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Learning Environments Research Abstract Introduction
- Learning Environments Research Learning
environments research, just over three decades old, is firmly established (Tobin
& Fraser, 1998) among a variety of education research and evaluation methods
dominated by academic achievement assessment of students (Fraser, 1998b). While
quantitative measures of classroom effectiveness are often based on "narrow
testable, standardized, superficial, and easily forgotten outcomes," other
areas of schooling are less emphasized (Kyle, 1997, p. 851) and a complete image
of the process of education is not formed within the research. In the early
1960s, Bloom pointed to measurements of educational environments as a decisive
component for prediction and successful learning manipulation (Anderson &
Walberg, 1974). Since then, numerous studies have demonstrated that students'
perceptions of their educational environments can be measured with survey
instruments and the results serve as valid predictors of learning (Anderson
& Walberg, 1974; Fraser, 1997, 1998a, 1998b), turning evaluation away from
individual student achievement and toward the effectiveness of the environment
of the learning organization (Walberg, 1974). Moreover, variables within
learning environments themselves can be manipulated to achieve different
learning outcomes (Anderson & Walberg, 1974). In addition to approaching learning environment research to enhance teaching and learning in the individual classroom, there are increasingly strong indicators of the need to accommodate tertiary education students in a globalised economy in order to create, distribute, and exploit knowledge for international competitive advantages (Commonwealth, 2000; Hinde, 2000; OECD, 2000; Salmi, 2000; Wagner, 1998). Given that many universities are marketing globally (Hinde, 2000; Salmi, 2000), assurances of quality in education move to the forefront and must be addressed (Olsen, 2000). Learning environment research can provide some of these assurances in the form of addressing what factors shape effective learning environments. Learning
Environments Research Background Learning
environments research can be traced to Lewin's classic human behaviour
definition (Fraser, 1998b) represented by B=f(P,E), whereby B represents
behaviour, f is function, P is person, and E is person's environment (Lewin,
1936). Lewin noted, "every scientific psychology must take into account
whole situations, i.e., the state of both person and environment" (1936, p.
12). Thus, determinants of B are describable by composite measures of P and E
(Stern, 1974). Lewin's purpose for this definition was to conceptualise human
behaviour with new strategies in psychological research where functional
relationships and states of interaction are emphasized over those of correlation
of disjointed responses derived from isolated stimuli—the prevailing
psychological trend of the time (Stern, 1974). Through the study of educational environments, students and teachers define their environment based upon their perceptions. Students, with their distinctive frame of reference generated from spending numerous hours as learners, have a large interest in what is going on around them in their educational environments "and their reactions to and perceptions of school experiences are significant" (Fraser, 1998b, p. 527) given that environments, like people, take on distinctive personalities (Insel & Moos, 1974; Kiritz & Moos, 1974). Likewise, there is an association between students' "psychosocial characteristics of their classrooms" (Fraser, 1998a, p. 17) and their learning achievements and viewpoints. Teachers, on the other hand, can utilize learning environments research to discover differences between their perceptions and those of their students and then attempt to make improvements in the actual classroom environment based upon the preferences of students. Distance
Education Research Currently,
research on distance education is narrow. According to Merisotis and Olsen
(2000), while a plethora of literature on the distance education phenomenon is
available, original research on distance education is limited. Distance
education evaluation is concentrated primarily 1) student outcomes (achievement,
grades, test scores); 2) attitudes of students and instructors; and 3)
satisfaction of students and instructors (Diaz & Cartnal, 1999; IHEP, 1999;
Harnar, Brown & Mayall, 2000; Olsen, 2000; Lane, n.d.). Postulated in the
context of distance education system evaluation, Harnish and Reeves (2000)
discovered the emergence of distance education evaluation in terms of: 1)
Training (programming skills, barriers, availability, identification of
needs, costs); 2)
Implementation (administration, costs, fees course credits, institutional
ownership, priority for use, integration, coordination); 3)
System Usage (information collection, electronic data collection,
accuracy); 4)
Communication (information sharing around internal, local, and regional
issues of concern regarding distance education); and 5)
Support (fiscal, staff, faculty, instructional, administrative resource
allocation). What
is conspicuously missing from evaluations and research related to the broader
body of distance education evaluation are issues related to learning
environments. Learning Environments Research and Distance Education Learning
environment research and associated survey instruments have been developed
related to computer use in classrooms or laboratories, telecomputing, and
computer-mediated communication. Related research includes studies of
perspectives of computer-mediated learning environments specific to teacher
education (Admiraal, Lockhorst, Wubbels, Korthagen & Veen 1998; Goh &
Tobin, 1999), computer-facilitated learning environments in higher education
(Bain, McNaught, Mills & Lueckenhausen, 1998), and collaborative distance
learning environment design (Spector, Wasson & Davidson, 1999). However,
only one study and related instrument, the Distance and Open Learning
Environment Scale (DOLES), developed in 1995, appears to focus exclusively on
distance education among college students (Fraser, 1998a; Jegede, Fraser &
