Literaturnachweis - Detailanzeige
| Autor/inn/en | Tran, Khoi-Nguyen; Lau, Jey Han; Contractor, Danish; Gupta, Utkarsh; Sengupta, Bikram; Butler, Christopher J.; Mohania, Mukesh |
|---|---|
| Titel | Document Chunking and Learning Objective Generation for Instruction Design [Konferenzbericht] Paper presented at the International Conference on Educational Data Mining (EDM) (11th, Raleigh, NC, Jul 16-20, 2018). |
| Quelle | (2018), (10 Seiten)
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| Sprache | englisch |
| Dokumenttyp | gedruckt; online; Monographie |
| Schlagwörter | Behavioral Objectives; Instructional Design; Reference Materials; Prediction; Verbs; Computational Linguistics; Teaching Methods; Semantics; Banking; Pharmacology |
| Abstract | Instructional Systems Design is the practice of creating of instructional experiences that make the acquisition of knowledge and skill more efficient, effective, and appealing [18]. Specifically in designing courses, an hour of training material can require between 30 to 500 hours of effort in sourcing and organizing reference data for use in just the preparation of course material. In this paper, we present the first system of its kind that helps reduce the effort associated with sourcing reference material and course creation. We present algorithms for document chunking and automatic generation of learning objectives from content, creating descriptive content metadata to improve content-discoverability. Unlike existing methods, the learning objectives generated by our system incorporate pedagogically motivated Bloom's verbs. We demonstrate the usefulness of our methods using real world data from the banking industry and through a live deployment at a large pharmaceutical company. [For the full proceedings, see ED593090.] (As Provided). |
| Anmerkungen | International Educational Data Mining Society. e-mail: admin@educationaldatamining.org; Web site: http://www.educationaldatamining.org |
| Erfasst von | ERIC (Education Resources Information Center), Washington, DC |
| Update | 2020/1/01 |
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