Printer Friendly

A distance education learning environment survey.

Abstract

This paper describes the research of psychosocial learning environments in post-secondary distance education using a recently validated survey instrument--the Distance Education Learning Environment Survey (DELES). The instrument validation data and study results are presented.

Introduction

Distance education has become a firmly embedded component of the higher education landscape in the last decade. Networked digital communication has facilitated an explosive growth in this relatively new method of reaching learning populations to the point that the higher education trend to produce distance education courses and programs has been referred to as a "land rush" (Molenda and Harris 2001, 6) to get online. However, at the same time many distance education classes and seminars are modelled after a traditional face-to-face, instructor-centred, deductive perspective of teaching (Diaz 2000; Palloff and Pratt, 1999). In light of the fissure between how education is classically delivered and what we know about how people learn (Palloff and Pratt, 1999) the question at hand becomes; "what leads to successful teaching and learning in distance education?" When teaching and learning leave the classroom and enter an electronic environment a new education paradigm must be adopted to facilitate successful distance education students. These successful students lend credence to that which makes higher education unique. "In this new e-learning environment there is no viable option for the university to do as it has always done. To do so will be to become more and more marginalised" (Spender 2001, 25). Given that, if we consider the human factor as a critical component of distance education, then the role of people in the distance education environment is essential to the development of a high functioning distance education class (Palloff and Pratt 1999).

Computer-mediated distance education classes have a distinctive social structure unlike those found in a face-to-face class. For example, there are idiosyncratic differences in how students interact and collaborate online and how one maintains "presence" in online classroom environments (Hughes et al. 2002; Picciano 2002). This social structure has a strong impact on students' learning and the method by which the class should be presented in the digital world (Swan 2001). Distance and social class play a limited role in student interaction, which is advantageous to asynchronous distance education. Social interaction is limited only by time and access. In the asynchronous distance education setting, participants can become a part of a social milieu with anyone who has access to a computer. "Connections are made through sharing of ideas and thoughts" (Pallof and Pratt 1999, 15). It is through presence, personal relationships, and interactions between participants that learning is developed.

The environment of the asynchronous distance education classroom is quite different than that of a face-to-face class and must be cultivated in order for it to be effective. In more familiar face-to-face classrooms the environment's press--the directional influence that the environment has on one's behaviour--can be established through visual cues, tone of voice, volume of voice, one's attractiveness, or ethnic/racial diversity. Factors such as these do not typically exist in asynchronous distance education. An area of study distinctively missing from the body of research related to distance education involves learning environments and what types of environments are successful. This investigation was designed to consider the character of the post-secondary distance education environment in terms of what researchers and practitioners find influential. This is an introduction to a larger body of work.

Background and Theory

Learning Environments Research

The term learning environment carries with it a variety of meanings. It has been used to indicate a type of learning task (Tynjala 1999) and to denote virtual spaces found in computer applications and on the Internet (Gibbs 1999). In this study, learning environments refers exclusively to psychosocial classroom environments. Learning environments research, just over three decades old, is firmly established (Tobin and 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" (Kyle 1997, 851), other areas of schooling are less emphasized 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 and 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 and 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 and Walberg 1974).

Evolution of Learning Environments Research

Learning environments research can be traced to Lewin's classic human behaviour definition represented as B=f(P,E), where B represents behaviour, f is function, P is person, and E is person's environment (Lewin 1936). 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--one of the prevailing psychological trend of the time (Stern 1974).

Moos later described what have long stood as environmental system domains in social ecology that can universally depict different environments in terms of three dimensions: 1) the Relationship Dimension, 2) the Personal Growth Dimension, and 3) the System Maintenance and Change Dimension (Moos 1974). Moos demonstrated the enduring quality of these dimensions in terms of family, work, school, health, military, prison, and community social contexts (Moos 2002). Through this framework, investigators can characterize and integrate the impacts that social environments have on individuals and groups, including those environments found in distance education. Through the study of educational environments, students and teachers define their environment based upon their perceptions. Students, with their distinctive frames 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, 527) given that environments, like people, take on distinctive personalities (Insel and Moos 1974; Kiritz and Moos 1974). Furthermore, there is an association between students' perceptions of psychosocial characteristics of their classrooms (Fraser 1998a) and their learning achievements. Instructors can utilize learning environments research to discover differences between their perceptions and those of their students and then attempt to make improvements in the environment.

