On 22 February 2011, the second day of the first semester, a devastating magnitude 6.2 earthquake struck the city of Christchurch forcing the campus of the University of Canterbury to close for several weeks. Here, we report on the sudden curriculum and assessment overhaul that needed to be implemented using two large, first-year introductory courses as case studies. We discuss the reasoning and justifications behind these changes, as well as the logistics of this process. We draw conclusions based on student feedback and assessments and formulate lessons learnt.
Following the devastation of the Canterbury earthquake sequence a unique opportunity exists to rebuild and restructure the city of Christchurch, ensuring that its infrastructure is constructed better than before and is innovative. By installing an integrated grid of modern sensor technologies into concrete structures during the rebuild of the Christchurch CBD, the aim is to develop a network of self-monitored ‘digital buildings’. A diverse range of data will be recorded, potentially including parameters such as concrete stresses, strains, thermal deformations, acoustics and the monitoring of corrosion of reinforcement bars. This procedure will allow an on-going complete assessment of the structure’s performance and service life, both before and after seismic activity. The data generated from the embedded and surface mounted sensors will be analysed to allow an innovative and real-time health monitoring solution where structural integrity is continuously known. This indication of building performance will allow the structure to alert owners, engineers and asset managers of developing problems prior to failure thresholds being reached. A range of potential sensor technologies for monitoring the performance of existing and newly constructed concrete buildings is discussed. A description of monitoring work conducted on existing buildings during the July 2013 Cook Strait earthquake sequence is included, along with details of current work that investigates the performance of sensing technologies for detecting crack formation in concrete specimens. The potential market for managing the real-time health of installed infrastructure is huge. Civil structures all over the world require regular visual inspections in order to determine their structural integrity. The information recorded during the Christchurch rebuild will generate crucial data sets that will be beneficial in understanding the behaviour of concrete over the complete life cycle of the structure, from construction through to operation and building repairs until the time of failure. VoR - Version of Record
Farming and urban regions are impacted by earthquake disasters in different ways, and feature a range of often different recovery requirements. In New Zealand, and elsewhere, most earthquake impact and recovery research is urban focused. This creates a research deficit that can lead to the application of well-researched urban recovery strategies in rural areas to suboptimal effect. To begin to reduce this deficit, in-depth case studies of the earthquake impacts and recovery of three New Zealand farms severely impacted by the 14th November 2016, M7.8 Hurunui-Kaikōura earthquake were conducted. The initial earthquake, its aftershocks and coseismic hazards (e.g., landslides, liquefaction, surface rupture) affected much of North Canterbury, Marlborough and the Wellington area. The three case study farms were chosen to broadly represent the main types of farming and topography in the Hurunui District in North Canterbury. The farms were directly and indirectly impacted by earthquakes and related hazards. On-farm infrastructure (e.g., woolsheds, homesteads) and essential services (e.g., water, power), frequently sourced from distributed networks, were severely impacted. The earthquake occurred after two years of regional drought had already stressed farm systems and farmers to restructuring or breaking point. Cascading interlinked hazards stemming from the earthquakes and coseismic hazards continued to disrupt earthquake recovery over a year after the initial earthquake. Semi-structured interviews with the farmers were conducted nine and fourteen months after the initial earthquake to capture the timeline of on-going impacts and recovery. Analysis of both geological hazard data and interview data resulted in the identification of key factors influencing farm level earthquake impact and recovery. These include pre-existing conditions (e.g., drought); farm-specific variations in recovery timelines; and resilience strategies for farm recovery resources. The earthquake recovery process presented all three farms with opportunities to change their business plans and adapt to mitigate on-going and future risk.
When disasters and crises, both man-made and natural, occur, resilient higher education institutions adapt in order to continue teaching and research. This may necessitate the closure of the whole institution, a building and/or other essential infrastructure. In disasters of large scale the impact can be felt for many years. There is an increasing recognition of the need for disaster planning to restructure educational institutions so that they become more resilient to challenges including natural disasters (Seville, Hawker, & Lyttle, 2012).The University of Canterbury (UC) was affected by seismic events that resulted in the closure of the University in September 2010 for 10 days and two weeks at the start of the 2011 academic year This case study research describes ways in which e-learning was deployed and developed by the University to continue and even to improve learning and teaching in the aftermath of a series of earthquakes in 2010 and 2011. A qualitative intrinsic embedded/nested single case study design was chosen for the study. The population was the management, support staff and educators at the University of Canterbury. Participants were recruited with purposive sampling using a snowball strategy where the early key participants were encouraged to recommend further participants. Four sources of data were identified: (1) documents such as policy, reports and guidelines; (2) emails from leaders of the colleges and academics; (3) communications from senior management team posted on the university website during and after the seismic activity of 2010 and 2011; and (4) semi-structured interviews of academics, support staff and members of senior management team. A series of inductive descriptive content analyses identified a number of themes in the data. The Technology Acceptance Model 2 (Venkatesh & Davis, 2000) and the Indicator of Resilience Model (Resilient Organisations, 2012) were used for additional analyses of each of the three cases. Within the University case, the cases of two contrasting Colleges were embedded to produce a total of three case studies describing e-learning from 2000 - 2014. One contrast was the extent of e-learning deployment at the colleges: The College of Education was a leader in the field, while the College of Business and Law had relatively little e-learning at the time of the first earthquake in September 2010. The following six themes emerged from the analyses: Communication about crises, IT infrastructure, Availability of e-learning technologies, Support in the use of e-learning technologies, Timing of crises in academic year and Strategic planning for e-learning. One of the findings confirmed earlier research that communication to members of an organisation and the general public about crises and the recovery from crises is important. The use of communication channels, which students were familiar with and already using, aided the dissemination of the information that UC would be using e-learning as one of the options to complete the academic year. It was also found that e-learning tools were invaluable during the crises and facilitated teaching and learning whilst freeing limited campus space for essential activities and that IT infrastructure was essential to e-learning. The range of e-learning tools and their deployment evolved over the years influenced by repeated crises and facilitated by the availability of centrally located support from the e-Learning support team for a limited set of tools, as well as more localised support and collaboration with colleagues. Furthermore, the reasons and/or rate of e-learning adoption in an educational institution during crises varied with the time of the academic year and the needs of the institution at the time. The duration of the crises also affected the adoption of e-learning. Finally, UC’s lack of an explicit e-learning strategy influenced the two colleges to develop college-specific e-learning plans and those College plans complemented the incorporation of e-learning for the first time in the University’s teaching and learning strategy in 2013. Twelve out of the 13 indicators of the Indicators of Resilience Model were found in the data collected for the study and could be explained using the model; it revealed that UC has become more resilient with e-learning in the aftermath of the seismic activities in 2010 and 2011. The interpretation of the results using TAM2 demonstrated that the adoption of technologies during crises aided in overcoming barriers to learning at the time of the crisis. The recommendations from this study are that in times of crises, educational institutions take advantage of Cloud computing to communicate with members of the institution and stakeholders. Also, that the architecture of a university’s IT infrastructure be made more resilient by increasing redundancy, backup and security, centralisation and Cloud computing. In addition, when under stress it is recommended that new tools are only introduced when they are essential.
