Training Information Brokers: A Curriculum Model

Christozov, Dimitar; Denchev, Stoyan; Toleva-Stoimenova, Stefka; Rasheva-Yordanova, Katya

doi:10.28945/997

Cited by 3 publications

(2 citation statements)

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“…The major of Information Brokerage was launched in 2002 (Christozov et al, 2008). During this period, it was updated several times to address changes in the area.…”

Section: Information Brokerage and Informing Science Concentrationmentioning

confidence: 99%

“…The two transdisciplines -Informing Science and Data Science -are in the scope of the Bulgarian University of Library Studies and Information Technologies (ULSIT). An information brokerage major was launched in 2002 (Christozov, Denchev, Toleva-Stoimenova, & Rasheva-Yordanova, 2008;Christozov & Nikolova, 2001) and its evolution follows developing Informing Science as a scientific field. Designing an Informing Science concentration within the Information Brokerage major and a Master program in Data Science, emphasizing the transdisciplinary nature of the two fields, faces several challenges, including what are the leading objectives in designing curriculum, how to define the content a discipline has to cover and the competences to train, what is an acceptable way of splitting the content in separate courses and scheduling offerings, how to identify and attract competent instructors.…”

Section: Introductionmentioning

confidence: 99%

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Challenges in Designing Curriculum for Trans-Disciplinary Education: On Cases of Designing Concentration on Informing Science and Master Program on Data Science

2019

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Aim/Purpose: The growing complexity of the business environment and business processes as well as the Big Data phenomenon has an impact on every area of human activity nowadays. This new reality challenges the effectiveness of traditional narrowly oriented professional education. New areas of competences emerged as a synergy of multiple knowledge areas – transdisciplines. Informing Science and Data Science are just the first two such new areas we may identify as transdisciplines. Universities are facing the challenge to educate students for those new realities. Background: The purpose of the paper is to share the authors’ experience in designing curriculum for training bachelor students in Informing Science as a concentration within an Information Brokerage major, and a master program on Data Science. Methodology: Designing curriculum for transdisciplines requires diverse expertise obtained by both academia and industries and passed through several stages - identifying objectives, conceptualizing curriculum models, identifying content, and development pedagogical priorities. Contribution: Sharing our experience acquired in designing transdiscipline programs will contribute to a transition from a narrow professional education towards addressing 21st-century challenges. Findings: Analytical skills, combined with training in all categories of so-called “soft skills”, are essential in preparing students for a successful career in a transdiciplinary area of activities. Recommendations for Practitioners: Establishing a working environment encouraging not only sharing but close cooperation is essential nowadays. Recommendations for Researchers: There are two aspects of training professionals capable of succeeding in a transdisciplinary environment: encouraging mutual respect and developing out-of-box thinking. Impact on Society: The transition of higher education in a way to meet current challenges. Future Research The next steps in this research are to collect feedback regarding the professional careers of students graduating in these two programs and to adjust the curriculum accordingly.

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“…The major of Information Brokerage was launched in 2002 (Christozov et al, 2008). During this period, it was updated several times to address changes in the area.…”

Section: Information Brokerage and Informing Science Concentrationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Challenges in Designing Curriculum for Trans-Disciplinary Education: On Cases of Designing Concentration on Informing Science and Master Program on Data Science

2019

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The Role of Mediators in Informing Process

2023

Advances in Linguistics and Communication Studies

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Chapter four addresses problems caused by informing via mediators and introduces information mediators as another risky factor for misinforming. In the cascade, two-sided asymmetry by adding mediators' subjective assumptions in a multi-steps process from the original data source toward the end-user's problem solving, are elaborated in a way to high light the factors and circumstances associated with misinforming risks. The role of the human mediators – information brokers – is discussed in the context of misinforming hazards. The issue of technology mediated informing is also addressed by emphasizing different categories of nowadays technologies. This chapter also presents and explores different topologies of communication processes according to their potential to mislead receivers. Topologies are contrasted according to their cardinality and feed-back availability.

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Data Literacy

Christozov

Rasheva-Yordanova

2017

International Journal of Digital Literacy and Digital Competence

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The article shares the authors' experiences in training bachelor-level students to explore Big Data applications in solving nowadays problems. The article discusses curriculum issues and pedagogical techniques connected to developing Big Data competencies. The following objectives are targeted: The importance and impact of making rational, data driven decisions in the Big Data era; Complexity of developing and exploring a Big Data Application in solving real life problems; Learning skills to adopt and explore emerging technologies; and Knowledge and skills to interpret and communicate results of data analysis via combining domain knowledge with system expertise. The curriculum covers: The two general uses of Big Data Analytics Applications, which are well distinguished from the point of view of end-user's objectives (presenting and visualizing data via aggregation and summarization [data warehousing: data cubes, dash boards, etc.] and learning from Data [data mining techniques]); Organization of Data Sources: distinction of Master Data from Operational Data, in particular; Extract-Transform-Load (ETL) process; and Informing vs. Misinforming, including the issue of over-trust vs. under-trust of obtained analytical results.

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Training Information Brokers: A Curriculum Model

Cited by 3 publications

References 1 publication

Challenges in Designing Curriculum for Trans-Disciplinary Education: On Cases of Designing Concentration on Informing Science and Master Program on Data Science

Challenges in Designing Curriculum for Trans-Disciplinary Education: On Cases of Designing Concentration on Informing Science and Master Program on Data Science

The Role of Mediators in Informing Process

Data Literacy

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