Measuring Knowledge Transfer Research Articles

ConBERT-RL: A policy-driven deep reinforcement learning based approach for detecting homophobia and transphobia in low-resource languages

In this work, we present a novel framework for discriminatory comment classification in targeted low-resource languages thereby enabling identification of discriminatory comments for promoting safer online environment in linguistically diverse contexts. Recently proposed literatures with Bidirectional Encoder Representations from Transformers (BERT) and its variants, have produced promising results, particularly in the case of transliterated Tamil words in English. Such approaches are seen as transfer learning and fine-tuning between a general environment and targeted downstream task. However, for an effective transfer of knowledge, from a source task to a targeted task, their feature space has to be correlated (similarity measure as metric, to measure knowledge transfer), which is unexplored in the previous literature works. In practice, such similarity conditions are often violated. We propose a Concatenated representation, powered with BERT in Reinforcement Learning (RL) - ConBERT-RL framework, to capture problem-specific features, as well as to understand nuances in case of transliterated Tamil words into English, to make decision in classifying discriminatory comments. ConBERT-RL incorporates a fusion of learned hidden-state representation from our pre-trained Classifier-Model (CM), along with the broader contextualized representation (pooled output) from BERT. The key idea is to utilize this concatenated representation to drive our policy network for hate comment classification. To effectively learn such a policy, we use the REINFORCE algorithm in a reinforcement learning setting, to guide our ConBERT-RL agent, in making informative decisions. To demonstrate the general aspects of ConBERT-RL, we conduct experiments for offensive comment classification on transliterated Tamil words in English dataset. ConBERT-RL obtains results, where it significantly improved the score of micro average accuracy with 90% (≈1.0% absolute improvement over BERT+FC), 93% (≈3.0% absolute improvement over BERT+FC), on transliterated Tamil words in English and an English-only dataset respectively. To further extend support to our previous argument, we present a 2-dimensional t-distributed Stochastic Neighbour Embedding (t-SNE) visualization of ConBERT-RL’s concatenated representation. Additionally, to compare the feature space understanding, specific to the problem of discriminatory comment, we present a graph network comparison our concatenated representation with BERT output embedding. We also design and conduct, a systematic evaluation, to observe the broader capability of ConBERT-RL, in capturing the contextual words in the vicinity of the primary offensive term, that amplifies an offensive term in the given input comment. We show that ConBERT-RL is robust and effective in capturing targeted language specific features for hate comment classification.

Measuring efficiency and effectiveness of knowledge transfer in e-learning

With e-learning rapidly gaining popularity, evaluating its effectiveness and efficiency has become a challenge in public education, the public sector, and the corporate sector. Measuring knowledge transfer is crucial in any learning process, but e-learning lacks validated methods for this. Here we examine ways to evaluate that particularly in case of e-learning, conducting a literature review to assess available measurement solutions, developing an evaluation method for knowledge transfer, and validating the method. Using logged data from e-courses, it is possible to assess the knowledge transfer in e-learning. We describe a novel method for classifying effectiveness and efficiency with measured values and measurement instruments. The new measurement method was aligned with a data set of an existing learning management system, and the effectiveness and efficiency of knowledge transfer was analysed using quantitative means, including descriptive statistics, regression modelling, and cluster analysis based on a specific e-learning course. This newly elaborated and validated knowledge transfer measurement technique could be a useful tool for anyone wanting to evaluate e-learning courses and can also serve as a baseline for academics to further develop or implement it on larger empirical datasets.

Measuring Knowledge Transfer in Innovation Projects: A Comparative Analysis

Collaboration of organizations with universities and research institutes is a way of decreasing not only the time but also the cost of R&D activities in innovation projects. This paper is a study on knowledge transfer measurement models in order to analyze their metrics and identify the use of techniques for measuring the flow of knowledge between companies, public research institutes, and universities in national innovation surveys. The comparative analysis of these models is part of a study to evaluate the ways to measure the impact of universities on society through innovation projects.

Dairy producer satisfaction and knowledge transfer with the veterinary-administered risk assessment and management plan in a voluntary Johne's disease control program

