Understanding Undergraduate Students’ Experiences in Blended Learning Through the Integration of Two-Factor Theory and the TPACK Framework

Abstract

Blended learning is widely adopted in higher education, yet little is known about how students experience its motivational and instructional features. In this study, we examined undergraduate students’ experiences regarding blended learning by integrating Herzberg’s two-factor theory with the TPACK framework. Semi-structured interviews were conducted with 24 undergraduates at a large Vietnamese university. A theory-informed qualitative content analysis approach was used to identify codes, categories, and themes. These were then mapped onto the pedagogical content knowledge (PCK), technological content knowledge (TCK), and technological pedagogical knowledge (TPK) intersections of the TPACK framework. The findings showed that hygiene factors included unengaging teaching practices, inadequate digital infrastructure, and limited online interaction. These factors often produced frustration and reduced engagement. Motivator factors included active and relevant pedagogical strategies, engaging and accessible digital resources, and technology-facilitated autonomous, expressive, and creative learning work. These factors encouraged deeper learning and stronger motivation. It is concluded that blended learning design must address both hygiene and motivator factors to improve student engagement. Integrating these factors with the TPACK intersections offers a practical model for improved course structures, enhanced digital resources, and the design of more interactive technology-supported pedagogy. The findings provide actionable implications for higher education institutions seeking to improve the quality of blended learning.

1. Introduction

1.1. Emergence and Advantages of Blended Learning in Higher Education

Throughout the 21st century, rapid advancements in technology have fundamentally reshaped the landscape of higher education. One of the most significant shifts is the growing adoption of blended learning—a pedagogical approach that integrates traditional face-to-face instruction with online learning components [1,2]. The necessity of flexible learning environments emerged in the wake of the COVID-19 pandemic, driving universities worldwide to transition from traditional face-to-face instruction to blended learning models [3]. The emergence of blended learning has also been driven by the growing demand among students for more personalized, engaging, and flexible learning experiences [4].

Blended learning is defined as a combination of traditional face-to-face teaching and e-learning modes, leveraging the strengths of both approaches to obtain advantages in classroom administration and performance [5,6]. Several previous studies have shown that undergraduates who study in blended learning environments exhibit greater academic achievement than those who study fully face-to-face or fully online [2,6,7,8,9]. The integration of online teaching materials in blended learning both satisfies the diverse learning needs of students and enhances their learning experiences [5]. Given its significant advantages over traditional face-to-face teaching methods, blended learning is increasingly being considered a priority in transitioning the traditional classrooms of higher education institutions towards a balance between technology integration and human interaction [1,2,10,11].

1.2. Blended Learning Design and the Role of the TPACK Framework

Although blended learning carries great potential, its effectiveness depends largely on instructional design regarding how technology, pedagogy, and content knowledge are integrated to create meaningful learning experiences. The success of blended learning is not limited to the inclusion of digital tools in the classroom; it also depends on how instructors coordinate them with instructional strategies and content knowledge [12]. To explain this complex interaction, the TPACK framework is seen as a useful tool that allows us to understand how these three core elements can be combined to optimize blended learning environments [13,14,15].

The TPACK framework includes three main knowledge domains: technological, pedagogical, and content knowledge [12]. Considering the interplay between these three elements allows instructors to design effective blended learning courses that balance technological integration, pedagogical alignment, and content relevance [12,16]. Technological integration involves using digital tools such as online videos, simulations, and discussion forums to enhance interactivity [17]. Pedagogical alignment refers to employing active learning strategies such as problem-based learning or collaborative projects to engage students [18]. Content relevance refers to theoretical concepts and their connections to practice [12].

Within the TPACK framework, three knowledge domain intersections are identified: PCK, TCK, TPK, and TPACK [15]. PCK refers to pedagogical knowledge that can be applied in teaching the content of a specific subject area [15]. TCK considers how technology and content influence and constrain each other [15]. Finally, TPK considers how teaching and learning can change when specific technologies are used in certain ways [15]. Understanding these intersections of knowledge is essential in optimizing blended learning environments.

Although the TPACK framework was originally developed to conceptualize teachers’ professional knowledge, in this study, we use it as an analytical lens through which to interpret students’ blended learning experiences. Students do not naturally organize their experiences in terms of PCK, TCK, or TPK. Instead, we can interpret students’ narratives through the TPACK framework. This approach enables a systematic analysis of the ways in which pedagogical, technological, and content-related instructional elements shape students’ blended learning experiences.

