Personal knowledge and information management – conception and exemplification

Abstract

Personal knowledge and information management (PKIM) as an integrated approach of three concepts – personal knowledge management, personal information management and information literacy – is an appropriate and comprehensive approach to these issues with overlapping and supplementary areas of interests. The theoretical basis and results of pioneering empirical studies in the PKIM field, carried out in an academic environment, are presented in this exploratory study. The development and validation of the PKIM scale are characterized. An analysis of the subject literature, discussions with experts and students, and statistical methods used in creation of the PKIM scale, which is an original instrument for measuring a self-assessment of knowledge and information skills of students, are reported. The PKIM self-assessment of Polish students of information science majors and related specializations was high, but not as high as expected. Master’s students reported higher level of PKIM self-assessment than Bachelor’s students.

Keywords

Information literacy knowledge and information management personal information management personal knowledge management students

1. Introduction

The economic and technological changes of today’s world have an unquestionable influence on individuals, organizations and society. These changes demand permanent adaptation to new circumstances and lifelong learning. Individuals, organizations and society appreciate the importance of personal knowledge and information, as well as the variety of skills and competences that enhance the effectiveness of human activity. Various concepts and theories are developing in many disciplines in order to help people to cope with contemporary, turbulent environments: social, organizational and technological. Some of these concepts developing in management science are closely connected with information users, information skills and information behaviour, which have been the focus of information science (IS) research for some decades.

At the turn of the twenty-first century, two separate concepts relating to management of knowledge and information by individuals emerged: personal information management (PIM) [1, 2] and personal knowledge management (PKM) [3, 4]. Both stem from management science, but are interdisciplinary and multidisciplinary in nature. At the same time, the third concept – information literacy (IL) – was developed, especially in library and information science (LIS) [5 –7]. The problem is, on the one hand, that these concepts have overlapping areas of interest, and on the other, that in the scientific literature in general none of them has achieved dominance, at least until now. It seems that LIS representatives get used to the information literacy concept. They are trying to develop new models of IL [8 –11], and they are convinced that IL is useful in a business environment [12, 13]. Unfortunately, IL is somewhat unsatisfactory for knowledge management (KM) representatives, probably because of the common association with the schoolroom or academic library [4, p. 11].

Therefore recently an integrated approach to PIM, PKM and IL, called personal knowledge and information management (PKIM) has been proposed [14], which has the potential to make a worthwhile contribution to various disciplines and to interdisciplinary research as well. The aim of PKIM is improved functioning of individuals in turbulent and competitive environments, in professional as well as everyday life. The basis of PKIM is, on the one hand, individual assets of knowledge and information, and on the other, competences in building information and knowledge collections, along with their use, in other words learning and creating new information and knowledge. A more in-depth theoretical analysis, together with additional empirical evidence, is required for the further development of PKIM.

This paper as an exploratory study aims to explore the application of an integrated approach in the learning context, that is, an academic environment. The origin of PIM is in a business environment [1, 15]. The origins of PKM and IL are connected with an academic environment, especially students [3, 7]. However, the current development of PKM is much more related to the business environment [16]. While IL studies have a rich subject literature [7, 8, 10, 11, 17, 18], there are few studies in PKM and PIM field among students [14, 19]. Therefore, a better understanding is needed of how students perceive their self-assessment of management of knowledge and information. By examining the results of the application of an integrated approach of three concepts, this paper will show how this approach can yield greater accuracy in assessment of information skills and other skills regarding management of personal knowledge and information. The study will also suggest that the instrument to measure the level of PKIM self-assessment herein described may be valuable for future research in PKIM field, as well as in its subfields (PIM, PKM and IL).

2. PIM, PKM, IL literature review

Personal information management and personal knowledge management originated, and have developed, separately. The term personal information management was used by Lansdale [1] as a set of methods for information organization in everyday activities, 10 years earlier than PKM. The term personal knowledge management was used for the first time as the name of a workshop for students in MBA programs at UCLA Anderson School of Management; Frand and Hixson [3] introduced it to help students gain the information skills necessary to succeed in the emerging global business environment. It is worth adding that PIM and PKM are partly related by their overriding concepts: information management (IM) and KM. Therefore, in the scientific literature, IM and KM are discussed from at least three perspectives: individual (PIM, PKM), organizational and social. In recent years two separate books about PIM and PKM have been published [2, 4]. The interconnections between PIM and PKM were only briefly mentioned in these publications. Apart from these books, the majority of subject literature exists in the form of articles and conference presentations separate for PIM and PKM. In 2012 the fifth PIM workshops [20] took place; an estimated three PKM workshops [21 –23] have been organized so far.

According to Jones, personal information management refers to the practice and the study of the activities a person performs in order to acquire or create, store, organize, maintain, retrieve, use and distribute the information needed to complete tasks (work-related or not) and fulfil various roles and responsibilities [24, p. 453]. There are two basic kinds of information management activity: keeping activities, which attempt to take us from information encountered to anticipated need; and finding/refinding activities, going in the other direction – from need to information. The group of keeping activities includes decisions and actions concerning how to keep the information for an anticipated use. The group of finding/refinding activities includes various activities of sorting, browsing and others allowing people to access and reaccess information. Moreover, there are four kinds of information management activity, which focus on the mapping itself, so-called meta-level activities: (a) organizing and maintaining; (b) managing privacy and the flow of information; (c) measuring and evaluating; and (d) making sense [25, 26]. Central in PIM is the need to manage the information processes of information creation, acquisition, organization, distribution and use so to meet personal information needs [27, p. 107].

Contemporary studies in the scope of PIM are focused on areas such as personal information collections [25, 28 –30], project management [31] and reference management [32, 33]. Research on the topic is being done in several disciplines, including human–computer interaction, database management, information retrieval and artificial intelligence [20].

Personal knowledge management has grown out of a combination of fields, personal information management, cognitive psychology, philosophy, management science, education, communications and many other disciplines, and is defined as an evolving set of understandings, skills and abilities that allows an individual to survive and prosper in complex and changing organizational and social environments [4, p. XVII]. In comparison to PIM, in the subject literature there are more theoretical models of PKM. They reflect, for instance, the processing approach to knowledge management, from knowledge gaining to its dissemination or competence approach, that is focused on a set of skills needed for effective knowledge management. Both approaches are complementary. According to Barth [34] there are seven PKM skills: (a) accessing information and ideas; (b) evaluating; (c) organizing; (d) analysing; (e) conveying; (f) collaborating around information and ideas and (g) securing. Wright [35] described an alternative model of PKM, connecting different types of problem-solving activities with specific cognitive information, social and learning competencies. An original PKM model proposed by Zuber-Skerritt [36] consisted of a system of seven principles of learning and matching strategies, called Actions and Reflect. Garcia [37] suggested four strategies in the context of PKM and e-learning: creative lifelong learning, environment adaptation, systemic view and community membership. One of the newest, PKM 2.0 model [16], had four components related to the notion of hierarchy: personal information management, personal knowledge internalization, personal wisdom creation and inter-personal knowledge transferring.

