Open Networked Learning: A Personal Journey and Lessons Learned

As a university teacher, I took charge of several large, mandatory courses with an online format to cater to a considerable student population. One such course even had annual registrations around a thousand. The courses were initially moved online due to its ability to support large student numbers and offer flexible and accessible learning through extensive teaching resources. However, a high dropout rate posed a major challenge for these online courses. As these were mandatory courses, students who dropped out had to re-enroll in the subsequent terms, further inflating the intake numbers.

While I had completed numerous pedagogical courses as a part of my employment agreement, they inadequately addressed the issue of high dropout rates in online learning. To bridge this gap, I decided to attend the “Open Networked Learning” course offered by Aalto University. Before this, I had used multiple ‘Plan, Apply, Check, Act’ (PACA) cycles – a continuous improvement tool for process enhancements – to improve the course design and organization, which somewhat lowered the dropout rates. My main objective for attending this course was to deepen my pedagogical knowledge, understand the root cause of the high dropout rate better, and possibly enhance the learning outcomes for my students.

The course surprised me initially by its focus on problem-based learning using the FISh (Focus-Investigate-Share) model, considering it was attended by global educational professionals. But this approach seemed justifiable as we delved deeper. The course started by discussing the reasons for hesitations toward completing online courses, touching upon aspects like identity representation in online interfaces. I found myself particularly interested in the motivational factors influencing such decisions. I looked into the “Uses and Gratification Theory” known for uncovering motivations behind media consumption choices and observed its relevance to online media consumption. I found the links between the Expectancy-Value Theory of motivation and decision-making intriguing. The realization that participation in online platforms could decrease due to self-efficacy concerns and the perceived value of outcomes not meeting expectations was insightful.

The course then moved on to the benefits of openness in the educational context, collaborative learning’s advantages, and the role of course design in student persistence. While these subjects could be viewed from various perspectives, I decided to keep examining them from a motivational standpoint. A significant hurdle to the wide adoption of online and open educational practices appears to be “digital burnout”. This stems from a lack of skills, self-efficacy concerns, and struggle with emotional regulation. So, while considering open educational practices, the motivation levels of both teachers and students must be kept in mind. Students and teachers likely discontinue the activity if they do not receive adequate guidance on utilizing and gaining from open educational practices and thus, lose motivation.

Another question that arose was how to foster collaboration in online platforms to reduce dropout rates. The FISh model greatly assisted in facilitating mechanisms for collaborative learning, like knowledge elicitation and grounding, thus heightening gratification. This leads to a sustainable decision cycle pushing task completion as shown below.

The key take-away from this diagram is the importance of setting achievable goals at the onset of any task. Otherwise, the obtained gratification can fall short of the desired expectations, which then leads to a decision to drop out. Hence, online courses should be structured to reflect the shared understanding of course objectives among the target audience and organizers. Every element of the course, from the overall structure down to individual sections and activities, should have clear outcomes. If these are not in place, the persistence of participants is guided by their goal orientation and self-determination when factors outside of their control emerge.

To sum up, the shift to online learning comes with a unique set of challenges and opportunities as explained in the course on open networked learning. My critical takeaway is the crucial role of clarity, achievable goals, and an aligned understanding across all stakeholders in promoting student persistence. The successful shift to effective online and open educational practices requires maintaining motivation, providing sufficient resources, and integrating well-defined strategies and methodologies comprehensively. In particular, institutional support for both teachers and students is paramount. Hence, as our understanding of online pedagogy grows, these considerations will remain integral to ensuring quality education in the digital era.

Motivation and Dropout Rates in Online Courses

In today’s society, our basic physiological and safety needs, as per Maslow’s hierarchy, are mostly satisfied. Consequently, it is challenging to argue that we are making decisions to attain a task or goal to fulfill our low-level needs. Instead, we seek to satisfy higher needs such as  (see, e.g., Uses and Gratification Theory ):

  1. Cognitive needs: Providing new knowledge, information, and facilitating a better understanding of the world.
  2. Affective needs: Offering aesthetic and emotional experiences.
  3. Integrative needs: Enhancing confidence, status, and credibility.
  4. Social needs: Strengthening relationships and fostering social connections.
  5. Relaxing needs: Providing an escape from responsibilities or promoting self-awareness.

