Impact of Ph.D. training: a comprehensive analysis based on a Japanese national doctoral survey
(2017) In Scientometrics 113(1). p.387-415- Abstract
- Ph.D. training in academic labs offers the foundation for the production of knowledge workers, indispensable for the modern knowledge-based society. Nonetheless, our understanding on Ph.D. training has been insufficient due to limited access to the inside of academic labs. Furthermore, early careers of Ph.D. graduates are often difficult to follow, which makes the evaluation of training effects challenging. To address these limitations, this study aims to illustrate the settings of Ph.D. training in academic labs and examine their impact on several training outcomes, drawing on a national survey of a cohort of 5000 Ph.D. graduates from Japanese universities. The result suggests that a supervising team structure as well as the frequency of... (More)
- Ph.D. training in academic labs offers the foundation for the production of knowledge workers, indispensable for the modern knowledge-based society. Nonetheless, our understanding on Ph.D. training has been insufficient due to limited access to the inside of academic labs. Furthermore, early careers of Ph.D. graduates are often difficult to follow, which makes the evaluation of training effects challenging. To address these limitations, this study aims to illustrate the settings of Ph.D. training in academic labs and examine their impact on several training outcomes, drawing on a national survey of a cohort of 5000 Ph.D. graduates from Japanese universities. The result suggests that a supervising team structure as well as the frequency of supervision, contingent to a few contextual factors, determine the Ph.D. graduates’ career decisions, performance, and degrees of satisfaction with the training programs. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/2132bdcc-cbdc-4df2-b604-49a1d1385c51
- author
- Shibayama, Sotaro LU and Kobayashi, Yoshie
- organization
- publishing date
- 2017-10
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Ph.D. training, Academic training, Postgraduate education, Academic career, Higher education
- in
- Scientometrics
- volume
- 113
- issue
- 1
- pages
- 387 - 415
- publisher
- Akademiai Kiado
- external identifiers
-
- scopus:85027384741
- pmid:29056786
- wos:000412527000019
- ISSN
- 1588-2861
- DOI
- 10.1007/s11192-017-2479-7
- language
- English
- LU publication?
- yes
- id
- 2132bdcc-cbdc-4df2-b604-49a1d1385c51
- alternative location
- http://rdcu.be/uWVs
- date added to LUP
- 2017-08-12 15:16:44
- date last changed
- 2022-04-25 01:49:32
@article{2132bdcc-cbdc-4df2-b604-49a1d1385c51,
abstract = {{Ph.D. training in academic labs offers the foundation for the production of knowledge workers, indispensable for the modern knowledge-based society. Nonetheless, our understanding on Ph.D. training has been insufficient due to limited access to the inside of academic labs. Furthermore, early careers of Ph.D. graduates are often difficult to follow, which makes the evaluation of training effects challenging. To address these limitations, this study aims to illustrate the settings of Ph.D. training in academic labs and examine their impact on several training outcomes, drawing on a national survey of a cohort of 5000 Ph.D. graduates from Japanese universities. The result suggests that a supervising team structure as well as the frequency of supervision, contingent to a few contextual factors, determine the Ph.D. graduates’ career decisions, performance, and degrees of satisfaction with the training programs.}},
author = {{Shibayama, Sotaro and Kobayashi, Yoshie}},
issn = {{1588-2861}},
keywords = {{Ph.D. training; Academic training; Postgraduate education; Academic career; Higher education}},
language = {{eng}},
number = {{1}},
pages = {{387--415}},
publisher = {{Akademiai Kiado}},
series = {{Scientometrics}},
title = {{Impact of Ph.D. training: a comprehensive analysis based on a Japanese national doctoral survey}},
url = {{http://dx.doi.org/10.1007/s11192-017-2479-7}},
doi = {{10.1007/s11192-017-2479-7}},
volume = {{113}},
year = {{2017}},
}