It is difficult to predict future research in PKM field, because of the broad definition of PKM, which has at least three categories [38]: (a) the management of personal knowledge; (b) the knowledge management from a personal perspective; and (c) the intersection of them both, which represents the management of personal knowledge from an individual’s perspective. The third PKM category is the closest to the PKIM concept, described in the next section.

The literature relating to IL, in comparison to PIM and PKM, is vast. The term information literacy was probably coined by Paul Zurkowski in the 1970s, that is, earlier than PIM and PKM [13, p. 720]. There are many definitions and models of IL [5 –13]. According to UK Chartered Institute of Library and Information Professionals [39], IL is knowing when and why you need information, where to find it, and how to evaluate, use and communicate it in an ethical manner. To be information literate requires an understanding of: a need for information; the resources available; how to find information; the need to evaluate results; how to work with or exploit results; ethics and responsibility of use; how to communicate or share your findings; and how to manage your findings. According to the Society of College, National and University Libraries [40], IL is a set of seven pillars, that is, abilities and skills of individuals: (a) identify – can identify a personal need for information; (b) scope – can assess current knowledge and identify gaps; (c) plan – can construct strategies for locating information and data; (d) gather – can locate and access the information and data that is needed; (e) evaluate – can review the research process and compare and evaluate information and data; (f) manage – can organize information professionally and ethically; and (g) present – can apply the knowledge gained, present the results of research, synthesize new and old information and data to create new knowledge, and disseminate it in a variety of ways. Very useful for the conception of PKIM is an old and still relevant model of IL, created by Christine Bruce in the 1990s [6]. She pointed out seven categories of IL: (a) the information technology conception – IL is seen as using information technology for information retrieval and communication; (b) the information sources conception – IL is seen as finding information located in information sources; (c) the information process conception – IL is seen as executing a process; (d) the information control conception – IL is seen as controlling information; (e) the knowledge construction conception – IL is seen as building up a personal knowledge base in a new area of interest; (f) the knowledge extension conception – IL is seen as working with knowledge and personal perspectives adopted in such a way that novel insights are gained; (g) the wisdom conception – IL is seen as using information wisely for the benefit of others.

In general, contemporary research on the scope of IL has three perspectives: (a) disciplinary – analysis of IL as culture of information and as a form of study of information; (b) social/political – analysis of IL as an educational policy goal; and (c) cognitive perspective: analysis of IL as an educational policy goal [11].

To summarize this section, it is worth saying that PIM and PKM concepts are developing and still need more theoretical and empirical research. The same concerns the IL concept, which transforms into new kinds of literacy, such as media literacy, computer literacy, web-literacy and literacy 2.0. The above three concepts may simultaneously develop further and independently of each other, but without an awareness of the developments in these fields there may be a risk of an unintentional duplication of research.

3. PKIM conception

Personal knowledge and information management originated from the overlapping areas of interest of PIM, PKM and IL. The fact is that all kinds of literacy (e.g. computer and media literacy) along with the wide spectrum of skills and competences are necessary for the management of knowledge and information by individuals. Some authors have tried to find similarities between PKM, which arose from PIM, and IL. The relation between PKM and IL was pointed out in the above-mentioned book about PKM [4, p. 12], but without deep insight. The editors mention vaguely that effective PKM requires its practitioners to be information literate, and IL can be viewed as an essential process and set of skills for PKM. Other authors [19] concluded that, compared with IL, PKM highlights two elements: it emphasizes that the individual learns how to structure the information and underlines the influence of communication on the identification of information.

An in-depth description of similarities between the three concepts PIM, PKM and IL is contained in Świgoń [14, pp. 191–272]. According to the author, PIM, PKM and IL are distinct and different, but also compatible and interconnected, as well as with two pairs of basic terms: information and knowledge and skills and competence.

The terms information and knowledge are universal, difficult to define and often used to describe each other. Farradane considers information a physical surrogate of knowledge (e.g. language) used for communication and mentions the conversion of information into knowledge and vice versa [41]. In the fundamental Brookes equation information is part of knowledge [42]. In another fundamental hierarchy, the so-called Knowledge Pyramid (data–information–knowledge–wisdom, DIKW) knowledge is somewhere between information and wisdom on the semantic ladder. Typically, information is defined in terms of data, knowledge in terms of information, and wisdom in terms of knowledge, but there is no consensus on the description of the processes that transform data or information into knowledge or wisdom [43]. Moreover, arguments have been offered that DIKW hierarchy, which is part of the canon of information science, as well as information management and knowledge management, is unsound and methodologically undesirable. Information is what is known in other literature as weak knowledge, which means ‘knowledge-that’; and knowledge itself is also weak knowledge. This makes knowledge and information synonymous [44]. Other authors have claimed, that amongst different kinds of knowledge – tacit [45 –47], implicit [48, 49] and explicit – its explicit form is the closest to the notion of information [46, 50, 51]. However, these different kinds of knowledge are dimensions of the same knowledge, like sides of the same coin. Knowledge can be regarded as personalized information related to facts, procedures, interpretations, regulations, observations and judgements [52]. Although we can define the term knowledge, we still cannot isolate it at an operational level. Therefore, in practice it is very difficult to estimate clear boundaries between information management and knowledge management, especially at an individual level.

As mentioned above, PIM and PKM are partly related by their overriding concepts: IM and KM. Both terms were widely discussed in the literature. The term information management is often equated with information resources management (IRM), or the management of information technology (IT), or the management of information policies or standards [27]. In contradiction to IM, the term ‘knowledge management’ has been perceived as nonsense [53]. Knowledge cannot be directly managed, and only information, which is treated as a thing, is manageable [54]. On the other hand, knowledge-that is articulable and recordable [44]. Nevertheless, KM has experienced phenomenal growth since around 1997 [55, 56] and has gained acceptance more by default than anything else [57]. Nowadays, KM is a distinct discipline, not yet a reference discipline, but it is progressing rapidly towards becoming one [58]. IM is also perceived as an enabler of KM maturity [59], and some aspects of IM are vital for successful KM [60]. It is worth adding that in the subject literature of IM and KM, as well as PIM and PKM, two main perspectives influence each other: (a) humanistic, connected with human resources management and self-development; and (b) technological, related to knowledge and information management systems, computer applications and software. Despite the benefits of technological tools, there is some evidence to suggest that they are less important in determining how individuals organize and use information than are the tasks that people perform [61]. Therefore, PKIM is a humanistic approach in which skills and competences of individuals are the greatest priorities, and technological advances play an important, but secondary, ground role.

