Student Satisfaction in Distance Learning - Research Proposal Example

SATISFACTION IN DISTANCE LEARNING: RESEARCH PROPOSAL 2007 SATISFACTION WITH A DISTANCE LEARNING IN SOCIAL SCIENCES:RESEARCH PROPOSAL 1. INTRODUCTION One major consequence of the remarkable technological surge was the rapid development of computer-mediated distance learning. The beginning of the third millennium was marked by an impressive growth in distance education enrolment. Institutions of higher education continued to further develop distance learning offerings targeting the populations of working adults and international students who otherwise have limited access to higher education (Smart, and Cappel, 2006; Liaw, and Huang, 2002). The online enrolment 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). However, 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). 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 overall development of the students (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). Student satisfaction is the key outcome of higher education 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 the educational environment in order to create learning settings highly conducive for student development. Student satisfaction is a factor that seriously affects 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 enrolment, 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). 2. LITERATURE REVIEW Student satisfaction has not been fully examined in the literature on evaluation aspects of education: academic performance has received considerably more attention. However, some practitioners such as Sweeny and Ingram (2001) claim that student satisfaction, preferences, and attitudes should also be treated as important factors too, especially in higher education. Elliott and Shin (2002) also argue that satisfaction is a worthy outcome variable to explore because it has a number of student and course related benefits, namely: lower attrition rates, increases in motivation and a greater number of referrals. Merisotis and Phipps (1999) also consider student satisfaction a broad measure of the effectiveness of the education process. Students' satisfaction is an important research area within educational evaluation. The growing concern for accountability in educational outcomes stimulated the need for meaningful and stable measures. The conventional analysis of satisfaction has been based on the assumption that satisfaction is best seen in terms of student response to course components and the methods used by teaching staff. Much of this analysis has focused upon comparing mean trends in these components. Satisfaction can be defined as "a post-experience evaluation that occurs at the conclusion of a psychological process" (Guolla, 1999: 89). The antecedents of satisfaction include expectations, perceived experience and performance of the service, perceived disconfirmation of expectations, and attitudes (Yi, 1990). Several models have been suggested in the literature, but there is still a need to design an effective structural model that would help explain the numerous complexities associated with student satisfaction. The institutions of higher education employ several instruments to collect data about student satisfaction. The College Student Satisfaction Questionnaire (CSSQ) adapted from a business employee satisfaction inventory is one of the most frequently used instruments in this field. This questionnaire was developed using factor-analytical approach and contains 70 items representing five subscales of student satisfaction: compensation, social life, working conditions, recognition, and quality of education. Student satisfaction data collected with CSSQ are typically analyzed using students' mean scores on each subscale and the mean of the overall level of satisfaction (Beltyukova, 2002:164). Sometimes researchers also collect students' ratings of each item's importance along with the satisfaction data to create a two-dimensional representation of satisfaction and importance (Polcyn, 1986). The Student Satisfaction Inventory (SSI), another widely applied instrument, adopts a similar two-dimensional approach to student satisfaction (Low, 2000). The SSI exists in two versions: a 73-item questionnaire for four-year institutions and a 70-item questionnaire for two-year colleges, and yields data on student satisfaction with different campus experiences as well as student ratings of the importance of these experiences. Scores from the SSI were highly correlated with those from the CSSQ and were interpreted as evidence that both instruments measured the same satisfaction construct (Beltyukova, 2002: 164-165). The existing instruments used to evaluate student satisfaction clearly demonstrate the overwhelming complexity of the satisfaction construct. Different factors and subscales imply that authors of different evaluation tools stick to varying definitions of student satisfaction, which is one of the most essential drawbacks of research in the field of student satisfaction. A popular solution to the problem of accurate measurement of student satisfactions is development of a 'universal' measure that would help standardize both the criteria and results (Beltyukova, 2002). Such measures have been traditionally used in the field of natural sciences, but only recently attempts have been made to take the same approach in the social sciences (Fisher, 1997). The term 'universal' in this case is used not in the meaning of 'perfect' or 'flawless': it rather "denotes measurement that transcends the particulars of the situation in which measurements occurred and the brandname of the instrument that was used" (Fisher, 1993: 272). Temperature (measured by degrees Fahrenheit), weight (measured by pounds and ounces), and height (measured by inches on a ruler) are some examples of universal measures. The universal measures are valid regardless of which specific ruler, scale, or thermometer is used. This is because these measurements are made using universally calibrated units of measurement with a shared meaning across users (Beltyukova, 2002). Similarly, developing a universal measure of student satisfaction is believed to allow the institutions of higher education to obtain a common set of interpretations of student satisfaction. The existing research in the field of student satisfaction with distance learning is characterized by dominance of 'the no significant difference' approach (Russell, 1999). 