1.3. Two-Factor Theory: Hygiene and Motivator Factors in Blended Learning

There are various frameworks used to explain human motivation, reflecting different theoretical approaches; these include needs-based approaches (e.g., Maslow’s hierarchy of needs and achievement motivation), cognitive process approaches (e.g., expectancy theory, equity theory, and goal-setting theory), and task-based approaches (e.g., Herzberg’s two-factor theory and job characteristics theory). Needs-based theories primarily focus on the satisfaction of fundamental human needs, while approaches based on cognitive processes emphasize individuals’ expectations, perceptions, and internal evaluations of outcomes. In contrast, task-based theories highlight how motivational conditions are embedded in the design and characteristics of work itself, shaping individuals’ engagement and growth. In the context of the present study, Herzberg’s two-factor theory is relevant because it allows blended learning courses to be examined as work environments, where course design features (such as pedagogical strategies and technological capabilities) may function as either hygiene factors or motivator factors.

While the TPACK framework provides a strong foundation for an understanding of the interplay between technology, pedagogy, and content in blended learning environments [19,20], it does not fully explain why some elements in these environments foster student engagement while others merely prevent disengagement. In practice, not all components of blended learning contribute equally to the student learning experience. Some features serve as baseline conditions that must be met to avoid frustration or dropout, while others actively stimulate deeper involvement and enthusiasm for learning among students. This distinction allows us to approach blended learning from a motivational psychology perspective, i.e., through Herzberg’s two-factor theory. The clear distinction between hygiene and motivator factors provides a new lens for the design of blended learning courses that are not only technically effective but also motivationally rich [21].

Hygiene factors are the necessary conditions of the blended learning environment to prevent frustration and disengagement among students when learning [22]. These include the quality of the virtual learning environment [1], the designed LMS platform [23], technical infrastructure [24], access to learning materials [25], a clear course structure, and effective communication from instructors [26].

Motivator factors reflect the intrinsic nature of the work, seeking to stimulate greater student engagement in blended learning [22]. They include active learning opportunities [18], personalized feedback, self-directed learning experiences [27,28], and virtual simulations or gamified assessments [29].

While motivator factors promote deeper learning and academic achievement among students, hygiene factors play a critical role in ensuring smooth learning experiences [30]. Without the foundational role played by hygiene factors, even well-designed blended learning courses may fail to maintain student engagement. Furthermore, the absence of strong motivators can lead to passive learning, where students simply complete tasks without intellectual curiosity or motivation [31]. Understanding hygiene and motivator factors is critical in designing effective blended learning experiences that minimize barriers to learning and actively promote student engagement and success.

1.4. Research Gaps and Purpose of the Study

Although blended learning has expanded widely across higher education, no systematic studies have been conducted on hygiene and motivator factors from the perspective of undergraduate students. While many studies have addressed various aspects of blended learning, such as technological infrastructure, pedagogical effectiveness, learner satisfaction, engagement, or technological usability [32], they lack a structured theoretical framework that distinguishes between the baseline conditions that prevent disengagement (hygiene factors) and those that actively drive deeper learning (motivator factors) among undergraduate students. Moreover, no existing studies integrate these motivational factors with the TPACK framework. As a result, it is not yet understood how hygiene and motivator factors align with the PCK, TCK, and TPK intersections. This represents a critical gap, because instructional design in blended learning requires careful alignment between technological tools, pedagogical strategies, and disciplinary content. Therefore, the purpose of this study was to explore undergraduate students’ experiences of hygiene and motivator factors in blended learning, using Herzberg’s two-factor theory in combination with the TPACK framework. By mapping students’ lived experiences onto the PCK, TCK, and TPK intersections, this study sought to provide theoretical knowledge and identify practical implications for the design of effective, motivating, and learner-centered blended learning experiences.

1.5. Conceptual Model and Research Questions

In this study, Herzberg’s two-factor theory and the TPACK framework were combined to construct a conceptual model. This conceptual model mapped hygiene and motivator factors according to the domain intersections of the TPACK framework, as shown in Figure 1.

Based on the conceptual model, the study focused on exploring undergraduate students’ experiences in blended learning by integrating Herzberg’s two-factor theory with the TPACK framework. There were three defined research questions:

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In blended learning, which hygiene and motivator factors do undergraduate students perceive corresponding to the PCK intersection of the TPACK framework?

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In blended learning, which hygiene and motivator factors do undergraduate students perceive corresponding to the TCK intersection of the TPACK framework?

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In blended learning, which hygiene and motivator factors do undergraduate students perceive corresponding to the TPK intersection of the TPACK framework?

