Student Satisfaction in Distance Learning - Research Proposal Example

SATISFACTION IN DISTANCE LEARNING: RESEARCH PROPOSAL 2007 SATISFACTION IN DISTANCE LEARNING: RESEARCH PROPOSAL Background One major consequence of the remarkable technological surge was the rapid development of computer-mediated distance learning at the higher education level. A survey carried out by the U.S. Department of Education's National Center for Education Statistics (NCES) seven years ago demonstrated that from 1994-95 to 1997-98 the number of distance education degree programs increased by 72 percent, while 20 percent of the institutions surveyed planned to establish distance education programs within the next three years. The survey estimated that more than 1.6 million students had been enrolled in distance education courses over the period of 1997-98 (Phipps, and Merisotis, 2000). The beginning of the third millennium was marked by even more intensive growth. Institutions of higher education continued to further develop distance learning offerings targeting the populations of working adults who otherwise have limited access to higher education (Smart, and Cappel, 2006; Liaw, and Huang, 2002). The online enrollment estimations made in the late 1990s have been exceeded and continues to grow at amazingly high rates. Thus, the number of online students reached 2.6 million in the fall of 2004 (Allen, and Seaman, 2004). Despite the tremendous success of distance technology-mediated learning (this term covers not only fully online courses, but also various blended approaches that integrate online components into traditional classes), experts suggests that it still remains at an early stage of development (Smart, and Cappel, 2006). The conventional concepts and theories of education were reported to retain their suitability in the web-based learning environment. Numerous research studies demonstrated that cognitive factors such as performance, learning, and achievement in distance education classes are comparable to those observed in traditional classes (Russell, 1999). Petracchi (2000) found out that students were pleased with the performance of their instructor, availability of materials, and performance of technological tools used for conducting the class. Some other studies found that undergraduates enrolled in an introductory psychology course performed better in distance education courses, although the level of their satisfaction with them was lower. Students in the web based course consistently scored an average of five percentage points higher on the final exam than did those in the lecture course, but they consistently reported less satisfaction than the students in the lecture course (Hagel, and Shaw, 2003). Student satisfaction is currently believed to be one of the major indicators of student development in conventional higher education. The mission of higher education is not only to impart knowledge but also to enhance the student's total development (Astin, 1993). One of the ways higher education institutions accomplish this mission is by continuously collecting information on student satisfaction, defined by various authors as an "everpresent campus variable" (Betz, Menne, Starr, and Klingensmith, 1971: 99), the key outcome of higher education (Astin, 1993), and the 'quality enhancement tool designed to improve the quality of the student experience' (Harvey, Plimmer, Moon, and Geall, 1997: 3). Traditionally, the institutions of higher education have used the data on student satisfaction to improve understanding of the educational environments. This understanding, it its turn, allowed to create settings more conducive for student development. Student satisfaction is an indicator of higher education institutions' responsiveness to the needs of students. Also it is a measure of institutional effectiveness, success, and vitality. Measuring student satisfaction is also important for maintaining and increasing enrollment, managing attrition and retention problems, and making better-informed decisions in the area of student affairs (Beltyukova, 2002). Additionally, student satisfaction data have high utility as a baseline in different types of student outcomes assessment, undertaken by institutions of higher learning in response to external pressures for accountability (Upcraft and Schuh, 1996). However, research in the field of student satisfaction in computer-based learning environment is characterized by dominance of 'the no significant difference' approach, which is the result of the prevailing tendency to compare effectiveness of the two study modes, namely the computer-based and conventional. This means that the studies tend to follow the same set of rules, patterns and criteria applied to evaluation of student satisfaction in conventional educational contexts. Furthermore, in the choice between the two measures traditionally used to assess effectiveness of various educational models, student performance is commonly given an edge over student satisfaction. Rationale Although recent research suggest that online education can be as effective as traditional classroom models, few studies have focused on the issue of learner satisfaction with computer-based instruction mode, particularly in the transition to online learning from traditional approaches. In particular, further research is needed to understand how student satisfaction relates to specifics of the course subject. The case study is supposed to provide a helpful insight into the elements of student