Knowledge Utilisation (KU) in Education: Lessons learned from other social sciences
Marjan Vermeulen
(Eapril nov 2014)
Abstract (ingeleverd 100 w)
Knowledge Utilisation (KU) in education is considered important by researchers, policy and practitioners. Although the debate on KU started some decennia ago, still little is known about successful factors which enhance KU. More insights on conditions that affect the usability of research knowledge and the processes that can lead to the use in the educational field, can be gained by studying the concepts and findings on KU in other areas, such as healthcare, were more research has been done. However, transition of knowledge from one situation to another is difficult, therefore a research program on KU in education is needed.
Abstract
Knowledge Utilisation (KU) in Education is gaining more and more attention from researchers, policy and practitioners. Although the debate on the use of research knowledgein educational practice within the research communityhas started some decennia ago, still little is known about successful factors to enhance knowledge utilization. In this debate different perspectives on knowledge (what is knowledge?) play an important role. This should be clarified before more insights can be gained More insights can be gained on conditions that affect the usability of research knowledge and the processes that can lead to the use of (research) knowledge in the educational field, by studying the concepts and research outcomes in other area’s such as Healt-care and agriculture.
Introduction
An often used representation of knowledge, based on a the view that knowledge is constructed (constructivism) comes from the work of Cleveland (1982), who presented the DIKW (Data, Information, Knowledge, Wisdom)pyramid. Many representations have been made throughout the years, a well-known is represented below.
Ceveland (1982) stated that understanding is a continuum by distinguishingdata, information, knowledge and Wisdom, based on the following definitions:
Datacomes about through research, gathering, and discovery.By organizing, analysing data(in order to draw conclusions) data is turned into information. Organizing can be done by for example "presenting", making it visual or auditory.
Informationhas context and it is static. For information to become knowledge experience is needed.
Knowledgehas the complexity of experience, seeing it from different perspectives, it is dynamic as we continually are constructing knowledge.Therefore, one cannot count on one person's knowledge transferring to another. In order for knowledge to become wisdom, knowledge needs to be communicated with even more insights in the personal contexts of our audience than with knowledge sharing.
WisdomisClevelands (1982) ultimate level of understanding. As with knowledge, wisdom is personal. We can share our experiences and in doing so we create the building blocks for wisdom.
There is some criticism on this representation of this continuum of understanding. For example the differences between definitions of data and information or information and knowledge and or wisdom and the sequence (pyramid), without loops. But for the purpose of this paper, the problem of the lack of knowledge utilization form research to the educational field, it is gives insight in what we are talking about, and an orientation on were the problems lay. ‘Knowledge’ from research is for a practitioner in the educational field not more than ínformation’. In order to become knowledge in terms of Cleveland, it must be experienced.
Models of Knowledge utilization
In the research community the debate on knowledge utilization, transformation or implementation (different words are used) is an important topic for some decennia. The debate is conducted from diverse perspective, stakeholders, and viewpoints. Although many different analyses and solutions are uttered, there is an agreement on the fact that the lack of utilization is not a problem solved easily and that there is a necessity of more practical use of research knowledge in educational practice. The lack of utilization of research outcomes is often called the ‘gap’ between the world of practice and the world of researchers (Ros & Vermeulen, 2010Eapril). When searching the web, many articles (more than 2400 in ebsco host on the keywords gap research practice education) can be found on the topic of the ‘gap’. However more overall models.
In the past decades, two models are proposedto overcome this ‘gap’: a linear one proposing a one way process from research to practice (more practical publications for example). Or a more interactive and incremental model presuming a dialogue or in other words a relationship model, were more co-production between practice and research is a key issue. The latter has been worked out in an instrument for practice based research by Vermeulen and Ros for an Eapril paper in 2012. In the healthcare science yet an another form is mentioned;system or network models. These models aim ata more broadly incorporation of the complex structures and contexts in which these dialogues are embedded (Wherens, 2014).
Classification on products of KU
Besides this so called process oriented model, a classification is developed that takes into account products of knowledge use; Instrumental, symbolic or conceptual. Instrumental use is research knowledge that directly shapes results in action in practice. Conceptual use refers to a change in awareness or understanding of a specific topics. Finally a symbolic use legitimizes existing policies, decisions or positions (Mitton, Adair, McKenzie, Patten, & Perry, 2007). Besides models for the products of KU also explanation has been sought for the processes underlying KU.
Four models explaining KU processes
The technological model or the science pus model (Landry, et al., 2001) focusses on the supply of research findings as the major determinants of KU (and can be compared with the linear model), factors who are of influence are; content attributes, type of research and research domains and disciplines.
The economic model (or demand pull model), stresses the needs and the context of the users to get more KU. Success factors are the way the research project fits to the needs of the users.
The institutional dissemination model explains KU by the combination of the former models, pushing the results and adaption on the user need.
Finally the social interaction model, (or interaction model) has been developed to overcome the criticism of the previous mentioned models (Landry, Amara & Lamari, 2001).This model combines the previous success factors and adds social interaction. It predicts that the more intense and sustained the interaction between researcher and user is at the different stages of the research the more KU takes place.