Objectives and Significance

The objectives of this research were two-fold. First, it was to develop and validate an instrument to measure the psychosocial learning environment in asynchronous, postsecondary distance education classes. Second, it was to describe the learning environment perceptions of students and instructors in courses delivered by distance.

Only two learning environment instruments are currently available for post-secondary distance education--the Distance and Open Learning Environment Survey (DOLES) and the Web-Based Learning Environment Instrument (WEBLEI). The DOLES (Jegede, Fraser, and Fisher 1998), developed in the mid-1990s, focuses on World Wide Web-delivered science education courses with a distinctive Australasian focus. The WEBLEI, a more contemporary instrument, focuses on emancipatory activities, co-participatory activities, distinctiveness in education environments, information structure, and design activities (Chang and Fisher 2001).

The availability of a new instrument, the Distance Education Learning Environments Survey (DELES), enables practitioners and researchers to examine educational learning environments in tertiary education settings. The DELES takes six psychosocial scales into consideration: 1) instructor support, 2) student interaction and collaboration, 3) personal relevance, 4) authentic learning, 5) active learning, and 6) student autonomy. A seventh attitudinal scale of satisfaction was included so associations between enjoyment and the six psychosocial scales could be investigated.

Research Design and Procedure

The design, development, and validation of the DELES were guided by consistency with learning environments research literature, consistency with previously developed learning environments instruments, and characteristics of relevance to distance education learning environments.

The survey was developed and validated in three stages. Stage one included identification of salient scales within Moo's (1974) three social organization dimensions of Relationship, Personal Development, and System Maintenance and Change. Stage two involved writing individual items within the scales. The items were content validated by an international panel of experts/practitioners. Stage three involved a pilot and a field test of items, followed by item analyses for reliability and construct validity, which resulted in a valid learning environments instrument.

This paper briefly presents the results of the stage three field test, followed by a presentation of the results of a separate administration of the validated DELES with one distance education class. Details regarding the stage one development of the scales, the stage two development of the items, and the stage three field test and subsequent reliability and construct validity analyses is presented in Walker (2003).

Findings

Instrument Validation-Stage Three

The DELES field test resulted in 680 responses primarily from the United States, Australia, New Zealand, and Canada. The 56 field tested items were reduced to 42 items in seven scales after principle component factor analysis and internal consistency reliability (Cronbach's alpha) analysis were conducted. The final seven scales were: (1) instructor support, (2) student interaction and collaboration, (3) personal relevance, (4) authentic learning, (5) active learning, (6) student autonomy, and the affective-trait scale of (7) enjoyment of distance education. The items with factor loadings of less than or equal to 0.55 within their own scales were kept. Items with factor loadings below 0.55 were discarded. For the seven scales, the alpha reliability coefficient ranged from 0.75 to 0.95.

When analysing associations between the affective-trait scale (enjoyment of distance education) and the six psychosocial scales on the field test of the DELES, the correlations ranged from r = 0.12 to 0.31 with the scale of personal relevance having the strongest correlation. Regression coefficients ranged from Beta = 0.00 to 0.23, again with the scale of personal relevance having the strongest association, followed by authenticity in learning with Beta = 0.16.

Application in an Online Class

After validation, the instrument was re-administered in an online, graduate-level course in the United States entitled Seminar in Math, Science, and Education Technology in two forms. A student form was given to each student (n=15). An instructor form, a variation of the student form, worded to capture the instructor's (n=1) perceptions of the class was given to the instructor. The student results were analysed by calculating the class mean for each item in the seven scales from the five-point response scale, whereby l-never and 5=always. These data (p<0.05) were contrasted against the instructor's results in order to compare differences between the students' perceptions and that of the instructor.