2. Methods

2.1. Research Context

This study focused on blended learning at Hanoi University of Science and Technology (HUST), a leading institution in Vietnam. From 2010 to 2019, HUST collaborated with the ASEAN Cyber University (ACU) project, funded by the Korean government, to build e-learning infrastructure and train faculty members to conduct online teaching. In 2012, HUST launched its first e-learning courses to supplement face-to-face instruction. However, as it was found that fully online learning could not replace traditional face-to-face interactions, HUST transitioned to blended learning in 2018, combining the strengths of both online and face-to-face methods. The university’s blended learning platform, available at http://lms.hust.edu.vn (accessed on 1 January 2025), provides various materials, video lectures, quizzes, and forums. This shift has improved the quality of teaching, creating a more modern and flexible learning environment. At the time of this study, blended learning had been in place for over five years, with HUST continuing to prioritize this approach in its courses.

2.2. Research Design

In this study, a theory-informed qualitative content analysis approach was used to explore hygiene and motivator factors in blended learning. The study was conceptually guided by Herzberg’s two-factor theory and the TPACK framework, which informed the design of the semi-structured interview protocol (Appendix A). Semi-structured interviews were conducted to collect data from 24 HUST students selected through purposive sampling [33]. Although the study was theoretically informed, participants were not introduced to the theoretical constructs during the interviews. Participants were encouraged to describe their blended learning experiences in their own words. We analyzed the interview data by generating codes, developing categories, and forming themes. Then, the resulting themes were interpreted and organized using the PCK, TCK, and TPK intersections of the TPACK framework as an analytical lens, rather than as a predefined coding scheme.

2.3. Participant Selection

We used a purposive sampling strategy to select undergraduate students to participate in our study. The students were selected based on the following criteria:

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They had participated in at least one blended learning course at HUST;

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They had various majors, ensuring diverse perspectives;

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They had completed online quizzes and attended both online and face-to-face sessions, ensuring that they had experienced all aspects of blended learning;

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They were diverse in terms of demographics, including gender, age, and duration of academic study.

Ultimately, we selected 24 undergraduate students to participate in our study, with their characteristics described in

Table 1. Sample characteristics.

Characteristic	Frequency	%
Gender
Male	18	75.0
Female	6	25.0
Age
19	15	62.5
20	9	37.5
Major
Chemical Engineering	4	16.7
Electronic and Telecommunication Engineering	4	16.7
Automation and Control Engineering	5	20.8
Mechatronics and Mechanical Engineering	3	12.5
Information Technology	4	16.7
Applied Mathematics	4	16.7

. The participant profile reflects the disciplinary and institutional context of the study. The sample was drawn from a technical university, where male students typically constitute a larger proportion of the population, particularly in engineering-related majors. This gender distribution was consistent with prior studies conducted in similar technical higher education contexts in Vietnam. Additionally, most participants were aged 19–20, corresponding to early undergraduate students who had recently completed blended learning courses.

2.4. Data Collection

We conducted semi-structured interviews to collect information about students’ experiences with hygiene and motivator factors in blended learning. The interviews took place in January 2025 at HUST, in a private office on campus, seeking to ensure a quiet and comfortable environment. Each session lasted 20–30 min and was audio-recorded, with participants’ consent, to ensure accurate transcription and analysis. During the interviews, we asked follow-up questions to clarify students’ responses. All data were securely stored to prevent unauthorized access.

2.5. Data Analysis

We applied a three-stage data analysis procedure: (1) condensing meaning units and formulating codes; (2) developing categories; and (3) developing themes [34]. In the first stage, all 24 interview transcripts were read in full and segmented into meaning units. These meaning units were condensed and summarized into 42 initial codes. Although the interview protocol was theoretically informed, codes were generated from participants’ descriptions and not from predefined theoretical categories. In the second stage, codes with similar meanings were compared and grouped into categories through constant comparison. Then, categories were interpreted as hygiene or motivator factors based on Herzberg’s two-factor theory and then mapped onto the PCK, TCK, and TPK intersections of the TPACK framework. As a result, the 42 codes were organized into 15 categories, including 6 categories at the PCK intersection (3 hygiene factor categories and 3 motivator factor categories), 5 categories at the TCK intersection (3 hygiene factor categories and 2 motivator factor categories), and 4 categories at the TPK intersection (2 hygiene factor categories and 2 motivator factor categories). In this phase, TPACK was used as an analytical lens through which to organize and interpret the results; it did not serve as a predefined coding framework. In the third stage, the 15 categories were synthesized into six overarching themes: three hygiene themes (unengaging teaching practices, inadequate digital learning infrastructure, and limited online interaction) and three motivator themes (active and relevant pedagogical strategies, engaging and accessible digital resources, and technology-facilitated autonomous, expressive, and creative learning work). These themes represented undergraduate students’ perceptions, interpreted across the PCK, TCK, and TPK intersections. At each stage, refinement was achieved through discussions within the research team. The results of the data analysis are shown in

Table 2. Results of interview data analysis.

