Using TechMining for designing research policy in a Colombian Higher Education Institution

Extended Abstract – NEW INDICATORS session at “1st Global TechMining Conference” 2011

Author(s):Jenny Marcela Sanchez-Torres (Universidad Nacional de Colombia)

The most important Higher Education Institution –HEI- of Colombia has designed a model for measuring its R&D activities which has a set of indicators, some of them are calculated using techmining techniques. Its results as used as input for formulating and implementing R&D policies. This paper shows this experience.

Measuring research capabilities at Universidad Nacional de Colombia.
One of the main challenges of the most important Higher Education Institution –HEI- of Colombia -Universidad Nacional de Colombia –UNAL has been to be a research university; however, before 2008 research policy-makers only had basic information related with its research and development –R&D activities. The UNAL is the biggest Colombian public university with 35000 students and 2993 researchers with eight branches around the country. Thus, during 2008 and 2009, the UNAL designed and implemented a model for measuring R&D capabilities. That model has two components: i) an Intellectual Capital -IC- measuring module; and, ii) a module for identifying thematic R&D capabilities using IC approach (Sánchez-Torres y Rivera, 2009). The first component shows a general R&D profile observing human, structural and relational capital thorough a system of indicators. It means that the Colombian HEI has designed a set of forty three indicators, thirty three of which are directly related to R&D activities, four related to formation activities and six related to third mission activities. The second component gives a specific R&D profile related with knowledge thematic also accounting human, structural and relational capital aspects.

With this framework, this paper analyzes and shows how the Colombian HEI, using some indicators which are calculated with tech-mining techniques, has given inputs for designing and implementing policies related with R&D activities.

In order to achieve this target using the results of the intellectual capital model the Colombian HEI found several shortcomings that show a weak R&D activities; for instance, during 2000 and 2008 UNAL´s researchers has published close to 2400 papers on ISI web of knowledge (20% of the Colombia´s production); however, 86% of these papers have between 1 and 10 citation; 76% of the authors of these papers has one in the whole period; the most important journals are UNAL´s journal with a low impact factor; close to 50% papers were written with  international collaboration and close to 70% papers were written with national collaboration (VRI et al, 2009). We have identify just 10 researcher groups who have international projection – more than 5 papers on SCOPUS or ISI web of knowledge plus more than 3 R&D international projects and more than 2 doctoral students during 2000-2008 (Molina y Sánchez-Torres, 2010).

Subsequently, inside of the Colombian HEI, different groups have worked in those shortcomings and have proposed different strategies to solve or mitigate them. These strategies were defined on the current Development Global Plan -DGP- for 2010 – 2012 period. The DGP has twelve R&D strategies; at least, seven of those strategies have arisen based on the inputs generated by the model combined with on policymakers expertise. We answered our research question through a qualitative way.

Formulating and implementing R&D policies
Applying the model provided a fourth type of results. (The model has been applied three times, the first results were published in (VRI et al, 2009) The second and the third results have an e-book. You can download these three publications from  http://www.viceinvestigacion.unal.edu.co/VRI/index.php)?option=com_content&view=category&layout=blog&id=13&Itemid=61)

The first one is related to reporting R&D capabilities (intellectual capital overview and thematic intellectual capital) of the UNAL, in other words, it means UNAL has reported time-series for years in the present decade for several indicators of the set.

The second one is associated with managing R&D within UNAL the process of designing and implementing R&D policies let to input being obtained for supporting decision-making processes. As we have mentioned for the UNAL, these policies are defined on the current DGP 2010-2012, which has twelve R&D strategies; at least, five of those strategies have arisen based on the inputs generated by the model combined with on policy-makers expertise. These strategies are: i)knowledge generation according with international levels; ii)knowledge for Colombia´s social and productive transformation; iii) academic production visibility; iv)Student and Professor Mobility Program; v) strengthening young researchers and artists; vi) strengthening researchers and artists; vii) R&D agendas for priorities areas. For instance, measuring human capital defined policy guidelines in areas of knowledge (whether linked to production sectors or not) in which UNAL have had consolidated capabilities, in construction or which were still growing, and inputs (including indicators and maps of general and specific capabilities) are obtained for initiating processes for defining long-term R&D agendas.

The third result is related to feed-back for the model and learning about process of applying it and measuring R&D capabilities in HEIs.

The fourth one is associated with managing R&D in other Colombian public HEIs whom have become to adapt the model for their own interested.

Applying tech mining techniques for calculating the most relevant indicators are those concerning with relational capital which presented UNAL’s interactions with other institutions arising from co-authoring/coresponsibility processes, inter-institutional work teams’ share in research projects and extension courses, the research policy-makers have obtained inputs for strengthening formation and internationalisation strategies considering guidelines for orientating the professors and students’ mobility strategy within HEI. It also has strengthened management processes for promoting R&D activities with external resources, on constructing spaces in national and international scale networks and R&D projects and strengthened links between the university and other social actors, between industry and the State.

Likewise, measuring structural capital (for instance, analysing Web of Science or Scopus or other Index Citations Systems) has led to obtaining policy inputs orientated towards by consolidating the academic community in terms of strengthening production having national and international visibility defining, by one hand, guidelines for writing-speaking-promoting programmes for foreign languages; and the other hand, special programs for increasing the editorial quality of the UNAL´s journals.

Ultimately, it is remarkable that UNAL has used its own databases or national databases as SCienTI or Web of Science and so on, for tech-mining analyst. (i.e. human resources database, R&D projects database). In order to be “easier” the decision-making processes the tech-mining reports are graphical depictions with short text interpretation.

Conclusions
The set of the model´s results and tech-mining results have obtained useful information at the right time for supporting decision-making processes. The policy-makers, by one hand, have achieved several data from different sources and have designed and implemented R&D policies; and by the other hand, have an instrument for following up these R&D policies. In spite of Tech mining reports are a good input for decision making process it is necessary to combine with an expert opinion.

An institution as a UNAL could have a number of own databases for providing coverage of its R&D activities. The databases preference will vary according to HEI needs. Using Tech mining techniques combined with an expert opinion as an inputs for designing, implementing and following-up R&D policies allow HEIs to have a heritage of knowledge and consolidate their R&D capabilities, advance their R&D processes.

References
Molina R. Sánchez-Torres JM. Caracterización de los grupos de investigación, una experiencia de aplicación de política pública en la Universidad Nacional de Colombia. En: Corrales, V; Castañeda B (Coord) 2010; Redes y Grupos de Investigación en la Sociedad del Conocimiento. Una panorámica desde las IES Iberoamericanas. Tomo III. pp 111-128 Sinaloa. ISBN: 978-607-7929-42-0.

Sánchez-Torres, JM,.Rivera, SC “A model for measuring research capacity from an intellectual capital based approach in a Colombian higher education institution.” Innovar: Revista De Ciencias Administrativas y Sociales, ISSN: 0121-5051. Bogotá. V19. p.179 – 197

Universidad Nacional de Colombia. Vicerrectoría de Investigación -VRI- Molina R, Sánchez-Torres JM, Landinez L, Rivera S, Gomez A. (2009). Capacidades de investigación de la Universidad Nacional de Colombia 2000-2008. Una aproximación desde el capital intelectual. Bogotá: Editorial Universidad Nacional de Colombia. 364 pp. ISBN: 978-958-719-368-8

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