On the psychosocial scale of instructor support the student mean fell at just above often (mean = 4.34 on the 5 pt. scale). Meanwhile, the instructor perceived himself as creating an environment that ranked at often occurring (mean = 4.00), a difference of 0.34. On the scale of student interaction and collaboration, the student mean was nearly ranked at often (3.83) and the instructor also perceived that the class environment was 3.83. On the scale of personal relevance the student mean indicated perceptions of often occurring (3.99), more so than that of the instructor who perceived his class as experiencing relevancy slightly above sometimes occurring (3.29), a difference of 0.70. On the scale of authentic learning the students perceived the class as having these characteristics nearly often (3.85), while the instructor had a slightly reduced view of class activities that were authentic (3.20), with a difference of 0.65. Regarding active learning, the students perceived the environment as being somewhat more than often (4.16) having characteristics of active learning. The instructor's views were similar at 4.00, a difference of 0.16. Notably, on the scale of student autonomy, the students viewed the class environment as more than often (4.29) allowing for autonomy. However, the instructor perceived the extent to which he offered student autonomy as only between sometimes and often (3.60), a difference from the students' views by 0.69. On the affective-trait scale of student enjoyment of distance education the students and the instructor had equal perceptions (3.88).

The results of this study indicate an overall student-perceived learning environment that is positive. If the instructor's views of the class were to rank above the students' perceptions on any particular scale, one could say that the instructor is viewing the class through "rose coloured glasses."

Conclusion

This article briefly describes the development of a new instrument designed to assess the perceptions of participants in postsecondary distance education learning environments along six psychosocial scales and one scale of attitude. The 42-item instrument is available on the World Wide Web for viewing at the South Central RTEC Instrument Library and Data Repository at http://insight.southcentralrtec.org. This paper presents how, using central tendency measurements, a distance education class is perceived by an instructor and his students. The availability of this instrument is a contribution to the bricolage of Web-based education theories, methods, and prior histories of learning environment studies, the implications of which provide for a tool that can be adopted by any distance education instructor or program administrator for use in evaluating the psychosocial learning environments.

The next steps for the application of the DELES is in program evaluation, subject-specific distance education class evaluation, and in a rigorous study of cross-national psychosocial learning environments.

Reference List

Anderson, G. J., and H. J. Walberg. 1974. Learning environments. In Evaluating educational performance: A sourcebook of methods, instruments and examples, ed. H. J. Walberg, 81-98. Berkeley: McCutchan Publishing.

Chang, V., and D. L. Fisher. 2001. A new learning instrument to evaluate online learning in higher education. In New horizons in university teaching and learning, ed. M. Kulski and A. Herrmann, 23-34. Perth, Western Australia: Curtin University of Technology.

Diaz, D. P. 2000. Carving a new path for distance education research. The Technology Source. http://ts.mivu.org/default.asp?show=article&id-648 (accessed June 11, 2004).

Fraser, B. J. 1997. Classroom environments. In Psychology and educational practice, ed. H. J. Walberg and G. D. Haertel, 323-341. Berkeley: McCutchan Publishing.

Fraser, B. J. 1998a. Classroom environment instruments: Development, validity and application. Learning Environments Research 1: 7-33.

Fraser, B. J. 1998b. Science learning environments: Assessment, effects and determinants. In International handbook of science education, ed. B. J. Fraser and K. G. Tobin, 527-564. London: Kluwer Academic Publishers.

Gibbs, G. R. 1999. Learning how to learn using a virtual learning environment for philosophy. Journal of Computer Assisted Learning 15 (3): 221-231.

Hughes, Sandra C., Leah Wickersham, David L. Ryan-Jones, and Sara A. Smith. 2002. Overcoming social and psychological barriers to effective on-line collaboration. Educational Technology & Society 5(1): 86-92.

Insel, P. M., and R. H. Moos. 1974. The social environment. In Health and the social environment, ed. P. M. Insel and R. H. Moos, 3-12. Lexington, MA: D.C. Heath and Company.

Jegede, O., B. J. Fraser, and D. L. Fisher. 1998. The distance and open learning environment scale: Its development, validation and use. Paper presented at the 69th Annual Meeting of the National Association for Research in Science Teaching, San Diego, CA, March.