Theme	Category	Code
(1) Pedagogical content knowledge
HF1: Unengaging teaching practices	Lecture delivery	- Unengaging online video lectures - Overly dense content in videos - Weak teacher pedagogical skills
	Group interaction	- Delayed feedback to online learners - Unequal group participation - Superficial discussions
	Class and group sizes	- Large class sizes - Large group sizes
MF1: Active and relevant pedagogical strategies	Active learning strategies	- Work-based learning - Situational learning (case-/problem-based) - Collaborative discussions
	Teamwork and collaboration	- Opportunities to develop teamwork skills - Connecting with new peers - Building relationships through teamwork - Instructor interest and involvement in student group tasks
	Instructor support and engagement	- Giving and receiving positive feedback from instructors - Friendly and approachable instructors - Dedicated instructors
(2) Technological content knowledge
HF2: Inadequate digital learning infrastructure	Presentation and multimedia quality	- Lengthy lecture PowerPoint slides - Large text density in PowerPoint slides - Unclear images in PowerPoint slides - Unattractiveness of multimedia in video lectures - Lack of captions in video lectures
	LMS usability and features	- Not yet fully utilizing the features of LMS - No online study reminder function - Unattractive LMS interface
	Technical infrastructure and devices	- Poor quality of internet - Limited skills of students in using new technologies - Low-performance personal smartphones - Poor quality of projectors in face-to-face classrooms
MF2: Engaging and accessible digital resources	Learning resource accessibility	- Diverse and rich learning resources - Media player accessible via multiple devices
	Engaging learning materials	- Information visualization/visual clarity - Transcripts and audio descriptions of multimedia
(3) Technological pedagogical knowledge
HF3: Limited online interaction	Forum and messaging interactions	- Inactive discussion forums - Off-topic group chats
	Utilizing technology and monitoring online learning	- Not using a variety of technologies - Lack of instructor online monitoring
MF3: Technology-facilitated autonomous, expressive, and creative learning work	Autonomous and expressive learning practices	- Exercising autonomy in learning activities - Opportunities for self-expression
	Technology-enabled interactive and creative learning formats	- Digital creativity tasks (producing learning artifacts using digital tools) - Interactive polling tools and anonymous Q&As

Notes: HF = hygiene factor, MF = motivator factor.

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To enhance the transparency regarding the analytical decisions underlying the results summarized in Table 2, variation in students’ accounts was examined and interpreted during the data analysis process. While the identified themes represented recurring patterns across the interview data, individual student experiences were not entirely uniform. During the analysis, some variation in their perceptions was observed. For example, although many students described pre-recorded lectures as monotonous or lacking instructor presence, a smaller number of participants noted that such materials were useful for self-paced learning. However, this perception reflects functional adequacy rather than motivational enhancement. In line with Herzberg’s two-factor theory, such features may prevent dissatisfaction by offering flexibility and convenience, but they do not inherently promote engagement, interest, or a sense of achievement. Therefore, pre-recorded lectures were conceptualized as hygiene factors, although some students reported certain benefits. Similarly, while limited online interaction was commonly perceived as a hygiene factor, some students viewed asynchronous discussion spaces as less intimidating and more flexible for participation. These differences did not constitute separate themes but rather reflected nuanced interpretations of shared learning conditions; they were not considered evidence of contradiction. They were considered during coding and category development but did not warrant the formation of separate categories or themes. Accordingly, the reported themes represent dominant and analytically robust patterns across the dataset, rather than demonstrating complete uniformity among individual experiences.

2.6. Intercoder Reliability

During the qualitative data analysis, intercoder reliability was ensured. This involved multiple researchers independently coding a subset of the interview data and then comparing their results to assess consistency in the coding process. In our study, three trained researchers independently coded all interview transcripts. After coding, all three researchers compared their results, discussing any discrepancies in the assigned codes and resolving them to achieve a consensus.

To further assess intercoder reliability, we used the Fleiss kappa statistic [35] to measure the agreement between coders for a total of 42 codes identified. The results of the intercoder reliability tests are shown in

Table 3. Fleiss’ kappa statistics for intercoder reliability.