Moreover, IM and KM are partly related to information science and librarianship. According to Macevičiūtė and Wilson [62], IM drew upon ideas from IS and librarianship. That is why in the 1980s, when IM emerged, it was perceived by some as a re-write of traditional librarianship. Similarly, in the 1990s, when KM emerged, it was also called librarianship in new clothes [63, 64]. Librarians often use knowledge (weak knowledge-that) and information as synonyms, and they need not be widely wrong to do so [44]. What are IM and KM? IM is the management of the processes and systems that create, acquire, organize, store, distribute and use information. The goal of IM is to help people and organizations access, process and use information efficiently and effectively [27]. KM is a young discipline, which emerged in response to the increasing pressure on private and public organizations to make more efficient and effective use of their knowledge [58]. The similarities in descriptions of IM and KM – ‘use information efficiently and effectively’ and ‘use knowledge more efficiently and effectively’ – imply interconnections with information science and librarianship. According to Hjørland, library and information science is both a knowledge-producing field and a knowledge-utilizing field [65]. Knowledge is also a central point of many classification schemes of information science [66 –68]. The goal of KM (and IM) in the information science field is to help facilitate human access to knowledge and information for effective learning, decision-making and problem-solving [14, 60].

The connections between IM, KM and information science and librarianship, as well as the fact that IM and KM draw upon ideas from IS and librarianship, are very important for the conceptualization of PKIM as an integrated approach to PIM, PKM and IL.

PKIM stands a great chance of becoming an interdisciplinary and multidisciplinary concept, recognized in both information science and management science. From an IS and librarianship perspective, the PKM concept may seem somewhat unsatisfactory, because the notion of information is invisible in it. In other words, IS representatives may be not interested in a concept with clear underestimation of the broad meaning of information. For the same reasons they are strongly attached to the IL concept, which is natural and will last until (if ever) there is a common agreement of the redefinition of information science into knowledge science [69]. However, nowadays IL is perceived in KM as a somewhat unsatisfactory concept, probably because of the connection with the classroom. KM representatives tend to prefer PKM to IL, despite the fact that PKM is based on IL. Therefore, the future duplication of research is a real danger and the PKIM concept may solve this problem.

Returning to the analysis of overlapping areas of three concepts, the issue of skills and competences must be included. Effective and efficient PIM and PKM are possible owing to the possession of appropriate skills and competences – another pair of basic terms, which are difficult to define without using the notion knowledge. In general, skills and competences are connected with applying personal knowledge in practice. A very helpful tool in defining these basic terms is Bloom’s Taxonomy [70] and his typology of cognitive, affective and psychomotor domains of educational activities. The cognitive domain relates to mental skills (knowledge), the affective domain is connected to attitudes, and the psychomotor domain is concerned with manual and physical skills [70, 71]. According to Winterton [72, 73], if intellectual capabilities are required to develop knowledge and if knowledge is operationalized in developing skills, all are prerequisites to developing competence. Moreover, the possession and use of wide practical knowledge can be viewed as wisdom from the DIKW hierarchy [44]. Competences and wisdom of individuals were taken into consideration in the above-mentioned PKM and IL models. One of the PKM models consisted of a variety of competences [35] and another of, among other things, personal wisdom creation [16]. One of the IL models included wisdom as well [6].

Therefore, PKM and IL, in comparison to PIM, seem to have broader meaning. However, there is a lack of consensus of which concept, PIM or PKM, is the overriding one. According to another author, PKM is nonetheless best regarded as a useful subset of PIM [4, p. 158, 24–26]. As mentioned, there is a widely held view that knowledge cannot be directly manipulated, only through information as an expression of knowledge. This view was even deemed worthy of inclusion in a book on PKM [4, p. XX]. On the other hand, Jones [24 –26] wrote about meta-level activities in PIM, among other things, making sense. It is necessary to add here that the well-known theory of sense-making developed by Dervin is strongly connected to knowledge and information management by individuals [74]. What is interesting is that her approach makes no distinction between knowledge and information. Instead, it refers to the making and unmaking of sense and has defined information/knowledge as product of, and fodder for, sense-making and sense-unmaking [74, p. 36]. Making sense is a kind of metacompetence, along with reflection and critical thinking. A person’s knowledge structure is changed to a new modified structure by passing through the so-called ‘information behaviour wheel’ [75], which consists of a variety of information activities, such as seeking, searching, spreading. Metacompetences of individuals play a crucial role in these activities.

Furthermore, PIM, PKM and IL models, presented in Section 2 [see wider description in 14], have many similarities. First of all, components in these three sorts of models can be analogous to each other or even the same. There are at least two kinds of these components: activities or processes [24 –27] and/or skills and competences [34, 35], connected with these processes. In general, components of PIM, PKM and IL models are simply steps of the knowledge and information life cycle or value-chain, from searching, gathering, through selecting and organizing, to using, sharing and creating new knowledge and information. All three kinds of models have fundamental connections with personal skills and competences, including meta-level skills or metacompetences [71 –73].

However, differences between PKM, PIM and IL models can be seen as well. The first main difference is that the component related to knowledge and information creation is an integral part of all PKM models, but it does not exist in all PIM and IL models. Moreover, PKM is strongly focused on knowledge sharing and information exchange, which is not the main concern of PIM and IL.

It is important to stress that a new, integrated approach to PIM, PKM and IL, which is personal knowledge and information management, originated from their above-mentioned overlapping areas of interest, which stem from basic connections between information, knowledge and competences. In PKIM all components of the knowledge and information life cycle are of equal status, and none is omitted. Similarly, skills and competences described in PIM, PKM and IL models all together constitute a list of PKIM competences. The simplified model of PKIM is presented in Figure 1.

Figure 1.

Personal knowledge and information management (PKIM) model.