When we set a goal to achieve a task, we assess two aspects of possible outcomes: 1) we expect to achieve a certain outcome with some attribute that is significant to us and 2) we assign a value to the outcome (and its gratification). The product of these two factors is known as instantaneous motivation, which dictates our decision to attend the task. Our initial decision to attending a task is based on our best guess. On the other hand, our decision to  continue with the task is a repeated assessment cycle of outcome expectancy and its reevaluated value of achieved or probable gratification (see the work by Rayburn II and Palmgreen) as shown below.


Tasks or activities that offer instant gratification usually have more appeal as they do not require long-term commitment or extra cognitive load to overcome other needs such as relaxing. However, delayed gratification is often more rewarding as it is integrative and socially valued. The difference between these two types of gratification is related to different happiness hormones, as recent studies by Kapetaniou et al. and Gao et al. show and revalidate the earlier results by McClure et al.

The online course dropout rate is relatively high, and several studies aim to understand the underlying reasons for students’ decisions to abandon the course. According to Tinto, who studies higher-education persistence, students have goals that are a combination of social or academic motives. Persistence in achieving these goals occurs when motivation is retained and nurtured continually as shown below.


For online courses, the most widely accepted reason for low retention rate is lack of social interactions. However, the study by Amaijde et al. summarizes that the most prominent, and also logical reasons for drop out online courses as

  1. Dissatisfaction with the learning environment: the learning environment does not meet with the students expectations in quality or method,
  2. Expected outcome incompatibility: divergence between student’s interests and structure of the course,
  3. Low confidence in distance learning: prejudice about the teaching phenomenon,
  4. Lack of time: personal — situational factors take precedence over academic goals,
  5. Insufficient back ground knowledge or skills: in sufficient self-efficacy,
  6. Feeling of isolation: nature of the online teaching might create a sense of lack of social interactivity, which result low emotional regulation level,
  7. Feeling of overwhelmed: improper course design colliding with poor time management inevitably creates feeling of overwhelmed,
  8. Hidden cost: external factors such as work or family may force financial decisions.

The aforementioned factors can be classified in the following groups:

  1. Goal mismatch: 1, 2 and 3
  2. Self-efficacy: 4, 5 and 7
  3. Social interactions (relationships): 6
  4. External factors:  4 and 8

These factors are not always within the student’s control and can lead to demotivation according to attribution theory. However, the gratification approach of attending a task or activity shed some light on how to improve students motivation.

The first group of drop-out reason is the “goal”. The goal orientation theory postulates that individuals adopt either mastery or performance orientation when attaining a learning task. A discord between personal goals and the objectives of a task can lead to a lack of motivation to engage in the task. For example, a performance-oriented person might decide to give up if the task evaluation does not permit comparison with respect to other people attaining the task. On the other hand, a mastery-oriented person assesses the obtained gratification based on cognitive gratification and might decide to give up when the task is not challenging. Since the mastery orientation is usually increased with experience, courses must be designed differently when they are targeted to higher degrees (mastery) and lower degrees (performance).

Self-determination theory (SDT) postulates that motivation dips when three fundamental innate needs are unfulfilled: autonomy (the need for choice and control), competence (the need for self-belief in one’s abilities), and relatedness (the need to form and sustain satisfactory relationships with others). If we ignore external factors, SDT is prominently recognized in academic literature, especially noted by Badali et al. ., as the prevailing explanation for students’ motivation to complete an online course.  In this perspective, students’ can be motivated by i.) recognizing and supporting their students’ choices, encouraging self-initiation, and minimizing control; ii.) structuring courses in a way that allows students to progressively gain skills and understanding, and slowly stretching their abilities; and iii.)  encouraging interactions and collaborations between them.

One interesting observation is how self-determination needs are modified among successive cycles of sought and obtained gratification. As the gap between sought and observed gratifications decreases, the need for autonomy increases, whereas the need for relatedness decreases. This might be due to consistent satisfaction of the competence need. Therefore, motivation also depends on addressing different self-determination needs consistently but also in a suitable order.