The Atlantic Johne's Disease Initiative (AJDI) aims to control Mycobacterium avium ssp. paratuberculosis infection by using veterinary-administered risk assessments to identify high-risk management practices and prompt changes in management behavior. Objectives for this study were to measure producer satisfaction with the veterinary-administered risk assessment and management plan (RAMP) process in a voluntary Johne's disease (JD) control program, compare RAMP-specific satisfaction results based on herd JD status, and measure knowledge transfer from certified veterinarians to producers during the RAMP. A satisfaction questionnaire was adapted to the RAMP process in the AJDI to measure producer satisfaction. The questionnaire included 9 RAMP-specific producer satisfaction items, 1 global RAMP satisfaction item, and 16 questions to assess producer knowledge and knowledge translation about JD, bovine viral diarrhea (BVD), and bovine leukosis virus (BLV) during the RAMP (BVD and BLV used for comparison purposes). A total of 133 dairy producers in the AJDI (79.6% response rate) completed the questionnaire by telephone. The RAMP-specific satisfaction was high among the AJDI producers surveyed, and these results were not found to differ based on herd JD status. The lowest satisfaction scores and the highest number of "unable to assess" responses were for the item relating to cost. Factors that contributed to RAMP-specific producer satisfaction were not identified from the demographic and herd information available in this study. The knowledge scores indicated moderate knowledge about JD and fair knowledge about BVD and BLV. Evidence of knowledge translation from the RAMP was mixed in this study. Bovine viral diarrhea knowledge scores were not found to differ based on whether or not the certified veterinarian discussed BVD during the preceding RAMP, but BLV knowledge scores were higher among dairy producers that discussed BLV during the preceding RAMP. Strengths and gaps in producer knowledge about these 3 infectious diseases were identified. By using this producer questionnaire, interventions aimed at improving the content, delivery, and satisfaction of RAMP in JD control programs, such as the AJDI, can be developed.

Measuring the knowledge translation and convergence in pharmaceutical innovation by funding-science-technology-innovation linkages analysis

Abstract We propose a backward tracking model for measuring knowledge transfer in the whole translational research spectrum. Using the drugs-patents-papers-grants backward linkages, we try to figure out the funding-science-technology-innovation translational pattern and ponder some policy implications on e.g., which priority areas and knowledge convergence level are more likely to generate new drugs. The drug-patent linkage data was accessed through the USFDA Orange Book, covering a drug's active ingredient, formulation, or methods of use for approved indications. It will take about 10 years from the application of earliest patent to the approval of the new drug. Also such high-value patents in FDA Orange Book tend to cite scientific knowledge published on average 10–15 years ago. The technology linkage of new drugs was relatively stable while the science linkage of technology inventions increased rapidly. Among the scientific papers cited by drug patents, private-institution originated papers are only a quarter of the public. By linking theses scientific papers with funding sources, we found a large majority (90%) are public-funded and only a very small part are private-funded or public-private joint-funded. Our study also indicates the importance of research on such fields as pharmacology, chemistry (including medicinal chemistry, biochemistry, and organic chemistry), molecular biology, neurosciences, and immunology on new drugs innovation. There is no obvious relationship between “basicness” and linkages to the resulting patents’ impact and to drugs innovation. A balanced basic research and applied research maybe essential for fostering drug innovation because it is a complete chain translating from basic discovery to clinical evidence then to clinical practice. In order to achieve successful pharmaceutical innovation, rather than focusing on only technology, convergence with science at moderate levels (maybe 1/3) is suggested.

A new bibliometric approach to measure knowledge transfer of internationally mobile scientists

This study introduces a new bibliometric approach to study the effects of international scientific mobility on knowledge transfer. It is based on an analysis of internationally mobile and non-internationally mobile German scientists publishing in journals that are indexed in Scopus. Using bibliometric data such co-authored articles, references and lexical abstract terms from the Scopus database, a method is presented that is based on cosine similarity to measure the similarity of the knowledge base of authors and their co-authors. This quantifiable method is capable of revealing potential knowledge transfer between internationally mobile scientists and different types of co-authors. In addition, the Shannon index is used as a diversity measure to analyse the knowledge base of scientists. Analyses are presented for an overall 9-year publication period (2007–2015), split into a pre-mobility phase, a mobility phase and a post-mobility phase, each of which lasts for 3 years. Internationally mobile scientists are compared with non-internationally mobile scientists and the potentials and limitations of the method presented are discussed. It is concluded that the bibliometric approach proposed is useful when applied on a large scale. International mobility proves to benefit the exchange of knowledge between scientists and various types of co-authors.

Navigating the Health Care System: An Adolescent Health Literacy Unit for High Schools

Currently, no intervention concerning transition of health care responsibilities from parents to teens exists for adolescents in the general population. The purpose of this intervention was to evaluate teacher satisfaction and student knowledge gain of a health unit developed for adolescents on becoming their own health care advocates. Throughout the 2014-2015 school year, 13 health and career technical education teachers in 11 Delaware high schools taught the unit to 948 students in 2 90-minute classes in 35 classrooms. Assessments included teacher reflections and student pre- and posttests to measure knowledge transfer and gain and gather feedback. Teacher and student feedback indicated the materials were appropriate and useful in teaching students to navigate the health care system. Student knowledge increased from pretest (64%) to posttest (82%), (p < .001). The educational background of the teacher did not influence this outcome. Students reported they will know what to do better at their next doctor's appointment because of this unit and indicated support for peers to learn this information. The unit resulted in content knowledge increase for students. It was consistently effective throughout all schools regardless of social and demographic characteristics, teacher type, or experience teaching the unit.