The PKIM model consists of two parts: (a) the components of knowledge and information value chain and (b) the spectrum of associated competences. The central point of this model is metacompetences, for example creativity, critical thinking, analysis, reflection and making sense. Metacompetences were not sufficiently highlighted in models of the three subordinate concepts. Meanwhile, they are necessary to use all others skills and competences. In other words, for effective learning, decision-making and problem-solving, cognitive, social and functional competences must be supplemented by metacompetences. PKIM competences can be called twenty-first-century competences. They cover so-called transversal skills, lifelong learning skills and a variety of literacies, which are all needed for participation in a knowledge-based society, in both private and professional spheres of life. To simplify the model only three main components of knowledge and information life cycle were presented: acquiring, creating and sharing. However, all activities and processes can be described under these labels. The general and elastic nature of the PKIM model implies its usefulness in a variety of future research, for instance in different information user groups and different environments and contexts. The PKIM scale, described in the next section, can be helpful in empirical studies in an academic environment.

4. PKIM examples

4.1. Research questions and procedures

The pioneering PKIM empirical studies addressed the following research questions:

How can we measure the self-assessment of management of personal knowledge and information?

How do IS students perceive the self-assessment of management of knowledge and information?

The respondents group comprised students of IS and librarianship majors and specializations in Poland: information management studies; information science and librarianship; and communication and information management. This group was chosen for the following reasons. Students of IS majors and specializations generally have a greater training in information skills. The author therefore felt that this training would have a greater influence on self-assessment of management of knowledge and information. A second important reason was the selection of a homogeneous and cohesive user group, because of the qualitative nature of this pioneering research.

The study applied a mixed methods research design, using both quantitative and qualitative methods to answer the research questions. This method was chosen for the following reasons. First of all, the author’s objective was to test the potential development and validation of the personal knowledge and information management self-assessment scale (PKIM scale, see Appendix A). It is worth adding that in the scientific literature no pattern regarding such instrument was given. Despite a deep analysis of the literature, qualitative methods including discussions with IS experts (lecturers, librarians) and students were used to design the initial questionnaire of the PKIM scale. It included 30 statements proposed via analysis of the subject literature (models of PIM, PKM and IL) and discussions with experts and students. These statements expressed behaviour, habits, skills, attitudes, feelings and emotions concerning the various activities of KIM: knowledge and information seeking and gathering, selecting, organizing, sharing, creating and presenting. The PKIM scale was created and validated on the basis of the initial 30 statements and five factors: 1, gathering and searching (ZB1–ZB6); 2, organizing and securing (ORG1–ORG6); 3, selecting and evaluating (SEL1–SEL6); 4, spreading and sharing (ROZ1–ROZ6); and 5, creating and presenting (TW1–TW6). Respondents selected an answer from a five-point Likert scale (1, strongly disagree; 2, disagree; 3, undecided; 4, agree; 5, strongly agree).

In particular, the group of survey participants consisted of 510 students of IS majors and related specializations from nine Polish state universities (throughout the whole country, Table 1). Eighty-six were male and 424 female. There were two groups reflecting their academic status – Bachelor’s students (294) and Master’s students (216) – and two groups concerning LIS major (402) and related specializations (108). The whole group of respondents was 20% of all IS majors and specializations students in Poland in 2011. Quantitative methods, including the survey among students, along with statistical methods were used to analysis of gathered data.

Table 1.

The list of respondents by university.

University	N
University of Warmia and Mazury in Olsztyn (UWM)	53
Nicolaus Copernicus University (UMK)	49
Adam Mickiewicz University (UAM)	55
University of Silesia in Katowice (UŚ)	49
University of Wrocław (UWr)	80
Warsaw University (UW)	59
Maria Curie-Skłodowska University (UMCS)	42
University of Łódź (UŁ)	50
Jagiellonian University in Krakow (UJ)	73
Total	510

In addition to the research questions, the following hypotheses guided data collection and interpretation:

There is no significant difference between male and female IS students as to their average scores of PKIM self-assessment.

There is no significant difference in the average scores of PKIM for IS students who studied at different universities in Poland.

There is no significant difference in the average scores of PKIM for the students who studied at IS major or related specializations.

There is no significant difference in the average scores of PKIM for respondents in relation to their academic status (Bachelor’s students, Master’s students).

The hypotheses were tested at a 0.05 level of significance.

4.2. Results

4.2.1. PKIM scale

The initial structured questionnaire consisted of 30 statements categorized into five groups. As was said, the statements reflected students attitudes, behaviours, skills, feelings concerning personal knowledge and information management process. Data from survey responses were put into Statistica PL. Negatively worded statements (SEL2, SEL3, SEL5) were reverse-scored (‘5’ was replaced by ‘1’, ‘4’ by ‘2’, and vice versa).

To test for internal consistency, Cronbach’s α was computed on all 30 statements. Cronbach’s α is a common index of reliability. When using this measure of reliability, the closer the results are to 1.0, the higher the estimate of reliability, and a criterion of 0.70 is acceptable. The resultant α coefficient of 0.762 for 30 items provided evidence of adequate internal consistency. Nevertheless, it was pointed out that a removal of some statements caused an increase in α coefficient. The maximum Cronbach’s α 0.786 was gained after removing three statements (ZB6, ORG4, SEL4). Exploratory factor analysis (EFA) was also utilized on the survey data to extract latent variables and examine correlations. EFA is a statistical procedure that can be utilized on a set of items (i.e. statements) to determine which items in the set form meaningful subsets or factors that are statistically independent from each other. EFA is a variable reduction technique that identifies the number of latent constructs and the underlying factor structure of a set of variables. The extraction method used was principal components, rotated orthogonally using a varimax procedure. Two variables with an absolute value of <0.30 were excluded (ZB6, SEL4). Moreover, the third variable (ORG4) was removed, because of high negative value. In the light of these results, these three statements were removed from the list and 27 remained.

A further issue was connected to the number of factors. The factor analysis yielded eight factors with eigenvalues >1. According to cumulative variance, 13 factors were needed to account for 70% of the total variance of the dataset. However, examination of the scree plot provided different results. The scree plot levelled off after five factors. As a result, five factors were retained, and they explained 44% of the total variance.

Nevertheless, the question of categorization of statements into five groups was raised. Therefore, a reliability analysis was performed. At the beginning the α coefficient was estimated for five initial groups of statements. Score reliability for each subscale was as follows: factor 1, ZB1–ZB6 (Cronbach’s α = 0.413); factor 2, ORG1–ORG6 (Cronbach’s α = 0.373); factor 3, SEL1–SEL6 (Cronbach’s α = 0.426); factor 4, ROZ1–ROZ6 (Cronbach’s α = 0.671); and factor 5, TW1–TW5 (Cronbach’s α = 0.731). The first three α coefficients were too low; only the final two were adequate. A different categorization seemed necessary.