In summary, we persist in attending a task (or activity) if we overcome the temptation of attaining tasks (or activities) that provide instant gratification. Once the initial decision of attaining a task (e.g., attending a course) is made, we must find a suitable environment to execute the task so that our long term goal is supported by the short-term tasks defined for us. This is also valid for students attending online courses. Course designers must address a range of reasons for dropping out, including not only a lack of social interaction but also other factors like goal mismatch and self-efficacy. By designing courses that meet students’ fundamental needs in timely manner according to their gratification evaluation cycles, we can help them stay motivated and achieve their goals.


Understanding Collaborative Learning: Cognitive Mechanisms and Factors for Success

Rochelle and Tesley define collaborative learning as a “coordinated and synchronous activity that results from a continuous attempt to construct and maintain a shared conception of a problem.” This succinctly summarizes “two or more people’s attempts to learn something together.” Although these definitions are not conflicting, they shed light on different aspects of collaborative learning.

Defining what “learning” means is important before delving into the details of collaborative learning. Dillenbourg defines it as “performing some activities (reading, building, experimenting, listening, predicting, etc.) which trigger some cognitive activities (deduction, induction, abduction, analogical reasoning, association, etc.) that result in learning or understanding.” Learning ultimately takes place at a personal level – collaborative learning doesn’t provide a recipe for knowledge construction, but it does involve cognitive activities like knowledge elicitation, grounding (explanation, internalization, and/or appropriation), and conflict resolution that can increase the likelihood of successful learning and improve learners’ understanding of the world.

Collaborative learning involves attempting to solve problems together. In a learning setting, the “problem” might be generalized as “solving a defined problem together,” which can be measured in terms of improvement in problem-solving skills and/or quality/level of elicited knowledge. Collaborative learning is, therefore, a side-effect of “joint problem-solving,” which depends on several crucial factors as identified by  Dillenbourg, shown in the figure.

For successful collaborative learning, participants must share a goal of solving the defined problem at the very least. Differing agendas are likely to cause coordination problems and jeopardize the shared objective. A successful shared goal is built on symmetrical group dynamic perception, including symmetry in knowledge level, status, or participation level. Mild asymmetry in knowledge level is desirable for activating collaborative cognitive mechanisms, but large asymmetry is likely to lead to asynchronous interactions, which prevent triggering conflict resolution, explanation, appropriation, or internalization mechanisms.

Vertical division of work might emerge in an environment where there is asymmetric status; low-level tasks might be performed by some group members, while high-level tasks (e.g., managerial tasks) might be performed by high-status members. Asynchronous interactions favor cooperation rather than “learning together.” Thus, horizontal division of labor requires synchronous interactions, making it more likely to trigger collaborative cognitive mechanisms.

Collaborative cognitive mechanisms are most likely to be triggered when interactions are negotiable, indicating participants’ willingness to argue their standpoint, justify their views regardless of their authority, attempt to convince, share/receive feedback, and reflect on their knowledge level. Interpersonal dynamics pose one of the obstacles to successful collaboration, partly due to participants’ motivation for attaining the task. Performance-oriented participants tend to have egocentric behavior, while mastery-oriented participants optimize the required cognitive effort since learning is personal and collaboration requires activating additional cognitive mechanisms. For either types of the motivation, collaboration bring reduced cognitive load, and is a driving force to attain the collaborative task. Therefore, successful collaborative learning can be achieved by understanding and mitigating the factors that prevent reduced cognitive load, such as coordination, time management problems, and managing interpersonal dynamics.

In conclusion, collaborative learning is a powerful tool for enhanced learning outcomes and problem-solving abilities. It requires coordination among participants, negotiability, and an environment that supports synchronous interactions that promote the triggering of collaborative cognitive mechanisms. However, maintaining the harmony of collaboration can be challenging, and participants must have a shared goal for successful collaboration. Symmetry in knowledge level, status, and participation among collaborators can further reinforce the attainment of this shared objective. It is essential to note that the success of collaborative learning is highly dependent on the quality of interactions, interpersonal dynamics, and effective communication within the group. Overall, the benefits of collaborative learning make it a favorable approach for learning and problem-solving tasks that require multiple perspectives and diverse solutions.

