Motivation and Passion for Research in E-Learning: History
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Shoeb Saleh
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Rommel AlAli
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Yousef Wardat
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Mohammed Al-Qahtani
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Yasser Soliman
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Mamdouh Helali

The advent of the distance education system was a direct response to the challenges brought forth by the information and knowledge revolution in the modern era. To overcome the constraints of time and location, contemporary techniques and tools such as e-learning and digital technology are being employed in university education for conveying information to students. The effectiveness of this approach is contingent upon the design of the technological educational environment and the consideration given to its fundamental components. Additionally, a multitude of studies have emphasized the urgent need for interactive learning environments that actively engage students, foster their motivation to persist in learning, and augment their ability to apply the acquired knowledge in real-life situations.

  • distance learning
  • harmonious passion emotional obsession
  • self-regulation
  • knowledge management

1. Studies That Have Examined the Reciprocal Influences of Passion and E-Learning

In the same vein, prior research has explored the relationship between e-learning and academic passion among students. For instance, Hussein’s [1] study found a positive correlation between e-learning and academic passion [1]. Similarly, Youssef’s [2] study revealed that the pattern of reinforcement (immediate/intermittent) in a mini e-learning environment had a significant impact on academic achievement, passion, and reduced mental wandering among low and high self-efficacy education technology students [2]. Soares’ [3] study indicated that e-learning models had a high impact on the development of scientific passion and digital culture [3]. Additionally, Brik and Al-Jariwi’s study concluded that there is a statistically significant correlation between psychological distance in its various dimensions and the total degree of academic passion [4]. Furthermore, Greenberger’s study [5] examined the relationship between academic passion (consensual and compulsive) and face-to-face or online teaching and found that 95% of the study sample who studied online were enthusiastic about e-learning and had academic passion for online learning [5].

2. Studies That Have Focused on Self-Regulation and Knowledge Management in Distance Learning Environments

Yeh’s [6] study aimed to investigate whether meaning-making, self-regulation, and knowledge management (KM) competencies would interact with a 17-week KM-based treatment and influence creativity in e-learning. The results showed that meaning-making indirectly affected creativity through knowledge management, and self-regulation affected creativity directly and indirectly through knowledge management. Additionally, college students with a higher level of knowledge and ability to self-regulate benefited more from the training than their peers [6]. Similarly, Hu and Driscoll [7] conducted a study to examine the effects of self-regulated learning (SRL) strategy training on learners’ achievement, motivation, and use of the strategy in an enhanced web-based college success course. The results indicated that the training improved students’ overall course performance, completion of long-term tasks, and enhanced their self-satisfaction and perseverance [7]. In the same vein, Bell and Kozlowski’s [8] study aimed to identify the effect of adaptive guidance in enhancing self-regulation, knowledge, and performance in technology-based learning. The results revealed that adaptive guidance had a significant impact on the nature of trainees’ study and practice, self-regulation, and acquired knowledge and performance. Furthermore, adaptive mentoring led to significant improvements in the acquisition of basic knowledge and performance abilities early in training, and significant improvements in the acquisition of strategic knowledge and strategic performance skills later in training [8].