satisfaction with a distance course in social sciences. The case study design does not allow making far-reaching generalizations, but the collected data may provide help in determining how the process of distance learning in social sciences may be optimized to ensure better satisfaction of students. Aims and Objectives The aim of this study is to investigate which elements have the largest impact upon student satisfaction in the specific environment of Dublin Economic School. The study is designed to fulfill the following research objectives: 1. Using secondary research, identify and describe the major contributors and predictors of student satisfaction; 2. On the basis of primary data, identify which elements are perceived by the sample of students as the most essential for ensuring satisfaction with distance learning in social sciences; 3. Relate case study results to the secondary data to identify which of the factors identified in the past research are relevant in the case study setting; 4. Make recommendations how to improve the quality of distance learning in terms of student satisfaction in the case study environment. Study Design Secondary and primary qualitative data will be collected from two sources: - Credible scholarly research in the field of student satisfaction; - Case study of a sample of second year students (social sciences course) from Dublin Business School; The choice of qualitative methodology is determined by several equally important considerations. Firstly, the non-quantifiable nature of student satisfaction barely allows for the use of quantitative methodologies which "produces findings not arrived at by means of statistical procedures or other means of quantification" (Strauss, and Corbin, 1990: 17). Secondly, the case study is carried out to identify those elements of student satisfaction which are important in a specific context and time: only qualitative research reveals findings observed in the real world context where the phenomena being studied unfold naturally. The basic motivation underlying qualitative research is the researchers desire to understand the social and cultural phenomena within the real-world setting. Qualitative methods are designed to provide the researchers with data explaining participants' perception and understanding of various phenomena, experiences and motivations, etc. (Patton, 2002). Qualitative methodologies generate rich and highly detailed data without taking it out of the context where it has been gathered. These features of qualitative methodology are highly important in our case. Similarly, case study is preferred because this type of qualitative research design suits the formulated objectives. Yin (1994) defines case study as "an empirical enquiry that investigates a contemporary phenomenon within its real-life context, especially when the boundaries between phenomenon and context are not clearly evident' and it relies on multiple sources of evidence" (13). Therefore, case study seems to be the adequate choice for better understanding of the phenomenon being studied. Secondary Data Collection Secondary data will be collected from a range of credible source to identify the key features of student satisfaction. With each source, factors such as the relevance, credibility and others will be considered to ensure relevant, trustworthy and informative selection of sources. Primary Data Collection The initial step of the primary data collection phase will involve a survey to define the overall sample: gender (male/female), residence (urban/rural), age, and agreement to participate in the research. The potential participants will be contacted via the instructors. Participants for the qualitative stage will be selected randomly from those whom show a willingness to participate in their response to the questionnaire. Selection of the sample for qualitative stage will be done in a way to make it as representative of the overall student population (gender, residence and age) taking the course as possible The second step of the primary data collection phase will involve a series of interviews with the selected participants. Interviewing is a popular method of collecting qualitative data that has certain advantages and disadvantages as compared with other qualitative methods such as participant observation or focus groups. The nature of interviews allows the researcher to retrieve as much information on the issue being studied as possible. Interviews are not as time-consuming and costly as other qualitative methods, while the data obtained via interviewing the participant is valid, diverse and reliable enough to ensure in-depth exploration of the issue being studied (Glesne, and Peshkin, 1992). Semi-structured interview is preferred as the data collection instrument for this study due to several considerations. Firstly, semi-structured interviewing allows for focused two-way communication. Secondly, while the questionnaire framework implies formulation of detailed questions, a semi-structured interview starts with more general topic or questions, identified ahead of time, and makes it possible for the interviewer to seek for relationships between the questions/topic and variety of relevant issues. The answers given by the interviewee serve as the basis for more specific questions formulated during the interview (Gillham, 2005). The questions prepared for the interview will be formulated on the basis of secondary research findings and will include various types of questions (e.g. open-ended, closed-ended and probing ones). Closed-ended questions give respondents a predetermined choice of answer such as 'yes' or 'no'. Though this type of questions is appropriate in some cases, closed-ended questions would not allow retrieving deeper meaning from the subject: therefore, open-ended questions, leading and probing questions will shape the core of the interview. Open ended questions allow respondents to give there own answers and leave enough options for the interviewer to guide the interviewee in the required direction (Fink, 1995 cited in Saunders et. al., 2000, p.291). The interview will be conducted in a specially selected place appropriate for both interviewee and interviewer. The interview will be tape recorded with assent of the interviewee for further transcribing and analysis. Limitations The study has several potential limitations. Although secondary data is relatively easy to collect, it is often too general and may sometimes not be accurate. The choice of highly credible sources, classic texts and peer-reviewed scholarly articles, is meant to address this potential limitation. The limitations associated with primary research are more serious. Firstly, data obtained during interviewing is believed to be subjective and descriptive (Patton, 2002). One of the main drawbacks of this method is related to the language-imposed constraints: the researcher's questions asked verbally during the interview are believed to frame responses of the participant being interviewed (Hancock, 1998). On the other hand, the use of a semi-structured interview is likely to help avoid the numerous pitfalls of questionnaires and phone interviews, misinterpretation or misunderstanding of the questions by respondents. Secondly, the sample size (10 students) is not large enough to make any deep far-reaching conclusions/generalizations. Although issuing recommendations applicable to the unique study setting is one of the study objectives, this limitation does not allow making overall conclusions related to the primary aim: reveal the elements which have the largest impact upon student satisfaction with the distance course in social sciences in Dublin Business School. No relationship between the participants' gender/age/residence and level of their satisfaction is assumed in this study. Data Analysis and Interpretation Analysis and interpretation of qualitative data collected during the study will follow traditional procedures for the accurate analysis of data collected using semistructured interviewing. This will involve taping and transcribing all the interviews; reading them thoroughly in order to identify key issues; examination and comparison of the interviews to identify differences and similarities. After that an attempt will be made to construct a conceptual framework to discuss and interpret the data with reference to the findings identified in the literature review. WORKS CITED Allen, E. I., and Seaman, J. Entering the mainstream: The quality and extent of online education in the United States, 2003 and 2004. Needham, MA: Sloan-C, 2004. Astin, A. W. What matters in college San Francisco: Jossey-Bass, 1993. Beltyukova, S. A., and Fox, C. M. "Student Satisfaction as a Measure of Student Development: Towards a Universal Metric". Journal of College Student Development 43 (2002): 161-172. Betz, E. L., Menne, J. W., Starr, A. M., and Klingensmith, J. E. "A dimensional analysis of college student satisfaction". Measurement and Evaluation in Guidance 4.2 (1971): 99-106. Gillham, B. The Research Interview (Real World Research). London: Continuum, 2005. Glesne, C., and Peshkin, P. Becoming qualitative researches: An introduction. New York, NY: Longman, 1992. Hagel, P., and Shaw, R. "Correlates of student satisfaction with study modes". Learning for an Unknown Future: Research and Development in Higher Education: Proceedings of the 2003 Annual International Conference of the Higher Education Research and Development Society of Australasia (HERDSA) 26 (2003): 264-272. Hancock, B. An Introduction to Qualitative Research. Trent Focus Group, 2002. Harvey, L., Plimmer, L., Moon, S., and Geall, V. Student satisfaction manual. Bristol, PA: Society for Research into Higher Education and Open University Press, 1997. Liaw, S., and Huang, H. "How web technology can facilitate learning". Information Systems Management 1 (2002): 56-61. Patton, M. Q. Qualitative evaluation and research methods (3rd ed.). Thousand Oaks, CA: Sage Publications, Inc., 2002. Petracchi, H.E. "Distance Education: What Do Our Students Tell Us" Research on Social Work Practice 10.3 (2000): 362 - 376. Phipps, R. A., and Merisotis, J. P. "Quality on the line: Benchmarks for success in Internet-based education". Institute for Higher Education Policy. Retrieved April 29, 2007 from http://www.ihep.com/Pubs/PDF/Quality.pdf. Russell, T. L. The no significant difference phenomenon. Raleigh, NC: North Carolina State University, 1999. Saunders, M., Lewis, P., and Thornhill, A. Research Methods for Business Students, 2nd edition. London: Pitman Publishing, 2000. Smart, K.L., and J. J. Cappel. "Students' Perceptions of Online Learning: A Comparative Study". Journal of Information Technology Education 5 (2006): 201-219. Strauss, A., and Corbin, J. Basics of qualitative research: Grounded theory procedures and techniques. Newbury Park, CA: Sage Publications, 1990. Upcraft, M.L., and Schuh, J.H. Assessment in student affairs: A guide for practitioners. San Francisco: Jossey-Bass Publishers, 1996. Read More