The new factor analysis was applied to 27 statements and five components. Factor loadings are presented in Table 2. Cronbach’s α was computed for new subscales and provided evidence of adequate internal consistency. Components of the personal knowledge and information management scale (see Appendix A) were labelled as follows: SEARCH – knowledge and information searching (Cronbach’s α = 0.643); KEEP – knowledge and information keeping and organizing (Cronbach’s α = 0.612); SHARE – knowledge and information sharing with other students (Cronbach’s α = 0.700); CREATE – knowledge and information creating and saving (Cronbach’s α = 0.714); STUDY SATISFACTION – satisfaction with teaching process, with methods of knowledge and information transfer from teachers to students; perceiving skills and competences acquired throughout the study as being useful in professional and private life (Cronbach’s α = 0.667).

Table 2.

Factor loadings. Varimax rotation procedure.

Statement	Factor 1	Factor 2	Factor 3	Factor 4	Factor 5
ZB1	0.677
ZB2	0.768
ZB3	0.547
ZB4		0.605
ZB5		0.333
ORG1		0.683
ORG2		0.549
ORG3		0.634
ORG5		0.575
ORG6				0.314
SEL1	0.611
SEL2	0.421
SEL3				0.383
SEL5		0.318
SEL6					0.596
ROZ1			0.739
ROZ2			0.725
ROZ3			0.689
ROZ4			0.663
ROZ5					0.739
ROZ6					0.681
TW1				0.746
TW2				0.584
TW3				0.602
TW4				0.570
TW5	0.494
TW6				0.778

4.2.2. PKIM self-assessment of students

The use of a five-point Likert scale for each statement is treated as a quantitative term of PKIM self-assessment level examination. Mean scores were determined using the responses provided by 510 IS students to 27 statements. Because of the normal distribution of mean scores the following five levels of PKIM self-assessment were proposed: very low (0.00–2.21), low (2.22–2.65), average (2.66–3.54), high (3.55–3.98), and very high (3.99–5.00).

The general level of PKIM self-assessment among IS students in Poland was high; the average of 3.67 falls into the high PKIM self-assessment range. Average assessment of five PKIM factors is presented in Table 3.

Table 3.

PKIM factor averages.

Factor	Mean	Standard deviation
SEARCH	3.91	0.52
KEEP	3.78	0.58
SHARE	4.16	0.62
CREATE	3.10	0.67
STUDY SATISFACTION	3.60	0.75

As can be seen in Table 3, only the factor SHARE, which is related to knowledge and information sharing between IS students in Poland, shows very high assessment. The factors SEARCH and KEEP, which are strongly connected with information literacy, and STUDY SATISFACTION, which illustrated appropriateness of skills and competences to private and professional life, receive high assessment. However, the factor CREATE, concerning knowledge and information creation and presentation, demonstrates only average self-assessment by Polish IS students.

4.2.3. Invariance of the PKIM

As noted earlier, respondents who completed the form were asked to answer four questions regarding themselves, comprising: studying IS major or related specialization (Major, Spec.), status (Bachelor’s, Master’s), university (UWM, UMK, UAM, UŚ, UWr, UW, UMCS, UŁ, UJ), and gender (M, F). These questions were used to assess the invariance of the PKIM. A one-way analysis of variance (ANOVA) was used to test for differences in PKIM self-assessment in these groups of students. The results of the ANOVA are presented in Table 4.

Table 4.

PKIM self-assessment and demographic differences.

Variable		Scores	F	p
Gender	Women	3.67	0.005
	Men	3.67
Level of study	Bachelor’s	3.62	12.290	<0.001
	Master’s	3.74
IS majors and related specializations	Major	3.65	5.298	0.021
	Specialization	3.74
University	UWM	3.77	2.588	0.008
	UMK	3.66
	UAM	3.72
	UŚ	3.54
	UWr	3.6
	UW	3.66
	UMCS	3.59
	UŁ	3.67
	UJ	3.78

It was hypothesized that there is no significant difference in the average PKIM scores for the male and female respondents. Because of the same scores in both groups (Table 4), there is no evidence to reject the hypothesis.

It was hypothesized that studying an IS major or related specialization does not play an important role in the PKIM self-assessment level. The results of the ANOVA did not produce any statistically significant result.

It was hypothesized that university does not play an important role in the PKIM scores. As can be seen from Table 4, the results of the ANOVA yielded a statistically significant result (p = 0.008), specifically within two places of study: UŚ and UJ. According to the above-mentioned levels of PKIM, the self-assessment of UŚ students was average, and that of UJ students (as well as all others) was high.

It was hypothesized that there is no significant difference in the average PKIM scores between two groups of respondents relating to their status. The results of the ANOVA produced a statistically significant difference (p < 0.001). A post-hoc test (i.e. Tukey’s honest significance difference) revealed that Master’s students reported higher levels of PKIM self-assessment than Bachelor’s students.

As a set, the above four findings suggest that the PKIM is relatively invariant with respect to gender and IS major vs specializations. On the other hand, the PKIM, to some extent, appears to vary as a function of level of study and university. However, it is not clear to what the extent these results are generalizable. Therefore, caution should be exercised in interpreting the instrument developer’s conclusions regarding the invariance of the PKIM.

5. Conclusions

PKIM expresses a human-centric perspective in knowledge and information user studies, that is, a focus on individual behaviour, skills, competences, attitudes, habits, feelings and emotions relating to various activities in the management process. The aim of PKIM is improved functioning of individuals in turbulent and competitive environments, in private and professional life. The basis of PKIM is, on the one hand, individual assets of knowledge and information, explicit and tacit, and on the other, skills and competences in building information and knowledge collections, along with their use and application, that is, learning and creating new information and knowledge. In other words, PKIM skills and competences cover, among other things: information and knowledge literacy, that is, information and knowledge seeking, searching, gathering, storing, evaluating, selecting, organizing, sharing, disseminating, creating and presenting; and computer and media literacy; as well as the meta- and transversal competences – creative thinking, reflection and interpersonal communication [14].

PKIM is an interdisciplinary and multidisciplinary concept, which can be explored in a variety disciplines. It is worth adding that the management of personal knowledge and information is a subject of research in various fields of study, for instance, computer and technology science (PKIM systems). PKIM systems have been developing for several years [52, 76] and are rather advanced [77 –81]. The important fact is, among other things, that the impact of effective PKM (and PKIM) will depend increasingly on skills–tools fit [82]. It seems that the humanistic approach still needs deeper insight [83], for instance in the IS field. The example of IS perspective in PKIM research was presented in this paper. It is a new combination of knowledge and information management user studies, which provides the next possible step in information user studies. PKIM as a kind of information behaviour is a promising path for further development of research in this scope or maybe knowledge and information behaviour. Jashapara [56] noted that a future challenge is for IS scholars to engage in KM discourse outside their traditional boundaries. Zins [69] suggested a redefinition of IS: from information science to knowledge science. Kebede [60] claimed that KM is a natural and long-awaited development in IS.

