Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 3, 1742-1754 2025 Publisher: Learning Gate DOI: 10.55214/25768484.v9i3.5686 © 2025 by the author; licensee Learning Gate © 2025 by the author; licensee Learning Gate History: Received: 20 January 2025; Revised: 10 March 2025; Accepted: 11 March 2025; Published: 22 March 2025 * Correspondence: sjkim@cju.ac.kr Effects of learning flow, learning interaction, and academic self-efficacy on learning satisfaction of college students who experienced HyFlex lecture Sun-Ju Kim1* 1Department of Dental Hygiene, College of Health &Medical Sciences, Cheongju University, South Korea, sjkim@cju.ac.kr (S.J.K.). Abstract: This study aims to examine the levels of learning flow, learning interaction, academic self- efficacy, and learning satisfaction among students who have experienced HyFlex lectures, as well as to investigate the correlations between these variables and the factors affecting learning satisfaction. The subjects of this study were 198 students taking HyFlex lectures offered in the first semester of 2024 who agreed to participate in the research among those attending a university located in Chungbuk. Data were collected through self-administered questionnaires from June 3 to June 10, 2024, using SPSS Statistics 22.0. The results of analyzing the differences according to general characteristics showed that learning satisfaction varied by type of class (F=4.728, p=.040) and was higher for theory classes compared to practical classes. It was also high when academic performance (F=11.089, p=.003) was 'above average.' The factors affecting learning satisfaction were academic performance (β=.322, p<.01), learning flow (β=.377, p<.001), learning interaction (β=.395, p<.001), and academic self-efficacy (β=.297, p<.01). Learning interaction was the variable with the most significant positive effect on learning satisfaction. The results of this study can be used as foundational data for establishing improvement measures to enhance the quality of HyFlex lectures and the learning outcomes of learners. Keywords: Academic self-efficacy, Hyflex learning, Learning flow, Learning interaction, Learning satisfaction. 1. Introduction 1.1. Research Background and Necessity College courses in the post-COVID-19 era are evolving into formats that integrate online classes into traditional classes. Many colleges have adopted online education systems in their academic systems after the pandemic, and active discussions have been made on various teaching methods using remote learning systems as well as their educational effectiveness [1]. However, several issues have been identified, including the limitations of online classes, lack of student participation and communication, declining academic performance, and deteriorating class quality. As a remedial action for these limitations, education that combines online and offline learning is being applied as a new teaching- learning method in higher education. In particular, there is a growing interest in HyFlex, which is a teaching method that combines online and offline learning. HyFlex is a compound for ‘hybrid’ and ‘flexible’, referring to an instructional approach in which some learners attend classes in person inside physical classrooms, while others participate in physical classroom activities online via video conferencing platforms. HyFlex lectures resolve issues incurred by the spatial constraints of face-to-face learning contexts, expand learning spaces, and offer various teaching-learning methods, which is why many colleges have created HyFlex learning environments and are actively adopting these courses [2]. The main feature of HyFlex lectures is that they give learners the right to choose how they will participate in class, enabling them to engage in learning activities suitable for their situations in diverse https://orcid.org/0000-0002-5054-1185 1743 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 3: 1742-1754, 2025 DOI: 10.55214/25768484.v9i3.5686 © 2025 by the author; licensee Learning Gate learning environments, such as face-to-face or online learning, or asynchronous online lectures. HyFlex lectures are receiving attention as a new instructional model amid the rapidly changing social and teaching-learning environments, but for successful and effective implementation of HyFlex lectures, there is a need for a thorough analysis of the effects of learning or learning satisfaction from the perspective of learners actually taking the courses. Learning satisfaction can be defined as the degree of satisfaction obtained when a learner achieves their intended goals in learning or when their personal expectations are met. Learning satisfaction is the learner’s subjective response to the teaching-learning process and reflects their overall reaction to the learning experience. Learning satisfaction of learners in online lectures is the result obtained when the learner’s expected needs and goals for the online courses are met, and it serves as a crucial element in knowledge acquisition [3]. Therefore, learning satisfaction can be considered a typical and important factor in measuring the effects of learning [4]. Learning flow is an optimal psychological state that appears when one is concentrated on specific learning activities or classes, indicating