) have a significant positive effect on college students’ OFLE. (3) Knowledge fragmentation (KF) affects college students’ OFLE, but it is not significant. These dimensions provide a theoretical reference for quantitative research on the impact of college students’ OFLE. Finally, also in this paper, improvement countermeasures are proposed from the perspective of improving college students’ OFLE and ability.

Examining the Impact of Fragmented Learning on Education: Empirical Evidence from SOR Theory Analysis

“…Zhu and Geng [16] explored fragmented learning among college students in the Internet era and analyzed its influences and strategies for enhancing effectiveness. Li [17] analyzed the application of fragmented learning in online courses. However, e-learning or online learning, such as learning on MOOCs platforms, is not typically classified as fragmented learning.…”

Antecedents of College Students’ Continuance Behaviors in Online Fragmented Learning: An Empirical Analysis from the Extended ECM Perspective

“…The outbreak of the COVID-19 pandemic has dramatically propelled the development of online fragmented learning. So far, online fragmented learning is prevalent among college students and has become an essential method for acquiring knowledge and improving autonomy in learning and application skills [5,6]. However, college students are prone to the phenomenon of "accept-interruption" in online fragmented learning, which makes it difficult for them to form a complete knowledge system.…”

“…Recent studies have paid attention to the determinants of online fragmented learning and its effect [4,6,7], but the research on the continuance behaviors in online fragmented learning is still relatively few. Although online fragmented learning, with the characteristics of high flexibility, strong pertinence, convenient learning, and high time efficiency, can make up for the deficiencies of traditional classroom-based learning and help students make better use of their fragmented time [5,6], the scattered and disorderly fragmented knowledge acquired by online fragmented learning lacks comprehensiveness and rigor [7,8]. Consequently, students must carry out continuance behaviors in online fragmented learning to master a complete knowledge system and rigorous logic system, thus improving their online learning efficiency and achieving better learning effects.…”

“…On the other hand, the learning time of college students is scattered and fragmented due to daily courses and social activities. In this case, college students can only use their spare time to study the contest knowledge in a fragmented manner [6]. Online platforms such as the Chinese university MOOCs provide abundant online courses by fully taking into account the fragmented learning features of college students.…”

“…Finally, using undergraduate students that have studied contest courses on the Chinese university MOOCs as the research object and 429 valid questionnaires collected from the sojump platform, a Chinese website similar to Qualtrics, we empirically test our predictions with the SEM technique with AMOS, and the results indicate that all hypotheses are supported. This study explores the influencing factors of college students' continuance behaviors in online fragmented learning from the perspective of the extended ECM and profoundly analyzes the mechanism of continuous behaviors in online fragmented learning, thus extending this line of literature on fragmented learning [6,14,15] and research on the ECM [16,17]. In addition, this study has important practical significance in guiding college students' CBOFL, which reinforces the practice of college students' continuous learning in the future and is beneficial for facilitating the sustainability of online learning.…”