Topic 2: Role of motivation in adopting Open Educational Practices

In this post, I examine the role of motivation in adopting Open Educational Practices (OEP) by teachers and students. I use the theoretical frameworks of Self-Determination Theory, Attribution Theory, and Goal Orientation in the context of OEP adoption and reflect upon their implications on addressing the challenges related to OEP adoption, such as lack of resources, institutional support, and perceived benefits. Additionally, I examine the potential benefits of Artificial Intelligence (AI) in personalizing learning experiences and providing analytical insights into student performance. I conclude that addressing motivational challenges and incorporating AI-powered tools can enhance the adoption of OEP and create a more inclusive and accessible educational system.


The evolution of information and communication technologies has reached a point where educational resources are readily accessible online, anytime, anywhere. This has catalyzed the development of Open Educational Practices (OEP); an embodiment of inclusive and accessible learning through collaborative pedagogy and teaching resources leveraged by participatory technologies. OEP is rooted in Open Educational Resources (OER), defined by UNESCOas learning materials freely available without any access, adaptation, or distribution restrictions. Consequently, OERs are not solely free, but also permit users to revise, remix, reuse, retain, and republish the content. This flexibility has broadened educational access, fostering a more inclusive and collaborative learning approach, enabling individuals to reach their educational ambitions, and encouraging lifelong learning.

Nonetheless, OEP has its challenges. A recent review by  Adil et al.. exposed several obstacles faced by OER users. These span from a lack of resources – including insufficient institutional support regarding equipment, skill development, policy formation, usage rights, and time for locating and adapting OERs – to impediments towards widespread usage. Barriers to OEP adoption include issues such as blurring of private and academic life boundaries and contextual collapse, which might also lead to “digital burnout“.

It is now established that extensive exposure to digital tools, constantly keeps the brain in multitasking mode, which creates a constant state of stress results in emotional weariness, a rise in negative emotions, digital deprivation, and decreased professional efficacy. A study by Yung and Du revealed that the primary cause of digital burnout in the educational realm is the lack of emotional regulation–the process of choosing, altering, and expressing emotions. Other contributing factors include lack of competence and concerns of self-efficacy, which stresses emotional regulation and potentially lead to digital burnout. Consequently, these complications discourage teachers and thereby limit the adoption of or observed benefits OEP in terms of improvement in learning achievement, as articulated in recent analysis by  Tlili et al.

This aforementioned conclusion constitutes one aspect of many resulting observations. The research identified other influencing factors such as course subject, educational level, and geographic location of learners. For example, OEP application in certain subjects, Asian countries, and in professional development courses has a positive correlation with successful learning outcomes. Therefore, invested and motivated educators can significantly harness OEP to boost their teaching efficacy, while lack of such dedication does not yield the potential OEP benefits. From a student’s perspective, motivation can be assessed using drop-out rates from Massive Open Online Courses (MOOCs), as most MOOCs incorporate OEP principles. Wang et al.‘s study established positive links between retention rates and factors like course design, presentation quality, difficulty level, and learner self-determination. Nonetheless, OERs and MOOCs alike grapple with challenges such as high drop-out rates, reducing utility despite their cost-free nature. Therefore, it is crucial to carefully consider both teacher and student motivation in order to maximize OEP’s potential benefits in education.

Self-determination theory (SDT), attribution theory, and goal orientation theory provide insightful explanations for the lack of motivation observed within some teachers and students. SDT hypothesizes that motivation dips when three fundamental innate needs are unfulfilled: autonomy (the need for choice and control), competence (the need for self-belief in one’s abilities), and relatedness (the need to form and sustain satisfactory relationships with others). The attribution theory suggests that individuals assign their successes or failures to either personal efforts or external circumstances. Feelings of demotivation may arise if they perceive their success or failure as the result of uncontrollable external circumstances. This theory also advances the idea that redirecting attributions of success or failure from external to personal factors can bolster intrinsic motivation. The goal orientation theory postulates that individuals adopt differing learning approaches, including a focus on mastery or performance. A discord between personal goals and the objectives of a task can lead to a lack of motivation to engage in the task.