3. Studies That Have Examined the Impacts of Emotion and the Dual Model of Passion

Luxford et al. [9] employed path analysis to explore the correlation between harmonious and sympathetic cravings for video games, self-regulation, and overall well-being. Their findings revealed that individuals exhibiting higher levels of harmonious video game cravings demonstrated greater self-regulation, whereas those with elevated sympathetic cravings had lower self-regulation. Additionally, the study indicated that self-regulation played a more comprehensive role in explaining the interplay between emotion and well-being [9]. Similarly, Rihtarić, et al. [10] conducted a study to investigate the connection between harmonious and obsessive cravings for video games, school behavioral interaction, and their indirect relationship with school engagement through gaming time. Utilizing the binary emotion model, their pathway analysis unveiled direct effects of both harmonious and obsessive cravings on school behavioral reactivity, along with indirect effects through time spent playing video games. The results indicated that higher harmonious passion was linked both directly and indirectly to greater school engagement, albeit with some negative influence due to increased gaming time. Conversely, higher levels of obsessive passion were associated with reduced school involvement directly and indirectly due to prolonged gaming [10].
In contrast, Eckley et al. [11] focused on examining the interplay between psychological needs fulfillment, educational factors, and students’ expectations of future grades amidst the COVID-19 pandemic. Through structural equation modeling, they found that meeting higher needs significantly predicted engagement in educational factors, which in turn fostered resilience, motivation, and effective learning mechanisms. Positive mutual influences were identified between academics and students across various learning pathways. Reciprocal determinism emerged as the most intrinsically linked factor to predicted scores, shedding light on the interrelationships between emotion, trait conscientiousness, and self-regulated learning [11]. Similarly, Kaluge et al. [12] analyzed the adaptation of emotion measurement among Japanese literature students engaged in online learning in Indonesia. Their investigation considered five criteria—time, value, emotion, identity—along with student characteristics (gender and age) and attendance conditions (first-year vs. advanced year). Their findings unveiled differing passion dimensions, with first-year students showcasing higher harmonious passion and second-year students displaying greater obsessive passion [12].
Lastly, Yeh and Chu [13] aimed to categorize patterns of academic passion in e-learning by identifying four emotion types (internal and external harmonious passion, internal and external obsessive passion). The study explored connections between these emotions, self-regulation, and knowledge management in e-learning. Their structural equation modeling demonstrated interrelations among the four passion types, with learning-mediated self-regulation influencing the connection between academic passion and knowledge management. Notably, consensual passion held a more substantial role compared to compulsive passion in e-learning, influencing learning management among undergraduate students during the e-learning process [13].
The existing body of literature and research in this domain has primarily concentrated on investigating the reciprocal influence between passion and e-learning, as well as exploring the dynamics of self-regulation and knowledge management processes within distance learning environments. Additionally, these works have delved into examining the diverse impacts of emotions and the dual model of passion on distance learning experiences. On the basis of the preceding discussions, it can be deduced that the most noteworthy aspect of this particular study lies in its assessment of students’ learning emotions and the organization and management of knowledge, which can serve as indicators of the distance learning system’s quality [2][4][6][9][11][12][13].

4. Theoretical Framework

A distance education system comprises various dimensions and elements that significantly contribute to its effectiveness, such as the learning environment, learning motives, passion for research beyond knowledge, learning organization, and learning management. Merely designing educational courses for e-learning and distance learning environments is no longer adequate to achieve desirable learning outcomes that satisfy students. Instead, it is crucial to consider learners’ motivation for learning. In this regard, Kim and Firck’s [14] study aimed to investigate the factors that stimulate and motivate students in e-learning from a distance, their level of motivation and perseverance, and how it changes during academic courses. The study concluded that several fundamental factors affect the level of motivation and learners’ continuity in learning effectively. Notably, perceived relevance, reported technology competence, and age emerged as the primary determinants of motivation to commence SDEL. Subsequently, during the SDEL process, perceived quality of instruction and learning (specifically, the belief that e-learning is suitable for one’s needs) and the initial motivation to begin were identified as the most influential factors in sustaining motivation. Moreover, the study established a noteworthy link between motivation during SDEL and positive changes in overall motivation. This, in turn, proved to be a significant predictor of learner satisfaction with SDEL. Consequently, the study’s findings shed light on essential instructional design principles that effectively sustain learner motivation in the realm of SDEL [14]. Furthermore, researchers will discuss the philosophical frameworks for the passion of learning and the essential differences between passion and motivation, as well as self-regulation and knowledge management. Researchers will also examine the concept of the dual model of emotion and the structural relationship between emotion and its impact on knowledge management processes through the mediating role of self-regulation.

