Research On The Renewal Design Of Informal Learning Space In Colleges And Universities Based On Multi-source Data Analysis

At present,in the rapid expansion and reconstruction of college buildings and the updating and slight progress of learning models,non-learning has gradually been highlighted.However,through preliminary findings,it is found that most of the alternative learning spaces are not efficient due to the uncomfortable physical environment,various behaviors interfering with each other or the lack of seating facilities.In view of this situation,and considering the design and transformation difficulties brought about by the complexities of additional learning space functions,the multi-source data research method is selected here to extract the physical environment data within the space,the user's positioning information data and subjective evaluation data By establishing the relationship between these data in the time and space dimensions,comparing and superimposing in the language of information graphics,presenting people's subjective choices,the objective behavior and the indoor physical environment are in conflict and connection with each other.Through the mutual support and verification of multi-source data,combined with the architect's subjective experience judgment,it helps to pick up the key problems of space use more accurately,and complete the problem-oriented update design method of the informal learning space And processes.This study first sorted out the forms and characteristics of informal learning and space,combined with field research on colleges and universities in Xi'an and other cities,and found the specific use of current alternative learning spaces.Then,through literature collection and classification of architectural cases,the classification of internal and external informal learning space forms and design strategies is analyzed,and influential factors for data use of space are extracted.According to the research method and case analysis,the research object of this time was selected-the fourth floor building square of the east building of Xi'an University of Architecture and Technology,from June to July,from 9 to 21 in six consecutive days,the location of the personnel was collected in the space Data,physical environment data and questionnaire data.In the analysis process,first of all,a preliminary statistical description of the three types of data is used to obtain different visualization results using time or space as scalars.Second,compare or overlap the visualization of data from different sources to find similarities and differences.As a result,we found that the sequence of the three kinds of data formed based on time and the distribution status in space have their own characteristics,showing different information content.For example,the time series of temperature and humidity changes steadily,the spatial distribution of objective positioning data interferes with each other during the exhibition and the usual two periods.The merger carried out the connection between the user's subjective preferences and objective positioning and the physical environment data,that is,the physical environment factors have different strengths for the user's choice.This shows that the combined verification between different data will find some Relevant information,and can capture the key issues in the space.Finally,combined with the design experience and data analysis results,the problem of space memory is analyzed in a targeted manner,and the transformation methods and measures are proposed.Through the research in this paper,the application prospect of data visualization analysis in the field of architecture research is opened up.The complete process of multisource data collection,visualization and analysis is sorted out,and it is designed for the update based on the behavior research of the data and a small amount of learning space.Provide some reference.