Teacher motivation

The lack of motivation among teachers to embrace new educational practices such as creating, utilizing and redistributing Open Educational Resources (OERs) and designing and implementing Massive Open Online Courses (MOOCs) poses a substantial barrier to the widespread adoption of open educational practices (OEP). SDT  proposes that one’s motivation and personal growth are directly related to how much they are naturally driven to take up tasks without external influences. As such, efforts to encourage teachers to adopt OEP should focus on cultivating their intrinsic motivation. This can be achieved by providing professional development opportunities that evoke their interest and relevance in Open Educational Resources and Massive Open Online Courses. Additionally, showcasing practical examples of successful implementation of these resources can also boost their confidence and ultimately their motivation to adopt these new practices. The immediate challenge is to create a supportive environment that appreciates and fosters curiosity, exploration, and innovation among teachers. Fostering a sense of self-efficacy and competence in embracing new educational practices will be the key to overcoming this barrier.

In attribution theory perspective, teachers may feel demotivated and not willing to adapt to OEP if they view their task’s success or failure is due to external circumstances they cannot control, such as inadequate resources, lack of support from relevant authorities, or insufficient training. To overcome this, there is a need to change their perception of control by providing necessary resources, support, training, and timely feedback. Attribution theory suggests that re-attributing success or failure to internal factors can enhance intrinsic motivation and promote the adoption of new teaching practices. Therefore, it is essential to encourage teachers to perceive their work’s outcome as within their control.

Teachers’ lack of motivation may be due to a misalignment between their goals and OEP’s objectives. For instance, teachers with a performance orientation may not feel motivated to embrace OEP if they perceive it as too time-consuming, require too much effort, or without the promise of immediate benefits or rewards. It is thus essential to align OEP with teachers’ personal and professional goals and show how these practices can enable them to reach their targets. Additionally, providing adequate training, support, and resources to minimize potential barriers could enhance teachers’ motivation to embrace OEP. Therefore, by aligning OEP with specific job responsibilities and career development opportunities, teachers might develop an incentive to integrate OEP into their teaching practices.

In summary, better OEP adoption is only possible if the university management shifts the job descriptions by providing training opportunities to practice using and adopting OERs, and also use these as a metric for promotion.

Student motivation

Self-Determination Theory (SDT) is prominently recognized in academic literature, especially noted by Badali et al. ., as the prevailing explanation for students’ motivation to complete Massive Open Online Courses (MOOCs). In the context of Open Educational Resources (OER)-based courses, the SDT suggests that learners’ determination increases when they hold the autonomy to sculpt their own educational journey. OER-focused courses bolster competency by offering students a variety of avenues to explore, learn, and develop their prior knowledge, although we are still on the verge of witnessing fully personalized courses. Via involvement in open courses, learners can establish connections with their counterparts and field experts through dynamic interaction and collaboration, acting as a robust stimulus incentivizing their thirst to learn and disseminate their knowledge. In this perspective, students’ can be motivated by i.) recognizing and supporting their students’ choices, encouraging self-initiation, and minimizing control; ii.) structuring courses in a way that allows students to progressively gain skills and understanding, and slowly stretching their abilities; and iii.)  encouraging interactions and collaborations between learners. On the whole, the SDT framework serves as an insightful perspective for comprehending students’ motivation towards participation in OEP-based coursework.

In Goal Orientation Theory perspective, students may exhibit mastery orientation, with a focus on learning and understanding, or they may display performance orientation, aimed at demonstrating competence relative to others. In OEP-based courses, those with a mastery orientation may find motivation in acquiring new knowledge and skills, hence actively contributing and making regular progress. Meanwhile, performance-oriented students might feel motivated by the opportunity to showcase their skills or compare their learning progress with their peers. However, it is to be noted that performance-oriented students require including collaborative teaching aspects; pure MOOCs might not be suitable for such students.

In summary, OEP is expected to be more successful when it is target toward students that have mastery-orientation and already are driven by autonomy and competence needs, despite the fact that OEP supports collaborative learning options to a great extent (to satisfy relatedness needs). Therefore, an OEP practitioner must take into account that not all students might benefit from OEP, and additional teaching methods must be employed.