The interdisciplinary and multidisciplinary character of the PKIM concept can contribute to the theory of some disciplines, e.g. knowledge management and intellectual capital, especially by highlighting an individual perspective of knowledge management. Cheong and Tsui [16] proved that the roles of PKM positively correlate with the values of PKM for individuals and organizations. PKIM research can contribute to education – by emphasizing the role of knowledge and information related skills and competences. It seems that the term ‘knowledge and information literacy’ is more appropriate than IL. Basili [11] wrote about the ‘culture of information’ as a new emerging discipline. Very important for the further development of the PKIM concept will be the results of psychology and neuroscience research, especially on the transformation of information into knowledge, and human memory [84].

In general, development of the PKIM research is helpful in the private and professional spheres of lives of individuals; it can enhance decision-making, problem-solving and lifelong learning. Therefore, the PKIM scale described in this exploratory study seems valuable not only in the theory, but in practice as well. The PKIM scale indicated adequate internal consistency (Chronbach’s α 0.786), and after revalidation of statements translated into English (Appendix A), it can be used by researchers globally. Nevertheless, researchers should continue to assess the psychometric properties of the PKIM, especially its invariance. It is only by continuing to scrutinize the PKIM scale that we can ensure that it continues to advance the field of knowledge and information science [14].

The general level of personal knowledge and information management self-assessment among IS students in Poland was high, but not as high as expected. IS students, as future information and knowledge managers, would be expected to have higher self-assessment in PKIM scope. That the curricula of IS majors in Poland may need modification is currently the subject of Polish conferences and seminars in this field. Moreover, PKIM corresponds to the European Qualifications Framework, which is currently being discussed by governmental and educational bodies in Poland [85].

Future research can be focused on PKIM self-assessment of students in other science majors: humanities and social sciences, life sciences and technology. Comparative studies in different countries would also be interesting. Moreover, future research may include more demographic variables which require analysis, for example, doctoral students and public vs private universities. Furthermore, empirical studies among other groups of respondents may be valuable, for example, knowledge workers in various sectors, such as service, administration and health.

PKIM research seems to be beneficial to organizations – the more effective the employee’s work is, the more productive the organization can be. Furthermore, such research is important in the transformation of a post-industrial society into an information society or knowledge-based society.

Footnotes

Appendix

Appendix A:

Personal knowledge and information management scale translated into English

Factor SEARCH
ZB1	I cope well with gathering information on subjects that interest me.
ZB2	I know a variety of information resources and I can use them, I am familiar with them.
ZB3	I know the deep Web and how to use this kind of resource.
SEL1	I know how to evaluate information on the Internet and I am able to select valuable information and webpages.
SEL2	In case of large search results (thousands of links) I have no problems with selecting high quality materials.
TW5	I am familiar with basic office applications (Microsoft Office, Open Office) needed for typesetting a paper (computer presentation, essay, Bachelor’s/Master’s thesis).
Factor KEEP
ZB4	I make lecture notes systematically.
ZB5	When I search for information, I try to find the people (teachers, experts, colleagues) who have knowledge in this field.
ORG1	I am trying to order, classify and sort gathered information to be able to find it later easily.
ORG2	Usually I keep encountered information that I do not need now but might be useful in the future.
ORG3	I keep information in both electronic (hard disk, USB drive) and paper forms (notes, binders).
ORG5	I try to note spoken information that is interesting for me in order to keep it and add to my collection.
SEL5	I never browse materials I have kept for the future unless I need them currently.
Factor SHARE
ROZ1	I like sharing my lecture notes and other materials (photocopies, data) with other students.
ROZ2	I like sharing knowledge (spoken information) related to studying with other students.
ROZ3	Other students share their notes with me in case of my absence from classes.
ROZ4	Other students share their knowledge (spoken information about our studies) with me.
Factor CREATE
TW1	I like preparing new subjects (writing tasks, speeches etc.) for classes.
TW2	I have no problems with preparing new subjects that are new to me, with deep analysis of the scientific subject literature.
TW3	I have no problems with searching for and forming new problem statements (analysis of literature, research questions, hypotheses), e.g. for Bachelor’s or Master’s thesis.
TW4	Conducting empirical studies (surveys, experiments) on my own would not be a problem for me, if that was necessary for my Bachelor’s/Master’s thesis.
TW6	I like public speaking (speaking on classes, conferences).
ORG6	I care about making copies of kept materials and saving them.
SEL3	Even if I use peer-reviewed journals and books, I have problems selecting the articles and publications that are the most important for the subject I am working on.
Factor STUDY SATISFACTION
ROZ5	Generally speaking, I am pleased with the ways and methods of teaching and knowledge sharing of my teachers and lecturers.
ROZ6	Our academic teachers are available and advise us cordially.
SEL6	I think that knowledge and skills I am gaining during my studies will be useful in my private and professional life.
Removed statements
ZB6	I prefer learning from experts, professionals than reading the scientific literature.
ORG4	I keep information only in electronic form, without any paper copies, hand notes etc.
SEL4	Sometimes I browse documents that I am keeping (both in electronic and paper form) and I throw away unnecessary and redundant materials.

Acknowledgements

I am sincerely grateful to the surveys participants and to my colleagues – IS researchers – from eight universities in Poland, who helped me in data-gathering: Dr Renata Aleksandrowicz, Dr Sabina Cisek, Dr Ewa Chuchro, Dr hab. Małgorzata Kisilowska, Dr Agnieszka Korycińska-Huras, Dr hab. Piotr Nowak, prof.UAM, Dr Vaclava Osińska, Dr Jarosław Pacek, Dr Arkadiusz Pulikowski and Professor Andrzej Wałkówski.

Funding

This work was supported by the National Science Centre in Poland (grant number 2011/03/B/HS2/04436).

Notes

References

Lansdale

. The psychology of personal information management. Applied Ergonomics 1988; 19: 55–66.

Jones

Teevan

. Personal Information Management. Seattle, WA: University of Washington Press, 2007.

Frand

Hixson

. Personal knowledge management: Who, what, why, when, where, how?, 1998, http://www.anderson.ucla.edu/faculty/jason.frand/researcher/speeches/educom98pkm/ (accessed 26 May 2013).