Group	κ	Asymptotic			95% CI		Level of Agreement
		SE	z	p	Lower	Upper
Overall agreement on codes for hygiene factors	0.419 1	0.118	3.558	<0.001	0.412	0.427	Moderate
Overall agreement on codes for motivator factors	0.413 2	0.136	3.035	<0.001	0.405	0.422	Moderate

Note: Intercoder reliability was calculated separately for (1) hygiene-related codes (n = 24 codes) and (2) motivator-related codes (n = 18 codes), based on independent coding by three raters; SE = standard error; CI = confidence interval.

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As seen in Table 3, based on Cohen’s suggestions regarding the strength of agreement [35], Fleiss’ kappa statistic showed that there was moderate agreement between the three coders regarding the 24 codes obtained for hygiene factors (κ = 0.419, 95%CI: 0.412 to 0.427, p < 0.001). Similarly, there was moderate agreement between the three coders for the 18 codes obtained for motivator factors (κ = 0.413, 95%CI: 0.405 to 0.422, p < 0.001). Overall, the κ values were greater than 0.40, indicating adequate agreement between coders [35]. In this study, given the moderate level of intercoder agreement, Fleiss’ kappa statistic was used to enhance the transparency of the coding process, while the analytic rigor was further strengthened through iterative consensus discussions among the research team.

3. Results

3.1. Undergraduate Students’ Perceptions of Hygiene and Motivator Factors at the PCK Intersection

3.1.1. Hygiene Factor: Unengaging Teaching Practices

Many students voiced concerns about the quality of online lecture content, particularly the lack of engaging delivery. They felt that some recorded lectures lacked energy and variation, leading to boredom and disengagement. In video lectures, facial expressions were perceived as “unnatural” or “robotic”, reducing the sense of presence and connection with instructors. One student stated,

“The teacher’s voice in the video lectures was too monotonous—it didn’t make me want to listen.”

(Student 5)

Students reported that group activities were often poorly structured and characterized by unequal participation among group members. Several students described an imbalance in contribution, where active members carried the load while others remained passive. The lack of instructor feedback on group outputs further exacerbated their frustration caused by large class sizes and poorly formed groups. One student remarked,

“Sometimes our group had five or six members, but only two people were active. The rest were silent and just signed their names at the end. It didn’t feel fair.”

(Student 2)

Another added,

“Our instructor didn’t give us clear feedback after the group task, so we had no idea if we did well or what to improve.”

(Student 22)

3.1.2. Motivator Factor: Active and Relevant Pedagogical Strategies

Students appreciated instructors’ use of interactive and context-relevant teaching strategies. Problem-based learning and real-life case studies were frequently cited as engaging and intellectually stimulating. Several students appreciated problem-/case-based discussions or hands-on tasks that connected theory to real-world applications. One student shared the following:

“When we worked on real case studies, I felt like I was learning something useful for my future job.”

(Student 24)

Effective teamwork was described as a valuable learning experience, particularly when instructors provided guidance, assigned clear roles, and showed genuine interest in students’ progress. Instructors who were approachable and responsive to students’ needs significantly contributed to motivation. One student recalled,

“Our lecturer checked in on each group weekly. It made us feel like our work was meaningful, and we felt encouraged to try harder. Whenever we asked questions, the teacher answered in detail and gave examples. That made a big difference.”

(Student 12)

3.2. Undergraduate Students’ Perceptions of Hygiene and Motivator Factors at the TCK Intersection

3.2.1. Hygiene Factor: Inadequate Digital Learning Infrastructure

Students raised many concerns regarding the design and use of digital learning materials. The quality of multimedia in PowerPoint lectures was often poor, with blurry images, excessive text, and long video durations. One student described the following:

“The slides had too much information, and the videos just repeated the text. It felt like reading a textbook on screen. I ended up skipping the videos and just reading the slides.”

(Student 10)

The LMS platform used in courses was also a frequent source of complaint. Students highlighted the absence of study reminders, unattractive interface design, and underutilization of the system’s capabilities. One student explained,

“The LMS platform didn’t help me organize my learning. There were no reminders or indicators for upcoming deadlines. I missed a quiz once because I thought the deadline was the following week.”

(Student 5)

Additionally, technical infrastructure further complicated the learning process, as many students reported challenges with internet connectivity, low-performance smartphones, and outdated classroom projectors. Some students also indicated a lack of familiarity or skills in navigating new technologies, leading to additional stress and reduced learning efficacy. One student mentioned,

“Sometimes I couldn’t watch a full lecture without the video lagging or freezing. My internet is not great at home, and the platform didn’t have options to reduce video quality or download offline.”