Measuring Knowledge Transfer through Facebook of Higher Education Classroom

 Abstract—This paper presents the outcome of a research that investigates the trend, attitude and perception of students using social media to share knowledge in the classroom. Whilst some people perceived social media as a phenomenon that distracts students from focusing on their studies, others view social media as a technology that can facilitate teaching and learning. This study used mixed method via questionnaire and using focus group to write and share knowledge through social media from 247 students in Nakhon Si Thammarat Rajabhat University of Thailand. The results of the study found that most students used Facebook to discuss and share knowledge in higher education classroom. This study highlights the advantage of social media via Facebook for sharing knowledge in the classroom and used as tools for teaching and learning.

Explicit Knowledge Transfers in New Product Development

The literature on learning in new product development (NPD) documents the processes globally but is short on specifics. Knowledge levels are not clearly conceptualized, nor are there clear devices for documenting knowledge transfers in terms of knowledge levels. This paper presents the methods of a qualitative research approach for measuring knowledge transfer directly in terms of knowledge. The paper specifically addresses the commonly avoided dimension of knowledge, depth. The methods are derived from a real-life comparative case study exploring knowledge sharing in product development. Our focused interview approach has been refined to avoid unproductive digressions by the subjects and certain forms of bias, yet still obtain rich accounts of project events. Evidence of transfer obtained by the interviews is analysed in terms of three knowledge dimensions: scope, depth and action. Methods for aggregating and interpreting data are discussed and an operational flowchart for knowledge transfer coding is proposed.

How Should We Measure Knowledge Transfer? : Comparison of the Knowledge Source's and the Recipient's Perspectives

How Should We Measure Knowledge Transfer? : Comparison of the Knowledge Source's and the Recipient's Perspectives

Making sense of knowledge transfer and social capital generation for a Pacific island aid infrastructure project

PurposeThe purpose of this research is to investigate how lessons learned from a case study of a construction project undertaken in the Pacific Islands relates to the interaction between social capital and knowledge transfer. The paper is reflective in nature focusing upon the experiences of one of the authors, being a Pacific Islander and trying to make sense of the role of social capital and the way that it impacts upon knowledge transfer.Design/methodology/approachThree theoretical frameworks are drawn upon in a pilot test of tools used to better understand and measure knowledge transfer including barriers to knowledge transfer to help explain the difficulty of knowledge transfer in a given context and the development of social capital for a foreign aid project. These tools allowed us to visualise project stakeholder outcomes for knowledge transfer and building social capital that were articulated by the aid recipient as being highly important. This was a pilot study and results reported upon in this paper were fed back to stakeholder representatives concerned for their comment and validation. Project documentation data, unstructured ad hoc interviews, together with personal reflection‐in‐practice, were gathered and used for the study.FindingsThe approach was found to be very useful in helping stakeholders better visualise and measure this project outcome, whereas experience from previous similar projects indicated that it was very difficult for stakeholders to find a tangible way of measuring this important element of success or failure.Originality/valueMany projects of the type exemplified by the case studies are funded by aid agencies. This paper makes a contribution by presenting an evaluation tool for intangible project outcomes. The findings may influence the design of project success measures.

Identifying and Measuring Knowledge Transfer in the Consumer New Brand Purchase Decision

ABSTRACT In the purchase decision of a new brand from a multi-branding firm, a consumer is likely to rely upon what he/she knows about the company to make an initial judgement. This paper attempts to explore how established consumer knowledge influences the consumer's new brand purchase intention and how the knowledge transfer can be moderated by some product characteristics. In this research, consumer knowledge is conceptualised by two variables, Category Expertise Belief and Category Association Belief, and product characteristics are measured by Product Sign Value and Product Pleasure Value. The research findings will help the brand manager understand how to shape and take advantage of consumer knowledge to facilitate consumer acceptance of a new brand.

Measuring knowledge transfer between fields of science

In this paper we report on the results of an exploratory study of knowledge exchange between disciplines and subfields of science, based on bibliometric methods. The goal of this analysis is twofold. Firstly, we consider knowledge exchange between disciplines at a global level, by analysing cross-disciplinary citations in journal articles, based on the world publication output in 1999. Among others a central position of the Basic Life Sciences within the Life Sciences and of Physics within the Exact Sciences is shown. Limitations of analyses of interdisciplinary impact at the journal level are discussed. A second topic is a discussion of measures which may be used to quantify the rate of knowledge transfer between fields and the importance of work in a given field or for other disciplines. Two measures are applied, which appear to be proper indicators of impact of research on other fields. These indicators of interdisciplinary impact may be applied at other institutional levels as well.