Future prospect: role of AI in advancing OEP

The motivation theoretical discussion above can be also enriched by including a future prospect. Artificial Intelligence (AI) has a significant potential in advancing OEP. Firstly, AI can be content-wise (OER) assistant for teachers and offer personalized learning experience for students, by creating or modifying available OER contents. Through machine learning algorithms and predictive analysis, AI can understand a student’s learning style, strengths, weaknesses, and pace, adapting content accordingly. This ensures each learner receives a tailored education experience, enhancing their engagement and, consequentially, their learning outcomes. Secondly, AI can provide analytical insights about student performance to educators. By processing vast amounts of data, AI could help teachers understand students’ learning patterns, potential difficulties, and progress. This information could be used to optimize course materials, improving the overall efficacy of OEP. Thirdly, AI-powered chatbots could support students at any instance, answering their queries and doubts, thereby facilitating constant learning support. Thus, AI can act as a personalized tutor, enabling mentor-mentee type of engagement.


A discussion about motivation can further be enriched by including the future prospect of Artificial Intelligence (AI). Incorporating AI, we can create a future where OEP can revolutionize educational institutions to become more inclusive and accessible. Harnessing AI for content creation or modification can provide personalized learning experiences for students. Additionally, AI can offer analytical insights about student performance to educators, thereby optimizing course materials and improving OEP’s overall efficacy. AI-powered chatbots can also provide 24/7 learning support to students, acting as personalized tutors.

In conclusion, Open Educational Practices (OEP) have immense potential in transforming education to become more inclusive and accessible. However, there are still challenges to be addressed, particularly in motivating teachers to adopt OEP. The theoretical frameworks of Self-Determination Theory, Attribution Theory, and Goal Orientation Theory provide insightful explanations for the lack of motivation among teachers and students. Furthermore, the incorporation of Artificial Intelligence (AI) in OEP presents significant opportunities for personalized learning experiences and analytical insights about student performance. By optimizing OEP through AI-powered tools and incentivizing teachers to embrace these practices, we can create a future where education is available anytime and anywhere for everyone.

Topic 1: Motivation and Benefits of Online Participation and Public Discourse

In today's digital age, online platforms have become an integral part of our daily lives, allowing us to socialize and expand our knowledge. While it may be comfortable to consume information online as anonymous users, the value of participating openly in public spaces may not be immediately evident. As a result, some individuals may be hesitant to engage in public discourse on online platforms.

Before discussing motivation, it is important to explore why we consume different types of media, such as social online platforms, newspapers, and television. The Uses and Gratification Theory  suggests that users seek different forms of gratification from each type of media. At the very least, each medium fulfills a combination of the following needs:

  1. Cognitive needs: Providing new knowledge, information, and facilitating a better understanding of the world.
  2. Affective needs: Offering aesthetic and emotional experiences.
  3. Integrative needs: Enhancing confidence, status, and credibility.
  4. Social needs: Strengthening relationships and fostering social connections.
  5. Relaxing needs: Providing an escape from responsibilities or promoting self-awareness.

These needs are fundamental and recent studies have even shown  a link between these needs and happiness levels. It is worth noting that media types that satisfy the needs 3 to 5 tend to attract more users. Consequently, choosing to stay away from such media types is a personal decision, but it carries the risk of feeling socially left out.

It is important to understand that the Uses and Gratification theory mainly focuses on the self-driven motivations to use a particular media type. However, to understand why individuals choose to engage in tasks such as publicly sharing opinions on online platforms, Atkinson's "Expectancy-Value Theory" of "Achievement Motivation" [Schunk, 2012; ch. 8] can be used to complement the Uses and Gratification theory. This theory suggests that people make judgments and decisions based on their expectations of the outcomes and the subjective value they assign to those outcomes. Expectancy refers to the belief that the task is attainable and will deliver desired outcomes, while value refers to the personal importance attributed to those outcomes. Therefore, online participation can be motivated by raising awareness of the value of the outcomes and addressing self-efficacy concerns (i.e., improving the belief in reaching the desired outcomes).