(Student 9)

3.2.2. Motivator Factor: Engaging and Accessible Digital Resources

Students acknowledged the benefits of having accessible and varied learning resources in blended learning courses. Multi-device compatibility, such as the ability to access lectures on smartphones, tablets, or laptops, was also seen as a motivating factor. These features supported flexible learning schedules and allowed students to study when they had time. One student commented,

“I really liked that I could log in from my phone or laptop whenever I had a free moment. Even if I wasn’t at home, I could quickly check lecture slides. It gave me a sense of control over my learning, like I wasn’t tied to a specific time or place.”

(Student 14)

Students especially valued multimedia presentations that included visual enhancements, transcripts, and audio descriptions. One student noted,

“Having transcripts made it easier to study on the go, like when I didn’t have my earphones or couldn’t play audio in public. I wish more courses had that.”

(Student 23)

3.3. Undergraduate Students’ Perceptions of Hygiene and Motivator Factors at the TPK Intersection

3.3.1. Hygiene Factor: Limited Online Interaction

Students described a lack of interaction in online spaces as a significant barrier to engagement. Discussion forums, often embedded within LMS platforms, were described as “dead” or “ignored”. One student shared the following:

“I posted a question on the forum, and no one replied—not even the teacher. After that, I stopped trying.”

(Student 11)

Real-time communication channels (such as messaging apps) were more active, but they were also ineffective in facilitating meaningful academic discussions. As one student described,

“In our class group chat, there were too many off-topic messages. Important information got buried under jokes and memes. I had to scroll up a lot to find what the teacher posted.”

(Student 1)

Another common issue was a lack of monitoring or feedback on students’ online participation. Students felt that their progress was invisible to instructors. One student stated,

“If you missed two weeks of online tasks, no one would check in. You’re on your own.”

(Student 8)

3.3.2. Motivator Factor: Technology-Facilitated Autonomous, Expressive, and Creative Learning Work

Students described their learning experiences as more autonomous and expressive when technology-supported activities allowed them to contribute ideas in open and self-directed ways. In particular, the use of blogs and wikis enabled students to decide how to articulate their understanding, reflect on their learning, and co-construct knowledge over time. Several students highlighted that writing blog posts gave them flexibility in how they approached learning tasks and expressed their personal perspectives. Two students explained this as follows:

“Writing blog posts allowed me to organize my thoughts in my own way and reflect on what I had learned, rather than just answering fixed questions.”

(Student 11)

“Working on a wiki helped me contribute my ideas and also learn from others. I could edit and improve my work as I learned more.”

(Student 19)

Assignments that allowed students to express their creativity through digital tools, such as creating short videos, infographics, or interactive slides, were particularly motivating. These tasks gave students a sense of ownership over their learning and allowed them to express themselves in new ways. One student shared,

“We made a video for our project instead of writing a report. It was hard, but fun, and I learned a lot from the process.”

(Student 7)

Additionally, students also valued tools that provided real-time feedback, such as in-class polling apps or anonymous Q&A features. One student noted,

“I usually don’t speak in class, but when the teacher used live polls, I felt like my opinion counted. I could participate without being nervous.”

(Student 13)

4. Discussion and Conclusions

4.1. Theoretical Contributions

This study makes a significant theoretical contribution by combining Herzberg’s two-factor theory with the TPACK framework to explore undergraduate students’ experiences in blended learning, as shown in Figure 2. Through this integration, the study enables a nuanced understanding of the hygiene factors (which prevent student disengagement) and motivator factors (which enhance student active learning) in blended learning from the perspective of undergraduate students. Unlike previous research that primarily focused on one of these theories in isolation, our study integrates them: Herzberg’s theory, which is grounded in motivation psychology, is aligned with the TPACK framework, which emphasizes the interaction among technology, pedagogy, and content knowledge in educational contexts. This approach allowed for a comprehensive analysis of students’ perceptions of the roles played by both foundational conditions (hygiene factors) and intrinsic motivators in their blended learning experiences.

One notable contribution of this study is its explicit mapping of Herzberg’s hygiene and motivator factors onto the PCK, TCK, and TPK intersections of the TPACK framework. Three hygiene factors involved in blended learning were identified for the PCK, TCK, and TPK intersections. These were (1) unengaging teaching practices, (2) inadequate digital learning infrastructure, and (3) limited online interaction, respectively. Additionally, three motivator factors involved in blended learning were identified for the PCK, TCK, and TPK intersections. These were (1) active and relevant pedagogical strategies, (2) engaging and accessible digital resources, and (3) technology-facilitated creativity and achievement, respectively. Moreover, the mapping of Herzberg’s hygiene and motivator factors onto the TPACK framework provides new insights into the complex interplay between technology, pedagogy, and content. While Herzberg’s two-factor theory has been applied in various educational settings [21], this is one of the first studies to examine it specifically within the context of blended learning through the TPACK framework. The unique integration of the TPACK framework allowed us to consider how different intersections (PCK, TCK, and TPK) can influence student engagement, offering clear guidance with which instructional designers and educators can enhance the quality of blended learning courses.