a state where one is absorbed in their learning activities or classes, displaying their best functions to make academic achievement [5]. Concentrating on classes in the learning process helps achieve more satisfaction and accomplishment from the classes, which may have a positive impact on the learning process and outcomes [6]. In other words, learning flow stimulates interest in learning that leads to active participation in learning activities, thereby increasing learning satisfaction. Particularly in online classes, if learners cannot be immersed in class, there may be disparities in learning among learners, which may affect learning achievement and satisfaction. Therefore, learning flow is essential for sustained learning, making it necessary to analyze the relationship between learning flow and learning satisfaction [Fig. 1]. Interaction in learning is crucial not only for improving the effect of education but also for learners to gain recognition and realize their identity within society represented by school. When learners recognize interaction with their instructors and fellow learners, they become more immersed in learning activities, which can enhance learning outcomes [7]. Among the many limitations of online learning is the lack of interaction, such as insufficient participation and communication among students. Learning interaction in HyFlex lectures is an important factor that can overcome the physical limitations of face- to-face and online classes and improve the quality of learning as well as learning satisfaction. 1744 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 3: 1742-1754, 2025 DOI: 10.55214/25768484.v9i3.5686 © 2025 by the author; licensee Learning Gate Figure 1. HyFlex model of instruction. Academic self-efficacy refers to a learner’s subjective belief that they can understand, analyze, and remember the content necessary to successfully acquire new knowledge and skills [8]. Academic self- efficacy is closely related to learning satisfaction, and it is a driving force that motivates learners to acquire and perform new knowledge and skills, as well as a key variable that mediates knowledge acquisition and performance among learners [9]. Thud, it is likely that improving interactions between learners and instructors as well as learning flow and academic self-efficacy of students have a significant relationship with learning satisfaction even in HyFlex classes, which raises the need for further research on this topic. A review of prior research on HyFlex lectures in Korea shows that research has been limited to case studies of HyFlex lectures, surveys on the perceptions of instructors and learners regarding HyFlex lectures, and research on instructional design models and strategies for effective HyFlex lectures [2, 10- 12]. However, these studies were mostly conducted in cyber universities or were conducted in online classes recently implemented at general colleges due to COVID-19, while there is insufficient research on the learning effectiveness or learning satisfaction from the perspective of learners who have experienced HyFlex lectures. Accordingly, this study seeks to analyze the current state of learning satisfaction among students who 1745 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 3: 1742-1754, 2025 DOI: 10.55214/25768484.v9i3.5686 © 2025 by the author; licensee Learning Gate have taken HyFlex lectures and the factors affecting learning satisfaction, and to provide improvement measures to improve the quality of HyFlex lectures as well as the learning outcomes of learners. 1.2. Research Objectives The specific research objectives are as follows. 1) To identify the levels of learning flow, learning interaction, academic self-efficacy, and learning satisfaction among the subjects. 2) To identify the differences in learning flow, learning interaction, academic self-efficacy, and learning satisfaction based on the sociodemographic characteristics of the subjects. 3) To examine the relationships between learning flow, learning interaction, academic self-efficacy, and learning satisfaction. 4) To examine the factors affecting learning satisfaction. 2. Research Methods 2.1. Research Participants This study employed convenience sampling of students taking HyFlex courses offered in the first semester of 2024 at C University located in Chungbuk. The courses were conducted in a uniform HyFlex classroom setting, where both offline and online learning environments were equally applied. The classroom was equipped with audio facilities (wireless microphone system, beamforming microphones), a speaker tracking camera, an electronic podium system, and an 86-inch electronic whiteboard, while the online class platform adopted Cisco Webex. 2.2. Ethical Considerations Ethical considerations were taken into account by distributing explanatory notes and consent forms about research to the participants who agreed to voluntarily participate, explaining the purpose and content of the study. The participants were informed that collected data were anonymized and not used for purposes other than research, and that they could withdraw from the survey at any time without any impact on their academic evaluations, after which the research was conducted with their consent. The survey was designed to take about 5 minutes considering participant fatigue, and a small token of appreciation was offered to respondents after completion. 