The growing number of tools and platforms required for online participation can be overwhelming, creating concerns related to technical skills, especially when individuals are in unfamiliar settings. Online platforms are designed to fulfill specific needs, and they have different usage scenarios that can be tailored to individuals. While the learning curves for these platforms may be low, effective usage is achieved through hands-on experience. A common feature of these platforms is their learnability through observation of other users. By observing these capabilities, individuals can easily find technical details needed to achieve their desired outcomes by attending online courses, joining communities, and participating in forums. Practice can be reinforced by creating dummy online profiles or users.

It can be argued that digital literacy and online communication skills are more important concerns than technical skills. Digital literacy refers to the ability to critically evaluate online information, discern credible sources, and recognize and respond to online threats such as misinformation or cyberbullying. This skill is developed by forming circles of trust, where collective knowledge is built through awareness and options to mitigate threats. On the other hand, communication skills involve expressing thoughts clearly, engaging in respectful and constructive discussions, and understanding the nuances of written communication such as tone and intent. These skills are similar to the ones required by scientific communities and are built through practice. It is important to accept that digital presence is virtual and not inherently tied to physical presence. Starting as a novice with dummy profiles/accounts and gradually becoming a proficient user is an effective approach. Therefore, online presence can be built gradually, even though it may seem overwhelming at first.

Online platforms can be designed to cater to different needs, providing gratification to users. Publicly sharing opinions, especially on subjects that require expertise, is primarily motivated by cognitive, integrative, and social needs. By consuming media created by others, we fulfill our cognitive needs by acquiring new knowledge and shaping personal identities. Sharing opinions publicly satisfies integrative and social needs by boosting confidence and credibility. The more people express agreement with ideas, the greater the feeling of gratification. Another benefit is the ability to use online platforms regardless of physical location, allowing for potentially larger-scale validation and recognition. Therefore, the main benefit of online presence lies in its potential scale.

Digital presence refers to using online media to create a digital identity that is not inherently tied to physical presence. Depending on the desired outcome, individuals can choose which side of themselves to expose. This versatility is a healthy behavior as elaborated on by Julian Keuzenkamp, who relates it to Carl Jung's definition of "persona." Jung defines persona as a kind of mask that conceals one's true nature while expressing certain traits in different social environments. Developing personas in physical social environments naturally aligns with the evaluations of social groups and requires persistence. However, digital personas can be chosen more deliberately and allow for switching without long-term consequences. This versatility enables individuals to experiment in safe, virtual environments, promoting personal growth and learning.

One last point that can be added is the role of online platforms in building collective knowledge, specifically through the use of blogs, articles, and other written sources. Nowadays, there is a growing interest in generative tools like chatGPT, which are considered to be general purpose artificial intelligence (AI) tools. To understand how these tools are developed, one can experiment with different prompts. For example, a prompt like "What are the self-efficacy concerns for online participation?" can yield a well-constructed response. However, if we enter a follow up prompt "What are the references for the above text?", we would receive the following explanation:

I apologize for any confusion, but as an AI language model, I don't have direct access to external references. The information I provided is based on the knowledge I acquired through training on a diverse range of data, including articles, blogs, and other textual sources. I generated the response by synthesizing and summarizing the common understanding and concepts related to self-efficacy concerns for online participation.

This response clarifies that the collective knowledge is built through a data-driven model, utilizing shared online content. In addition to the personal arguments I mentioned earlier in favor of publicly sharing knowledge, there is also a civic responsibility aspect. Our ideas and interpretations can have an unprecedented impact, and although concerns about judgment, social comparison, and being perceived as uninformed are valid, we should trust that these issues will be rectified.  The following image, generated by AI,  illustrates that out individual contribution, regardless how small it is, has an impact.

In summary, online participation is motivated by various needs, including cognitive, integrative, and social needs. The Uses and Gratification Theory explains how different media types fulfill these needs, while the Expectancy-Value Theory emphasizes the importance of users' expectations and subjective value of outcomes in motivating online participation. By addressing self-efficacy concerns, developing digital literacy and communication skills, and recognizing the potential benefits of online presence, individuals can engage in public discourse and contribute to collective knowledge in a meaningful way.


D.Sc. Yusein Ali

Aalto University,

Espoo, Finland