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PCK-related insights into teaching practices in blended learning

This study contributes to the understanding of how PCK influences undergraduate students’ experiences in blended learning. Hygiene factors such as monotonous lectures, limited feedback, and poorly structured group work reduced student engagement. These results are consistent with prior research showing that ineffective pedagogical delivery undermines learners’ motivation and reduces the perceived value of content [26]. While blended learning allows for diverse teaching modalities, the present study reveals that students may disengage when pre-recorded videos lack emotional expression. Additionally, students shared frustration over unbalanced group work, whereby some members contributed while others remained passive. This imbalance was perceived as unfair and demotivating, especially when instructors did not provide feedback or monitor group dynamics. These concerns reflect previous research that has emphasized the importance of well-structured teamwork and continuous instructor support to foster student motivation [36].

Conversely, motivator factors within PCK include the use of active learning techniques, real-life problem solving, and instructor-led discussions. Students reported increased engagement when lessons included application-oriented tasks and when instructors took an active role in guiding group collaboration. These findings align with [18], which highlights the role of student-centered pedagogies in fostering motivation. The relevance of content is supported by the findings in [37], which note that real-world applicability and experiential learning enhance student motivation. Additionally, the role of instructor support, as identified here, mirrors the findings described in [36] regarding the critical influence of instructor–student relationships in blended learning environments.

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TCK-related insights into digital infrastructure and learning resources

TCK plays a pivotal role in blended learning environments, where digital tools are used to deliver subject-specific knowledge. In this study, several hygiene factors that hinder student engagement were identified, including low-quality multimedia materials, unattractive and underutilized LMS platforms, and inconsistent technical infrastructure. Students expressed frustration with overly dense slides, large text volumes, and video lectures that merely repeated text. Such frustration can be theoretically explained through the cognitive theory of multimedia learning, which emphasizes that learning effectiveness is reduced when instructional materials place a large cognitive load on students due to violations of core multimedia design principles. In our study, this reduced students’ willingness to engage with the content, aligning with previous research that stresses the need for high-quality, interactive multimedia in online learning environments [23]. Students also reported problems with the LMS platforms used in their blended courses. They expressed disappointment in the absence of useful features such as automated reminders or progress-tracking tools. These observations are consistent with the findings in [23], which indicated that technical limitations in LMS design can negatively impact user satisfaction. Similarly, [24] argued that inadequate technical infrastructure reduces students’ ability to benefit from the flexibility of blended learning.

In contrast, motivator factors within TCK include the accessibility and richness of digital resources, such as interactive visualizations, transcripts, and multi-device compatibility. Students reported feeling more motivated when digital resources were accessible across devices. Many students found value in multimedia content as it included captions and transcripts, which allowed them to learn more flexibly. These observations extend the findings in [25], which note the critical role of accessible and reusable learning objects in promoting autonomy and deep engagement.

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TPK-related insights into online interaction and technology-enhanced engagement

When discussing the intersection between pedagogy and technology, students pointed to the quality of online interaction as a major factor influencing their engagement. Many students shared disappointment in the lack of meaningful communication through forums and chat platforms. Forums embedded in LMS platforms were often described as “dead spaces”, where student questions went unanswered. Group chats, while more active, were cluttered with off-topic conversations, making it challenging to focus on learning. These concerns reflect the views expressed in [1], where the authors observed that poorly facilitated online environments could lead to superficial engagement and a reduced sense of academic community. Students also reported that, when instructors failed to monitor online activity or provide timely feedback, they felt “invisible” and disengaged. Such findings underscore the importance of pedagogical presence in technology-mediated contexts, as also noted in [1]. These findings can also be interpreted through the Community of Inquiry (CoI) framework, which conceptualizes meaningful learning in blended environments as the interplay among teaching presence, social presence, and cognitive presence. Students’ reports of inactive discussion forums, limited instructor monitoring, and delayed feedback reveal weaknesses in teaching presence that limit students’ cognitive engagement. The lack of meaningful online interaction observed in this study is consistent with the CoI framework, suggesting that insufficient instructional guidance can lead to superficial participation and a weakened sense of learning community in blended learning contexts.

