Applying Entrepreneurial Teaching Methods to Advanced Technical STEM Courses
(2018) 2018 IEEE International Conference on Engineering, Technology and Innovation, ICE/ITMC 2018- Abstract
A vast majority of Science, Technology, Engineering, Mathematics (STEM) courses and pedagogical frameworks concentrate on teaching the fundamental concepts and theoretical underpinnings of the tools related to the subject. While this aspect is important, we recognize that the teaching methods in a majority of the STEM courses today are broken; there is a major discrepancy between the skills and mindsets in technical classes and the ones that are useful to solve actual problems in 'the real world'. Therefore, we suggest a new teaching framework called Data-X where entrepreneurial teaching methods developed in the Berkeley Method of Entrepreneurship are applied to advanced technical topics. Through inductive learning and by practicing... (More)
A vast majority of Science, Technology, Engineering, Mathematics (STEM) courses and pedagogical frameworks concentrate on teaching the fundamental concepts and theoretical underpinnings of the tools related to the subject. While this aspect is important, we recognize that the teaching methods in a majority of the STEM courses today are broken; there is a major discrepancy between the skills and mindsets in technical classes and the ones that are useful to solve actual problems in 'the real world'. Therefore, we suggest a new teaching framework called Data-X where entrepreneurial teaching methods developed in the Berkeley Method of Entrepreneurship are applied to advanced technical topics. Through inductive learning and by practicing story creation, stakeholder generation, adaptation, ideation, innovation processes, and by having a diverse mix of students being coached by a network of expert advisors, this highly applied teaching method empowers students to pursue and find solutions to open-ended projects and problems. The Data-X framework has been implemented and tested for three semesters in a UC Berkeley course called Applied Data Science for Venture Applications. In the class the students pick up, become comfortable, and utilize state-of-the-art tools in Data Science, Machine Learning, and Artificial Intelligence. The results, feedback, and testimonials we have received upon offering the class have been overwhelmingly positive, and we propose that the ideas and concepts behind Data-X can help fix many problems in modern STEM education.
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- author
- Sidhu, Ikhlaq ; Fred-Ojala, Alexander ; Iqbal, Sana and Johnsson, Charlotta LU
- organization
- publishing date
- 2018-08-13
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- data science, entrepreneurial mindsets, inductive learning, innovation processes, machine learning, pedagogical frameworks, STEM education, teaching methods
- categories
- Higher Education
- host publication
- 2018 IEEE International Conference on Engineering, Technology and Innovation, ICE/ITMC 2018 - Proceedings
- article number
- 8436264
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- 2018 IEEE International Conference on Engineering, Technology and Innovation, ICE/ITMC 2018
- conference location
- Stuttgart, Germany
- conference dates
- 2018-06-17 - 2018-06-20
- external identifiers
-
- scopus:85052499370
- ISBN
- 978-1-5386-1469-3
- DOI
- 10.1109/ICE.2018.8436264
- language
- English
- LU publication?
- yes
- id
- d9b827bd-704f-4fe6-9b3a-46b30a3909e8
- date added to LUP
- 2018-10-08 15:25:53
- date last changed
- 2022-04-25 17:48:25
@inproceedings{d9b827bd-704f-4fe6-9b3a-46b30a3909e8,
abstract = {{<p>A vast majority of Science, Technology, Engineering, Mathematics (STEM) courses and pedagogical frameworks concentrate on teaching the fundamental concepts and theoretical underpinnings of the tools related to the subject. While this aspect is important, we recognize that the teaching methods in a majority of the STEM courses today are broken; there is a major discrepancy between the skills and mindsets in technical classes and the ones that are useful to solve actual problems in 'the real world'. Therefore, we suggest a new teaching framework called Data-X where entrepreneurial teaching methods developed in the Berkeley Method of Entrepreneurship are applied to advanced technical topics. Through inductive learning and by practicing story creation, stakeholder generation, adaptation, ideation, innovation processes, and by having a diverse mix of students being coached by a network of expert advisors, this highly applied teaching method empowers students to pursue and find solutions to open-ended projects and problems. The Data-X framework has been implemented and tested for three semesters in a UC Berkeley course called Applied Data Science for Venture Applications. In the class the students pick up, become comfortable, and utilize state-of-the-art tools in Data Science, Machine Learning, and Artificial Intelligence. The results, feedback, and testimonials we have received upon offering the class have been overwhelmingly positive, and we propose that the ideas and concepts behind Data-X can help fix many problems in modern STEM education.</p>}},
author = {{Sidhu, Ikhlaq and Fred-Ojala, Alexander and Iqbal, Sana and Johnsson, Charlotta}},
booktitle = {{2018 IEEE International Conference on Engineering, Technology and Innovation, ICE/ITMC 2018 - Proceedings}},
isbn = {{978-1-5386-1469-3}},
keywords = {{data science; entrepreneurial mindsets; inductive learning; innovation processes; machine learning; pedagogical frameworks; STEM education; teaching methods}},
language = {{eng}},
month = {{08}},
publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
title = {{Applying Entrepreneurial Teaching Methods to Advanced Technical STEM Courses}},
url = {{http://dx.doi.org/10.1109/ICE.2018.8436264}},
doi = {{10.1109/ICE.2018.8436264}},
year = {{2018}},
}