2.3. Research Method The researcher visited the classrooms from June 3 to 10, 2024 and explained the intent of research to the students. Only those who agreed to participate were asked to complete a structured self- administered questionnaire. G*power 3.1.9.2 software was used to determine the appropriate sample size. To calculate the required number of participants for multiple regression analysis, the study used a significance level of 0.05, a statistical power of 0.95, a medium effect size of 0.15, and 10 predictor variables (general characteristics, learning flow, learning interaction, academic self-efficacy, learning satisfaction), based on which the required sample size was calculated as 172 participants. A total of 201 students responded to the survey, but survey results from 198 participants were used in the final analysis excluding 3 incomplete responses, indicating that the number of participants has power as an adequate sample size. 2.4. Research Tool The survey tool used in this study consisted of 6 items on general characteristics (gender, academic year, type of class, major satisfaction, academic performance, commute time, online learning experience, HyFlex learning experience), 22 items on learning flow, 14 items on learning interaction, 10 items on academic self-efficacy, and 8 items on learning satisfaction (Table 1). 1746 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 3: 1742-1754, 2025 DOI: 10.55214/25768484.v9i3.5686 © 2025 by the author; licensee Learning Gate Table 1. Research tool. Variables Item Range Cronbach’s α Learning flow 22 1~5 0.901 Learning interaction 14 1~5 0.887 Academic self-efficacy 10 1~7 0.928 Learning satisfaction 8 1~5 0.933 2.4.1. Learning Flow To measure the level of learning flow, this study used a questionnaire that was originally developed by Seok [13] and later modified and supplemented by Yoon [14] to be suitable for college students. The questionnaire consists of a total 22 items rated on a 5-point Likert scale, consisting of “Strongly disagree” (1 point), “Disagree” (2 points), “Neutral” (3 points), “Agree” (4 points), and “Strongly agree” (5 points), with higher scores indicating higher levels of learning flow. The reliability coefficient (Cronbach’s α) for this tool was 0.868 in the study by Yoon [14] and 0.901 in this study. 2.4.2. Learning Interaction To identify the learning interaction perceived by learners in an online lecture platform environment, this study used a tool developed by Williams and Deci [15] and later modified and supplemented by Lee [7]. The learning interaction questionnaire consists of a total 14 items rated on a 5-point Likert scale, consisting of “Strongly disagree” (1 point), “Disagree” (2 points), “Neutral” (3 points), “Agree” (4 points), and “Strongly agree” (5 points), with higher scores indicating higher levels of perceived learner interaction. The Cronbach’s α was 0.927 in the study by Lee [7] and 0.887 in this study. 2.4.3. Academic Self-Efficacy This study used a tool originally developed by Ayres [16] and later adapted, modified, and supplemented by Park and Kwon [17] to measure academic self-efficacy among college students. This tool consists of total 10 items rated on a 7-point Likert scale, consisting of “Strongly disagree” (1 point), “Generally disagree” (2 points), “Slightly disagree” (3 points), “Neutral” (4 points), “Slightly agree” (5 points), “Generally agree” (6 points), and “Strongly agree” (7 points), with higher scores indicating higher levels of academic self-efficacy. The Cronbach’s α was 0.950 in the study by Park & Kwon (2012), and 0.928 in this study. 2.4.4. Learning Satisfaction To measure the online learning satisfaction of college students, this study used a tool developed by Wang [18] and later modified and supplemented by Park [19] for cyber university students. The tool consists of a total 8 items rated on a 5-point Likert scale, consisting of “Strongly disagree” (1 point), “Disagree” (2 points), “Neutral” (3 points), “Agree” (4 points), and “Strongly agree” (5 points), with higher scores indicating higher levels of learning satisfaction. The Cronbach’s α was 0.90 in the study by Park [19] and 0.933 in this study. 2.5. Research Analysis The collected data was analyzed using SPSS Statistics 22.0 Version (IBM Co., Armonk, NY, USA), and the specific analysis methods were as follows. Frequency analysis was conducted on the demographic characteristics of the subjects. Differences in learning flow, learning interaction, academic self-efficacy, and learning satisfaction according to the demographic characteristics of the subjects were calculated using t-tests and one-way ANOVA, with post hoc tests conducted using Scheffé’s test. The correlations among learning flow, learning interaction, academic self-efficacy, and learning satisfaction were analyzed using Pearson’s correlation coefficients, and factors affecting learning satisfaction were 1747 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 3: 1742-1754, 2025 DOI: 10.55214/25768484.v9i3.5686 © 2025 by the author; licensee Learning Gate analyzed through multiple regression (Figure 2). Figure 2. Study model. 