In many situations, the term open learning is used interchangeably to refer to e-learning, flexible learning, and distance learning. Paine (1989) as cited by Fraser and Dean (1997: 25) defines open learning as both a process which focuses on access to educational opportunities and a philosophy which makes learning more client and student centred. It is a type of learning which gives flexibility in terms of how to learn, when to learn, where to learn and what to learn as far as possible within the resource constraints of any education and training provision.

According to Caliskan (2012) the term “openness” refers to any teaching organisation or institution that offers a variety of choices to learners by giving them the opportunity to study and learn in ways that are independent of time and place. It should also be noted that the degree of openness and flexibility will vary form one institution to another. The flexibility that is required by the teaching institutions develops as the institution’s philosophy becomes more learner centred. Learning in this sense could happen outside formal learning settings and its characterised by lifelong process.

Sariola (1997) as cited by Caliskan (2012) highlights some of the characteristics of an open system as follow:

• Physical characteristics: these refer to the physical nature of the learning situation and its accessibility by learners. These characteristics determine whether facilities are open to users at any time.
• Didactic characteristics: these are related to the learning methods and evaluation processes. They try to answer how learners study and learn.
• Psychological characteristics: these are related to the motivational factors regarding learning. They try to answer what motivates the learner and how?
•  Virtual characteristics: these refer to the advanced media and technologies used in teaching and learning processes. They determine which technologies or media best suit the needs of learners under particular circumstances.

Openness is directly connected to individuals and their psychological make-up. Openness is one of the five personality traits empirically established in research. Norman, (1963) posits that the following are five broad dimensions that are used to describe human personality:

(1) extraversion vs introversion (sociable, assertive, playful vs aloof, reserved, shy);

(2) emotional stability vs neuroticism (calm, unemotional vs insecure, anxious);

(3) agreeableness vs disagreeableness (friendly, cooperative vs antagonistic, fault

finding);

(4) conscientiousness vs unconscientiousness (self-disciplined, organised vs

inefficient, careless); and

(5) openness to experience (intellectual, insightful vs. shallow, unimaginative).

Openness is sometimes interpreted as ‘intellect’, seen as ‘openness to experience’ and associated with appreciation of art, curiosity, adventure and the imagination (Peters & Britez, 2008).

According to Jardin, Gnambs & Batinic (2013) knowledge sharing has been predominantly studied within virtual work teams. Virtual teams are groups of geographically dispersed individuals. Within organisations, virtual teams are formally created by the leader of an organisational unit for the duration of a specific task at hand. Outside the organizational context, individuals also cooperate in online communities such as open-source projects (e.g., Linux) without being given a formal assignment by a supervisor in charge. 

While online communities for knowledge sharing have emerged as an important asset in various settings, numerous factors can affect the degree of knowledge sharing within communities and virtual teams. On the individual level, these include several abstract

personality traits (Matzler et al., 2008) and also various motivational sources (Lin, 2007) cited by Jardin, Gnambs & Batinic (2013).

Jardin, Gnambs & Batinic (2013) propose two alternative frameworks for the study of personality and knowledge sharing in virtual communities: diffusion theory and the concept of social value orientation.

Diffusion theory studies factors which influence the rate at which new ideas and technologies spread within a community (Rogers, 2003). The speed with which innovations diffuse among members of a social network occurs through various stages over time: from the point where an individual hears about the innovation for the first time and seeks to increase his/her knowledge about it, over his/her decision to give it a try and, finally, the evaluation which results in a decision to continuously use or abandon the new idea or technology (Rogers, 2003).

The people in this category are called innovators with high levels of trendsetting and opinion leadership. They are attracted by the novelty of a technology and use an application because they are among the first (or the few) to do so, they are rather communicative and discuss their experiences with their peers. Therefore, these individuals high in trendsetting are expected to share their experiences over the Internet and the central drive behind their participation in the online community is the innovation itself (Jardin, Gnambs & Batinic, 2013).

Social value orientations are individual differences in “certain patterns of outcome for

oneself and others”.  According to Jardin, Gnambs & Batinic, (2013) prosocial value orientations characterise individuals who try to maximize the joint outcome for themselves and others, while individualistic orientations result in a tendency to maximize one’s own outcome without considering the consequences for others. A previous lab study demonstrated that prosocial value orientations increase knowledge sharing behaviour in face-to-face teams, while individualistic orientations do not (Galletta, Marks, McCoy, Polak, 2003).

Refence list

Balmaceda, J, & Schiaffino, S & Godoy, D. (2014). How do personality traits affect communication among users in online social networks? Online Information Review. 38. 10.1108/OIR-06-2012-0104

Caliskan H. 2012. Open Learning. Springer Science+Business Media, LLC, DOI: 10.1007/978-1-4419-1428-6_52

Galletta, D. F., Marks, P. V., McCoy, S. & Polak, P. (2003). What leads us to share valuable knowledge? Proceedings of the 36th Hawaii International Conference on System Sciences, Hawaii (USA).

Johnson, J. A. (2017). Big-Five model. In V. Zeigler-Hill, T.K. Shackelford (Eds.), Encyclopedia of Personality and Individual Differences (1-16). New York: Springer. DOI: 10.1007/978-3-319-28099-8_1212-1

Peters, A. M & Britez, G. R. (2018). Open Education for Openness. Educational Future, Rethinking Theory and Practice, Volume 7

Rogers, E. M. (2003). Diffusion of Innovations. New York: Free Press.