5. The Philosophical Frameworks for the Emotion of Learning and the Distinction between Passion and Motivation

According to Vallerand [15], passion refers to the driving force that motivates individuals to engage in a specific activity. It is the underlying motivation that inspires individuals to exhibit dedication, enthusiasm, and admiration towards an activity, concept, or person, and encourages them to invest regular time in it. From a philosophical perspective, passion is an essential human experience that provides individuals with the psychological energy to engage in activities that hold value for them. Without passion, individuals may struggle to find meaning in their lives [15]. Passion also plays a crucial role in enhancing individuals’ participation in the activities they are interested in, as highlighted by Curran Hill, Appleton [16][17].
Passion is often linked to motivation, curiosity, lifelong learning, self-efficacy, and a love of learning, but it is distinct from these concepts. Passion and self-efficacy are interconnected in a complex and reciprocal relationship [18]. Passion fuels motivation and perseverance, leading to mastery experiences that enhance self-efficacy. In turn, increased self-efficacy reinforces passion, resulting in continued commitment and achievement in the domain of interest. This interplay between passion and self-efficacy is instrumental in driving individuals towards success and personal fulfillment in their chosen pursuits. While motivation and passion share a close relationship [18], Vallerand [19] has sought to draw distinctions between the two concepts. Motivation serves as a theoretical construct encompassing internal and/or external influences that trigger, guide, intensify, and sustain behavior. According to this perspective, individuals are reactive entities responding to internal or external stimuli. In contrast, proponents of emotion theory perceive individuals as proactive beings who actively seek meaningful interactions with their environment to lead a purposeful life. Vallerand [19] posits “Passion necessitates a unique bond with an activity one holds dear. However, unlike intrinsic motivation, it mandates that the activity holds personal significance and contributes to one’s sense of identity to qualify as passion”. Consequently, a tennis player might be motivated to play due to their affection or fascination for the sport, yet their passion arises when tennis becomes an integral part of their identity [19].
Furthermore, passion assumes particular importance for a select few activities that propel researchers to thrive in life (e.g., a professional tennis player) due to its responsiveness, curiosity, enthusiasm, and unwavering commitment [20].

6. The Dual Model of Emotion in E-Learning Environments

Vallerand et al. [21] proposed a theoretical model known as the Dualistic Model of Passion to study individuals’ passion for activities. This model comprises two dimensions: harmonious passion, which arises from self-independence and willingness to engage in activities that align with the individual’s personality. It stems from a controlled inner feeling that allows the individual to freely and voluntarily pursue their passion activities without feeling pressured. This type of passion is characterized by a balanced integration with other aspects of an individual’s life, without causing any conflicts. On the other hand, obsessive passion results from planning a specific action that is subject to control, driven by an uncontrolled inner feeling that dominates the individual’s emotions when engaging in passionate activities on a repetitive and organized basis. This type of passion is characterized by internal pressures that compel the individual to engage in the activity, potentially leading to neglect of other essential activities, and causing conflicts between their passionate activity and other life domains [21].
Vallerand et al. [22] introduced innovative categories of emotion in the binary model of emotion, but did not provide clear indicators for harmonious craving, compulsive craving, or obsessive-compulsive disorder [21]. Previous studies have identified that internal or interpersonal factors such as curiosity, interest, and an internal need for self-improvement enhance an individual’s passion for learning. Conversely, external or interpersonal factors can significantly influence students’ eagerness in the context of e-learning [23][24]. Hence, in the context of e-learning, both harmonious and compulsive or obsessive cravings can be influenced by internal and external factors. Among the internal factors that influence harmonious craving, there are those that express controllable and harmonious emotions derived from enjoyment and satisfaction during interactions with others. Furthermore, external factors can influence harmonious craving, which expresses the harmonious and controllable emotion derived from self-designed enjoyment and satisfaction during interactions with others. In contrast, obsessive or compulsive craving is influenced by a group of internal factors, namely, excessive and uncontrollable cravings for an activity derived from internal forces such as impulsive and ego-centered thinking during interactions with the activity. Additionally, obsessive craving is affected by a group of external factors referring to excessive and uncontrollable passion towards an activity derived from external forces such as pressures and commitment during interactions with others [13].
It is worth noting that there are indicators of learners’ practices of harmonious passion in e-learning environments. For instance, learners tend to use e-learning to keep updated with the latest information, access rich educational materials and information that align with their competencies and meet their needs, and stimulate their ideas and learning through interactions with others. On the other hand, there are indicators of learners’ emotional obsessive practices in e-learning environments. For example, learners may feel uncomfortable when they fail to complete their e-learning requirements immediately after waking up, and they may find life boring if they do not use e-learning interfaces that day. They may also struggle to control their impulses to use e-learning, and usually use it only under the pressure of task deadlines. Additionally, they may feel obligated to use e-learning because their friends frequently learn through its interfaces [25].

