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Lafuente, Deborah; Cohen, Brenda; Fiorini, Guillermo; Garci´a, Agusti´n Alejo; Bringas, Mauro; Morzan, Ezequiel; Onna, Diego – Journal of Chemical Education, 2021
Machine learning, a subdomain of artificial intelligence, is a widespread technology that is molding how chemists interact with data. Therefore, it is a relevant skill to incorporate into the toolbox of any chemistry student. This work presents a workshop that introduces machine learning for chemistry students based on a set of Python notebooks…
Descriptors: Undergraduate Students, Chemistry, Electronic Learning, Artificial Intelligence
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Gerbing, David W. – Journal of Statistics and Data Science Education, 2021
R and Python are commonly used software languages for data analytics. Using these languages as the course software for the introductory course gives students practical skills for applying statistical concepts to data analysis. However, the reliance upon the command line is perceived by the typical nontechnical introductory student as sufficiently…
Descriptors: Statistics Education, Teaching Methods, Introductory Courses, Programming Languages
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Zschocke, Thomas – Program: Electronic Library and Information Systems, 2012
Purpose: This paper aims to address the issue of matching controlled vocabulary on agroforestry from knowledge organization systems (KOS) and incorporating these terms in DITA markup. The paper has been selected for an extended version from MTSR'11. Design/methodology/approach: After a general description of the steps taken to harmonize controlled…
Descriptors: Vocabulary, Classification, Forestry, Agriculture
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Losee, Robert M. – Information Processing & Management, 1997
Proposes a model for digital library and hypermedia organizations that is adaptive, providing different conceptual orderings to support browsing for different individuals' or groups' needs. Highlights include types of links, document ordering and the Gray code (a binary programming code), adaptive classification, and an economic model for document…
Descriptors: Classification, Documentation, Electronic Libraries, Hypermedia
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Bennedsen, Jens; Eriksen, Ole – Computer Science Education, 2006
The main contribution of this paper is a proposal for a universal pedagogical pattern categorization based on teaching values and activities. This categorization would be more sustainable than the arbitrary categorization implied by pedagogical pattern language themes. Pedagogical patterns from two central patterns languages are analyzed and…
Descriptors: Learning Theories, Classification, Program Proposals, Programming Languages
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Henze, Nicola; Dolog, Peter; Nejdl, Wolfgang – Educational Technology & Society, 2004
The challenge of the semantic web is the provision of distributed information with well-defined meaning, understandable for different parties. Particularly, applications should be able to provide individually optimized access to information by taking the individual needs and requirements of the users into account. In this paper we propose a…
Descriptors: Access to Information, Metadata, Internet, Educational Resources
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Rodriguez-Artacho, Miguel; Verdejo Maillo, M. Felisa – Educational Technology & Society, 2004
This paper presents a reference framework to describe educational material. It introduces the PALO Language as a cognitive based approach to Educational Modeling Languages (EML). In accordance with recent trends for reusability and interoperability in Learning Technologies, EML constitutes an evolution of the current content-centered…
Descriptors: Learning Processes, Standards, Teaching Methods, Instructional Materials
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Abel, Marie-Helene; Benayache, Ahcene; Lenne, Dominique; Moulin, Claude; Barry, Catherine; Chaput, Brigitte – Educational Technology & Society, 2004
E-learning leads to evolutions in the way of designing a course. Diffused through the web, the course content cannot be the direct transcription of a face to face course content. A course can be seen as an organization in which different actors are involved. These actors produce documents, information and knowledge that they often share. We…
Descriptors: Course Content, Internet, College Instruction, Models