**1. Introduction**

For several decades, online learning has not received enough attention, especially at universities [1,2]. Although numerous virtual universities, such as open universities and distance teaching universities, already offer online learning, most ordinary universities prefer to offer face-to-face courses [3]. Since the 1990s, the widespread use of the internet has greatly promoted the development of online education and has had a potential impact on university teaching methods, resource allocation, and development strategies [4,5]. Since 2013, there has been an explosive growth of large-scale online courses [6].

In early 2020, various industries and sectors were affected by the massive global spread of COVID-19 [7]. For example, total urban traffic has seen a significant drop due to the impact of travel controls. The home quarantine policy has led to high growth in the size of transactions in the new retail industry. The rapid changes in the epidemic have led to large fluctuations in the psychological situation of the population [6]. Similarly, universities around the world have struggled to return to normal teaching and learning in the wake of the epidemic due to the excessive range of movement of people. This situation forced all universities to operate remotely and to put emergency remote teaching into practice [8]. University students and teachers have to use online learning as a supplement to traditional face-to-face teaching and learning [9]. To ensure the safety of students, the education authorities in each country have taken measures to ensure the normal teaching and learning process at universities, requiring them to rely on various online course

**Citation:** Zhang, Y.; Chen, X. Students' Perceptions of Online Learning in the Post-COVID Era: A Focused Case from the Universities of Applied Sciences in China. *Sustainability* **2023**, *15*, 946. https://doi.org/10.3390/su15020946

Academic Editor: Hao-Chiang Koong Lin

Received: 15 November 2022 Revised: 27 December 2022 Accepted: 1 January 2023 Published: 4 January 2023

**Copyright:** © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

platforms and online learning spaces during the COVID-19 pandemic [10]. Universities have also asked students to postpone their return to university and engage with online teaching. In this case, students are studying online off-campus through platforms such as Zoom, Tencent Meeting, etc. [11]. As learning styles and learning environments change, so do students' choices of courses and attitudes towards learning. Students and faculty often found themselves logging onto Zoom or other platforms for the first time, with little knowledge of how to use virtual learning. As the COVID-19 pandemic eases, many universities are realising that well-planned online platforms will allow them to better serve students [12,13].

Online learning became the default in 2020. Nevertheless, remote learning via Zoom and Tencent Meeting is now used by the majority of universities [14]. However, a variety of new platforms and technologies have emerged in recent years, grounded in machine learning, artificial intelligence, etc. MOOC platforms such as Coursera and EdX use machine learning to automatically grade assignments and deliver adaptive content and exams by combining data from billions of course datapoints and tens of millions of students [15].

The need for online education is enormous and expanding quickly during the epidemic [16]. From 2016 to 2023, the online education industry is anticipated to expand at a 16.4% CAGR. In ten to fifteen years, it is possible that the teaching style in schools may alter due to the internet's rapid development. More and more students are favouring online learning [17]. However, few studies have involved the influencing factors of students' perceptions of the online learning situation during COVID-19, especially the students of universities of applied sciences. Higher education that emphasises applications is essential for a nation's development since it fosters employment and raises competitiveness [16]. Its potential to enhance learners' capacity to gain knowledge, develop skills, and express creativity is what gives it its distinctive worth [18–20].

In order to improve the understanding of the overall evaluation of online learning in the post-COVID era from the perspective of students of universities of applied sciences in China, it is necessary to identify which implicit and explicit factors are present in the research on online learning. This is a necessary first step towards having a robust debate about the influencing factors in online learning.

### **2. Theoretical Frameworks**

Just as COVID-19 spread to many countries in 2020, the COVID-19 pandemic affected universities in these countries around the world. During lockdowns, university teachers have almost exclusively used digital tools to ensure the continuation of teaching and learning [7]. However, not all countries, universities, and students were equally affected. At this point, central aspects from the educational, sociological, and economical perspectives that influence online learning are presented. This includes various forms of the digital divide and other factors. The digital divide is a fundamental problem for online learning [21]. This approach is, in turn, influenced by other aspects such as socio-economic factors. At the beginning of the research on the digital divide, the focus was on access to the internet and digital media. Internet skills are addressed as a second digital divide [22,23].

### *2.1. The Expectation Confirmation Theory (ECT)*

In 1980, Oliver proposed the expectancy disconfirmation theory (EDT). Before purchasing a product or service, users have certain expectations of it. After the product or service is actually used, the difference between the user's perceived performance and their expectations is known as expectation disconfirmation [24]. Expectancy confirmation theory (ECT) was developed based on EDT and provides an important basis for the study of sustained use by users [25]. Patterson et al. [26] were the first to apply ECT to information systems. Bhattacherjee [27] proposed the expectation confirmation model (ECM), which includes four main variables: expectation confirmation, perceived usefulness, satisfaction, and repurchase intention. After ECM was proposed, many academics confirmed the validity of the ECM. For example, Larsen et al. [28] examined mobile commerce using the ECM, Tang and Chiang [29] verifies the effectiveness of the ECM by examining blogs, Doong and Lai [30] examined knowledge sharing using the ECM, and Kim [31] explored the effectiveness of the ECM by examining mobile data services. Moreover, many academics have combined online learning with the ECM. Wang et al. [32] determined if online learning helps students accomplish learning activities during the pandemic and increases their motivation to continue utilising online learning in the future. In order to investigate the potential drivers of continuous learning willingness in a Massive Open Online Course (MOOC) environment, Hai et al. [33] developed and extended the ECM by including cognitive and emotional variables (including intrinsic motivation, attitude, and curiosity). Based on the foregoing literature, the ECM can be utilised to describe the impact of online learning on students' learning experiences.
