The Perceived Influence of Learning Environment on Design Student Imagination
Abstract.This study was aimed to analyze the perceived
influence of learning environment on design student imagination in different
design phases. Participants (n =
1,004) involved in this study were design school students from ten universities
across Taiwan. Influences in the learning environment were deconstructed into
four factors: physical component, organizational measure, social climate, and
human aggregate. Our results indicated that social
climate was claimed to be the greatest influential factor, followed by organizational measure, human aggregate, and finally physical component. These various
effects were seen in the design process, especially in the phase of problem
definition and design analysis, and with a lesser effect in the phase of
detailed design and communication.
Keywords: design education; design process; imagination stimulation;learning environment.
Introduction
The key to the success of the design lies in the capacity of creative thinking. Imagination is the basis for cultivating creative thinking, and thus the driving force of innovation (Finke, 1996). Creativity-related research has progressed for many years, but the understandings of imagination and the imagination process still remain unclear. So far, few studies have clearly discussed how imagination manifests itself, let alone developed an evaluation tool for assessing imagination stimulation in the design field (Liang, Chang, Chang, & Lin, 2012). In this study, “imagination” refers to the process of transforming the inner imagery of design school students when they face a design task. Such images are usually developed from the individual’s image memory and shaped into something new.The purpose of this study is to analyze the perceived influence of learning environment on design student imagination in different design phases. Generally speaking, the design process can be divided into three major phases: problem definition and design analysis, concept development and prototyping, and detailed design and communication (Shneiderman, 2000; Peffers et al., 2006).
Method
Since measures of the influence that environmental factors
had on imagination stimulation in different design phases were unavailable, new
scales needed to be developed for this study. Based upon the literature review,
items were created to represent the issues identified. All these 27 preliminary
items addressed various environmental influences and were grouped into four
dimensions, namely physical component, social climate, organizational measure,
and human aggregate.In order to make the standpoints of the surveyed clearer,
the items were measured using 4-point Likert scales, ranging from 1 = strongly
disagree to 4 = strongly agree. The scale was pre-tested by over 200 college
students and then verified by preliminary validation analyses.
Participants involved in this study were students from ten
universities across Taiwan. Students had to satisfy two requirements in order
to participate for this study. First, students must have been a design major.
Second, students must have had at least sophomore standing prior to the study.
In the first phase, a total of 1,004 valid samples were collected, including
294 sophomores, 300 juniors, 277 seniors, and 133 in their master programs.
There were 277 male and 727 female. The demographical data of the other two phases
are presented in Table 1. Because the participants were not forced to
contribute in all the three phases, the numbers of participants differed
slightly between each phase.
The questionnaire asked participants to determine the
strength of influence that each identified environmental factor had on their
imagination in the current design phase. The questionnaire was distributed to
the participants in three different periods. The first period, the phase of
problem definition and design analysis, was during the first two weeks of
October 2011. The second period, the phase of concept development and
prototyping took place in the final two weeks of November 2011. The third and
final period, the phase of detailed design and communication, was during the middle
two weeks of January 2012. Each survey was conducted by trained graduate
assistants who were accompanied by the course instructor.
Three items were dropped from the scale due to low factor
loading (< .3): “the congestion of messages in the learning environment,”
“the route and pattern planning of the learning environment,” and “the location
of the learning environment on campus.” Based on the satisfactorily analytical
results, a total of 24 items were chosen to construct the formal questionnaire.
The measured items were organized by item analysis on the mean (2.77-3.54),
standard deviation (> .75), skewness (< ±1), extreme value test results (p < .05, t > ±1.96), correlation coefficients (> .3), and factor
loading values (> .3) of the data acquired during the formal survey. The
environmental influence scale was found to be reliable (refer to Table 1).