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 measure effectiveness of educational models, student performance has been given an edge over student satisfaction. The majority of authors in the field compare rigor and outcomes of conventional face-to-face versus distance courses instead of in-depth quality examination of distance learning environment. Reasonability of such approach has been repeatedly questioned over the recent years. Thus, Sonwalker (2002) suggest that pedagogical models developed for online distance education do not take full advantage of the online medium. In attempting to harness the capabilities of digital interfaces, the mistake is often made of recreating a classroom-teaching model within an online learning environment. Online technology designed to mimic the classroom becomes a restriction and a barrier to the teacher's ability to impart knowledge. Sonwalker (2002) postulates the need for a fundamental paradigm shift in order to create an effective learning model suitable for distance education environment. The No Significant Difference approach has had much impact on research in the field of student satisfaction. Studies and surveys published in the 1990s and early 2000s tend to demonstrate that satisfaction patterns found in students participating in online courses do not differ considerably from the satisfaction patterns in students taking conventional classes (Hara and Kling, 1999). Only in recent years several authors attempted to reveal and study the new factors that affect the level of student satisfaction in the distance learning environment. In the late 1990s, Beller and Or (1998) reported that insufficient research was available on the issues of web-based education and learning. Although many of additional studies and surveys have been carried out over the last 8 years time, exploration of some issues still leaves much to be desired (O'Neill, Singh, and O'Donoghue 2004; Smart and Cappel, 2006). Student satisfaction seems to be one of the poorly explored issues. Thus, Wang (2003) reports that research rarely addresses the factor of learner satisfaction with distance online learning. Given the tremendous recent expansion of the use of online learning, especially in higher education, the issue of student satisfaction may be one of the keys to improving our understanding of the conditions and circumstances under which the advantages of online learning can be utilized most effectively. Although recent research suggest that online education can be as effective as traditional classroom models, only a 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 presents study is supposed to provide an insight into the basic elements of student satisfaction with a distance course in social sciences. The qualitative design of the study does not allow for making serious generalizations unless the results are replicated in a series of other similar studies, 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. 3. METHODOLOGY Methodological framework employed for this is qualitative in nature. Applicability of such methodology to studying the problem of student satisfaction with online learning course in social sciences deserves specific explanation. Irrelevance of direct comparison drawn between traditional and distance education stressed by the recent research is an essential factor to be observed in choosing the appropriate study design and methodology. A comparison of the qualitative and quantitative methodological paradigms demonstrates strengths and weaknesses of each approach as well as illustrates the areas of tension between them. Researchers in the field of distance learning tend to rely upon quantitative methodology which employs methods historically applied in the natural (physical) sciences. The primary task of quantitative research is to ensure validity and reliability of results (Patton, 2002). The concept of reliability as applied in quantitative research can be defined as: "The extent to which results are consistent over time and an accurate representation of the total population under study is referred to as reliability and if the results of a study can be reproduced under a similar methodology, then the research instrument is considered to be reliable" (Golafshani, 2003: 598). Consequently, quantitative research implies standardized questionnaires and methods of data analysis, specific position of the researcher whom is considered external to the research he carries out, replicability of the results regardless of the context, etc (Wainer and Braun, 1998). While reliability and validity are the most often cited strengths of the quantitative methodology, poor applicability of this methodology to studying a phenomenon, which is difficult or impossible to quantify, is considered a serious weakness. The main drawback that limits applicability of quantitative paradigm in distance learning research is the so-called 'decontextualization': models built using data obtained through quantitative methods do