2.6. Limitations This study was conducted with students from a single university, selected by convenience sampling, and the findings are based on the subjective judgments of the participants regarding the variables and thus there are limitations in generalizing the results to a broader population. 3. Results 3.1. General Characteristics of Subjects Frequency analysis was conducted to examine the general characteristics, and the results are shown in (Table 2). There were 114 male (57.6%) and 84 female students (42.4%); and 96 subjects (48.5%) were juniors and 102 (51.5%) were seniors. For the type of HyFlex class, 142 subjects (71.7%) took theory classes and 56 (27.3%) took combined (theory and practical) classes. Commute times were distributed as follows: 47 subjects (23.7%) spent less than 30 minutes, 67 subjects (33.9%) spent 30 minutes to 1 hour, and 84 subjects (42.4%) spent more than 1 hour. For academic performance, 4 subjects (27.4%) were above average, 109 (55.0%) were average, and 35 (17.7%) were below average. For major satisfaction, 131 (66.2%) were satisfied, while 67 (33.8%) were not. 100% of the subjects responded they have experience taking an online class, whereas 100% responded they do not have experience taking a HyFlex class. 1748 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 3: 1742-1754, 2025 DOI: 10.55214/25768484.v9i3.5686 © 2025 by the author; licensee Learning Gate Table 2. General characteristics of the subjects. N=198 Variables N % Gender Male 114 57.6 Female 84 42.4 Grade Junior 96 48.5 Senior 102 51.5 Type of Class Theory 142 71.7 Theory + Practice 56 28.3 Commute time ≤ 30min 47 23.7 30mi n~ 1hr 67 33.9 > 1hr 84 42.4 Major satisfaction Satisfied 131 66.2 Unsatisfied 67 33.8 Academic performance Above average 54 27.3 Average 109 55.0 Lower than average 35 17.7 Experience of online class Yes 198 100.0 No 0 0.0 Experience of HyFlex class Yes 0 0.0 No 198 100.0 3.2. Levels of Learning Flow, Learning Interaction, Academic Self-Efficacy, and Learning Satisfaction of Subjects The levels of learning flow, learning interaction, academic self-efficacy, and learning satisfaction of subjects are shown in (Table 3). Learning flow scored an average of 3.78±0.51 out of 5 points, learning interaction 3.91±0.71 out of 5 points, academic self-efficacy 5.89±0.81 out of 7 points, and learning satisfaction 3.88±0.57 out of 5 points. Table 3. Learning flow, learning interaction, academic self-efficacy, learning satisfaction. N=198 Variables M±SD† Min Max Range Learning flow 3.78±0.51 2.89 4.32 1~5 Learning interaction 3.91±0.71 2.25 4.42 1~5 Academic self-efficacy 5.89±0.81 2.37 6.80 1~7 Learning satisfaction 3.88±0.57 2.14 5.00 1~5 Note: †M±SD: mean±standard deviation. 3.3. Differences In Learning Flow, Learning Interaction, Academic Self-Efficacy, and Learning Satisfaction According to General Characteristics The results of analyzing learning flow, learning interaction, academic self-efficacy, and learning satisfaction according to general characteristics are shown in (Table 4). Learning flow showed a significant difference depending on academic performance (F=12.661, p=.003). The results of the post- hoc analysis showed that learning flow was higher for students whose academic performance was ‘above average’ compared to ‘average’ or ‘below average.’ learning interaction also showed a significant difference depending on academic performance (F=8.621, p=.023), with post-hoc analysis revealing 1749 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 3: 1742-1754, 2025 DOI: 10.55214/25768484.v9i3.5686 © 2025 by the author; licensee Learning Gate higher learning flow for those whose academic performance was ‘above average.’ Academic self-efficacy showed a significant difference depending on the type of class (F=11.775, p=0.003), with higher academic self-efficacy found in theory classes compared to practical classes. Learning satisfaction varied by type of class (F=4.728, p=.040) and was higher for theory classes compared to practical classes, and it was also high when academic performance (F=11.089, p=.003) was ‘above average.’ There were no statistically significant differences in learning flow, learning interaction, academic self-efficacy, and learning satisfaction depending on gender, academic year, commute time, or major satisfaction. Table 4. Differences of learning flow, learning interaction, academic self-efficacy & learning satisfaction to general characteristics. Variables Learning flow Learning interaction Academic self- efficacy Learning satisfaction M±SD† t/F(p) M±SD t/F(p) M±SD t/F(p) M±SD t/F(p) Gender Male 3.74±0.56 -1.113 (.102) 3.84±0.81 2.963 (.330) 5.98±0.88 2.848 (.095) 3.82±0.66 -0.848 (.185) Female 3.81±0.46 3.98±0.61 5.79±0.74 3.93±0.48 Grade Junior 3.77± 0.33 1.601 (.246) 3.95±0.54 0.354 (.378) 5.78±0.73 1.115 (.266) 3.80±0.51 0.915 (.266) Senior 3.79±0.68 3.86±0.88 5.99±0.89 3.95±0.63 Type of class Theory 3.82±0.48 0.899 (.289) 3.93±0.75 3.487 (.491) 6.17±0.75 11.775 (.003) 4.03±0.60 4.728 (.040) Theory +Practice 3.74±0.53 3.88±0.67 5.61±0.87 3.73±0.54 Commute time < 30 min 3.82±0.40 1.320 (.088) 3.94±0.51 2.648 (.719) 5.95±0.70 1.208 (.490) 3.93±0.43 1.017 (.210) 30 min ~1 hr 3.77±0.54 3.88±0.81 5.83±0.88 3.83±0.68 1 hr < 3.75±0.48 3.90±0.60 5.89±0.74 3.86±0.46 Academic performance Above averagea 4.03±0.44 12.661 (.003) (c,b