Borrowing from other research fields
Although, the development from linear models to complex is seen as huge progress in addressing the problems of KU (Wherens, 2014), these models are still based on an underlying issue, namely the ‘gap’ between two communities or two worlds (research and practice). Others (Belkhodja, 2014) state that the field of KU is still in its infancy with regard to the development of a conceptual framework for KU, and therefore there is only a use of concepts borrowed from other disciplines such as decision making.
Based on these four models Landry, Amara & Lamari, (2001) introduced the ladder of research knowledge utilization, consisted of six stages, based on the decision making ladder and increasing in the way knowledge is used.
figure 1 Stages of the ladder of Knowledge Utilization (Landry, Amara & Lamari, 2001)
Results from their empirical research (from the point of view of the researcher) leads to some important conclusions. First researchers should decide which stages of utilization they want and which actions they take to accomplish that. The higher the researcher wants to climb on the ladder, the more cost (money and effort) to accomplish this. The other mechanism is that the more utilization the more the results are used by a single user. KU for the largest possible number of users with the highest stage on the ladder is yet a contradiction.
Overall the crucial stage of KU seems to be transmission, nearly 30% of the scholars failed to reach this stage (Landry et al, 2001). Variables that influence coming in this stage are types of research methods, focus on advancement of scholarly knowledge, external funding, users’context, adaption of products, dissemination efforts, and linkage mechanisms. Only two variables explain the climbing up higher; external funding and users’ context. Landry et al (2001) suggest that there are barriers between no transmission and the stage of transmission[MV1]. These results are interesting for utilization in the educational sector, but two warnings should be kept in mind. First the science discipline is of great importance when it comes to utilization, every discipline have its own specific characteristics that influence KU, here no distinction could be made between the disciplines. Second, only the point of view of the researcher is taken into account. The perception of utilization from the practice is missing, as in most of the research on KU of research results.
Research among practitioners and administrators in social services lead to the conclusion that KU benefitted when there was relational capital among researchers and practitioners and when users perceived usefulness of the research based knowledge was higher. For administrators,in the variable perceived usefulness, the dissemination efforts of the researcher played an important role, for practitioners the use of active knowledge transfer strategies was more essential.
Finally, because of the lack of knowledge on KU in the educational field (science, practice and policy) we should gather evidence on what factors determine KU on three dimensions, the KU ladder, combined with the number of users (micro level for a single user such as a teacher or a teachers team; meso level; the whole organization(s) even if they are not immediately involved; the macro level being the level from a whole group of schools or specific sector (for instance special education, or vocational education) to the national level including all schools, teachers or other personnel).
Perhaps a starting can be made by funding research on KU initiatives, and besides the requirements in the tender formats that KU strategy has been formulated, based on effective variables, enforce commitment for cooperation by the evaluation of these strategies in order to build on our knowledge how to successfully enhance KU.
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References
Belkhodja, O. (2014). Knowledge Utilization in Canadian Health Service Organizations: A Path Analysis.International Journal Of Public Administration,37(6), 339-352.
Chagnon, F., Pouliot, L., Malo, C., Gervais, M., & Pigeon, M. (2010). Comparison of determinants of research knowledge utilization by practitioners and administrators in the field of child and family social services.Implementation Science,5(1), 41.
Cleveland H. (1982) "Information as Resource", The Futurist, December 1982 p 34-39.)
Desforges, Charles, (2001). Learning and Skills Development Agency. 2001.Putting Educational Research to Use through Knowledge Transformation. The Agency Comments. n.p.: 2001.ERIC, EBSCOhost(accessed October 25, 2014).
Mitton, C., Adair, C. E., McKenzie, E., Patten, S. B., & Perry, B. (2007). Knowledge Transfer and Exchange: Review and Synthesis of the Literature.Milbank Quarterly,85(4), 729-768. doi:10.1111/j.1468-0009.2007.00506.x
Ros, A., & Vermeulen, M. (2010). Standards of Practice-Based Research. Paper, presented at the EAPRIL in Lissabon.
Vermeulen, M. & Ros, A. (2011). An instrument for design choices. Paper, gepresenteerd op de EAPRIL in Nijmegen.
Wehrens, R. R. (2014). Beyond two communities - from research utilization and knowledge translation to coproduction?.Public Health (Elsevier),128(6), 545-551. doi:10.1016/j.puhe.2014.02.004
[MV1]The receptivity of users to research (users’ context) explained the ascent from transmission to influence.
The influence of funding of sources outside the university explained climbing from no transmission at all to application.
Furthermore when internal funding is the case, it is difficult to even come in the stage of transmission. Factors that influence this stage are the number of publications.
The variable focus on users’ needs totally failed to explain a climb up the ladder , the variable users’ context however predicted the stage of transmission, the step from transmission to cognition, or from cognition to reference ect until the stage of influence.
Adaption of products and dissemination efforts turned out to be predictors to get in the stage of transmission, but not for climbing further on the ladder.
Finally, linkage mechanisms (from the social interaction model) explained the stage of transmission and from transmission to cognition, but no further climb up on the ladder.