Pauleen

Gorman

. Personal knowledge management: Individual, organizational and social perspectives. Farnham: Gower, 2011.

Doyle

. Information literacy in an information society: A concept for the information age. New York: ERIC Clearinghouse on Information and Technology, Syracuse University, 1994.

Bruce

. The seven faces of information literacy. Adelaide: AUSLIB Press, 1997.

Information Literacy (IL), IL definitions and models, 2013, http://www.informationliteracy.org.uk/information-literacy-definitions/ (accessed 26 May 2013).

Mackey

. Implementing a convergent model for information literacy: Combining research and web literacy. Journal of Information Science 2005; 31: 541–555.

Špiranec

Zorica

. Information literacy 2.0: Hype or discourse refinement? Journal of Documentation 2010; 66: 140–153.

10.

Nazari

. A contextual model of information literacy. Journal of Information Science 2011; 37: 345–359.

11.

Basili

. Report on current state and best practices in information literacy. EMPATIC project report, 2011, http://empat-ic.eu/eng/Reports (accessed 26 May 2013).

12.

Mutch

. Information literacy: An exploration. International Journal of Information Management 1997; 17: 377–386.

13.

Zhang

Majid

Foo

. Environmental scanning: An application of information literacy skills at the workplace Journal of Information Science 2010; 36: 719–732.

14.

Świgoń

. Zarządzanie wiedzą i informacją. Podstawy teoretyczne. Badania w wymiarze indywidualnym. [Knowledge and information management. Theoretical basis. Studies at an individual level]. Olsztyn: Wydawnictwo Uniwersytetu Warmińsko-Mazurskiego w Olsztynie, 2012.

15.

Jones

Thomas

. Understanding interaction between office-based professionals for the development of advanced communication and information technologies. Journal of Information Science 1997; 23: 353–364.

16.

Cheong

RKF

Tsui

. The roles and values of personal knowledge management: An exploratory study. VINE: The Journal of Information and Knowledge Management Systems 2010; 40: 204–227.

17.

Pinto

. Design of the IL-HUMASS survey on information literacy in higher education: A self-assessment approach. Journal of Information Science 2010; 36: 86–103.

18.

Pinto

. Insights into translation students’ information literacy using the IL-HUMASS survey. Journal of Information Science 2010; 36: 618–630.

19.

Schreiber

Harbo

. Information literacy and personal knowledge management, 2004, http://www2.db.dk/NIOD/Schreiber-harbo.pdf (accessed 26 May 2013).

20.

Personal information management workshop, 2012, http://pimworkshop.org/2012/ (accessed 26 May 2013).

21.

Personal knowledge management, 1st international workshop, 2009, http://www.km-conference2009.org/workshops/PKM.php (accessed 26 May 2013).

22.

Personal knowledge management, 2nd international workshop, 2010, http://2010.personalknowledge.org/home (accessed 26 May 2013).

23.

Personal knowledge management workshops. Harold Jarche blog, 2012, www.jarche.com/2012/09/pkm-workshops/ (accessed 26 May 2013).

24.

Jones

. Personal information management. Annual Review of Information Science and Technology 2007; 41: 453–504.

25.

Jones

. Keeping found things found: The study and practice of personal information management. San Francisco, CA: Morgan Kaufmann, 2008.

26.

Jones

. No knowledge but through information. First Monday 2010; 15(9), http://firstmonday.org/htbin/cgiwrap/bin/ojs/index.php/fm/article/viewArticle/3062/2600 ( accessed 26 May 2013).

27.

Detlor

. Information management. International Journal of Information Management 2010; 30: 103–108.

28.

Bruce

. Personal, anticipated information need. Information Research 2005; 10(3), http://InformationR.net/ir/10-3/paper232.html (accessed 26 May 2013).

29.

Khoo

Luyt

. How users organize electronic files on their workstations in the office environment: A preliminary study of personal information organization behaviour. Information Research 2007; 12(2), http://InformationR.net/ir/12-2/paper293.html (accessed 26 May 2013).

30.

Jones

Bruce

Jones

. Providing for paper, place and people in personal project. In: Personal information intersections: What happens when PIM spaces overlap? ASIS&T 2009 workshop, 7–8 November, 2009, Vancouver, BC, http://pimworkshop.org/2009/papers/jones-pim2009.pdf (accessed 26 May 2013).

31.

Bruce

Wenning

Jones

. Seeking an ideal solution to the management of personal information collections. Information Research 2011; 16(1), http://InformationR.net/ir/16-1/paper462.html (accessed 26 May 2013).

32.

Fourie

. Librarians alert: How can we exploit what is happening with personal information management (PIM), reference management and related issues? Library Hi Tech 2011; 29: 550–556.

33.

Fourie

. Personal information and reference management: Librarians’ increasing creativity. Library Hi Tech 2011; 29: 387–393.

34.

Barth

. Self-organization: Taking a personal approach to KM, 2004, www.knowledgeboard.com/download/3285/pkm-chapter-stevebarth.pdf (accessed 26 May 2013).

35.

Wright

. Personal knowledge management: Supporting individual knowledge worker performance. Knowledge Management Research & Practice 2005; 3: 156–165.

36.

Zuber-Skerritt

. A model of values and action for personal knowledge management. The Journal of Workplace Learning 2005; 17: 49–64.

37.

Garcia

. Developing connectivity: A PKM path for higher education workplace learners. Online Information Review 2009; 33: 276–297.

38.

Zhang

. Personalising organizational knowledge and organisationalising personal knowledge. Online Information Review 2009; 33: 237–256.

39.

The Chartered Institute of Library and Information Professionals (CILIP), An introduction to information literacy, 2009, http://www.cilip.org.uk/get-involved/advocacy/learning/information-literacy/Pages/definition.aspx (accessed 26 May 2013).

40.

Society of College, National and University Libraries (SCONUL), The seven pillars of information literacy, 2011, http://www.sconul.ac.uk/sites/default/files/documents/coremodel.pdf (accessed 26 May 2013).

41.

Farradane

. Knowledge, information, and information science. Journal of Information Science 1980; 2: 75–80.

42.

Brookes

. The foundations of information science. Part 1: Philosophical aspects. Journal of Information Science 1980; 2: 125–133.

43.

Rowley

. The wisdom hierarchy: Representations of the DIKW hierarchy. Journal of Information Science 2007; 33: 163–180.

44.

Frické

. The knowledge pyramid: A critique of the DIKW hierarchy. Journal of Information Science 2009; 35: 131–142.