not take into account certain variables that act in the real world context (Patton, 2002). Qualitative methodology represents a distinct research paradigm that ensures the researcher' immersion in the context of his study and makes him an active participant of the study. Qualitative framework utilizes a naturalistic approach seeking to understand phenomena in a specific context, such as "real world setting [where] the researcher does not attempt to manipulate the phenomenon of interest" (Patton, 2002: 39). The broad definition of qualitative research is "any kind of research that produces findings not arrived at by means of statistical procedures or other means of quantification" (Strauss and Corbin, 1990: 17). Qualitative research reveals findings observed in the real world context where the phenomena being studied unfold naturally (Patton, 2002). Qualitative methods used in distanced are expected to provide the researchers with data explaining participants' perception and understanding of various phenomena, experiences and motivations, etc. Extrapolation of the qualitative study results to other similar situations and contexts is also an important aspect of qualitative research (Hoepfl, 1997). Qualitative methodologies generate rich and highly detailed data without taking it out of the context where it has been gathered. However, the qualitative research paradigm has not yet received absolute recognition in the academic community. A number of theorists keep questioning reliability, validity and generalisability of data obtained using qualitative methods. Qualitative researchers adopt a different view on adequacy and applicability of the concepts of validity and reliability than quantitative researchers do. Defined in qualitative terms these concepts do not apply to the quantitative paradigm and visa versa. Thus, the replicability criterion is not applicable to qualitative research (Glesne and Peshkin, 1992), while the criteria of credibility, transferability and precision are treated as very important in assessment of qualitative research findings (Hoepfl, 1997). Therefore, researchers tend to develop their own concepts of validity or adopt other assessment criteria that are more appropriate in each particular case. The examples of such criteria are quality, trustworthiness, rigor and some others (Patton, 2002). Evidently, both paradigms, qualitative and quantitative may be considered a weakness or strength: the perception depends entirely on the situation in which either methodology is supposed to be employed. The context of this study suggests that using the qualitative methodology is more appropriate. Such choice seems to be justified by the study purposes: Firstly, the study expresses an interest in understanding the experiences (satisfaction) perceived by the students and strongly emphasises the context in which the perceptions occur; Secondly, the study involves in-depth exploration of the issue: the participants are required to provide comprehensive information on their experiences. Thirdly, the type of reasoning employed is inductive which means no specific hypothesis or theory is expected to be verified: the hypothesis or theory may emerge from the data collected during the research. Data collection The initial step of 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 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 (Gillham, 2005). 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. Safety and Ethical Considerations Since the study involves human subjects the key ethical issue associated with it is confidentiality. The data collected and analysed within the framework of this study will not be disclosed to anyone. The study does not involve any direct measurements, experiments or interventions which may negatively affect performance of the participants: it only seeks to evaluate the level and structure of their satisfaction with the online course. The interviews will be recorded only granted conscious informed assent of each participant. No other ethical or safety considerations seem to be involved in the study. Biases and Limitations 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 (is not expected to exceed 15-17 participants) is not large enough to make any serious 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 School of Social Sciences, Humanities and Languages. No relationship between the participants' gender/age/residence and level of their satisfaction is explored 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 through 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. 4. RESEARCH TIMEPLAN The following steps are needed to complete the research: 1. Identification of the potential sample of participants. This will be done via school/university administration after obtaining appropriate permission. 2. The potential participants will be contacted via e-mail or phone with the request to fill in the questionnaires. 3. The sample of students whom agree to fill in the questionnaires and take part in the main phase of research (interview) will be analysed in order to identify the group representative of the whole student population (residence, gender, age) of the school/university where the research is carried out. Members of the selected sample will be contacted in order to arrange a meeting with the interviewer. 4. A series of interview with the selected participants will be carried out. 5. Transcription of audio recordings 6. Notes and transcripts matching 7. Analysis of data and study of findings. 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: Sloan-C, 2004. Astin, A. W., What matters in college San Francisco: Jossey-Bass, 1993. Beller, M. and Or, E. 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