Fisher, 1998). Study Objective
The
learning environments study presented below was designed to assess the learning
environments of two online education technology graduate classes. The study used
the DOLES, a validated survey instrument, to assess 1) student/student
interaction, 2) student/instructor interactions, 3) student expectations, and 4)
course content/structure. Study
Method
Preferred Form Examples
of the preferred form given initially included: Student/student
interaction - “I should be able to develop friendships with other students in
this class.” Student/instructor
interaction – “If I have a study related inquiry, the professor should be
able to find time to respond.” Upon
completion of the web-based form, students submitted it electronically to a
research assistant who compiled the data. The course instructor did not view the
students’ submissions or the data that were compiled. Actual Form Student/student
interaction - “I was able to develop friendships with other students in this
class.” Student/instructor
interaction – “When I had a study related inquiry, the professor found time
to respond.” Upon
completion of these surveys, the results were electronically submitted to a
research assistant who compiled the data. Instructor Form Student/student
interaction - “Students are able to develop friendships with other students in
this class.” Student/instructor
interaction – “If students have a study related inquiry, I am able to find
time to respond.” Results
Summary The
results of the three instruments were compiled by the graduate research
assistant and then submitted to the instructor after final grades had been
posted in the two online classes. Ideally, what should occur is that students’
preferred form of a class is met and the actual form survey results should
represent that students’ preferences were met or exceeded, or at least
improved upon. Likewise, the instructor’s form should reflect awareness of
what students prefer and actually meet their preferences or nearly meet their
preferences. What readers will note however, is that the instructor often did
not meet student preferences. The results are presented in line charts comparing
means of each item in the preferred, actual, and instructor forms of the scale. Student/Student
Interaction [Link to line graph] Students
in these two classes preferred to be able to make friends with one another, but
what actually happened is that they did not. However, it appears they did get to
know one another as preferred, although apparently they did not consider
themselves friends. Students’ ability to organize themselves into work groups
appears to be in sync early in the classes, as well as later, in keeping with
the instructor’s perception of the classes. Students preferred to be able to
contact one another by fax, yet did not. The instructor did not expect students
to contact one another by this method, considering these were online classes.
Students appear to not have been concerned with developing likes and dislikes of
one another, yet actually they later disagreed that they were able to develop
these distinctions. Student/Professor
Interaction For
the most part, students’ preferences for interaction with the professor and
the professor’s perception of his interaction with students was nearly the
same throughout. However, while the professor thought he was meeting students’
preferences, he did so only in part—the distinction between students
“strongly agreeing” as preferred, yet simply “agreeing” in actuality.
Course
Content/Structure In
this case, the primary class environment characteristic of note is the
difference between the instructor considering the students working at their own
pace and the actuality of the students ‘strongly disagreeing’ that they were
able to work at their own pace. As for students being expected to cover the same
material as one another (not necessarily a positive point) and students being
able to follow areas of their own interest, the instructor again slightly
assumed he was meeting the preferences of the students when in reality he was
not. Student
Expectations This
is likely the most telling graph in the disparity of what a professor believes
he is doing and what students perceive him as doing. Students appear to have
understood more about what was expected of them than the instructor thought they
understood—not necessarily a negative disparity. However, where the professor
thought he was carefully planning student activities, the students perceived
otherwise. Likewise, where the instructor fully agreed he was providing
materials meeting student’s needs, the students maintained a more neutral
point of view. The
data and graphs above indicate several areas in the socio-psycho realm of a
classroom were this professor was meeting students’ preferences toward their
online classroom environment. It also indicates a variety of disparities where
the professor can make improvements upon his work, not in catering to student
wishes, but being aware of what is really going on in an online class and
focusing in bridging gaps. If
higher education in an online environment is to accommodate tertiary education
in a worldwide market, addressing factors shaping effective learning
environments is of importance. This cursory study of two classes provides only a
snapshot of one instructor’s ability to meet these needs, however, a larger
study of an online degree or series of online classes can uncover aspects of
learning not found in assessment of student
outcomes, student and instructor attitudes or low-level evaluations of student
satisfaction. Moreover, improvements can be made in the study of online learning environments with improvement and validation of better-defined instruments. The DOLES, used in this study, was developed in the mid-1990s. Numerous changes in technology and the way higher education faculty use technology for the delivery of distance education has occurred. Improved distance education instruments that can be widely distributed and given in the online environment will improve our evaluation of teaching and learning in the future. References
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last updated: 03/17/01