Characterizing post-disaster reconstruction training methods and learning styles

ABSTRACT

Large disasters damage or destroy infrastructure that is then reconstructed through programmes that train community members in construction techniques that reduce future risks. Despite the number of post-disaster reconstruction programmes implemented, there is a dearth of research on education and training in post-disaster contexts. To address this gap, we applied a mixed methods approach based upon experiential learning theory (ELT) to three shelter programmes administered in Eastern Samar, Philippines following Typhoon Haiyan. First, we characterize post-disaster training programmes based on learning modes and then, compared this to the learning styles of community members. To assess learning modes of training programmes, we analysed qualitative data from interview accounts of community members and aid organizations; and, to delineate community member’s learning style preferences, we analysed quantitative data from survey questionnaires. Findings show that aid organizations administered training largely in lecture format, aligning with the reflective observation mode of ELT, but lacked diversity in formats represented in other poles of ELT. Moreover, analysis revealed that community members tended to grasp new information in accordance with the concrete experimentation mode, then preferred transforming newly acquired knowledge via the reflective observation mode. The lecture-based training predominately administered by aid organizations partially aligned with community learning preferences, but fell short in cultivating other forms of knowledge acquisition known to enhance long-term learning.

KEYWORDS:

• Training
• disasters
• experiential learning theory

Acknowledgements

This research would not have been possible without the assistance and support of our competent research assistants, Marielle Bacason, Lebeth Manguilimotan, and Phoebe Tabo. Additionally, Ursula Grunewald, who assisted with qualitative coding and coding validation within QSR NVivo. The authors would also like to thank the Hay Group who graciously permitted the use of the Kolb LSI questionnaire for the learning style assessment.

Disclosure statement

No potential conflict of interest was reported by the authors.

ORCID

Alexander Zerio http://orcid.org/0000-0002-8175-5389

Aaron Opdyke http://orcid.org/0000-0003-1507-6270

Amy Javernick-Will http://orcid.org/0000-0002-3933-2614

Additional information

Funding

This material is based upon work supported by the National Science Foundation [under grant number 1434791]. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.