In addition, students described intrinsically meaningful learning practices within the TPK domain. For example, blog- and wiki-based activities enabled students to articulate their understanding, reflect on their learning, and collaboratively construct knowledge over time. Students reported that producing digital learning artifacts, such as short videos, interactive presentations, or infographics, gave them a sense of ownership over their learning work. Furthermore, tools such as real-time polls and anonymous Q&A applications supported expressive and inclusive participation, especially for students who were less comfortable speaking in class. These technology-facilitated practices align with previous research suggesting that thoughtful pedagogical uses of technology can enhance engagement and equity by embedding autonomy, expression, and communication within learning activities [14].

4.2. Practical Implications for Blended Learning Design

Our study has several practical implications for the design of effective blended learning environments. It highlights the importance of addressing both hygiene and motivator factors in course design.

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Applying PCK to improve teaching practices and pedagogical strategies

To optimize blended learning environments, instructors should prioritize pedagogical clarity by integrating explicit instructional cues, varied vocal delivery, and a visible instructor presence in both live and recorded lectures. This requires not only the presentation of material in a coherent manner but also the incorporation of active learning strategies, such as the use of real-world case studies, problem-based learning, and group activities that encourage student–instructor interaction. These strategies allow students to apply theoretical knowledge in practical contexts, thereby enhancing their critical thinking and problem-solving skills. Additionally, providing timely and constructive feedback, alongside well-structured group tasks, plays a vital role in maintaining student engagement and promoting collaboration. Continuous monitoring from instructors ensures accountability and fosters a sense of responsibility among students.

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Applying TCK to strengthen digital infrastructure and resource design

The application of TCK in blended learning requires the seamless integration of technology with content delivery. Instructors must ensure that multimedia materials, such as video lectures, PowerPoint presentations, and online learning resources, are of high quality, engaging, and easily accessible. This includes reducing cognitive overload by redesigning digital learning materials, segmenting content into shorter, coherent units, minimizing redundant on-screen text, and aligning visuals with spoken explanations. Moreover, LMS platforms need to be optimized to improve their usability, providing features such as progress trackers, automated reminders, and easy access to study materials. These elements can significantly enhance student engagement by offering a flexible learning experience that accommodates different learning styles.

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Applying TPK to enhance online interaction and technology-supported engagement

The application of TPK in blended learning involves designing pedagogical strategies that are not only supported but enriched by technology. Instructors should enhance student engagement by creating technology-supported learning practices that promote autonomy, expression, and meaningful interaction. Instructors can integrate tools such as blogs and wikis to support reflective and collaborative learning. Blogs allow students to articulate ideas, reflect on learning experiences, and develop personal perspectives, while wikis enable collaborative knowledge construction through shared editing and revision. Additionally, real-time feedback tools, such as live polls and anonymous Q&A sessions, can enhance student involvement, particularly those who may be hesitant to speak in class. Creative digital tasks, such as producing short videos, infographics, or interactive presentations, further support expressive and creative learning practices among students. Through such designs, technology becomes an integral component in fostering a dynamic, interactive, and inclusive learning environment that supports intrinsically meaningful learning work.

4.3. Limitations and Future Research Directions

While this study provides important insights into undergraduate students’ experiences of blended learning, several limitations should be acknowledged. First, the participant sample reflects the institutional context of a technical university, where male students constituted approximately 75% of the population. Although this gender distribution aligns with the enrollment patterns reported in prior studies conducted at similar technical universities, it limits the transferability of the findings to more gender-balanced or non-technical higher education contexts. Future studies should include more diverse gender representations. Second, most participants were aged 19–20, representing early-stage undergraduate students. As a result, the findings may not fully capture the experiences of older students or those with greater academic or professional experience. Future research should examine whether the identified hygiene and motivator factors hold true across diverse disciplinary contexts. Third, the study was conducted within a Vietnamese higher education context, where cultural norms related to teacher authority, classroom interaction, and student participation may shape students’ learning experiences. This may limit the direct transferability of the findings to other national or cultural contexts. Future studies could replicate this research in different cultural contexts to explore how hygiene and motivator factors manifest differently in blended learning. Fourth, while qualitative methods provide an in-depth understanding of students’ experiences, future research could complement this with quantitative approaches to measure the prevalence and impacts of specific hygiene and motivator factors across larger and more diverse samples. Finally, as blended learning continues to evolve, it is essential to explore how new technological advancements, such as artificial intelligence and virtual reality, may impact the hygiene and motivator factors identified in this blended learning context. Future research should investigate how these emerging technologies can be integrated into the blended learning experience to enhance both the effectiveness of teaching and the motivation of students.