Kiritz, S., and R. H. Moos. 1974. Physiological effects of the social environment. In Health and the social environment, ed. P. M. Insel and R. H. Moos, 13-35. Lexington, MA: D.C. Heath and Company.

Kyle, W. C. 1997. Editorial: Assessing students' understanding of science. Journal of Research in Science Teaching 34 (9): 851-852.

Lewin, K. 1936. Principles of Topological Psychology. New York: McGraw-Hill.

Molenda, M., and P. Harris. 2001. Issues and trends in instructional technology. In Educational media and technology yearbook, ed. R. M. Branch and M. A. Fitzgerald, 3-15. Englewood, CO: Libraries Unlimited, Inc.

Moos, R. H. 1974. Systems for the assessment and classification of human environments: An overview. In Issues in social ecology: Human milieus, ed. R. H. Moos and P. M. Insel, 5-29. Palo Alto, CA: National Press Books.

Moos, R. H. 2002. The mystery of human context and coping: An unraveling of clues. American Journal of Community Psychology 30(1): 67-78.

Palloff, R. M., and K. Pratt. 1999. Building learning communities in cyberspace: Effective strategies for the online classroom. San Francisco: Jossey-Bass Publishers.

Picciano, Anthony, G. 2002. Beyond student perceptions: Issues of interaction, presence, and performance in an online course. Journal of Asynchronous Learning Environments 6(1): 21-40.

Spender, D. 2001. Panel discussion: Online education are universities prepared? In Online learning in a borderless market. Canberra: Department of Education, Training, and Youth Affairs.

Stern, G. G. 1974. B=f(P,E). In Issues in social ecology: Human milieus, ed. R. H. Moos and P. M. Insel, 559-568. Palo Alto, CA: National Press Books.

Swan, K. 2001. Virtual interaction: Design factors affecting student satisfaction and perceived learning in asynchronous online courses. Distance Education 22:306-331.

Tobin, K., and B. J. Fraser. 1998. Qualitative and quantitative landscapes of classroom learning environments. In International handbook of science education, ed. B. J. Fraser and K. G.

Tobin, 623-640. London: Kluwer Academic Publishers.

Tynjala, P. 1999. Towards expert knowledge? A comparison between a constructivist and a traditional learning environment in the university. International Journal of Educational Research 31 (5): 357-442.

Walberg, H. J. 1974. Evaluating education performance. In Evaluating educational performance: A sourcebook of methods, instruments, and examples, ed. H. J. Walberg, 1-9. Berkeley: McCutchan Publishing.

Walker, Scott L. 2003. Development and validation of an instrument for assessing distance education learning environments in higher education: The Distance Education Learning Environments Survey (DELES). ScEdD thesis, Curtin University of Technology.

Scott L. Walker, Texas State University-San Marcos

Walker, ScEdD, is an Assistant Professor of Geography with extensive experience in the study of postsecondary psychosocial learning environments in distance education.
COPYRIGHT 2004 Rapid Intellect Group, Inc.
No portion of this article can be reproduced without the express written permission from the copyright holder.
Copyright 2004, Gale Group. All rights reserved. Gale Group is a Thomson Corporation Company.

Article Details
Printer friendly Cite/link Email Feedback
Author:Walker, Scott L.
Publication:Academic Exchange Quarterly
Date:Dec 22, 2004
Words:2979
Previous Article:Teaching basic information literacy skills online.
Next Article:Jumpstarting research with essential questions.
Topics:


Related Articles
Factors Influencing Student Satisfaction with Online Courses.
Graduate Students' Perceptions of Distance Learning.
Distance Learning Survey Results.
Why interact online if it's not assessed?
A comparative analysis of learning experience in a traditional vs. virtual classroom setting.
Gender, age, ethnicity, and interest in taking an online course.
Factors which motivate community college faculty to participate in distance education.
Making interactivity count: best practices in video conferencing.
Faster, cheaper, better: distance education is no longer the next great phase of K-12 education. Acceptance is growing, technologies are improving...
Motivation and learning strategies of students in distance education.

Terms of use | Privacy policy | Copyright © 2021 Farlex, Inc. | Feedback | For webmasters