7. Organizing and Managing Knowledge in E-Learning Environments

Self-regulation and knowledge management are essential steps and actions that learners can plan and adapt to organize and manage their learning effectively. These steps can help learners acquire information through their personal learning environment and smart assistant, ultimately leading to achieving their educational goals and improving their learning outcomes [26]. Self-regulation refers to a dynamic process through which learners construct their own learning activities by employing relevant cognitive and behavioral strategies. Within self-regulatory learning strategies, individuals utilize various techniques for acquiring knowledge, including actions such as organizing and transforming information, maintaining and overseeing records, and establishing learning objectives. A crucial aspect of self-regulation involves the capacity to monitor and control the learning processes themselves [27].
In contrast, knowledge management constitutes a systematic undertaking wherein learners actively generate knowledge through interactions with their environment. This process encompasses a range of competencies associated with acquiring and retaining knowledge, applying it in practical contexts, sharing knowledge with others, utilizing acquired knowledge effectively, incorporating new knowledge, and even generating original knowledge [28].
Indicators of learners’ practice of knowledge self-organization processes in e-learning environments include several factors, such as their ability to save essential information or links that help them identify the content they need, their capacity to choose e-learning interfaces that provide relevant information, their ability to adjust their search methods to obtain useful information, and their ability to adjust their criteria for choosing e-learning interfaces to find the ones that make them feel most comfortable when learning. Additionally, indicators of learners’ knowledge management practices in e-learning environments include obtaining information through search engines (such as Google and Yahoo), downloading static information (such as words and signs) from reviewed websites, and actively participating in e-learning communities (such as bulletin board systems, Facebook, etc.) to access important and current information.

8. The Structural Relationship of Emotion and Its Impact on Knowledge Management Processes through the Mediating Role of Self-Regulation in Distance Learning Environments (the Proposed Model)

The current research proposes a model that illustrates the structural relationship between emotion and its impact on knowledge management processes in distance learning environments, with the mediating role of self-regulation. The research proposes a hypothesis that suggests self-regulation might serve as an intermediary between emotion and knowledge management in the context of e-learning. Additionally, it postulates that passion could impact self-regulation within the realm of e-learning. However, it is important to note that passion alone may not suffice for achieving favorable learning outcomes unless learners effectively oversee their learning process. The self-regulation of learning encompasses three key components: the application of self-regulatory learning strategies, response to self-directed feedback regarding learning effectiveness, and interconnected motivational mechanisms. This framework is closely intertwined with the ability to establish learning objectives, as well as monitor and control the processes of learning [27].
Consequently, individuals who actively engage in self-regulation demonstrate a heightened involvement in their learning, taking proactive steps to seek out information as needed. This proactive approach nurtures self-awareness and a knowledgeable stance toward learning methods [29]. Therefore, self-regulation likely assumes a pivotal role as an intermediary factor that strengthens the impact of emotion on knowledge management within the e-learning milieu. Moreover, individuals exhibiting well-aligned passion may possess improved self-regulation skills, thereby facilitating effective knowledge management. Conversely, those harboring an affective obsession might impede self-regulation, potentially resulting in a mishandling of knowledge during the e-learning process.
The proposed model of the structural relationship between emotion and its impact on knowledge management processes through the mediating role of self-regulation is depicted in Figure 1.
Ejihpe 13 00114 g001
Figure 1. The proposed model of the structural relationships of emotion and its impact on knowledge management processes through the mediating role of self-regulation.
Figure 1 illustrates the proposed model of the structural relationship between emotion and its impact on knowledge management processes through the mediating role of self-regulation in distance learning environments, based on various indicators of the processes of learning emotion, organization, and knowledge management. The figure demonstrates that learning emotion, including harmonious passion and emotional obsession, plays a crucial role in influencing the processes of organizing and managing knowledge in distance learning environments. The proposed model assumes that self-regulatory processes, with their dimensions such as retrieving, organizing, controlling, scheduling, and efficient time management, will function as a mediator for the effects of emotion on knowledge management, and provide a distinctive contribution to explaining individual differences in the processes of acquisition, application, participation, formation, and knowledge management in a secure distance learning environment.

This entry is adapted from the peer-reviewed paper 10.3390/ejihpe13090114

References

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