Table 1: Analysis of the demographical data and Cronbach’s α
|
Demographical data & α |
Phase 1 (n = 1,004) |
Phase 2 (n = 974) |
Phase 3 (n = 943) |
|
Gender Male/ Female |
277（27.6%）/ 727（72.4%） |
293（30%）/ 681（70%） |
266（28.2%）/ 677（71.8%） |
|
Grade Sophomore/ junior Senior/ master |
294（29.3%）/ 300（29.9%） |
252（25.9%）/ 292（30%） |
282（29.9%）/ 296（31.4%） |
|
|
277（27.6%）/ 133（13.2%） |
300（30.8%）/ 130（13.3%） |
252（26.7%）/ 113（12%） |
|
Cronbach’s α Whole/ item |
.891/ .884-.891 |
.913/ .907-.912 |
.903/ .897-.910 |
Results
Factor analysis results indicated that the 24 items could
be organized into four environmental factors. The first one, physical component, a six-item scale,
measured the degree to which participants considered the facilities and
messages in an environment would stimulate imagination. The second one, organizational measure, a six-item
scale, assessed participant perceptions of the influence from the institutional
structure and organizational measures. The third one, social climate, a seven-item scale, measured the extent of which
participants reported being influenced by the climate of the class. The fourth
one, human aggregate, a five-item
scale, indicated the degree to which participants felt that their imagination
was influenced by the organizational culture, tradition, or style. Reliability
estimates were satisfactory and are reported with factor loadings in Table 2.
Four extracted factors explained a cumulative variance of 52.68%.
An independent samples t-test (95% CI) was conducted to compare gender differences. The statistics showed that there was no significant difference between genders in the three phases. However, the statistics also showed that the item “teacher’s respect for individual differences” in the second phase achieved a significant level (p = .002 < .01). ANOVA was continually conducted to compare the effect of environmental factors on participant imagination stimulation between students of different grades. The study found that there was a significant effect of environment factors on imagination stimulation at the p< .05 level for the four conditions in all three phases.
In the second phase, the most influential items
include “pleasant learning climate,” “discussion with classmates,” “climate of
free expression,” “encouragement for taking risk,” “opportunities for solitary
thinking,” “dynamic audiovisual stimuli,” “rich learning resources,” and
“sharing constructive feedback”. The item “mutual support” was dropped,
partially due to the emphasis on the personal attribute of an individual
imagination during this phase of design. The newly added item “rich learning
resources” reflected the need of external stimuli (such as related cases,
seniors’ examples, competition messages) for the students in the design
school.
According to the analysis, the seven most influential
items in the third phase are “discussion with classmates,” “pleasant learning
climate,” “encouragement for taking risk,” “climate of free expression,”
“opportunities for solitary thinking,” “dynamic audiovisual stimuli,” and “a
personal space for creation.” The item “sharing constructive feedback” was
dropped between phase two and phase three, possibly because the feedback might
not be acknowledged within the busy schedule during the phase three. The
addition of the item “a personal space” implied that the third phase is a time
for detailed design. These results confirm the findings of the previous study
(Liang, Hsu, & Chang, 2013; Liang, Hsu, Huang, & Chen, 2012),
especially in the aspect of environmental factors.
Closing Remarks
Compared to concepts such as personality traits and
individual psychology, external environments are factors which are easier to
grasp and shape. It is also easier to adjust the learning environment with
different instructional strategies than to change an individual’s traits or
psychological states.
It should be noted that the research target of this
study is students in the design field. It is expected that the reactions of
this target population would differ from those of professional designers in the
real world. This study, however, can serve as a stepping stone for inquiring
into the imagination of professional designers. The study of the expected gap
between naive designers and professional ones can lend insights for design
educators to restructure or reinvent their curriculum and learning
environments.
An excellent designer who is capable of simulating invisible possibilities is only able to because he or she has an exceptional imagination. How do we help our students construct imagery through the external learning environment? How do we help them facilitate the development of these memories? How do we help them translate their images into professional design capabilities? What instructional strategies can be adjusted and/or invented from this study? How can these strategies be implemented? All of these are crucial challenges for us, as educators in the design fields, to face.
Ju-Sen Lin, FoGuang
University, Yilan, Taiwan
Chaoyun Liang, National
Taiwan University, Taipei, Taiwan
International Journal
of Learning, Teaching and Educational Research
Vol. 2, No.1 pp. 124-136, February 2014