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A FRAMEWORK FOR PHENOMENOGRAPIC ANALYSIS AND CLASSIFICATION OF TROUBLESOME KNOWLEDGE IN THE ENGINEERING DOMAIN
KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Production Systems.ORCID iD: 0000-0002-0723-1712
2016 (English)In: EDULEARN16: 8TH INTERNATIONAL CONFERENCE ON EDUCATION AND NEW LEARNING TECHNOLOGIES / [ed] Chova, LG Martinez, AL Torres, IC, IATED-INT ASSOC TECHNOLOGY EDUCATION A& DEVELOPMENT , 2016, 5882-5888 p.Conference paper, Published paper (Refereed)
Abstract [en]

The design of effective teaching and learning activities must create an experience able to elicit the intended learning outcomes of the educational unit. For this purpose, it is then fundamental to account for the different ways students can experience the specific content taught. This paper introduces a structured approach to perform phenomenographic studies aimed at disclosing the most common student perceptions of a given topic and highlight the patterns that can bring students with poor understanding of the target concept to a more sophisticated perception. The method has been formulated based on specific cases in the production engineering domain. In detail a phenomenographic study the first step is to describe, as a knowledgeable person would do, both the subject of the study and its domain. This description is then considered the target perception of the focal topic. In the second phase the students that have already been assessed for the educational unit in exam must be interviewed with open question about both subject and domain. Their answer must be plotted according to sound parameters along two dimension (again subject and domain related) of increasingly sophisticated level of understanding. The result of such interview must be then classified in clusters of understanding that will give the different common perception of the students about the given topic. Finally, the relation among the cluster must be studied with the aim of disclosing suitable teaching and learning activities to help students migrate to a perception cluster close to the above-mentioned target perception.

Place, publisher, year, edition, pages
IATED-INT ASSOC TECHNOLOGY EDUCATION A& DEVELOPMENT , 2016. 5882-5888 p.
Series
EDULEARN Proceedings, ISSN 2340-1117
Keyword [en]
Phenomenology, Methodology, Engineering education
National Category
Educational Sciences
Identifiers
URN: urn:nbn:se:kth:diva-210978ISI: 000402955905148ISBN: 978-84-608-8860-4 (print)OAI: oai:DiVA.org:kth-210978DiVA: diva2:1121545
Conference
8th International Conference on Education and New Learning Technologies (EDULEARN), JUL 04-06, 2016, Barcelona, SPAIN
Note

QC 20170711

Available from: 2017-07-11 Created: 2017-07-11 Last updated: 2017-07-11Bibliographically approved

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Maffei, Antonio

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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
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