45.

Polanyi

. Personal knowledge: Towards a post-critical philosophy. London: Routledge 1958.

46.

Nonaka

Takeuchi

. The knowledge-creating company. How Japanese companies create the dynamics of innovation. New York: Oxford University Press, 1995.

47.

Miller

. I = 0 (Information has no intrinsic meaning). Information Research 2002; 8(1), http://InformationR.net/ir/8-1/paper140.html (accessed 26 May 2013).

48.

Day

. Clearing up ‘implicit knowledge’: Implications for knowledge management, information science, psychology, and social epistemology. Journal of the American Society for Information Science and Technology 2005; 56: 630–635.

49.

Bennet

. Engaging tacit knowledge in support of organizational learning. VINE: The Journal of Information and Knowledge Management Systems 2008; 38: 72–94.

50.

Al-Hawamdeh

. Knowledge management: Re-thinking information management and facing the challenge of managing tacit knowledge. Information Research 2002; 8(1), http://InformationR.net/ir/8-1/paper143.html (accessed 26 May 2013).

51.

Bates

. Information and knowledge: An evolutionary framework for information science. Information Research 2005; 10(4), http://InformationR.net/ir/10-4/paper239.html (accessed 26 May 2013).

52.

Alavi

Leidner

. Review: Knowledge management and knowledge management systems: Conceptual foundations and research issues. MIS Quarterly 2001; 25: 107–136.

53.

Wilson

. The nonsense of knowledge management. Information Research 2002; 8(1), http://informationr.net/ir/8-1/paper144.html (accessed 26 May 2013).

54.

Buckland

. Information as thing. Journal of the American Society for Information Science 1991; 42: 351–360.

55.

Davenport

Prusak

. Working knowledge. How organizations manage what they know. Boston, MA: Harvard Business School Press, 1998.

56.

Jashapara

. The emerging discourse of knowledge management: A new dawn for information science research? Journal of Information Science 2005; 31: 136–148.

57.

Martin

. Knowledge management. Annual Review of Information Science and Technology 2008; 42: 369–424.

58.

Serenko

Bontis

. The intellectual core and impact of the knowledge management academic discipline. Journal of Knowledge Management 2013; 17: 137–155.

59.

Kruger

Johnson

. Information management as an enabler of knowledge management maturity: A South African perspective. International Journal of Information Management 2010; 30: 57–67.

60.

Kebede

. Knowledge management: An information science perspective. International Journal of Information Management 2010; 30: 416–424.

61.

Barreau

. The persistence of behaviour and form in the organization of personal information. Journal of the American Society for Information Science and Technology 2008; 59: 307–317.

62.

Macevičiūtė

Wilson

. The development of the information management research area. Information Research 2002; 7(3), http://InformationR.net/ir/7-3/paper133.html (accessed 26 May 2013).

63.

Koenig

MED

. Intellectual capital and how to leverage it. The Bottom Line: Managing Library Finances 1997; 10: 112–118.

64.

Koenig

MED

. Knowledge management, user education and librarianship. Library Review 2003; 52: 10–17.

65.

Hjørland

. Library and information science: Practice, theory, and philosophical basis. Information Processing and Management 2000; 36: 501–531.

66.

Zins

. Classification schemes of information science: Twenty-eight scholars map the field. Journal of the American Society for Information Science and Technology 2007; 58: 645–672.

67.

Zins

. Conceptions of information science. Journal of the American Society for Information Science and Technology 2007; 58: 335–350.

68.

Zins

. Knowledge map of information science. Journal of the American Society for Information Science and Technology 2007; 58: 526–535.

69.

Zins

. Redefining information science: From ‘information science’ to ‘knowledge science’. Journal of Documentation 2006; 62: 447–461.

70.

Bloom

. Taxonomy of educational objectives: The classification of educational goals; Handbook I: Cognitive Domain. London: Longman, 1956.

71.

Cheetham

Chivers

. The reflective (and competent) practitioner: A model of professional competence which seeks to harmonise the reflective practitioner and competence-based approaches. Journal of European Industrial Training 1998; 22: 267–276.

72.

Winterton

Stringfellow

. Typology of knowledge, skills and competences: Clarification of the concept and prototype, 2005, http://www.ecotec.com/europeaninventory/publications/method/CEDEFOP_typology.pdf (accessed 26 May 2013).

73.

Winterton

. Competence across Europe: Highest common factor or lowest common denominator? Journal of European Industrial Training 2009; 33: 681–700.

74.

Dervin

. Sense-making theory and practice: An overview of user interests in knowledge seeking and use. Journal of Knowledge Management 1998; 2: 36–46.

75.

Godbold

. Beyond information seeking: Towards a general model of information behaviour. Information Research 2006; 11(4), http://InformationR.net/ir/11-4/paper269.html (accessed 26 May 2013).

76.

Jones

Thomas

. Empirical assessment of individuals’ ‘personal information management systems’. Behaviour and Information Technology 1997; 16: 158–160.

77.

Grundspenkis

. Agent based approach for organization and personal knowledge modelling: Knowledge management perspective. Journal of Intelligent Manufacturing 2007; 18: 451–457.

78.

Jung

. Knowledge distribution via shared context between blog-based knowledge management systems: A case study of collaborative tagging. Expert Systems with Applications 2009; 36: 10627–10633.

79.

Völkel

Haller

. Conceptual data structures for personal knowledge management. Online Information Review 2009; 33: 298–315.

80.

Pirró

Mastroianni

Talia

. A framework for distributed knowledge management: Design and implementation. Future Generation Computer Systems 2010; 26: 38–49.

81.

Razmerita

Kirchner

Sudzina

. Personal knowledge management: The role of Web 2.0 tools for managing knowledge at individual and organizational levels. Online Information Review 2009; 33: 1021–1039.

82.

Agnihotri

Troutt

. The effective use of technology in personal knowledge management: A framework of skills, tools and user context. Online Information Review 2009; 33: 329–342.

83.

Doong

Wang

. Predictors of diverse usage behaviour towards personal knowledge management systems. Online Information Review 2009; 33: 316–328.

84.

Pircher

. Targeting the blind spot: Personal knowledge management as an enabler for knowledge creation and application, 2010, http://2010.personalknowledge.org/home (accessed 26 May 2013).

85.

Reforms of research and higher education systems in Poland. Ministry of Science and Higher Education, 2010, http://www.nauka.gov.pl/ministry/reforms-of-research-and-higher-education-systems-in-poland/ (accessed 26 May 2013).